Stay ConnectedArtificial General Intelligence — the type of AI that reaches or even surpasses human capabilities — is an exciting topic. But what is not explored as much is an equally important question: what happens before AGI is here? That is, what should we be doing to prepare?
In Before AGI, I hope to have honest conversations about what are the goals, what are the problems, and what lies ahead as we develop AI.
Copyright: © Copyright 2024
Artificial intelligence is rapidly transforming the world, raising urgent questions about its impact, governance, and the future of human-machine collaboration. As AI systems become more capable, society faces challenges around safety and the balance of power. What does it mean to build and deploy technology that can reason, create, and potentially automate research itself? How do leading researchers navigate the technical and ethical frontiers of this new era?
Jakub Pachocki, Chief Scientist at OpenAI, and Szymon Sidor, Technical Fellow at OpenAI, share their journeys from early programming competitions in Poland to shaping some of the most advanced AI systems in the world. They discuss the evolution of AI research, the technical and emotional challenges of building breakthrough models, and the profound societal questions that come with unprecedented progress.
2:42 - Origin story: high school to OpenAI
6:31 - “AI enlightenment” and AlphaGo moment
17:12 - Early OpenAI culture and impostor syndrome
23:30 - Power duo dynamic and collaboration
27:25 - Shift to reasoning models
36:23 - Possibilities of AGI
42:12 - OpenAI’s pandemic efforts showed AI’s immaturity
51:15 - Governance lessons from crisis
55:39 - AI safety and optimism for the future
AI systems are beginning to act on our behalf — executing tasks, making decisions, and influencing daily life in ways that often escape direct human oversight. What are the consequences of delegating decision-making to systems we don’t fully understand? How do we design AI to enhance human capabilities without sidelining human judgment?
In this episode, host Aleksander Mądry welcomes Jonathan Zittrain, Professor at Harvard Law School and Co-Founder of the Berkman Klein Center for Internet & Society. They explore the legal, ethical, and societal challenges of living alongside increasingly autonomous AI. Drawing on lessons from the internet’s evolution, Zittrain examines how we can structure responsibility, foster innovation, and build systems that truly serve the public good — all while navigating the profound opportunities and risks of this technological transformation.
09:20 - Three eras of internet evolution
14:56 - Generative tech and equilibrium challenges
20:59 - Generativity vs. closed systems
26:36 - The promise and pitfalls of AI assistants
32:56 - Privacy, privilege, and AI user rights
39:01 - Regulation, self-regulation, and global policy
48:28 - Defining AI agents and their real-world impact
52:26 - AI’s potential to empower the marginalized
1:15:41 - Acceleration, agency, and the future
As AI becomes more integrated into daily life, it raises urgent questions about trust, accountability, and human agency. What happens when people over-rely on AI or when helpful tools are held back by perfectionism? Can we deploy imperfect systems while still earning public confidence?
Reid Hoffman, Co-Author of “Superagency: What Could Possibly Go Right with Our AI Future,” joins this episode to explore how AI can enhance, not replace, human judgment. He discusses democratic leadership, global competition, and the design choices that shape user agency. Reid also shares his perspective on long-term AI investment beyond short-term hype.
03:00 - Superagency and human-centered design
17:27 - Risk, regulation, and collective action
21:42 - Rethinking agency in the age of agents
31:18 - Trust, regulation, and system design
55:09 - Building trust through real-world AI benefits
1:06:07 - China’s ambition and multipolar competition
1:09:00 - Investing in applied AI with real impact
1:14:00 - Reid’s hope for AI engagement
As AI continues to permeate various aspects of society, its impact on decision-making, bias, and future technological developments is complex. How can we navigate the challenges posed by AI, particularly when it comes to fairness and bias in algorithms? What insights can be drawn from the intersection of economics, computer science, and behavioral studies to guide the responsible development and use of AI?
In this episode, Sendhil Mullainathan, a prominent economist and professor, delves into these pressing issues. He shares his journey from computer science to behavioral economics and discusses the role of AI in shaping the future of decision-making and societal structures. Sendhil provides a nuanced view of algorithmic bias, its origins, and the challenges in mitigating it. He also explores the potential and pitfalls of AI in healthcare and policymaking, offering insights into how we can harness AI for the greater good while being mindful of its limitations.
0:00 - Start
1:51 - Introducing Sendhil
14:20 - Algorithmic bias
29:20 - Handling Bias
41:57 - AI and Decision Making
57:01 - AI in our Future
1:02:29 - Conclusion and the last question
AI technology is transforming the world, raising crucial questions about governance, regulation, and societal impact. What measures should governments adopt to regulate AI effectively? How can academic institutions contribute to this development?
Luis Videgaray is a professor at MIT and the director of the MIT AI Policy for the World Project. Previously, he also served as the Minister of Finance and the Minister of Foreign Affairs in the Mexican Government. In this episode, Luis shares his journey and insights on the role of governments in regulating and utilizing AI. He also covers the evolution of AI policy, the geopolitical landscape, and the future of AI regulation.
3:47 - Luis’ time in the government
7:12 - AI in the past
20:19 - Regulation of AI
43:13 - Governments using AI
51:03 - Geopolitics of AI
1:11:31 - Luis at MIT
1:16:50 - Luis’ perspectives on AI
1:25:28 - Conclusion and the last question
Governments are playing a crucial role in ensuring the safe and ethical deployment of AI technologies, protecting citizens while fostering innovation. What steps can policymakers take to safeguard our future? How can we, as citizens, contribute to the conversation and advocate for beneficial AI practices?
Anna Makanju, VP of Global Affairs at OpenAI, has extensive experience in national security and foreign policy roles across the U.S. government, UN, NATO, and Facebook. In this episode, Anna discusses her global tour with Sam Altman, her journey to her current role, and the steps governments can take to ensure a safe AI future.
3:18 - Anna and OpenAI’s goals
8:23 - Sam’s tour and government's role
19:25 - AI and the government
38:48 - AI and the military
51:25 - Anna’s time in the government
55:52 - Geopolitics of AI
1:04:28 - AI safety and the future
1:14:50 - Conclusion and the last question
The rapid advancement of AI technology presents both opportunities and challenges. As AI becomes more integrated into various aspects of life, how can companies ensure that these technologies are used innovatively and ethically? What measures can be taken to navigate potential pitfalls and enhance human connections rather than causing harm?
Reid Hoffman, Co-founder of Inflection AI, Co-founder and executive chairman of LinkedIn, and Founding investor and former board member at OpenAI has recently used AI in innovative ways. In this episode, Reid talks about his experience doing an interview of his AI digital twin, his time on the board of OpenAI, and the potential to integrate AI into our own lives in interesting ways.
3:11 - Digital twin
9:07 - Innovative ways to engage with AI
26:05 - Different perspectives on AI
28:41 - Reid’s time with OpenAI
36:00 - Why Inflection?
47:56 - Future of AI
1:01:08 Board dynamics
1:10:48 - World stage for AI
1:39:19 - Conclusion and the last question
Recent developments of AI offer an opportunity to transform traditional educational systems through tools that provide personalized learning and equal access to quality education. As we advance in our understanding of AI and its integration into daily life, how can we leverage these tools to dismantle educational barriers? What would a safe and beneficial AI education tool look like, and how should it be implemented to benefit everyone?
Sal Khan, an advocate for educational access and the founder of Khan Academy, has dedicated significant effort to this challenge. In this episode, Sal shares his personal journey with AI and elucidates how it can revolutionize educational access, support teachers, and inspire students. He discusses Khan Academy’s new AI tool, “Khanmigo,” and its potential to transform learning for the better.
2:35 - Pre-ChatGPT Khanmigo
14:13 - Sal’s journey with AI
21:09 - AI’s effects on our learning and thinking
38:33 - AI and human relationships
44:01 - Envisioning future AI use
47:41 - Economics of education
56:39 - Standardized testing
1:02:10 - Societal impacts of AI
1:09:48 - Future of AI
1:13:22 - Conclusion and the last question
While the rapid development of AI technology promises unprecedented productivity gains and innovations, concerns of job displacement and increasing inequality persist. How can we ensure AI complements human labor rather than replacing it? What measures can we take to prevent a dystopian AI future?
Erik Brynjolfsson is a professor at Stanford University and has pioneered research on the economics of information technology and AI. In this episode, Erik discusses the potential for AI to enhance job productivity, complement our workforce, and boost economic growth at scales comparable to the Industrial Revolution while also exploring potential negative futures and strategies to avoid them.
(03:16) Imagining the future
(09:41) Impacts on Productivity and Labor
(21:14) GPTs are GPTs!
(31:02) Workhelix
(32:07) Self Driving Cars
(36:25) AI Helping Innovation
(38:02) Negative Impacts
(38:39) Historical Context and Economic Concerns
(42:56) AI's Impact on Job Markets and Productivity
(48:22) Shared Benefits
(49:46) Pessimism and Belief about AI
(01:03:59) Strategies for a Positive AI Future
(01:12:17) Last Question
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