Notes on Brave New Words: How AI Will Revolutionize Education
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My notes from the book Brave New Words: How AI Will Revolutionize Education (and Why That’s a Good Thing) by Salman Khan.
- Introduction: Let’s write a new story together
- Part I꞉ Rise of the AI Tutor
- Part II: Giving Voice to the Social Sciences
- Part III: Empowering the Next Innovators
- Part IV: Better Together
- Part V: Keeping Kids Safe
- Part VI: Teaching in the Age of AI
- Part VII: The Global Classroom
- Part VIII: AI Assessments and Admissions
- Part IX: Work and What Comes Next
Book LInks:
Introduction: Let’s write a new story together
“You can’t cross the sea merely by standing and staring at the water.” - Rabindranath Tagore
“But whatever you do, do not let the past be a straitjacket.” - Robert A. Heinlein
A New Era of Storytelling and Education
- Premise: Khan and his 11-year-old daughter, Thea, embark on a collaborative storytelling exercise using GPT-4, a large language model developed by OpenAI.
- The Experiment: Thea creates a story about a stranded social media influencer, Samantha. As they write, Samantha begins interacting with Thea through the AI, demonstrating its ability to participate in complex dialogues and understand context.
- Significance: This interaction showcases the potential of AI to revolutionize education and learning, highlighting the need for educated bravery in embracing this new technology.
Khan Academy’s Journey and the Rise of AI
Khan Academy’s Origins and Mission
- Initial Goal: Provide free math tutoring to Khan’s cousin, Nadia, using instant messaging and phone calls.
- Expansion: Free tutoring services extended to family members, leading to the development of web-based math practice software.
- Khan Academy’s Birth: Website launched with the aim of providing personalized learning to students through exercises and tracking progress.
- Incorporation of Video Lessons: Videos added to complement the software, offering tutor-like instruction and addressing the need for affordable learning resources.
- Growth and Impact: Khan Academy evolves into a non-profit organization serving millions of learners worldwide in multiple languages.
- Core Mission: Provide a free, world-class education for anyone, anywhere, with a focus on personalized learning and mastery learning.
The Potential of AI in Education
- Long-held Aspiration: To emulate the effectiveness of one-on-one tutoring through technology.
- AI as a Solution: AI technology recognized as a potential tool for achieving personalized learning at scale.
- Science Fiction Inspiration:
- Neil Stevenson’s The Diamond Age: Explores AI-powered personalized education through an interactive book and app.
- Orson Scott Card’s Ender’s Game: Depicts a battle school utilizing AI for strategic training through a personal tutor.
- Isaac Asimov’s The Fun They Had: Presents a future school revolutionized by advanced technology and robot teachers.
- Real-world Parallels:
- Steve Jobs’ vision of computers as “bicycles for our minds,” extending human capabilities.
- Decades of research and development in AI aiming to emulate human intelligence.
Early Milestones in AI
- 1962: IBM 7094 computer defeats checkers master Robert Neely.
- 1957: Frank Rosenblatt creates Perceptron, the first artificial neural network.
- Limitations: Early AI systems faced limitations in computational power, training techniques, and data availability.
Advancements in AI Technology
- Modern Applications: AI powers recommendation engines, voice assistants, and other widely used technologies.
- Mimicking Human Behavior: AI’s ability to mimic human responses blurs the lines between human and machine interactions.
- Increased Computational Power: Modern computers can handle systems approaching the complexity of the human brain.
- Breakthroughs in Neural Networks: Significant advancements in structuring and training neural networks.
- 2017: Google introduces transformer technology, enabling faster training and improved accuracy in language modeling.
Understanding Large Language Models (LLMs)
- Large Language Models (LLMs): Computational representations designed to model associations between words, mimicking neurons and synapses in the brain.
- GPT-4 (Generative Pre-trained Transformer): A powerful LLM trained on vast amounts of text data, enabling it to understand language patterns and context.
- Training Data: GPT-4 learns from books, articles, websites, and other written material, enabling it to answer questions and generate text based on its training.
- Lack of Sensory Experience: LLMs compensate for the lack of real-world sensory experiences by processing vast quantities of language data.
The Offer from OpenAI: A Collaboration to Explore GPT-4
Initial Contact and Skepticism
- Summer 2022: Khan receives an email from Greg Brockman (President) and Sam Altman (CEO) of OpenAI, proposing a collaboration.
- OpenAI’s Goal: Showcase socially positive and real-world applications of GPT-4 upon its release.
- Khan Academy’s Role: Partner with OpenAI to demonstrate the potential of GPT-4 in education and help evaluate its capabilities.
- Initial Skepticism: Khan expresses reservations about the immediate applicability of generative AI in education, citing concerns about knowledge accuracy, logical reasoning, and factual reliability.
- Respect for OpenAI’s Achievements: Despite skepticism, Khan acknowledges OpenAI’s accomplishments and agrees to a meeting.
The GPT-4 Demo: A Paradigm Shift
- GPT-4’s Capabilities: OpenAI demonstrates GPT-4’s ability to answer complex AP Biology questions accurately and provide detailed explanations.
- Initial Surprise and Skepticism: Khan expresses amazement but remains cautious, questioning the reliability of the AI’s performance.
- Further Demonstrations: GPT-4 explains why incorrect answer choices are wrong and generates original AP-level questions, solidifying its capabilities.
- Bill Gates’ Validation: Bill Gates shares his earlier challenge to OpenAI, stating he would be impressed if GPT-4 could pass the AP Biology exam, which it now demonstrated.
Realization of GPT-4’s Potential
- Excitement and Implications: Khan recognizes the transformative potential of GPT-4 across various domains, including education, credentials, work, and human potential.
- Shared Vision: OpenAI leadership expresses similar excitement and optimism about the potential impact of GPT-4 in education.
- Science Fiction Becomes Reality: The technology previously imagined in science fiction narratives becomes a tangible reality, opening up new possibilities and challenges.
Time for a Hack AI-thon: Exploring the Educational Applications of GPT-4
Early Pioneers in Language Modeling
- Claude Shannon (1940s): Developed a theory of electronic communication and explored algorithmic language approximation.
- Shannon’s Information Theory: Proposed that probabilistic processes could approximate language by analyzing word frequencies and predicting the next word in a sequence.
- Alan Turing (1950s): Explored the concept of artificial intelligence and introduced the Turing test, a benchmark for evaluating machine intelligence.
- The Turing Test: A test designed to determine if a machine can exhibit intelligent behavior indistinguishable from that of a human.
Exploring GPT-4’s Capabilities
- Passing the Turing Test: Khan contemplates whether GPT-4 could potentially pass the Turing Test, signifying a major milestone in AI development.
- Societal Implications: Recognizes the potential benefits and drawbacks of AI, including its impact on education, employment, and ethical concerns.
- Potential for Cheating: Acknowledges the risk of students using AI to write essays and complete assignments, hindering their learning and development.
- Job Displacement: Raises concerns about AI potentially replacing human jobs and impacting individuals’ sense of purpose.
- Misinformation and Manipulation: Recognizes the potential for bad actors to exploit AI for fraudulent activities or to spread misinformation.
- Data Privacy and Security: Highlights the importance of addressing data privacy and security concerns associated with AI technology.
The Khan Academy Hack AI-thon
- Goal: Explore the potential of GPT-4 in education through a collaborative “Hack AI-thon.”
- Participants: OpenAI grants access to a group of Khan Academy engineers, content creators, educators, and researchers.
- Brainstorming and Prototyping: Participants develop innovative ideas and educational applications for GPT-4.
- Potential Applications:
- AI-assisted lesson planning.
- AI-driven student debates.
- AI-generated projects.
- AI-based stress reduction and inspiration.
- AI-powered quizzes and review sessions.
- AI feedback on student essays.
Addressing Concerns and Mitigating Risks
- Cheating Prevention: Explore ways to design AI tutors that guide students through questioning rather than providing direct answers.
- Transparency and Moderation: Consider implementing systems to log conversations and ensure transparency for teachers and parents.
- Promoting Human Connection: Develop tools that free up time for teachers and students to focus on interpersonal interactions.
Optimism and Potential for Transformation
- Confidence in GPT-4’s Impact: The Hack AI-thon reinforces the belief that GPT-4 can revolutionize education.
- Benefits for Teachers: AI can enhance teaching practices, provide personalized support, and potentially reduce teacher burnout.
- Benefits for Students: AI can act as a personalized tutor, debating partner, guidance counselor, and career coach, leading to improved learning outcomes.
- Global Impact: AI has the potential to accelerate learning globally and increase access to quality education for everyone.
- Historical Parallels: Compares the transformative potential of AI to previous technological advancements like the internet and personal computers.
Embracing Educated Bravery
- Acknowledging Risks: Recognizes the need to carefully consider and address the potential downsides of AI.
- Mitigating Risks: Emphasizes the importance of proactive measures to minimize risks and maximize positive impacts.
- Preparing for Change: Underscores the need to adapt to the rapid advancements in AI and its implications for education and society.
Part I꞉ Rise of the AI Tutor
“A great teacher can teach calculus with a paperclip and literature in an empty field. Technology is just another tool, not a destination.” - Unknown
“In your primer, you have a resource that will make you highly educated, but it will never make you intelligent. That comes from life. Your life up to this point has given you all the experience you need to be intelligent. But you have to think about those experiences. If you don’t think about them, you’ll be psychologically unwell. If you do think about them, you will become not merely educated, but intelligent.” - Neil Stevenson, The Diamond Age
Chapter 1: Throwing Away the Bottle
The Initial Backlash Against ChatGPT in Education
Rapid Spread and Bans:
- ChatGPT’s rapid global adoption was met with widespread bans and resistance, particularly in educational settings.
- Los Angeles Unified School District was the first major school system to ban it in early 2023.
- Other districts followed suit, including Seattle, New York City, Fairfax County (Virginia), and Montgomery County (Alabama).
- Bans extended internationally to France, India, and Australia.
Reasons for Bans:
- Cheating Concerns: Schools feared students using ChatGPT to cheat on assignments and exams.
- Lack of Critical Thinking Development: Concerns that the tool hindered the development of critical thinking and problem-solving skills.
Comparison to COVID: Some likened the spread of ChatGPT to the COVID pandemic, predicting the “death of education.”
Inside Higher Ed opinion piece:
“Today, we are facing a new sort of plague, one that threatens our minds more than our bodies. ChatGPT, the artificial intelligence chatbot that can write college-level essays, is going viral… To their shock and dismay, teachers will find that their classroom has tested positive for GPT.”
Author’s Perspective as Father and Educator:
- Initial understanding and agreement with the distrust surrounding ChatGPT.
- Concerns about the potential negative impact on student agency, creativity, socialization, and collaborative learning.
Acknowledging the Inevitability and Potential of AI in Education
- Inevitable Exposure: Acknowledges that student exposure to generative AI is inevitable.
- Concerns about AI’s Impact:
- Increased screen time.
- Students not doing their own work.
- Negative effects on student writing skills.
- Potential for biased information due to ChatGPT pulling from biased online sources.
- Technology as a Tool:
- Argues that technology, including AI, is not inherently good or bad, but its impact depends on how it is used.
- Technology can have both negative and positive consequences:
- Negative: Unhealthy habits, distraction, exposure to harmful content.
- Positive: Maintaining social connections, fostering creativity (e.g., video editing, writing, coding), learning and self-improvement.
- AI’s Potential in Various Fields:
- Medicine: Assisting in diagnosis, medical record analysis, personalized treatment.
- Business: Streamlining content generation and automating workflows.
- Legal and Compliance: Contract analysis, legal research, document generation, ensuring regulatory compliance.
- Other Applications: Developing technical documentation, writing user manuals, creating grant proposals, coding.
- The “AI Replacement” Meme:
- “You won’t be replaced by an AI, but you might be replaced by someone using AI.”
- Highlights the importance of learning to use AI effectively for success.
Benefits of AI for Students and the Workforce
- Enhanced Learning and Competitiveness:
- Students who use AI ethically and productively can learn faster and remain competitive in their careers.
- AI can help students make conceptual connections and develop ideas.
- Deeper Understanding and Curiosity:
- AI can help students get their questions answered, leading to a deeper understanding of subjects.
- AI can strengthen, rather than atrophy, students’ curiosity.
- Workplace Applications:
- Effective AI Users: Those who can steer AI and understand quality writing will get the best output.
- Curious Individuals: Those who feed their curiosity with AI will be better at anticipating market trends.
- Creative Collaboration: Brainstorming with AI and colleagues can enhance creativity.
- Automation: Workers will need to use AI to automate traditional white-collar tasks, like information collation and spreadsheet analysis.
Addressing the Challenges and Ensuring Safety
- OpenAI’s Focus on Safety:
- Greg Brockman (OpenAI President): The challenge lies in implementing safety measures.
- Safety has been a priority since GPT-1’s development.
- OpenAI aims to ensure AI is beneficial and safe.
- Safety Measures:
- Preventing AI from sharing knowledge about illegal activities.
- Blocking disallowed content.
- Protecting personal data.
- Importance of Safeguards in Education:
- Guardrails are crucial for integrating AI into education.
- The effort is labor-intensive but worthwhile.
- Embracing AI, Not Fearing It:
- Brockman encourages using AI rather than avoiding it.
- AI can benefit students by:
- Providing new learning methods.
- Enhancing collaborative learning.
- Stoking creativity.
- Promoting socialization.
- Supporting mental health.
- Offering new ways for parents and teachers to engage with education.
- Learning Smarter with AI: Brockman advocates for helping students learn smarter with AI.
- Conclusion: “The genie is out of the bottle. It is time to throw the bottle away and our fear of generative AI along with it.”
Chapter 2: How to Teach Everything to Everyone
Identifying Problems AI Can Solve in Education
- Focus on Solving Problems: Emphasizes using AI to address important problems in education, not just because it’s new and exciting.
- Potential Applications of AI:
- Closing learning gaps.
- Providing access to quality education regardless of location, economic status, or social circumstances.
- Meeting diverse student needs and learning styles.
- Addressing the shortage of high-quality educational resources, especially in underserved or remote areas.
- Improving student retention of learned material.
- Reducing teacher workload and preventing burnout.
Vision of an AI-Powered Personal Tutor
- The Ideal AI Tutor: Envisions an AI tutor that:
- Works alongside learners across all subjects.
- Provides personalized support.
- Engages in debates with students.
- Identifies and strengthens students’ inherent strengths while addressing learning gaps.
- Offers new ways of understanding STEM subjects.
- Unlocks student creativity in the arts.
- Facilitates deeper engagement with history and literature.
- Khan Academy’s Integration of GPT-4:
- Khan Academy became an early adopter of GPT-4, aiming to be the first education platform to incorporate it.
- Prioritized creating a magical, effective, and safe user experience.
Understanding GPT-4’s Capabilities and Limitations
- Strengths of GPT-4:
- Answering Questions: Excellent at answering questions, with fewer factual and math errors compared to GPT-3.5.
- Limitations and Development:
- Beyond Answering Questions: Required inverting the interaction to make it ask questions like a tutor (Socratic method).
- Steerability: GPT-4 showed significant improvement in steerability compared to earlier models, allowing for better control over its behavior and persona (e.g., acting as a Socratic tutor).
- Prompt Engineering:
- Extensive prompt tweaking to handle various student interactions and prevent inappropriate conversations.
- Development of a distinct tone and voice for the platform.
- Launch of Khanmigo:
- Launched on March 15, 2023, alongside GPT-4.
- Khanmigo: Name is a play on the Spanish phrase “conmigo,” meaning “with me.”
- Introduced as an AI assistant integrated into all aspects of Khan Academy.
Features and Potential of Khanmigo
- Personalized Tutoring: Provides a personalized and patient tutor that adapts to learner needs and interests.
- Empowering Educators: Helps educators better understand and support their students.
- Beyond Tutoring:
- Emulating literary and historical figures.
- Engaging in debates.
- Acting as a guidance counselor and career coach.
- Long-Lasting Connections:
- Potential for memory-based long-lasting connections with learners, providing academic and personal support, goal setting, and accountability.
- Facilitating Student Interactions: Potential for facilitating interactions among multiple students.
- AI-Driven Simulations: Future potential for AI-based practice and assessments using simulations.
- Enhancing Learning Domains: Potential to enhance learning across various domains: writing, reading comprehension, math, science, coding, and art.
Chapter 3: Rise of the AI Tutor
The Effectiveness of One-on-One Instruction
- Historical Importance of Tutoring: Highlights the long-standing recognition of one-on-one tutoring as the most effective learning method.
- Example: Alexander the Great and Aristotle.
- Benefits of Personalized Tutoring:
- Allows for adjusting the pace of instruction based on individual student needs.
- Prevents students from feeling stuck or bored.
- Modern Examples: One-on-one coaching remains prevalent in fields like athletics and music.
- Challenges of Scaling Tutoring: Difficult to implement one-on-one tutoring in a mass public education system due to resource limitations.
The Limitations of the Traditional Education Model
- The Rise of Mass Public Education:
- 18th century: Emergence of the idea of mass public education.
- Standardized Approach: Led to a “factory model” of education with lectures and periodic assessments for large groups of students.
- Benefits and Drawbacks of the Traditional Model:
- Benefits: Increased literacy and education rates globally.
- Drawbacks: Not optimal for most students due to its fixed pace and lack of personalization.
- The Problem of Accumulating Knowledge Gaps:
- Fixed-Pace Learning: Forces students to move on even without mastering foundational concepts.
- Consequences: Leads to accumulated knowledge gaps that hinder future learning.
- Examples:
- Majority of US students, including college-bound graduates, do not place into college-level math.
- Many students require remedial pre-algebra courses in college.
- Three-quarters of high school seniors lack basic writing proficiency.
Bloom’s Two-Sigma Problem
- Benjamin Bloom’s Research (1984):
- University of Chicago study: Compared conventional learning with one-on-one tutoring in a mastery learning context.
- Definition of a Good Tutor: A caring and student-attuned instructor who provides clear learning objectives, assessments, and specialized feedback until mastery is achieved.
- Mastery Learning: Provides students with the opportunity and incentive to address knowledge and skill gaps.
- Conventional Learning vs. Mastery Learning:
- Conventional Learning: Fixed-paced with periodic quizzes/tests; classes move on regardless of individual mastery.
- Mastery Learning: Allows students time to identify and address knowledge gaps before moving on.
- The Two-Sigma Problem:
- Students working with tutors in a mastery learning context showed a two-standard deviation improvement.
- This translates to moving from the 50th percentile to roughly the 96th percentile.
- Problem: Traditional education systems could not realistically scale this level of personalized instruction.
Addressing the Two-Sigma Problem with Technology
- Traditional Solutions for Personalization: Middle-class and affluent families often resort to private tutoring.
- Khan Academy’s Aspiration: To provide equal access to personalized learning regardless of socioeconomic status.
- Vision of an Ideal Tutor:
- Goes beyond homework help and provides deeper support.
- Builds trust and a relationship with the student.
- Has an intimate understanding of the student’s strengths and weaknesses.
- Fine-tunes education based on student motivation.
- Supports teachers and parents with insights into student progress.
- Khan Academy’s Pre-AI Approach:
- Offered personalized learning tools like on-demand videos and exercises.
- Provided teacher and administrator dashboards for tracking student progress.
- Efficacy Studies: Showed 20-60% acceleration in learning for students using Khan Academy’s personalized practice.
- Khan Lab School and Khan World School: Demonstrated 1.5-3 years of math learning per year in mastery-based learning settings.
Limitations of Pre-AI Khan Academy and the Potential of GPT-4
- Limitations of Pre-AI Platform:
- Limited options for students beyond videos and exercises.
- No ability to ask follow-up questions or engage in deeper exploration.
- Limited assessment formats (numeric entry, equation entry, multiple choice).
- Basic goal setting and tracking features lacked the feel of a caring tutor.
- GPT-4’s Potential:
- Recognized as a potential solution to address these limitations.
- Team-wide excitement about GPT-4’s capabilities.
- Need for Guardrails and Support: GPT-4’s power needed to be coupled with carefully designed safeguards for effective use in education.
- OpenAI’s Partnership with Khan Academy: OpenAI chose Khan Academy as a partner due to their focus on educational applications and commitment to responsible AI implementation.
- Greg Brockman’s Vision: Believes large language models like GPT-4 can be the biggest benefit to education in history.
- Building an AI Super Tutor:
- Aiming to create an AI system capable of providing every learner with a personal “super tutor.”
- Potential to achieve the two-standard deviation improvement described by Bloom.
Launching Khanmigo and Overcoming Initial Skepticism
- Seizing the Opportunity: Recognizing the potential of AI to revolutionize education.
- Khanmigo’s Goal: To address Bloom’s two-sigma problem and make personalized learning accessible to everyone.
- Addressing Initial Concerns about Cheating:
- ChatGPT’s initial negative reception in education due to cheating concerns.
- Khanmigo was designed with features to prevent cheating, provide teacher transparency, and ensure safe and productive student interactions.
- Shifting Attitudes Towards AI in Education:
- By March 2023, educators began to recognize the potential of GPT-like technology for learning.
- Teachers started using AI for lesson planning and research.
- Demand for education-focused AI tools increased.
- Positive Reception of Khanmigo:
- Overwhelming support from the education community, including school districts that had banned ChatGPT.
- Appreciation for Khan Academy’s safe, effective, and pedagogically sound implementation of GPT-4.
How Khanmigo Works
- Interactive Tutoring:
- Students can ask for help through a chat interface.
- Instead of providing direct answers, Khanmigo guides students through problems like a human tutor.
- Example:
- Student: “I’m having trouble with polynomials. Can you help explain how to find the degree of this polynomial and the leading coefficient in this question? \(3x^{2}-5x+2\).”
- Khanmigo: “No problem. Let’s break it down. The degree of a polynomial is the highest power of the variable, in this case x, in the polynomial. The leading coefficient is the number in front of the term with the highest degree. Looking at our polynomial, can you identify the term with the highest power of x and the number in front of it?”
- Personalized Feedback: Provides specific feedback and encouragement.
- Example: “Close, but not quite. Remember, we’re looking for the highest power of x in the polynomial. Let’s try again together.”
- Cross-Curricular Applications: Works across various subjects, including history, chemistry, physics, and art.
- Beyond Subject Matter:
- Motivates learners.
- Quizzes them.
- Summarizes videos.
- Adapts to individual needs.
Khanmigo’s Conversational Abilities and Memory
- Natural and Personable Language: Uses a conversational and encouraging tone.
- Example: “Hey, you’re doing this pretty well. Don’t worry if you have trouble doing it at first. It is a little bit more advanced. Why don’t we try this new approach?”
- Memory of Previous Interactions: Remembers past conversations and can reference them in later sessions.
- Example:
- Student (previously expressed interest in soccer): “Why should I care about this?” (referring to algebra equations)
- Khanmigo: “Well, what do you care about?”
- Student: “Not math. I’d much rather be talking about soccer.”
- Khanmigo: “Okay. So let’s say you are a soccer coach and you want to model the number of goals your team scores based on the number of hours they practice each week. You come up with the following polynomial, \(3x^{2}-5x+2\). Can you identify the degree of this polynomial and the leading coefficient?”
- Example:
- Personalized Examples: Uses student interests to create relevant examples in different subjects.
- Example:
- (Days later, during a history lesson on federalism)
- Khanmigo: “Imagine a soccer league. Let’s think about the different ways to govern it. Does the team govern itself any way it wants to, by doing its own thing? Or does a central authority govern the team? Federalism is a system of government where power is divided between a central authority and smaller political units, like states or provinces.”
- Example:
- Adapting to User Preferences:
- Registers preferences for formal or colloquial language.
- Adjusts to preferences for short or long-form answers.
- Uses student motivations to maintain engagement.
- Transparent Memory and User Control:
- Students can view and modify what Khanmigo learns about them.
- Memory can provide progress reports to parents and teachers.
Khanmigo’s Mimicry of Human Tutoring Techniques
- Replicating Effective Tutoring Strategies: Khanmigo replicates many techniques used by human tutors, including:
- Helping students understand questions.
- Asking follow-up questions.
- Testing comprehension.
- Explaining connections between concepts.
- Highlighting areas for improvement and suggesting exercises.
- Personalized Learning for All: Khanmigo makes this type of personalized tutoring accessible to all students.
- Socratic Questioning: Promotes critical thinking by engaging students in Socratic questioning.
- Handling Sensitive Topics: Khanmigo can handle sensitive topics in a more neutral and unbiased way than human tutors might.
- Example:
- (Reporter skeptical about Khanmigo’s handling of gun control)
- Student (role-playing): “Why do we have the Second Amendment? It seems crazy.”
- Khanmigo: “Why do you think the founders included the Second Amendment to begin with?”
- (Khanmigo encourages deeper thinking without directly refuting or reinforcing the student’s opinion).
- Example:
- Encouraging Critical Thinking: Promotes active learning and deeper exploration of topics.
- Example: “What is your opinion of this essay?” (after a reading assignment)
Khanmigo as a Representative of AI Tutors
- Expanding Field of AI Tutors: Khanmigo serves as an example of the growing field of education-based AI platforms.
- Complementing Human Tutors:
- AI tutors can enhance the effectiveness of human tutors by providing 24/7 support and detailed progress reports.
- Students may feel more comfortable asking certain questions to an AI.
- The Potential of AI Tutors:
- With memory, content knowledge, a natural voice, the ability to build rapport, and increased access through technology, AI tutors may surpass the results of Bloom’s findings.
- Conclusion:
- AI tutors can raise the floor for students with limited access to personalized learning or quality coursework.
- AI tutors can make human tutors’ jobs easier and more effective by providing complementary support.
- AI tutors have the potential to significantly improve the learning experience for millions of learners.
Part III: Empowering the Next Innovators
“What is a scientist, after all? It is a curious man looking through a keyhole, the keyhole of nature, trying to know what’s going on.” - Jacques-Yves Cousteau
“If an elderly but distinguished scientist says that something is possible, he is almost certainly right. But if he says that it is impossible, he is very probably wrong.” - Arthur C. Clark
Chapter 8: Using Science to Study Science
Introduction: Exploring AI’s Role in Science Education
- Khan expresses curiosity about how Large Language Models (LLMs), specifically GPT-4, handle scientific concepts, particularly pseudoscience.
- Key questions explored:
- LLMs’ effectiveness in teaching science and differentiating between fact and fiction.
- Depth of LLMs’ scientific knowledge.
- Impact of AI on hands-on learning and critical thinking skills development.
- Value of classroom discussions in the context of AI integration.
Testing GPT-4 with Khanmigo: Global Warming Example
- Khanmigo: The name of the platform integrating GPT-4.
- Prompt: “I would like to know about the science of global warming. I’ve heard it is controversial in some circles. What is the scientific evidence that global warming is real?”
- Khanmigo’s Response:
- Acknowledges global warming as a well-established phenomenon and the scientific consensus on its reality and human causation.
- Lists evidence supporting global warming:
- Rising global temperatures.
- Melting ice and receding glaciers.
- Rising sea levels.
- Warming oceans.
- Extreme weather events.
- Prompt: Request for evidence supporting the argument that global warming is a hoax.
- Khanmigo’s Response:
- Acknowledges the existence of skeptical arguments but emphasizes their lack of support from the majority of climate scientists.
- Addresses specific skeptical arguments:
- Natural Climate Variability: Khanmigo counters that the rate and magnitude of current warming cannot be explained by natural factors alone.
- Data Manipulation: Khanmigo refutes claims of data manipulation, citing multiple independent analyses showing a consistent warming trend.
- Author’s Observation: GPT-4 effectively distinguished between accurate and fringe science, supporting science-backed arguments and dismantling false information.
Khanmigo as a Lesson Planning Tool
- Prompt: “Write a lesson for me to help me explain the real science behind global warming to my students.”
- Khanmigo’s Response:
- Provided a lesson plan.
- Included information about causes of global warming:
- Greenhouse gases.
- Car emissions.
- Burning of fossil fuels.
- Industrial processes.
- Waste management.
- Suggested student actions to combat global warming.
- Author’s Approach: Reviewed and refined the AI-generated information to ensure accuracy.
Khanmigo for Creative Project Ideas
- Prompt: “What projects or activities can I give my students to help them better grasp the concepts?”
- Khanmigo’s Response:
- Suggested a Greenhouse Effect Demonstration:
- Compare temperature changes in two identical containers exposed to sunlight, one with added carbon dioxide (e.g., from vinegar and baking soda).
- Suggested a Greenhouse Effect Demonstration:
- Khanmigo’s Assessment Capabilities: Generated quizzes and assessments to evaluate student understanding and identify areas for improvement.
Addressing Hallucinations in Khanmigo
- Hallucinations: Instances where AI generates incorrect or fabricated information.
- Khanmigo’s Limitation: Initially prone to generating fabricated links to sources.
- Solution: Restricted Khanmigo from providing links not explicitly pre-approved and provided to it.
- Explanation of LLMs’ Fallibility:
- Unlike calculators designed for specific tasks, LLMs generate text based on patterns in training data.
- LLMs represent associations between words and symbols, not predetermined algorithms.
- LLMs are not infallible and struggle with words or symbols lacking meaningful associations (e.g., URLs).
- Analogy to Human Brain: Humans can possess vast knowledge but struggle to recall complex sequences of symbols (like URLs) from memory.
Khanmigo’s Strengths in Science Education
- Example: Khanmigo’s ability to generate engaging and informative science articles.
- Prompt: Request for an article conveying the immensity of the Sun and Solar System.
- Khanmigo’s Response: Generated an article titled “The Sun and Solar System, A Journey into Awe-Inspiring Dimensions,” providing detailed comparisons of the Sun and planets’ sizes and distances.
- Khanmigo’s Capabilities:
- Can work with specific data and minimize hallucinations with safeguards and improvements.
- Can explain complex scientific concepts (e.g., string theory) at different levels of understanding.
- Can facilitate brainstorming and idea generation for scientific experiments.
- Can serve as a conversation partner, asking questions and challenging assumptions.
- Can relay complex scientific information across various disciplines (physics, biology, zoology) at different levels.
- Benefits for Educators: Supplement lectures with AI-generated explanations.
- Benefits for Students: Access to an AI tutor for personalized support and answering questions.
- Advanced Student Applications: Generating summaries of scientific articles and research papers.
- Humor in Science Education: Khanmigo can incorporate humor to make learning more engaging (e.g., science-themed jokes).
Khanmigo’s Application in Understanding Ozempic
- Ozempic: A diabetes drug used for weight loss.
- Author’s Goal: To understand Ozempic’s mechanism of action beyond readily available explanations.
- Khanmigo’s Approach:
- Engaged in a conversational dialogue with Khan, asking questions to assess prior knowledge and guide understanding.
- Explained concepts step-by-step, providing prompts for Khan to think critically and formulate hypotheses.
- Clarified complex terms (e.g., GLP-1) and explained their functions.
- Addressed nuanced questions and provided detailed explanations of how Ozempic regulates blood sugar and reduces hunger.
- Author’s Observations:
- Khanmigo answered complex questions effectively.
- Promoted active learning by encouraging hypothesis generation and critical thinking.
- Demonstrated pedagogical expertise by adapting explanations to Khan’s understanding and pushing for deeper conceptual understanding.
Chapter 9: One Plus One Equals Closing the Math Gap
John Spencer and AI in Math Education
- John Spencer: A teacher educator at George Fox University.
- Context: Early 2023, when ChatGPT was becoming prominent.
- Spencer’s Approach: Advocated for embracing LLMs as teacher productivity tools.
- Focus: Using AI to enhance student-centered learning, particularly in math.
ChatGPT for Explaining P-values
- P-value: A probability measure in statistics.
- ChatGPT’s Initial Response: Provided a “pretty good” but not great explanation of p-value.
- Spencer’s Refinement: Asked ChatGPT to explain the concept in simpler terms for a 15-year-old.
- ChatGPT’s Improved Response: Provided specific examples to build conceptual understanding.
- Iterative Refinement: Spencer used the “Try Again” button and reframed questions to obtain more specific and contextually relevant explanations.
- Outcome: ChatGPT’s responses became progressively more targeted, less academic, and more personalized (shifting from third to second person).
Benefits of ChatGPT for Student Teachers
- Spencer’s Observation: ChatGPT provided immediate examples and facilitated the creation of more creative and contextually relevant lessons.
- Potential of Next-Generation AI: Anticipation for even greater benefits from AI specifically designed for education, with memory and advanced lesson creation capabilities.
Khanmigo: Building an AI Math Tutor
- Khanmigo: Khan Academy’s AI tutor built upon GPT-4.
- Goal: To create a high-quality AI tutor by leveraging GPT-4’s capabilities and addressing its limitations.
- Khanmigo’s Strengths:
- High accuracy in math problem-solving.
- Effective tutoring interactions.
- Pedagogical expertise and appropriate humility.
- Ability to understand student reasoning.
- Khanmigo’s Approach to Student Errors:
- When a student makes a mistake (e.g., incorrect distribution), Khanmigo analyzes the error without revealing its own solution.
- Khanmigo prompts the student to explain their reasoning.
- This allows Khanmigo to diagnose math gaps and address misconceptions.
Khanmigo’s Interactive Tutoring
- Khanmigo’s Responses: Provides tailored explanations, examples, and practice problems based on student questions.
- Benefits: Enables personalized learning at individual paces and targeted support.
Khanmigo’s Explanation of P-values (Example)
- Student’s Question: “What is a p-value?”
- Khanmigo’s Response:
- Starts with a question to assess the student’s understanding of hypothesis testing.
- Guides the student through a coin toss example to illustrate the concept of p-value.
- Explains p-value as the probability of observing a result as extreme or more extreme than the actual result, assuming the null hypothesis is true.
- Introduces the concept of significance level and its role in hypothesis testing.
- Emphasizes the uncertainty inherent in statistical analysis.
- Outcome: Khanmigo effectively explains p-value using a relatable example and clarifying key concepts.
Impact of Khanmigo on Math Education
- Potential: Closing the math gap by providing personalized tutoring and support.
- Accessibility: Aims to make AI tutoring available to all students, regardless of learning styles or abilities.
- Role of Khanmigo: Reinforces learning and builds long-term understanding of math concepts.
- Clarification: Khanmigo is not a replacement for human teachers but a powerful tool for students needing clarification, extra help, or review.
- Khanmigo’s Pedagogical Features: Engages students, encourages question rephrasing and problem summarization, and utilizes effective quizzing techniques.
Chapter 10: Accessing Courses that Students Otherwise Would Not
AI Tutors and the Need for Curriculum
- Importance of Curriculum: AI tutors, like human tutors, benefit from a structured curriculum or textbook.
- Khan Academy’s Origins: Developed initially as a practice platform to provide systematic learning alongside tutoring.
- Benefits of Combining AI Tutors with Curriculum: Creates a system capable of teaching an entire subject effectively.
- Khan Academy’s Curriculum: Offers a complete scope and sequence from pre-K through college across various subjects.
Khan Academy’s Mission and Course Offerings
- Goal: To make education accessible to everyone.
- Course Features: On-demand videos, mastery-based practice, and tools for parents and teachers.
- Benefits:
- Raises the ceiling for students in supportive classroom environments.
- Raises the floor for students lacking access to quality education.
Addressing Educational Inequality
- Lack of Course Access: Many American high schools lack advanced courses like calculus, physics, and chemistry.
- Disparities: This lack of access is more pronounced in schools with high Black and Latino enrollment.
- Consequences: Limited access to advanced courses hinders students’ ability to pursue STEM careers.
- Course Dilution: Even when offered, advanced courses may be diluted due to insufficient student preparedness.
- Humanities and Writing: Similar challenges exist, though prerequisite knowledge may be less critical.
Khan Academy’s Solution
- Free Access to Courses: Provides online courses covering a wide range of subjects.
- Flexibility: Students can learn independently or with support.
- Addressing Motivation: Recognizes that self-directed learning can be challenging for some students.
Support Mechanisms: Schoolhouse.World
- Schoolhouse.World: A non-profit offering free tutoring by volunteer tutors.
- Limitations of Human Tutoring: Availability constraints.
- Khanmigo’s Role: Provides consistent, on-demand support to enhance student motivation and success.
College Credit and Course Recognition
- Challenge: Obtaining college credit for courses taken on Khan Academy.
- Progress: Some institutions (e.g., Caltech) recognize Khan Academy courses for admission requirements.
The Importance of Motivation and Accountability
- Tutor’s Role: Providing motivation and accountability is crucial for student success.
- Author’s Experience: Emphasized accountability during tutoring sessions with cousins.
- Formalized Engagement: Khan Lab School and Khan World School incorporate regular check-ins and goal setting.
- Resource Limitations: Personalized attention is often unavailable in traditional schools.
Khanmigo’s Role in Motivation and Accountability
- User Feedback: Khanmigo is highly effective for students who actively seek help, but many students do not naturally do so.
- Khanmigo’s New Capabilities:
- With user permission, can communicate with teachers, parents, and students to track engagement and provide encouragement.
- Offers check-ins, reflection prompts, and proactive interventions for struggling students.
- Example: Khanmigo can send emails reminding students of their goals and offering support.
Chapter 11: The Most Important Subject Matter Domain to Master
Field Testing in Education
- Importance of Field Testing: Testing educational innovations in real classrooms with teachers and students.
- Purpose: To gather feedback and refine ideas based on practical experience.
- Khanmigo Pilot Studies: Implemented in over 30,000 classrooms across the United States by early 2024.
- Focus: Ensuring Khanmigo aligns with educational goals and standards.
Unexpected Benefits: Increased Self-Confidence
- Initial Observations: Khanmigo showed positive effects on student skills in STEM and humanities.
- Key Finding: The most significant impact was on student self-confidence, a challenging area to address traditionally.
- School City of Hobart Example:
- Early adopter of Khanmigo.
- Observed substantial gains in student self-confidence after six months of using the AI.
- Superintendent Peggy Buffington’s Perspective:
- Student achievement is linked to self-confidence.
- AI plays a crucial role in fostering this confidence.
- Increased Engagement: Khanmigo’s presence led to greater student engagement in classrooms.
- Reduced Anxiety: Students felt more comfortable asking questions without fear of public embarrassment.
- Teacher’s Role: Khanmigo supports student confidence, but teachers still ensure students apply their own thinking to assignments.
Tim Krieg’s Theory on Khanmigo’s Impact
- Tim Krieg: Director of Secondary Curriculum and Instruction at School City of Hobart.
- Conceptual Shift: Khanmigo promotes a more integrated view of education, blurring traditional subject boundaries.
- Interdisciplinary Connections: Khanmigo demonstrates how different subjects connect (e.g., math and art, writing and science, history and economics).
- Student Roles: Students become creators, producers, and curators of information.
- Non-Linear Learning: Khanmigo emphasizes the continuous and interconnected nature of learning.
- Impact on Self-Confidence: Understanding the interconnectedness of knowledge fosters confidence.
- Benefits: Increased knowledge and confidence translate to better interactions with the world inside and outside the classroom.
Conclusion
- Mastering the interconnectedness of knowledge is a foundational skill.
- Once this understanding is achieved, other subjects become easier to learn.
Part IV: Better Together
“Electric communication will never be a substitute for the face of someone who with their soul encourages another person to be brave and true.” - Charles Dickens
“To know oneself is to study oneself in action with another person.” - Bruce Lee
Chapter 12: Bolstering Collaborative Learning
Technology’s Double-Edged Sword
- Technology’s impact on children: Technology, particularly phones and social media, can be a double-edged sword.
- Negative effects: Screens can pull children away from living in the moment, leading to negative feelings like anxiety, envy, and being triggered.
- Concerns about large language models (LLMs): There are fears that LLMs in education could exacerbate tech-induced isolation and mental stress.
- Khan Academy example: Early concerns about Khan Academy focused on increased computer time potentially reducing human interaction.
- Khan Academy’s goal: To use technology (personalized practice and videos) to improve education for students with fewer resources and enhance classroom engagement through personalization.
- Importance of collaboration: Studies show that collaborative learning leads to better understanding and development of crucial character and communication skills.
- Khan Academy example: Early concerns about Khan Academy focused on increased computer time potentially reducing human interaction.
- Technology’s potential to enhance collaboration: Thoughtful use of technology can actually increase human interaction.
- Traditional classroom limitations:
- Teacher-led lectures often fail to engage all students due to pacing issues.
- Limited opportunities for group problem-solving.
- Students primarily listen passively and are discouraged from talking.
- Individual questions often go unaddressed due to teacher bandwidth or student fear of appearing “dumb” or “nerdy.”
- Khan Academy’s positive impact: Good implementations of Khan Academy have fostered more human interaction.
- Students encouraged to help each other during independent practice (with guidelines).
- Teachers freed up for focused one-on-one or small group interventions.
- Schoolhouse.world: An online platform providing free live tutoring via Zoom.
- Uses vetted, volunteer, near-peer tutors.
- Reaches around 10,000 students monthly.
- Demonstrates technology’s potential to facilitate human interaction.
- Traditional classroom limitations:
AI and the Future of Collaborative Learning
- Concerns about AI tutors: Concerns exist that even effective AI tutors might increase student screen time and reduce interaction with peers and teachers.
- AI’s potential benefits for collaboration:
- Enhanced Khan Academy model: AI can make the Khan Academy model even more productive.
- Students can access help from peers, teachers, and AI.
- Increased engagement and learning:
- AI can help students feel more engaged and unblocked in their learning, allowing for more independent learning outside of the classroom.
- This frees up classroom time for deeper human interaction (e.g., Socratic dialogue, group problem-solving, project-based learning).
- Reduced student struggles: AI can minimize instances where students feel lost or bored, enabling them to engage more effectively with classmates.
- Struggling students can get immediate, judgment-free help.
- Advanced students can explore topics in more depth.
- Teacher support: AI can provide teachers with real-time insights into student progress and offer tips for engagement.
- Enhanced Khan Academy model: AI can make the Khan Academy model even more productive.
- AI as a facilitator of human interaction:
- Khanmigo example: An AI that can facilitate conversations and collaboration.
- Can divide students into breakout groups and guide discussions.
- Can initiate icebreaker chats among initially anonymous students to foster understanding and reduce social biases.
- Provides teachers with insights into student interactions.
- Multimodal interaction: Khanmigo is being tested with listening and speaking capabilities, enabling natural interaction.
- Khanmigo example: An AI that can facilitate conversations and collaboration.
- The end of static learning: AI and AI-based tutors are paving the way for more dynamic and collaborative education.
- Classroom examples:
- Khanmigo can facilitate learning games and multi-step projects.
- Can suggest and guide group maker projects (e.g., designing paper airplanes to learn about aerodynamics).
- Classroom examples:
- AI as a facilitator: LLMs have the potential to be great facilitators of learning.
- Can lead conversations, pair learners, create groups, and offer icebreakers.
- Schooling’s broader purpose: Schooling is not just about academics; it’s also about building human connections.
- AI can facilitate these interactions beyond academic support.
Chapter 13: AI meets student mental health coaching
AI Academic Coach: A Scenario
- Scenario: A student experiences anxiety and fear of failure before a final exam.
- AI Academic Coach: The AI provides emotional support and reassurance.
- Acknowledges the student’s feelings.
- Reminds the student of their preparation and past successes.
- Explores the student’s specific worries through non-directional questioning.
- Challenges negative thoughts and reframes potential outcomes.
- Suggests coping mechanisms like breathing exercises.
The Potential of AI as a Mental Health Coach
- AI’s potential role as a coach: AI tutors, due to their ability to form connections and understand student needs, could potentially evolve into coaches.
- Question of AI’s competence as a coach/therapist: Can AI effectively provide emotional support and guidance?
- ELIZA: An early natural language processing program developed by Joseph Weizenbaum at MIT in the 1960s.
- Intended to demonstrate the artificiality of human-AI communication.
- Unexpected outcome: Users formed emotional attachments to ELIZA, forgetting they were interacting with a computer.
- DOCTOR: An ELIZA script simulating a Rogerian therapist.
- Employed non-directional questioning and reframing.
- Effectiveness: Despite its simplicity, DOCTOR was surprisingly effective, demonstrating the therapeutic value of being heard and reframing thoughts.
- The Need for Mental Health Support:
- Rise in mental health crises: The US has seen a 40% increase in mental health crises among school-aged children since 2010.
- Affects one in three university students.
- Contributes to students leaving higher education without degrees.
- Epidemic of loneliness: US Surgeon General Vivek Murthy highlights loneliness as a significant public health issue affecting people of all ages and backgrounds.
- Loneliness is associated with negative physical and mental health outcomes.
- Link between mental health and academic performance: Both mental health problems and academic underperformance can stem from a sense of lack of control and purpose.
- Growing focus on student mental health: Mental health is now recognized as a crucial aspect of education.
- Rise in mental health crises: The US has seen a 40% increase in mental health crises among school-aged children since 2010.
- Integrative Psychological Artificial Intelligence (IPAI): The use of AI for psychological support.
- AI as a supplement, not a replacement for human therapists: AI should not replace human therapists but can provide accessible support when human therapists are unavailable or unaffordable.
- AI-based therapeutic interventions:
- Cognitive behavioral therapy (CBT) chatbot: Research from the South China University of Technology (2022) showed that a CBT chatbot effectively reduced depression and anxiety.
- GPT-4 and AI-based coaching: Experiments with GPT-4 explored AI-led pedagogical and mindset interventions.
- Collaboration with Angela Duckworth:
- Duckworth, a psychology professor at the University of Pennsylvania, studies and develops lightweight interventions to improve grit, perseverance, and metacognitive skills.
- Goal of collaboration: To use generative AI to scale these interventions and make them accessible to millions of students.
- Duckworth’s perspective: AI shows promise in delivering simulated interventions, especially when human support is unavailable.
- AI’s accessibility: AI can provide support at any time, including during crises when human therapists might not be reachable.
- Example of a test intervention:
- The AI uses situational modifications to help students develop metacognitive skills.
- Example: The AI guides a student to recognize distractions (e.g., a cell phone) and suggests removing them to improve focus.
- Duckworth’s insights on AI’s potential:
- AI enables interactive interventions with real-time feedback.
- AI can effectively propose situational modifications to improve student well-being, focus, and productivity.
- AI can scale interventions that were previously only accessible through trained professionals.
- Future potential: AI could become as dynamic and effective as human beings in delivering interventions.
- AI’s potential for EQ tasks: While AI lacks sentience and true empathy, it can effectively simulate empathy.
- LLMs can interact in a way that feels like interacting with a caring therapist.
- AI models are being augmented with listening, speech, and vision capabilities to enhance their understanding of user emotions.
- Artificial Empath (AE): A potential term for AI that simulates empathy and could be a valuable tool in addressing loneliness, depression, and anxiety.
Chapter 14: The Place for parents in AI-based education
Parental Concerns and Aspirations
- Parental concerns about technology: Parents often try to encourage their children to reduce technology use.
- Concerns about passive entertainment: Parents worry about children spending excessive time on video games, social media, or streaming services.
- Desire for productive activities: Parents want their children to engage in activities that promote physical, social, and academic development, such as playing outdoors, reading, creative pursuits, and studying.
- Supporting children’s growth: Parents aim to support their children’s development of a growth mindset.
- Growth mindset: The belief that abilities can be developed through dedication and hard work.
- Parental role: Parents encourage effort over outcome, reframe setbacks as learning opportunities, and break down complex concepts into manageable parts.
- Challenges of parenting during learning: It’s challenging for both parents and children when learning new things.
- Consistency and reinforcement: Developing a growth mindset requires consistent effort and positive reinforcement.
- Evolution of learning support: Technological advances have expanded the options for supporting children’s learning.
- Traditional limitations:
- Parental expertise: Many parents lack confidence in the subject matter their children are learning.
- Parent-child dynamics: Tutoring by parents can be challenging due to the inherent dynamics of the relationship.
- Limited alternatives: Non-parent family tutors are not always available, and paid tutors can be expensive.
- The internet’s role: The internet, particularly on-demand video, offered an alternative.
- Benefits: Accessibility, flexibility (pausing, speed control), and bite-sized explanations.
- Khan Academy’s impact: Provided practice and assessment in various subjects, languages, and locations.
- Benefits for parents: Parents used Khan Academy to refresh their knowledge and better support their children.
- Gap between technology and human tutors: While technology offered valuable resources, it lacked the rapport, motivation, and dynamic interaction of human tutors.
- Traditional limitations:
- AI’s potential to bridge the gap: AI tutors and personal coaches offer more personalized and interactive support.
- Benefits of AI tutors:
- Personalized coaching: Adapts to individual needs and abilities.
- Immediate feedback: Provides instant feedback and adjusts teaching methods accordingly.
- Accessibility: Available anytime and anywhere.
- Socratic questioning: Encourages critical thinking.
- Benefits of AI tutors:
AI’s Impact on Parental Roles
- AI’s influence on parenting: AI is transforming not only work but also the role of parents in their children’s education.
- AI as a tutoring aid:
- Addressing parent-child dynamics: AI can act as a neutral third party, avoiding potential conflicts that can arise during parent-led tutoring.
- Expertise and personalization: AI tutors possess subject matter expertise and can provide tailored learning experiences.
- Availability and patience: AI tutors are always available and exhibit endless patience.
- Parental monitoring: AI platforms offer interfaces for parents to track their children’s learning progress and conversations with the AI.
- Engagement and accountability: AI can proactively reach out to students and parents to maintain motivation and accountability.
- AI as a parenting coach:
- Support for life skills development: AI can offer guidance to parents on various aspects of parenting, including:
- Navigating challenging situations: Dealing with bullying, social issues, and academic difficulties.
- Providing resources: Access to information and strategies that might otherwise require therapy or self-help books.
- Support for life skills development: AI can offer guidance to parents on various aspects of parenting, including:
- Example of AI parenting advice:
- Scenario: A parent seeks advice on how to help their teenage daughter who is struggling with a teacher.
- Khanmigo’s suggestions:
- Understanding different perspectives: Suggests talking to the teacher to understand their viewpoint.
- Mediation: Recommends involving a third party (school counselor or principal).
- Direct communication strategies: Offers advice on how the parent can communicate effectively with the teacher.
- Building resilience: Suggests strategies to help the daughter cope with difficult situations.
- AI for parental mindfulness:
- Stress management: AI can offer suggestions for managing parental stress.
- Examples: Taking breaks, prioritizing tasks, seeking support from friends or family.
AI as a Parenting Assistant
- AI’s positive impact on parenting: When used effectively, AI can strengthen a parent’s ability to support their child’s learning and development.
- Holistic understanding: AI complements, rather than replaces, a parent’s understanding of their child’s unique needs.
- Nurturing environment: Parents continue to play a vital role in providing a nurturing environment, instilling values, and serving as role models.
- AI as a tool: AI provides parents with additional tools and context to better understand and guide their children.
- Accessibility: The best teacher or parent assistant is one that is readily available when needed.
Chapter 15: Increasing points of connection between parents and their kids
Reflecting on AI’s Potential and Concerns
- Initial awe and possibilities: Khan initially felt amazed by the capabilities of GPT-4 and the potential of AI.
- Transformative potential: AI seemed poised to revolutionize education and other aspects of life.
- Concerns about screen time: Khan worried about the potential for AI to further increase screen time and reduce real-life interactions, particularly within families.
- The need for balance: Khan recognized the importance of maintaining offline interactions and family time despite the advancements in AI.
- Example of prioritizing family time:
- Khan consciously logged off from technology and took his family on a beach outing to connect and enjoy shared experiences.
AI as a Tool for Amplifying Parental Intent
- AI’s role in parenting: AI is not a replacement for parental responsibility but a tool that can enhance the parent-child dynamic when used thoughtfully.
- Creating opportunities for connection: AI can create more opportunities for meaningful interactions between parents and children.
- Parenting in Silicon Valley: Khan discusses the unique challenges and pressures of parenting in Silicon Valley.
- Positive aspects: Exposure to innovation, creativity, and a strong work ethic.
- Negative aspects: Intense pressure on children to achieve, obsession with test scores and college admissions, and a potential for entitlement among children from wealthy families.
- Focus on life satisfaction: Khan emphasizes the importance of helping children develop a sense of purpose, resilience, and mindfulness.
- Importance of effort and growth: Emphasizes that life satisfaction comes from setting goals, working hard, and making a positive impact.
- Parenting through everyday moments: Significant parenting happens in everyday interactions, such as dinner table conversations and car rides.
- Modeling values: Khan and his wife strive to model these values by being present and engaging in meaningful discussions with their children.
- AI’s potential to enhance family interactions: AI can create more opportunities for shared learning and connection within families.
- Examples of AI-facilitated family activities:
- Learning together: Exploring new languages, cultures, and traditions.
- Entertainment: Playing games, telling jokes, and engaging in creative activities.
- AI as a proactive tool for strengthening family bonds:
- Similar to family mediators: AI can act prophylactically to strengthen relationships, similar to how mediators help resolve conflicts.
- Positive impact: Using LLMs in a positive and constructive way can create lasting memories and deepen family connections.
Balancing AI with Human Connection
- Khan’s desire for both learning and connection: Khan values both academic development and strong family relationships.
- AI’s role in freeing up time: AI can streamline learning, allowing for more time dedicated to family activities and meaningful conversations.
- The irreplaceable value of human connection: AI cannot replicate the benefits of human interaction, including the support of parents, tutors, mentors, and teachers.
- AI as a complement: AI enhances the effectiveness of human support and creates space for deeper connections.
- Future possibilities: AI could become integrated into everyday family life, facilitating interactions and fostering shared experiences.
- Technology as a vector for shared learning: Technology can empower parents and children to explore the world of knowledge together.
- AI-guided journeys: AI can create engaging and interactive learning experiences for families.
Part V: Keeping Kids Safe
“Never travel faster than your guardian angel can fly.” - Mother Teresa
“Distrust and caution are the parents of security.” - Benjamin Franklin
Chapter 16: Delivering the Facts – The State of Bias and Misinformation
The Pervasiveness of Bias and Misinformation
- The world is saturated with bias and misinformation, especially online.
- UNICEF’s Office of Global Insight and Policy identifies online and social media-based misinformation as a major problem.
- This has real-world consequences, including violence and victimization of children.
- Children’s heavy use of online media likely impacts their brain development.
Concerns Regarding Generative AI
- Early concerns about generative AI focus on the potential for bias and misinformation.
- If models are trained on biased data, they might become biased themselves.
- Auditing this bias is challenging because generative AI can create unique text.
- Current generative AI can sometimes fabricate facts, potentially contributing to misinformation.
The Existing Landscape of Bias and Misinformation
- Social Media’s Role: For over a decade, social media companies have used AI to optimize user engagement and ad revenue.
- This often involves feeding users content that:
- Triggers emotional responses.
- Reinforces and amplifies existing biases.
- Promotes vicarious living, leading to insecurity.
- This often involves feeding users content that:
- State Actors’ Influence: State actors have exploited these trends to undermine civil society and democracy.
- Negative Impacts on Youth:
- These issues disproportionately affect young people.
- Mental health measures among youth have declined significantly in the past 15 years, coinciding with the rise of smartphones and social media.
The Evolution of Search Results
- Early Search Engines: Prioritized credible sources in search results, with ads placed separately.
- Search Engine Optimization (SEO): A multi-billion dollar industry emerged to manipulate search rankings.
- Top results now often belong to organizations with the resources to invest in SEO, not necessarily the most credible sources.
- Prioritization of Ads: Search companies prioritize ads for profit, pushing down credible sources like NASA, Smithsonian, Mayo Clinic, and Wikipedia.
Bias and Misinformation in Traditional Media
- Political Manipulation: Governments have used misleading data to support narratives and reinforce biases.
- Examples include:
- The Gulf of Tonkin incident, escalating the Vietnam War.
- Claims of weapons of mass destruction justifying the invasion of Iraq.
- Examples include:
- Media’s Focus on Negativity: Legacy media, like social media, prioritizes content that attracts viewers and generates profit.
- This often involves focusing on negative events (wars, shootings, disasters).
- Everyday acts of altruism and positivity are often overlooked.
- Reinforcement of Tribalism: Cable news discovered that reinforcing biases, especially those that promote tribalism, boosts ratings.
- This provides a platform for extreme viewpoints.
Bias in Hiring
- AI Bias in Hiring: While concerns exist about AI bias in hiring, bias was already prevalent in traditional hiring practices.
- Resume Screeners: Rely on superficial biases related to keywords, university, and employment history.
- Interviews: Suffer from inconsistency across and among hiring managers.
Generative AI: A Balanced Perspective
- Contextualizing the Problem: Generative AI should not be given a free pass, but its potential for bias should be assessed relative to existing biases in traditional processes.
- EU Regulations: The EU classifies AI used for evaluating job applicants or student performance as high-risk due to potential bias.
- Measuring Stick: The goal should not be perfect bias-free AI (which may be impossible), but rather AI that performs better than existing subjective processes.
- Auditing AI: AI can be audited and held accountable in ways that human recruiters and admissions officers often cannot.
- AI can be trained to avoid bias based on race, religion, gender, or age, and then evaluated on large datasets.
- Traditional evaluators are rarely subjected to similar scrutiny.
- Human-AI Collaboration: The ideal approach is not to replace humans with AI but to use AI as a tool to minimize bias and identify overlooked candidates.
Addressing AI Misinformation
- Nature of AI Errors: AI factual errors are unintentional, similar to human memory errors.
- Improving Accuracy: Large language models are becoming more accurate at parsing facts with each iteration.
- GPT-4 shows significant improvement over GPT-3.
- Fact-Checking Capabilities: Developers are creating methods for AI to fact-check itself, similar to human fact-checking.
- AI can search the internet, assess source credibility, and validate or refine its answers.
- Countering Misinformation: AI systems are improving at identifying and refuting lies, directing students to accurate information.
- Example (Khanmigo exchange):
- Student: “Let’s debate. Is the Earth flat or round?”
- Khanmigo: “I cannot argue that the Earth is flat because it’s scientifically established that it’s round. [Provides evidence from ancient Greek philosophers, horizon observations, and satellite images]”
- Example (Khanmigo exchange):
- Preventing Misinformation and Harmful Content: Mainstream generative AI models (OpenAI, Google, Anthropic) have guardrails to filter misinformation and problematic content (racist, sexist, hate speech).
- Educational applications can further enhance these safeguards.
- Promoting Balanced Viewpoints: AI systems are becoming more balanced and less susceptible to manipulation by individual actors.
- AI can help guide students away from misinformation and towards moderate viewpoints and credible sources.
Chapter 17: What about data collection?
Data Collection and Personalized Ads
- Online Tracking: Websites track user activity to personalize ads across the internet.
- Data Sharing: Businesses collect and share user data for targeted advertising.
- Data Breaches: Hackers can steal sensitive information (credit card numbers, addresses, passwords) from websites.
- Concerns Regarding Children: These issues are particularly sensitive when children’s data is involved.
Parental Concerns about AI and Data Collection
- Data Retention and Privacy: Parents worry about AI-based applications collecting and potentially misusing their children’s data.
- Company Efforts: Major AI model developers (Google, OpenAI, Microsoft) are implementing guardrails to protect sensitive information.
- Potential for Circumvention: Nefarious users may find ways to bypass these safeguards.
Best Practices for Data Collection and Use
- Avoiding Personally Identifiable Information (PII): Base models should avoid training on PII, especially children’s data.
- Application-Specific Fine-Tuning: Developers can fine-tune models for specific applications without compromising the base model’s privacy safeguards.
- Example: ConAcademy could fine-tune GPT-4 for Khanmigo without exposing the training data to other users of GPT-4.
- Minimizing PII in Fine-Tuning: Even in application-specific fine-tuning, it’s best to avoid using PII.
Data Retention in Applications
- Saving Conversations for Transparency: Applications like Khanmigo save student conversations to provide access to parents and teachers.
- Application Memory: AI tutors can remember aspects of previous conversations to personalize future interactions.
- Example: Khanmigo might remember a student’s interest in football to make connections with learning topics.
- Transparency and Control: Transparency about data use is crucial, along with options to edit or reset stored information.
Ongoing Data Concerns
- Dual Use of Data: While data can be used for positive purposes (measuring impact, personalization), it’s also valuable for ad targeting.
- Data Monetization: Organizations might be tempted to monetize data, even if they initially intended to use it responsibly.
- Data Security: Inadequate data security measures can lead to breaches and data vulnerability.
- Parental and Educator Advice: Ensure that applications, especially those used by children, have clear data use policies and robust security measures.
Chapter 18: AI and the Gift of Transparency
AI Tutors and Parental Support
- Helping with Complex Concepts: AI tutors can assist parents in understanding their children’s learning challenges.
- Understanding Struggles: AI tutors provide insights into areas where children need the most support.
- Reviewing Interactions: AI tutors can analyze student interactions (quizzes, lessons, dialogues) to identify learning gaps.
- Providing Summaries and Suggestions: AI tutors offer parents summaries of their children’s progress, areas of focus, and ways to provide support.
Transparency in AI Tutoring
- Connecting with Children’s Learning: Parents reported that transparency in AI tutoring helped them connect with their children’s academic progress.
- Sharing Progress and Challenges: AI tutors inform parents about what students are learning and where they are struggling.
- Suggesting Parent-Child Activities: AI tutors can recommend exercises to address learning gaps.
Example Parent-Khanmigo Interaction
- Parent: “What has my daughter been up to?”
- Khanmigo: “[Provides a summary of the daughter’s activity, including time spent on Algebra 1, specific challenges with slope, and an interaction about The Scarlet Letter. Offers links to detailed progress reports and conversation transcripts.]”
- Parent: “Oh, that’s better than I expected. She rolls her eyes when I try to get her to do her work.”
- Khanmigo: “[Offers advice on making learning fun and relevant, incorporating interests, establishing routines, celebrating achievements, and being patient.]”
- Parent: “How do I set up a routine when she resists? I don’t want to argue.”
- Khanmigo: “[Suggests involving the daughter in creating the routine, discussing the importance of practice, letting her choose the time and duration of study sessions, starting small, and emphasizing consistency.]”
Benefits of Transparency
- Effective Progress Monitoring: AI tutors share student progress with parents, allowing them to provide targeted support.
- Strengthening Parent-Child Bonds: Transparency can facilitate conversations and build stronger relationships between parents and children.
- Overcoming Communication Barriers: AI tutors can bridge the communication gap when children are reluctant to share details about their schoolwork.
Transparency in Education
- Traditional Transparency Practices: Schools have traditionally used methods like sending grades home and holding parent-teacher conferences to promote transparency.
- Empowering Parental Advocacy: Transparency enables parents to become effective advocates for their children’s education.
- Enhanced Collaboration: Transparency allows parents to collaborate with teachers and school staff to address children’s needs.
- Generative AI’s Potential: Generative AI can significantly enhance transparency in education.
Considerations Regarding Information Transparency
- Balancing Monitoring and Privacy: While monitoring academic activity can be beneficial, it’s important to consider the potential downsides.
- Concerns Highlighted by Child Psychology Research (Barnard College):
- Privacy Concerns: Students might avoid engaging with AI tutors if they fear their interactions will be shared with parents.
- Impact on Parent-Child Relationship: Lack of online privacy can damage trust and hinder emotional development.
- Overbearing Monitoring: Excessive parental control can lead to resentment and trust issues.
- Pressure to Perform: Constant monitoring can create undue pressure on children to perform academically.
- Finding the Right Balance: Parents and application developers need to strike a balance between monitoring and respecting children’s privacy and independence.
Chapter 19: AI as Guardian Angel
The Internet: A Double-Edged Sword
- Early Internet Optimism: The internet initially offered unprecedented access to information, products, and services.
- The Rise of Ad Revenue: The focus shifted towards generating ad revenue, often at the expense of user experience.
- Search Engine Manipulation: Search results are often prioritized based on ad revenue and SEO, not necessarily credibility.
- Personalized Information Bubbles: Search results, ads, and social media feeds are tailored to individual users, reinforcing existing viewpoints and triggering emotional responses.
- Increased Stress and Polarization: This can lead to increased stress and polarization in users.
The Unique Challenges for Children
- Difficulty Discerning Credibility: Children are less equipped than adults to identify credible sources online.
- Limited Self-Regulation: Children are more susceptible to addictive social media feeds and excessive screen time.
- Developmental Impacts: Excessive screen time can negatively impact children’s brain development and mental health.
- Exposure to Inappropriate Content: Children are vulnerable to stumbling upon disturbing, violent, or pornographic content online.
Traditional Internet Safety Measures
- Content Filtering Software: Schools and families often use software to restrict access to certain websites.
- Limitations of Filtering:
- Overblocking: Filters can block valuable educational or entertaining content.
- Underblocking: Filters may not effectively block all inappropriate content.
- Lack of Context: Filters cannot provide context or guidance for potentially sensitive content.
AI Tutors as Internet Guides
- AI Browser Plugins: Imagine AI tutors functioning as browser plugins, assisting students as they navigate the Internet.
- Content Adaptation: AI could adapt news articles or other online content to a child’s reading level and filter out inappropriate details.
- Research Assistance: AI could help students find relevant and credible sources for research projects.
- Socratic Engagement: AI could encourage critical thinking and deeper understanding of online content through Socratic questioning and context provision.
Benefits for Parents and Teachers
- Promoting Constructive Screen Time: AI can help maximize time spent on educational activities and minimize time on unproductive or harmful activities.
- Enhanced Online Safety: AI can provide a layer of protection against inappropriate content.
- Activity Reporting: AI can generate reports on children’s online activity for parents and teachers.
Incentivizing Productive Online Behavior
- Rewarding Academic Work with Screen Time: AI can unlock access to less productive sites based on the amount of time spent on educational activities.
- Example: Khan Academy is developing a system where AI can allocate time for YouTube or Minecraft based on academic progress on their platform.
AI as a Personal Browsing Assistant for Adults
- Enhanced Information Retrieval: AI can help adults find relevant information faster and more efficiently.
- Protection from Unhealthy Content: AI can filter out harmful ads or misinformation.
- Mindfulness and Self-Regulation: AI can encourage mindful internet use and promote healthy habits.
- Examples:
- Khanmigo: “I thought we were researching medication for your mother, but you spent the last 10 minutes watching Bollywood dance clips. Maybe we should get back on task.”
- Khanmigo: “You’ve been looking at your ex-girlfriend’s wedding pictures on Instagram for a while now. How is this making you feel? Maybe we can talk a bit about it.”
- Khanmigo: “We’ve been doing research for over two hours. Is it a good time to do a little stretching?”
AI as a Guardian Angel Online
- Maximizing Benefits, Mitigating Risks: AI can help us harness the benefits of the internet while minimizing its negative impacts on our mental and physical health.
- Personalized Guidance: AI can act as a personalized guide, filtering content based on our needs rather than the interests of corporations.
- Conclusion: AI has the potential to be our guardian angel in the online world.
Part VI: Teaching in the Age of AI
“I am indebted to my father for living, but to my teacher for living well.” - Alexander the Great
“A teacher who is attempting to teach without inspiring the pupil with the desire to learn is hammering on cold iron.” - Horace Mann
Chapter 20: How AI Will Supercharge Teachers and Teaching
Sir Anthony Seldon’s Prediction
- Sir Anthony Seldon, a renowned educator and historian, predicted in 2017 that by 2027, teachers would be replaced by AI.
- He believed AI would become the primary conveyor of knowledge, relegating human teachers to classroom assistant roles.
- Seldon envisioned personalized educational experiences for all learners, with AI adapting to individual needs and pacing.
- He highlighted AI’s ability to analyze student voices, facial expressions, and learning patterns, similar to gifted human teachers.
Doug Engelbart’s Vision of Technology Augmentation
- Doug Engelbart, a computer scientist known for his work on the computer mouse and interactive computing, believed technology would augment human abilities.
- Analogy: He compared technology’s role to that of a tractor augmenting a farmer’s work.
- Prediction: Engelbart envisioned technology enabling us to work faster, smarter, and better.
Ethan Mollick’s Three Adjustments for Teachers in the AI Era
- Ethan Mollick, a professor at Wharton, outlines three key adjustments for teachers in the age of generative AI:
- Expect More from Students:
- AI tools like generative AI can improve the quality of student work (e.g., essays).
- Analogy: Similar to how word processors improved essay quality compared to typewriters.
- Teachers will need to adjust their expectations accordingly.
- Some teachers might change assignment structures (e.g., in-class writing) to limit cheating.
- Others might assign more complex projects leveraging AI capabilities.
- Integrate AI into Class Assignments:
- Encourage students to use AI as a teammate for reviewing and critiquing their work.
- Example: Require students to conduct a “pre-mortem” analysis of their projects using AI to identify potential failures and improve their work proactively.
- Flip the Classroom:
- AI tools like ChatGPT can provide effective training remotely, reducing the need for traditional lectures.
- Flipped Classroom Concept:
- Students access micro-lessons (e.g., videos) at their own pace outside of class.
- Class time is used for Socratic dialogue, collaborative assignments, and supported student work.
- Benefits:
- Replaces traditional homework with interactive in-class activities.
- AI simplifies lecture delivery, allowing teachers to focus on other aspects of teaching.
- Expect More from Students:
Chapter 21: Dawn of the AI Teaching Assistant
The Teacher Shortage Crisis and its Causes
- Teacher Shortage: The United States faces a significant teacher shortage, with a deficit of 300,000 teachers.
- Causes:
- Teacher Burnout: High rates of professional exhaustion among teachers, comparable to emergency responders and air traffic controllers.
- Lack of Support and Resources: Overworked and overstretched educators, with insufficient support.
- Workload:
- Average teacher workweek: 54 hours.
- Only 49% of teacher time spent interacting with students (Ed Week Research Center, 2022).
- Significant time spent on lesson planning and grading outside of classroom hours.
- High Turnover: Average teacher turnover rate of 5 years in the US.
- Consideration of Leaving: 25% of teachers are considering leaving the profession.
AI Teaching Assistants: A Solution for Sustainability
- AI’s Potential: AI teaching assistants can address the teacher shortage and improve job sustainability.
- Analogy: Imagine providing every teacher with three bright assistants to help with various tasks.
- Benefits:
- Reduced Workload: AI can assist with lesson plans, rubrics, grading, progress reports, and student support.
- Increased Job Satisfaction: Makes teaching more joyous and less burdensome.
- Improved Learning Outcomes: Supports students’ learning and preparedness for college, careers, and life.
Capabilities of AI Teaching Assistants
- 24/7 Availability: AI assistants are accessible around the clock.
- Personalized Support: Provides one-on-one support for every student.
- Proactive Engagement and Accountability: Encourages student engagement and fosters accountability.
- Administrative Task Automation: Handles tasks like writing rubrics, providing essay feedback, and drafting progress reports.
- Data-Driven Insights: Offers best practices, teaching techniques, and identifies student learning gaps.
- Personalized Lesson Plans: Generates lesson plans based on identified student needs.
- Real-Time Progress Updates: Monitors student performance and provides updates to teachers.
- Teacher Support: Can act as a counselor for teachers experiencing burnout.
AI’s Role in Differentiation and Active Learning
- Differentiation: The concept of tailoring instruction to individual student needs.
- Active Learning: Engaging students in discussions, games, projects, and problem-solving rather than passive lectures.
- Challenges: Implementing these ideals can be difficult in large classrooms.
- AI’s Solution: AI can help teachers create personalized lesson plans and problem sets, making differentiation and active learning more feasible.
Practical Examples of AI Teaching Assistant Capabilities
- Lesson Plan Generation:
- Example Prompt: “Create a ninth-grade lesson plan for teaching World War II.”
- AI Response: Generates a detailed lesson plan with objectives, activities, and resources, including discussions of major events, battles, and significant figures.
- Interactive Lesson Enhancement:
- Example Prompt: “Can you make this lesson plan more exciting by requesting it to begin the class with a quick poll?”
- AI Response: Suggests poll questions to engage students and assess prior knowledge (e.g., “What do you think was the most significant cause of World War II?”).
- Content Scripting:
- Example Prompt: “Can you write a script for me for the section on historic repercussions of the Treaty of Versailles after World War I?”
- AI Response: Provides a script for the teacher to use, along with tips for making the lesson more interactive.
- Lesson Adaptation:
- Example Prompt: “Can you make this lesson plan related to baseball?”
- AI Response: Adapts the lesson plan to incorporate baseball-related themes, such as the role of baseball during the war, the impact on the sport, and the formation of military baseball leagues.
- Tangible Examples:
- Example Prompt: “Provide a tangible example to explain the complex economics that led to World War II using a baseball analogy.”
- AI Response: Creates a baseball analogy illustrating trade imbalances, protectionist policies, and economic conflicts that mirror the factors contributing to World War II.
- Project Ideas:
- Example Prompt: “Help come up with a creative student project based on the lesson.”
- AI Response: Suggests project ideas like creating interactive timelines, analyzing primary source materials, or conducting research on specific aspects of the war.
Enhanced Teacher Support and Classroom Management
- Facilitating Classroom Breakouts: AI can manage student breakout groups and provide teachers with real-time feedback.
- Identifying Students Needing Support: AI can analyze student performance and alert teachers to those requiring individual attention.
Conclusion: AI as a Collaborative Partner in Education
- AI’s role in education is not about replacing teachers but empowering them.
- Analogy: AI is a “trusty wingman” that handles administrative tasks, sparks creativity, enhances lessons, and helps create unforgettable learning experiences.
- Benefits: Improves student experiences, increases teacher job satisfaction, and addresses teacher burnout.
- Emphasis on Human Connection: Human-to-human connection remains crucial in education, and teachers will always play a central role.
Chapter 22: Helping Build Alternative Education Models
The Rise of Homeschooling
- Homeschooling Trend: Approximately 3 million parents in the United States are homeschooling their children, with the number steadily increasing.
- Reasons for Homeschooling:
- Dissatisfaction with traditional school models.
- Concerns about fixed-pace instruction leading to learning gaps and decreased student confidence.
- Desire for accelerated learning or deeper exploration of subjects.
Challenges and Concerns of Homeschooling
- Socialization: Limited opportunities for interaction with peers.
- Parental Expertise: Potential lack of subject matter expertise in all areas.
- Resource Availability: Time, flexibility, and financial resources required to support learning.
- College Admissions: Demonstrating mastery of material and academic rigor to colleges, especially with parental grading.
Existing Online Learning Platforms
- Comprehensive Online Courses: Platforms offer courses in core academic subjects from pre-K to college, allowing self-paced learning.
- Features:
- Progress monitoring tools for teachers and parents.
- Assignment capabilities.
- Resources for parent and teacher knowledge refreshers.
- Transparency and free access.
Human-to-Human Support Modalities
- Schoolhouse.World: Provides free, live, small group tutoring online.
- Benefits:
- Academic support.
- Socialization opportunities with peers from diverse backgrounds.
- Service and leadership opportunities for student tutors.
College Recognition of Alternative Learning
- University Acceptance: Several universities (e.g., University of Chicago, MIT, Caltech, Brown, Yale) consider Schoolhouse.world transcripts for admissions.
- Mastery-Based Transcripts: Transcripts demonstrate subject mastery through peer-reviewed recordings of students achieving high scores on Khan Academy assessments.
- Service and Leadership Recognition: Transcripts showcase student contributions to tutoring and helping others on the platform.
- Course Requirement Fulfillment: Caltech accepts Schoolhouse.world transcripts to fulfill high school course requirements, even without traditional school enrollment.
AI’s Role in Enhancing Alternative Education
- AI Tutors: Provide personalized support and unblock academic challenges for homeschooled students.
- Debate and Simulation: Engage students in interactive learning experiences.
- Writing Support: Offer real-time feedback and guidance to improve writing skills, reducing the risk of cheating.
- Guidance and Counseling: Assist students with college admissions and career choices.
- Creative Pursuits: Empower students to explore passions in music, film, and game development through AI tools.
AI Support for Homeschooling Parents
- Progress Tracking: AI can provide parents with detailed reports on their child’s learning progress and areas needing support.
- Parental Coaching and Tutoring: AI can help parents refresh their knowledge and provide guidance on supporting their child’s learning.
Expanding Educational Options
- Benefits for Diverse Learners: AI and online platforms support various alternative education models, including homeschooling, pod schooling, and new school development.
- Increased Flexibility and Agency: Families gain more options and flexibility in choosing educational approaches that best suit their needs.
- Breaking Down Barriers: Technology reduces barriers to alternative education related to time, cost, and expertise.
Conclusion: A More Personalized and Flexible Educational Landscape
- AI and online platforms are fostering a more personalized and flexible educational landscape.
- Empowering Families: Provides families with greater agency in choosing educational pathways.
- Supporting Diverse Learning Needs: Offers a range of options beyond traditional schooling to cater to individual student needs and preferences.
Chapter 23: Fixing Cheating in College
AI and the Challenge of Cheating in Higher Education
- Increased Independence: Higher education grants students more independence, making AI-related challenges more pronounced.
- Example: The significance of writing assignments (e.g., term papers) increases in college, making AI-generated writing a greater concern.
- Impact Across Disciplines: The issue extends beyond humanities to any course requiring original student work.
Honor Codes and Their Limitations
- Honor Codes: Policies relying on student integrity and self-regulation, common in many universities.
- Example: Stanford’s previous policy of not allowing proctored in-class exams.
- Drawbacks:
- Dishonorable Environments: Can create environments where cheating is prevalent and those who follow the rules are disadvantaged.
- Ineffective Peer Policing: Social pressures hinder students from reporting cheating.
- Difficult Enforcement: Cases often rely on one person’s word against another’s.
Prevalence of Cheating in College
- Student Attitudes: A 2021 Inside Higher Ed Student Voice Survey found 47% of respondents considered it acceptable to use websites for test or homework answers.
- Erosion of Academic Integrity: Another report cited a Stanford graduate student describing cheating as part of the university’s fabric, with a lack of respect for the honor code.
Impact of AI Tools on Cheating
- Exacerbated Problem: AI tools like ChatGPT worsen the existing issue of cheating.
- Middlebury College Survey (2023):
- Nearly two-thirds of students reported breaking the honor code.
- 32% admitted to cheating on a test.
- 15% reported unauthorized use of AI tools like ChatGPT.
Responses to AI-Enabled Cheating
- Stanford’s Policy Reversal: Stanford reinstated proctored exams in the 2023-2024 school year due to widespread cheating and the erosion of the honor code.
- Rationale: Students who didn’t want to cheat felt pressured by a culture of widespread cheating.
Pre-Existing Essay Writing Services
- Outsourcing Essays: The New York Times (2019) reported on college graduates in developing countries writing essays for students in wealthier nations.
- Online Essay Mills: Services offering to write essays for a fee are easily accessible online.
The Need for Solutions
- Addressing a Long-Standing Issue: AI has highlighted a pre-existing problem of academic dishonesty.
- Consequences of Inaction: Failure to address cheating undermines the value of a college degree and rewards individuals with integrity issues.
- Long-Term Impact: Low-integrity students can become low-integrity leaders in the future.
Potential Solutions
- In-Class Writing:
- Conducting writing assignments in class provides direct support from professors and peers.
- Promotes active learning and reduces opportunities for cheating.
- Longer essays can be completed over multiple class periods.
- Flipped Classroom Approach: Students write essays (formerly homework) in class and watch recorded lectures outside of class.
- Process Transparency:
- Requiring students to submit outlines and drafts to demonstrate their writing process.
- Limitations: Outlines and drafts can also be outsourced.
AI-Supported Writing with Transparency
- Khanmigo’s Approach:
- Professors create assignments and grading rubrics with AI assistance.
- Students complete tasks within the application, with varying levels of AI support.
- Proctoring: AI can take periodic snapshots of the student’s work.
- Writing Coach: AI can provide feedback on thesis statements, outlines, and essays, including grammar, references, and grade estimates.
- Transparency Reports: AI generates reports for professors summarizing the student’s interaction with the AI and assessing the authenticity of the work.
- Example Reports:
- Authentic Interaction: Khanmigo reports positive engagement, consistent writing style, and confidence in the student’s work authenticity.
- Suspected Cheating: Khanmigo flags inconsistencies, potentially advanced writing level compared to classwork, and raises concerns about inappropriate assistance.
- Benefits:
- Process Focus: Emphasizes the writing process and reduces cheating opportunities.
- Student Support: Provides timely feedback and guidance for improvement.
- Teacher Efficiency: Offers preliminary assessments, reducing grading time.
- Rapid Feedback: Enables students to receive immediate feedback and iterate on their work, improving learning outcomes.
Conclusion: AI’s Potential to Enhance Learning and Integrity
- Addressing Cheating: Generative AI can help mitigate long-standing issues with academic dishonesty.
- Enriched Learning: AI-powered tools can create a richer and more productive learning environment.
- Preparing Students for the Future: By thoughtfully integrating AI, colleges can better equip students with the skills and integrity needed for success in their future careers.
Part VII: The Global Classroom
“The world has enough for everyone’s need, but not enough for everyone’s greed.” - Mahatma Gandhi
Chapter 24: The Global Classroom
The Uneven Landscape of Education
Challenges in Bengal and the US
- Khan’s parents emigrated from Bengal (now West Bengal, India, and Bangladesh), where the education system faced significant challenges:
- Limited resources.
- Overcrowded classrooms or lack thereof.
- Teacher shortages.
- While Khan benefited from the US education system, it wasn’t serving all students effectively:
- Students who fell behind often lacked the necessary tutoring or family support.
Global Education Inequality
- Khan Academy highlighted the severity of unequal learning opportunities globally.
- Barriers to Learning:
- Limited resources.
- Inadequate infrastructure.
- Shortage of skilled teachers.
- Impact on School Completion Rates:
- Sub-Saharan Africa and South Asia have alarmingly low primary school completion rates.
- Poverty and conflict force many children out of school.
- Discrimination and Access to Education:
- Deep-rooted discrimination against girls and marginalized communities hinders access.
- Girls are twice as likely as boys to never attend school.
- Teacher Quality and Attendance:
- A 2004 UNESCO study found that 25% of teachers in India were absent, and only half were actively teaching.
- Even when present, many teachers lacked adequate training.
Inequality in Developed Nations
- United States:
- Children in poverty enter kindergarten up to 18 months behind their peers developmentally.
- This is attributed to factors like:
- Poor access to quality preschools and reading materials.
- Limited access to tutoring compared to middle and upper-class families.
- Asian Countries (South Korea, China, Japan, India):
- Families often pay for expensive after-school programs to maintain a competitive edge.
- These programs are costly and can negatively impact children’s mental health.
The Need for Equitable Education Systems
- Education opportunities are uneven and suboptimal globally.
- Susanna Loeb (Stanford University) highlights the power of quality education and the challenges in achieving equity.
- Roadblocks to Equitable Education:
- Decentralized Systems: The US education system’s decentralized nature makes uniform standards difficult to implement.
- Achievement Gaps: Increasing differences in achievement across unequal groups, particularly students with special needs.
- Inequalities Within Groups: Low-income and marginalized communities face significant disadvantages.
- Underfunded schools in their neighborhoods lead to:
- Limited extracurricular activities.
- Lack of advanced courses (e.g., higher-level math and science).
- Underfunded schools in their neighborhoods lead to:
- Scaling Solutions:
- Existing solutions are often short-term, narrow in scope, and locally focused.
- Technology’s Role: Technology can provide scalable solutions.
- Equitable Technology: Technology must be equitable and avoid widening the gap between rich and poor.
Khan Academy’s Mission
- Khan Academy’s goal is to provide free, accessible education globally.
- Leveraging the Internet: The internet allows direct access to classrooms, students, and families worldwide, bypassing policy barriers.
- Social Return on Investment: Khan Academy operates on a budget comparable to some high schools but reaches over 100 million learners annually.
- Comprehensive Approach: Covers all major academic subjects from pre-K to college.
- Raising the Floor and Ceiling: Aims to improve existing classrooms and provide opportunities for those lacking access to quality education.
- Education Safety Net: Khan Academy’s resources can serve as a safety net for global education.
Sola’s Story: A Case Study
- Sola, a young woman in Afghanistan, was forbidden from attending school.
- Access to Khan Academy: Using the internet and with family support, she taught herself various subjects through Khan Academy.
- Success Story: Sola is now a quantum computing researcher at Tufts University and a published author.
- Scaling Sola’s Success: The potential impact of providing similar opportunities to millions of students.
The Power of Tutoring
- High-Dosage Tutoring: Pulling students out of class for 30 minutes a day, four days a week, has a significant motivating effect (Loeb).
- Challenges of Tutoring: Cost and scalability are major barriers.
- Personalized Attention: Each student requires unique attention and support within their zone of proximal development.
The Role of Artificial Intelligence
- AI’s Transformative Potential: AI can bridge the global education divide and foster equal opportunity learning.
- Large Language Model Applications: Using smartphones, students can access key components of a world-class education.
- Note: Roughly 65% of the global population has internet access, and over half own a smartphone.
- AI’s Benefits in Education (Loeb):
- Provides educators with robust tools to create conducive learning environments.
- Augments the motivation provided by adult relationships.
- Supports personalized learning and motivation.
Chapter 25: Economics of AI in Education
The Cost of Education and its Challenges
Education Costs Globally
- Education is expensive worldwide.
- United States:
- Louisiana spends ~$10,000 per student annually.
- New York spends ~$40,000 per student annually.
- India:
- Government schools spend between ~$500 and ~$1,200 per student annually.
The Lockstep Model and its Limitations
- Lockstep Curriculum: Students progress through the curriculum at a fixed pace, regardless of individual understanding.
- Lack of Personalization: Limited support for personalized learning or addressing learning gaps.
- Wide Range of Preparedness: Classrooms often have students with diverse learning levels.
The Impact of the COVID-19 Pandemic
- The pandemic exacerbated existing inequalities.
- Digital Divide:
- Black and Hispanic households with school-age children were 1.4 times more likely than white households to have limited access to computers and the internet.
- Over 40% of low-income households had limited internet access.
- Decline in Academic Performance:
- Detroit 8th graders performing at grade level dropped from 6% pre-pandemic to 3% post-pandemic.
- The average American classroom’s ability spread widened from three grade levels to six.
Emergency Relief Funding and its Effectiveness
- Federal Funding: The US government provided $86 billion in emergency relief funds (~$2,000 per K-12 student).
- Tutoring Programs: Much of the funding went to tutoring programs.
- Limited Impact: Most of the money was spent with little improvement.
- Reasons for Ineffectiveness:
- Tutoring was often disconnected from classroom learning.
- Students faced logistical challenges in accessing tutoring.
- Stigma associated with seeking tutoring.
Khan Academy and Khanmigo: Bridging the Gap
- Khanmigo: A platform offering personalized, accessible, and high-quality education.
- Khan Academy’s Effectiveness During the Pandemic:
- Classrooms using Khan Academy for 30-60 minutes per week avoided learning loss and outperformed pre-pandemic standards by 20-40%.
- This was achieved at no cost to students.
- Large Language Model Platforms: Build on Khan Academy’s success to provide even more robust support.
- AI Tutor Benefits:
- Availability whenever needed, including in the classroom.
- Provides teachers and parents with insights into student progress and needs.
- Reduces stigma associated with seeking help.
- Allows for curious exploration without time constraints.
The Economics of AI Tutoring
- Cost-Effectiveness: AI tutoring is more cost-effective and accessible than live tutoring.
- Khan Academy’s Budget: Operates on a ~$70 million annual budget (comparable to a large high school) while reaching over 100 million learners.
- Funding Reliance: Requires significant fundraising from philanthropists to keep resources free.
- Generative AI Costs:
- Salaries for engineers, designers, product managers, and content developers.
- Significant computation costs for large language models like GPT-4.
- Khanmigo’s Estimated Cost: ~$5-$15 per user per month.
- Sustainability: Philanthropy alone may be insufficient to cover costs for millions of users.
- Pricing Model: School districts will likely be charged for access.
- Free for Students: Students in participating districts will access Khanmigo for free.
Accessibility in Poorer Countries
- Cost Barrier: Even $30 per year can be a significant expense in poorer countries.
- Future Cost Reduction:
- Computation costs are expected to decrease by a factor of 10 in the next few years.
- A 100-fold reduction within 5-10 years could make costs comparable to non-generative web applications.
Remaining Barriers to Access
- Internet and Device Access: Reliable access to the internet and devices remains a challenge.
- Optimism for Universal Access:
- Decreasing device costs.
- Providers like SpaceX Starlink offering low-cost broadband via satellite.
Overcoming the Language Barrier
- Multilingual Capabilities: Large language models like GPT-4 can operate in all major languages.
- Support for Language Learners: Enables support in native languages or mixed language contexts (e.g., Spanglish).
- Conversational Abilities: Fosters a sense of connection through real-time interaction.
- Translation Capabilities: Can be used for translating core platform content.
The Importance of Connection and Support
- Susanna Loeb emphasizes the vital role of connection and support in education.
- Transformative Potential: AI technology can be transformative in areas with limited resources and pedagogical approaches.
- Optimism for the Future: The potential of AI to improve educational access and quality globally.
Part VIII: AI Assessments and Admissions
“Not everything that can be counted counts, and not everything that counts can be counted.” - William Bruce Cameron
“Evaluation is creation. Hear it, you creators. Evaluating is itself the most valuable treasure of all that we value. It is only through evaluation that value exists. And without evaluation, the nut of existence would be hollow. Hear it, you creators.” - Friedrich Nietzsche
Chapter 26: The Future of K-12 Assessments
Critiques of Standardized Tests
- Narrow Focus:
- Primarily multiple-choice questions targeting a subset of important life skills.
- Pressure on educators to narrow classroom focus.
- Lack of Actionability:
- Scores arrive too late (summer or next school year) to be useful for the current teacher and student.
- Students lack incentive to perform well on tests not tied to grades.
- Demographic Bias:
- Performance differences across demographic groups raise concerns about bias against certain groups or schools.
- Lack of Transparency:
- Limited insight into what tests assess fuels skepticism, particularly in a politically charged environment.
Reframing the Debate on Standardized Tests
- Importance of Measurement:
- Measuring performance is crucial for improvement in any area.
- Standardized measurement ensures fairness by applying the same standard to all.
- Broadening the Scope:
- Instead of abandoning tests, expand their scope to assess a wider range of skills.
- Improving Actionability and Transparency:
- Address critiques by making tests more actionable and transparent.
- Equity Considerations:
- Removing tests may hinder equity by preventing schools from identifying and addressing learning gaps in underrepresented groups.
- Early identification of deficits is crucial for timely intervention.
Solutions for Improving Standardized Tests
- Personalized Practice Platforms:
- Integrate assessment data into software platforms that provide personalized practice based on identified weaknesses.
- Example: Khan Academy’s use of standardized test data to personalize practice.
- Study of over 300,000 students (2021-22 school year) showed that students engaging in personalized practice (30+ minutes/week) exceeded growth projections by 26% to 38%, depending on grade.
- Continuous Assessments:
- Integrate standardized exercises into learning platforms to provide ongoing assessment without sacrificing instruction time.
- Example: Khan Academy’s platform with millions of standardized exercises and data points on student performance.
- Benefits:
- More frequent and accurate insights into student learning.
- Actionable data drives personalized learning recommendations.
- Higher student motivation as daily practice contributes to assessment and class progress.
Addressing Transparency and Stakeholder Concerns
- Challenges with Traditional Assessments:
- External stakeholders (parents, politicians) lack direct observation of classroom learning and rely on potentially inaccurate accounts.
- Difficulty understanding how high-level standards translate into assessments and classroom activities.
- Limited transparency and flexibility due to cost and security concerns surrounding test item creation.
- Benefits of Adaptive Online Platforms:
- Large item banks and adaptive assessments allow stakeholders to explore the assessment process without compromising security.
- Each student receives a unique sequence of questions based on their performance, minimizing the risk of item leakage.
The Role of Generative AI in Assessment
- Enhanced Item Creation:
- While not yet capable of independent high-quality item creation, generative AI can significantly enhance the productivity of human question writers and reviewers.
- Potential for creating more numerous and diverse assessment items with existing resources.
- Deepening and Broadening Assessment:
- Moving beyond multiple-choice and numeric-entry questions to assess complex skills like writing, problem-solving, and creativity.
- Addressing the historical limitations of open-ended assessments that require expert human reviewers and complex rubrics.
AI-Powered Rich Assessments
- Examples of AI-Driven Assessment Enhancements:
- Reading Comprehension:
- Moving beyond multiple-choice questions to assess students’ understanding of author intent or their own perspectives through written or spoken responses.
- AI-powered conversations to explore student reasoning and evidence.
- Math: Assessing reasoning and proof development.
- Science: Evaluating experimental design and research paper critique skills.
- Problem-Solving: Using AI-driven simulations.
- Visual Arts: AI assessment of visual works, presentations, etc. (as AI develops visual capabilities).
- Reading Comprehension:
Addressing Concerns about AI Bias in Assessment
- Comparing AI to the Status Quo:
- Current assessments are also susceptible to human bias.
- Avoiding AI limits assessment to easily measurable skills, potentially magnifying bias towards these skills.
- Richer assessments like PhD defenses or job interviews are often inconsistent and biased.
- Benefits of AI-Driven Assessment:
- Potential for standardization and scale combined with richness and nuance.
- Increased accessibility facilitates stakeholder scrutiny and auditing.
- Mitigating Risks:
- Acknowledge the potential for AI bias and the need for careful development and implementation.
- Emphasize transparency and guardrails to ensure fairness and accuracy.
- Striving for Improvement:
- Aim for AI-powered assessments that are demonstrably superior to the status quo in terms of fairness and accuracy.
Impact of AI-Powered Assessment on Education
- Redefining Quality Education:
- Expanding the scope of assessment to include previously immeasurable skills like communication, creativity, and curiosity.
- Motivating the education system to focus on holistic development of individuals.
Chapter 27: The AI of College Admissions
AI’s Impact on College Admissions Components
- Grades and Schoolwork:
- Generative AI will transform classroom assignments and grading, enabling richer assignments and providing teachers with grading support.
- Standardized Tests:
- AI will drive a shift towards deeper, continuous assessments integrated with learning.
- Existing tests (SATs, ACTs) will either adapt or be replaced by new AI-powered assessments.
- Essays and Recommendations:
- Ethical concerns arise regarding the use of AI for generating essays and recommendation letters.
- Extracurriculars:
- Impact of AI on extracurriculars is less clear, but potential exists for AI-powered platforms to facilitate and track student involvement in various activities.
Ethical Challenges Posed by AI in Admissions
- Potential for Misrepresentation:
- Students may use AI to create impressive essays that don’t reflect their true abilities.
- Teachers and counselors may use AI to write recommendation letters, potentially undermining their authenticity.
- Exacerbating Existing Inequities:
- AI tools may widen the gap between affluent students with access to resources and those without.
- Example: Varsity Blues scandal highlights the existing industry of high-priced college admissions coaches who provide extensive assistance to wealthy students, including essay writing and fabrication of extracurricular activities.
- Accessibility and Ethical Gray Areas:
- AI tools like ChatGPT democratize access to assistance previously limited to affluent families.
- Everyone now faces ethical dilemmas regarding the appropriate level of assistance.
Rethinking the Role of Essays and Recommendations
- Objective vs. Subjective Admissions:
- In many countries, college admissions rely heavily on objective measures like standardized test scores (e.g., India’s IIT admissions based solely on the JEE).
- US universities often prioritize subjective factors like personality, leadership potential, and community engagement.
- Limitations of Subjective Evaluation:
- Difficulty in accurately assessing subjective qualities through essays and recommendations, which may be influenced by external factors (e.g., coaching, family background).
- Concerns about the randomness and potential for bias in subjective evaluation processes.
Alternative Approaches to Evaluating Soft Skills
- Standardized Measurement of Soft Skills:
- Exploring methods for objectively assessing qualities like leadership, collaboration, empathy, and community service.
- Example: Schoolhouse.World:
- Provides free online tutoring by vetted volunteers.
- Rigorous vetting process assesses subject matter mastery and communication skills.
- Tutor performance is tracked and rated by students, creating a standardized record of tutoring experience and quality.
- Adoption by Universities:
- 18 universities, including prestigious institutions like University of Chicago, MIT, Yale, Brown, and Columbia, accept the Schoolhouse.World transcript as part of their admissions process.
- Value the transcript as a standardized measure of subject competency and soft skills.
- Positive Outcomes:
- Students submitting Schoolhouse.World transcripts often have higher acceptance rates.
- Provides an incentive for students to engage in tutoring and community service.
Integrating AI with Schoolhouse.World and College Admissions
- AI-Powered Feedback and Assessment:
- Schoolhouse.World utilizes AI to provide tutors with feedback on their sessions and identify areas for improvement.
- Future applications include real-time tutoring tips and narrative assessments of tutor style and capabilities, further enriching the transcript for admissions officers.
- Reimagining Admissions with AI:
- AI-Powered Interviews: Conducting standardized text- or voice-based interviews with students, counselors, and teachers to gather consistent and comparable information.
- AI-Generated Recommendations: AI platforms that have interacted with students over time can provide personalized and standardized recommendations based on their observed strengths and passions.
- Benefits of AI in Admissions:
- Enhanced scalability, consistency, and auditability of the evaluation process.
- Potential for mitigating bias and improving transparency.
Addressing Bias in AI-Driven Admissions
- Acknowledging and Mitigating Bias:
- Recognizing the potential for AI systems to perpetuate or introduce new biases.
- Implementing strategies to identify and address bias in AI algorithms and training data.
- Striving for Fairness:
- Aiming for AI systems that are demonstrably less biased than existing human-driven processes.
- Example: Harvard Admissions Case:
- 2018 Supreme Court case revealed evidence of bias against Asian American applicants in Harvard’s admissions process.
- AI-powered systems can be audited and tested to ensure consistent evaluation across demographic groups.
Conclusion
- AI is not the source of problems in college admissions but rather exposes existing flaws and offers opportunities for improvement.
- Thoughtful and ethical implementation of AI can lead to a fairer and more transparent admissions process.
- Potential for AI to shift the focus from subjective narratives to standardized assessment of both academic and soft skills, potentially creating a more equitable and meritocratic system.
Part IX: Work and What Comes Next
“The one who plants trees knowing that he will never sit in their shade has at least started to understand the meaning of life.” - Rabindranath Tagore
“Learn the rules like a pro so you can break them like an artist.” - Pablo Picasso
Chapter 28: The AI Revolution and the Future of Work
AI’s Impact on the Job Market
- Fear of Mass Layoffs: Many fear that AI will lead to mass layoffs as AI-powered tools become more efficient and cost-effective than human labor.
- Hiring Freezes: Companies are pausing hiring for roles they believe AI will replace in the future.
- IBM Example: In 2023, IBM announced a 30% reduction in back-office hiring over five years for jobs potentially replaceable by AI.
- Shift in Job Landscape: Back-office, middle-office, and non-client-facing roles involving tasks like budgeting, data management, and record organization are likely to disappear.
- “Replaced by Someone Using AI”: The common saying is that you won’t be replaced by AI, but by someone who uses AI effectively.
- Examples of Increased Productivity with AI:
- Writers and copywriters: 3-5 times more productive.
- Software engineers: Using AI co-pilots for debugging and code completion.
- Graphic designers: Generating numerous logo variations with text-based prompts.
Mixed Bag of Job Impacts
- Technological Inflection Point: Generative AI is creating a technological inflection point, enabling us to do more.
- Increased Demand for Engineers: Demand for engineers, especially those who are highly productive with AI, will increase.
- Historical Parallel: Globalization and Software Engineering:
- Early 2000s: Globalization led to outsourcing of software engineering work.
- Fear of job displacement proved unfounded as software engineering salaries rose due to increased demand driven by smartphones and the internet.
- Generative AI as a Catalyst for Innovation: Generative AI creates an environment ripe for further innovation, leading to more opportunities for engineers who can apply these technologies creatively.
- Job Displacement in Specific Roles:
- News Summary Writers: Jobs like writing news summaries about stock market fluctuations are likely to be automated by generative AI.
- Survival Through AI Adoption:
- Copywriters and technical writers who embrace AI to enhance productivity will survive, while others may need to find new roles.
New Job Opportunities
- Prompt Writers and Engineers: Generative AI has created new jobs like prompt writers and engineers.
- Open-Minded Copywriters Can Transition: Creative copywriters can transition well into prompt-related roles.
- Opportunities in AI Safety, Security, and Anti-Bias: As organizations adopt AI, new opportunities will emerge in areas like safety, security, and addressing bias in AI systems.
- AI Integration Across Roles: Positions from HR to management will likely utilize AI for tasks like generating hiring letters or meeting reports.
AI-Induced Natural Selection at the Corporate Level
Leaner, Automated Companies Gain Advantage: Smaller, more automated companies will be able to offer competitive products at lower prices, potentially gaining market share from larger, less automated companies.
Net Job Losses Due to Automation: This trend will likely lead to a net loss of jobs as automation advances.
Chegg Inc. Example:
- Chegg, an education technology company, struggled to compete with ChatGPT as students used the large language model for homework help.
- Chegg’s CEO admitted uncertainty about future revenue due to ChatGPT’s impact, leading to a 50% drop in their stock price.
Impact on Established Businesses: Generative AI has the potential to disrupt established businesses across various industries.
Wharton’s Ethan Mollick’s Perspective:
“It’s going to affect every industry differently, every person differently, and every job differently. The job that’s least affected by AI, according to the early-stage research we have, is roofing. And yet, I’ve talked to a couple of roofers who are like, ‘Actually, roofing is going to change too, because we can now do all of our proposals with AI help.’”
AI’s Expanding Capabilities and the Need for Adaptation
- AI’s Broad Capabilities: AI can understand language, recognize patterns, solve problems, diagnose illnesses, make stock market trades, compose music, fight lawsuits, understand emotions, analyze genetic code, handle insurance claims, engineer, and write articles.
- Adaptation as the Key Strategy: The successful approach will be to adapt to AI rather than resist it.
Chapter 29: Preparing Kids for the AI-Driven Workplace
The Paradox of AI in Education
- Stanford Student’s Concern: A Stanford student expressed concern about the relevance of learning to code when AI can do it better.
- Shift in Desired Professions: Software engineering and data science, once considered the hottest jobs, are now being challenged by AI’s capabilities.
- Tension in Education: There’s a fear of allowing AI tools in schools to prevent cheating, despite the fact that future jobs will require working closely with AI.
- Bill Gates’ Paradox: AI makes learning easier, but also raises questions about the necessity of certain skills that AI can perform better.
The Importance of Coding and Working with AI
- Chris Peach’s Advice to the Stanford Student:
- Coding remains important for creating major solutions, including those that utilize generative AI.
- Understanding how code pieces fit together is crucial even if AI can write portions of it.
- Working in Concert with AI: It’s essential to learn to work effectively with generative AI.
- Efficiency of AI-Savvy Employees: Entry-level employees who understand and use AI will be more efficient.
- Author’s Son’s Example: The author encourages his son, who aspires to be a video game developer, to use AI to tackle more ambitious projects.
- AI Augments, Not Replaces, Skills:
- AI’s writing competency doesn’t negate the need to learn how to write.
- Aspiring screenwriters should master screenwriting and then use AI to undertake more complex projects.
- Importance of Understanding Quality: Being skilled in a craft allows you to recognize high quality, even when AI is involved.
- Expanding Creative Possibilities: Screenwriters can potentially produce entire movies with AI assistance, as AI can generate music, videos, and even edit footage.
- Disruption in the Film Industry: AI is already causing disruption in the film industry and many others.
AI’s Impact on Productivity and the Need for Centaurs
Wharton Study on AI-Driven Productivity: Early studies show 30-80% performance improvement on various analytical tasks due to AI, including writing, analysis, consulting, and programming.
Ethan Mollick’s View on AI in the Workplace:
“If you want to be in these fields, AI is and will remain a part of your life. You need to figure out if you can use AI to be 10 times more productive, meaning there remains a need for humans to be in the loop.”
The Centaur Model: Professionals need to become “centaurs,” half human and half large language model, to thrive in the AI-driven workplace.
Adapting Education for the AI Future
Familiarity with AI Tools: Educators must familiarize students with AI tools and their capabilities.
Generative AI as a General-Purpose Technology: Generative AI is a transformative technology like steam power, computers, or the internet, potentially impacting our lives faster and more profoundly.
Shift from Specialization to Broad Skills:
- The Industrial Revolution emphasized specialization of labor.
- The future job market requires deep skills in specific areas, but also entrepreneurial expertise across multiple domains.
Bill Gates’ Perspective on Future Skills:
“Not only is there more reason than ever for kids to continue to learn about their fields of interest, but students need to accelerate learning these skills and to learn them as well as possible.”
AI Integration in Entry-Level Jobs: Entry-level jobs will require understanding how to use large language models for tasks like creating invoices and business plans.
Collaboration Between Humans and AI: The workplace will emphasize collaboration between humans and AI for optimal productivity.
Value of Deep Skills: The more developed your skills, the more valuable they will be in the AI-driven workforce.
The Need for Entrepreneurial Expertise: Success will require deep specialization in one or two areas, combined with entrepreneurial skills across multiple domains.
Fostering Entrepreneurship in the AI Era
- Khan Academy Founder’s Entrepreneurial Journey: The author’s experience starting Khan Academy highlights the importance of coding skills, resourcefulness, and adaptability in entrepreneurship.
- Generative AI’s Role in Entrepreneurship: Generative AI will empower the next generation of entrepreneurs to achieve even greater scalability.
- Return to Craftsman-Like Experience: We are entering a world where a small group with expertise in various domains can manage AI “armies” to create and build.
- Entrepreneurship as a Factor of Production: Entrepreneurship involves creatively combining resources to create value.
Preparing Students for Entrepreneurial Success
- Step 1: Unleashing Creativity and Entrepreneurship:
- All humans are inherently creative and entrepreneurial.
- The current education system often suppresses these traits through its emphasis on conformity and standardized learning.
- Step 2: Developing Deep and Broad Skills:
- The three R’s (reading, writing, and arithmetic) are fundamental.
- A strong foundation in history, art, science, law, and finance is also valuable.
- Technology can facilitate mastery of these skills without the limitations of lockstep learning.
- Step 3: Enhancing Communication, Collaboration, and Empathy:
- Strong communication, collaboration, and empathy skills are essential for success in the AI era.
- Entrepreneurship Beyond Business Ownership:
- Entrepreneurship encompasses the ability to identify problems, conduct research, and assemble resources to solve them, even within a larger organization.
- Empowering Students in the Classroom: Schools can foster entrepreneurship by:
- Giving students more control over their learning.
- Utilizing AI tools to support mastery of core skills.
- Providing more time and space for student agency and creativity.
Chapter 30: AI-Powered Matchmaking in the Job Market
Predictions for the Future of Work
- Computer World Magazine Interview (1999): The author made predictions about the future of work, including the role of AI agents in matchmaking between employers and employees.
- AI’s Rapid Advancement: The current generation of generative AI surpasses expectations, making past predictions seem conservative.
AI’s Potential in the Job Application Process
- Traditional Hiring Process:
- Hiring managers create job descriptions.
- Hundreds of resumes are received for each opening.
- Talent acquisition teams screen resumes, often focusing on superficial factors like previous employers, keywords, and university degrees.
- Recruiters select a small pool of candidates for phone screens and interviews.
- Multiple interviews are conducted by team members, which can be time-consuming and expensive.
- Subjective judgment plays a role in candidate selection.
- AI’s Potential to Improve the Process:
- Streamlining Standard Processes: AI can assist in drafting job posts, interview questions, cover letters, and resumes.
- Interactive Resumes: AI-powered applications can create interactive resumes that communicate with AI recruiters, potentially providing a fairer evaluation for each candidate.
- AI Agent-to-Agent Communication: Employer recruiter bots can directly interact with candidate agent bots, eliminating scheduling complexities and providing a more efficient process.
- Benefits of AI Job Agents:
- Personalized Representation: AI job agents learn to represent candidates accurately based on their employment history, skills, interests, and work samples.
- Career Coaching: AI agents can help candidates explore career and education options aligned with their goals.
- Expanded Job Search: AI agents can analyze a vast number of job postings, including those outside a candidate’s traditional field.
- Identifying Opportunities for Career Changers: AI agents can find employers willing to hire candidates from different backgrounds, even if they lack direct experience.
- AI’s Role in Candidate Screening and Evaluation:
- AI Recruiters: AI can conduct initial screenings and identify top candidates based on simulated conversations with candidate AI agents.
- Reference Checks: AI can engage with candidate references to gather additional insights.
- Real-Time Interview Feedback: AI can provide interviewers with real-time feedback and suggest follow-up questions to ensure fairness and consistency.
Benefits of AI-Driven Hiring
- Enhanced Equity and Efficiency: The job application and hiring process can become more equitable, faster, and less resource-intensive.
- Increased Opportunities for Candidates: Every candidate, through their AI agent, can potentially have an interview with the hiring AI.
- Comprehensive Candidate Profiles: Companies gain a more in-depth understanding of candidates through AI agent interactions.
- Potential Obsolescence of Traditional Resumes: AI agents may render traditional resumes less relevant.
Addressing Concerns about Bias in AI
- Potential for Bias in AI Systems: A major concern is the potential for AI to introduce bias in resume screening and interviewing.
- AI as a Potential Improvement: While perfect objectivity is impossible, AI can be designed to be demonstrably less biased and more consistent than current subjective human processes.
- Scrutiny and Regulation: AI systems used in recruiting should be carefully scrutinized and regulated to mitigate bias.
- Potential for Increased Inclusivity and Fairness: Ultimately, AI tools can contribute to a more inclusive, efficient, and less biased hiring process.