Title: Behind the Tech: Ethan Mollick, Author & Associate Professor at the Wharton School of the University of Pennsylvania Resource URL: https://www.youtube.com/watch?v=Son-ZEiji4s Publication Date: 2024-06-11 Format Type: Video Reading Time: 59 minutes Contributors: Kevin Scott;Ethan Mollick; Source: Microsoft (YouTube) Keywords: [Artificial Intelligence in Work, AI in Education, AI Transformation, AI for Entrepreneurs, Future of Work with AI] Job Profiles: Chief of Staff;Artificial Intelligence Engineer;Business Consultant;Chief Technology Officer (CTO);Chief Executive Officer (CEO); Synopsis: In this video from Microsoft, chief technology officer Kevin Scott speaks with Wharton professor Ethan Mollick about how AI is reshaping education, work, and entrepreneurship. They explore how AI complements human intelligence, enhances creativity, and inspires transformative thinking. Takeaways: [AI enhances creativity and productivity by complementing human capabilities, but it won't fully replace human ingenuity., The power of open-access AI, such as ChatGPT, levels the playing field by enabling individuals globally to leverage advanced tools., AI offers personalized learning, empowering students with tailored insights and expanding access to knowledge., AI's ability to reduce repetitive tasks allows founders to focus on creative, high-value innovations and disrupt established industries., A balance is needed between fast experimentation and thoughtful regulation to maximize AI's benefits while mitigating risks.] Summary: Kevin Scott and Ethan Mollick explore the evolving role of AI in transforming work, education, and entrepreneurship. Mollick argues that AI functions as "co-intelligence," complementing human expertise by taking on repetitive and tedious tasks, thus allowing people to focus on higher-value, creative work. They discuss the Best Available Human (BAH) framework, which positions AI as an accessible tool that democratizes expertise across fields like education and healthcare. Mollick emphasizes that AI’s ease of use bypasses the need for technical expertise, making it available to non-programmers. This shift is likened to the PC revolution, where access and usability drove innovation. The conversation highlights examples like AI-assisted education, where students leverage tools like ChatGPT to break down complex concepts, empowering them to explore subjects far beyond their current capabilities. The duo discusses how AI is transforming industries. Startups now aim to remain small, leveraging AI to scale operations without large teams. Businesses should focus on what AI makes possible, rather than cost-cutting measures. However, Mollick and Scott caution against underestimating AI’s impact or delaying experimentation, urging organizations to explore the frontier of AI capabilities proactively. They also address challenges, such as information integrity, cybersecurity risks, and societal shifts like the rise of AI companions. Both agree on the need for nimble regulation and highlight the untapped opportunities for education, entrepreneurship, and equitable access to AI tools worldwide. Content: ## Introduction In conversations with corporate leaders, two consistent themes emerge: first, tasks once deemed valuable may have lost their relevance, and immediate recognition of this shift is advantageous. Second, capabilities previously considered impossible are now within reach. This episode of *Behind the Tech* explores both phenomena through an in-depth discussion with Ethan Mollick, an associate professor at the Wharton School of the University of Pennsylvania and New York Times–bestselling author of *Co-Intelligence*. **Hosts:** - **Kevin Scott**, Chief Technology Officer and EVP of AI at Microsoft - **Christina Warren**, Senior Developer Advocate at GitHub **Guest:** - **Ethan Mollick**, Associate Professor, Wharton School, University of Pennsylvania; author of *Co-Intelligence*; newsletter author, *One Useful Thing* (nearly 150,000 subscribers) --- ## 1. The Current AI Revolution ### 1.1 Scope and Impact Modern artificial intelligence (AI), particularly large language models (LLMs), has evolved from a formidable research challenge into an accessible, nearly ubiquitous technology. This transformation parallels the personal computing revolution driven by Moore’s Law, yet differs in its human-centric interface: nonprogrammers can now leverage AI tools effectively without specialized coding knowledge. ### 1.2 The Human-Machine Leapfrog Unlike earlier technologies that progressed from command-line interfaces to graphical user interfaces over time, LLMs have introduced a direct, conversational modality. This “leapfrog” effect means managers, teachers, and professionals can interact with AI as they would a human assistant—despite its probabilistic nature and occasional errors in reasoning. --- ## 2. Early Technological Influences ### 2.1 Childhood Exposure to Computing Professor Mollick traces his interest in technology to the 1980s, when he and his neighborhood peers pooled resources to form a computer club. They traded software—often on floppy disks—for Apple IIe machines and even ran a bulletin board system (BBS). This grassroots community of “nerds” fostered collaborative exploration long before the internet’s arrival. ### 2.2 Academic Formation Although not a naturally gifted mathematician, Mollick excelled at systems thinking and historical analysis of technology. At Harvard University, he crafted an interdisciplinary undergraduate major in science, technology, and policy. His first thesis investigated Moore’s Law, including an interview with Intel cofounder Gordon Moore, laying the groundwork for subsequent scholarship at MIT’s Sloan School of Management. --- ## 3. The Concept of Co-Intelligence ### 3.1 Defining Co-Intelligence In *Co-Intelligence*, Mollick argues that contemporary AI serves as a form of “co-intelligence”—an augmentation rather than a replacement of human capabilities. Far from the doomsday scenarios of sentient machines, today’s tools excel at tasks that even talented humans find tedious or stressful. ### 3.2 Practical Benefits vs. Theoretical Fears Most public discourse around AI polarizes between utopian and apocalyptic visions. By contrast, Mollick focuses on immediate, pragmatic applications—such as automating routine work, assisting with writing or programming, and serving as a personal tutor or research interpreter. This perspective encourages organizations to shift from cost-cutting to opportunity-seeking. --- ## 4. AI in Education and Knowledge Access ### 4.1 Democratizing Tutorship Education stands to gain exceptionally from AI. Traditional one-on-one tutoring remains prohibitively expensive for many learners; AI can bridge gaps by providing personalized explanations and feedback. For instance, a 15-year-old biochemistry student can use a public GPT interface to decode complex research papers, effectively acting as an on-demand tutor. ### 4.2 Beyond “Explain Like I’m Ten” While many users default to prompts such as “explain like I’m ten,” the optimal approach involves sharing one’s background, goals, and current knowledge level. An AI that understands the learner’s context can tailor explanations more accurately than generic simplifications. --- ## 5. Transforming the Future of Work ### 5.1 From Task Automation to Job Reimagination Mollick emphasizes that AI’s greatest impact may be enabling tasks once impossible or uneconomical. He counsels students and companies to identify “impossible” objectives and prototype minimum-viable solutions using existing AI capabilities. For example, his entrepreneurship classes assign projects in which students create GPT-based agents that replace parts of their own prospective jobs—challenging them to rethink value creation. ### 5.2 Best Available Human Framework To assess AI’s utility, compare its performance not against perfect automation but against the best human resource available. In domains such as medical second opinions, legal research, or specialized consulting, AI often outperforms human experts by offering broader, faster, and cost-effective insights. --- ## 6. Entrepreneurship in the AI Era ### 6.1 New Models of Scale Startups are reimagining scale: rather than hiring hundreds of employees, small teams can leverage AI “interns” or agents to deliver services previously requiring large workforces. Entrepreneurs should target transforms in which AI multiplies human effort, not merely automates existing workflows. ### 6.2 Embracing Ambition Given ongoing advances in model power and interface design, incremental improvements risk obsolescence. Mollick advises founders to position their ventures at the “ragged frontier” of capability—tackling use cases that are barely feasible today but will rapidly mature. --- ## 7. Regulatory and Ethical Considerations ### 7.1 Addressing Immediate Harms Inevitable pitfalls include sophisticated phishing attacks, the proliferation of AI-generated misinformation, and privacy concerns. Rather than focus solely on hypothetical sentient AI, policymakers should enact responsive regulations to mitigate these known risks while preserving room for innovation. ### 7.2 Fast, Smart Regulation Echoing economist Joshua Gans, Mollick calls for “fast, smart responsive regulation” that identifies emerging harms—such as identity fraud and algorithmic bias—and addresses them swiftly. At the same time, regulators should provide safe experimentation zones in critical areas like healthcare, ensuring that beneficial applications can proceed under clear guidelines. --- ## 8. Future Outlook and Personal Pursuits ### 8.1 Optimism Tempered by Agency Mollick views this period as a rare opportunity to shape a general-purpose technology that will influence every sector, from education to customer service to creative industries. He urges professionals to learn AI tools thoroughly—logging at least ten hours with frontier models—and then to leverage their domain expertise for strategic advantage. ### 8.2 Balancing Work and Play Outside academia, Mollick finds balance in family life and in challenging “roguelike” video games, which blend randomness with problem-solving. He also experiments with AI as a game designer, exploring how generators can enhance interactivity and learning experiences. --- ## Conclusion The AI revolution demands both critical attention to its adverse effects and a spirit of pragmatic optimism. As Ethan Mollick’s work illustrates, co-intelligence offers unprecedented opportunities to augment human potential—from personalized education to entrepreneurial ventures. By recognizing obsolete practices and daring to realize long-deferred ambitions, individuals and organizations can harness AI’s transformative power while guiding its responsible evolution.