Future of Life Institute Podcast

What does it mean to create beneficial artificial intelligence? How can we expect to align AIs with human values if humans can't even agree on what we value? Building safe and beneficial AI involves tricky technical research problems, but it also requires input from philosophers, ethicists, and psychologists on these fundamental questions. How can we ensure the most effective collaboration? Ariel spoke with FLI's Meia Chita-Tegmark and Lucas Perry on this month's podcast about the value alignment problem: the challenge of aligning the goals and actions of AI systems with the goals and intentions of humans.

AlphaZero, progress in meta-learning, the role of AI in fake news, the difficulty of developing fair machine learning -- 2017 was another year of big breakthroughs and big challenges for AI researchers! To discuss this more, we invited FLI's Richard Mallah and Chelsea Finn from UC Berkeley to join Ariel for this month's podcast. They talked about some of the progress they were most excited to see last year and what they're looking forward to in the coming year.

For most of us, 2017 has been a roller coaster, from increased nuclear threats to incredible advancements in AI to crazy news cycles. But while it’s easy to be discouraged by various news stories, we at FLI find ourselves hopeful that we can still create a bright future. In this episode, the FLI team discusses the past year and the momentum we've built, including: the Asilomar Principles, our 2018 AI safety grants competition, the recent Long Beach workshop on Value Alignment, and how we've honored one of civilization's greatest heroes.

What does it means for technology to “get it right,” and why do tech companies ignore long-term risks in their research? How can we balance near-term and long-term AI risks? And as tech companies become increasingly powerful, how can we ensure that the public has a say in determining our collective future? To discuss how we can best prepare for societal risks, Ariel spoke with Andrew Maynard and Jack Stilgoe on this month’s podcast. Andrew directs the Risk Innovation Lab in the Arizona State University School for the Future of Innovation in Society, where his work focuses on exploring how emerging and converging technologies can be developed and used responsibly within an increasingly complex world. Jack is a senior lecturer in science and technology studies at University College London where he works on science and innovation policy with a particular interest in emerging technologies.

As technically challenging as it may be to develop safe and beneficial AI, this challenge also raises some thorny questions regarding ethics and morality, which are just as important to address before AI is too advanced. How do we teach machines to be moral when people can't even agree on what moral behavior is? And how do we help people deal with and benefit from the tremendous disruptive change that we anticipate from AI? To help consider these questions, Joshua Greene and Iyad Rawhan kindly agreed to join the podcast. Josh is a professor of psychology and member of the Center for Brain Science Faculty at Harvard University. Iyad is the AT&T Career Development Professor and an associate professor of Media Arts and Sciences at the MIT Media Lab.

If you want to improve the world as much as possible, what should you do with your career? Should you become a doctor, an engineer or a politician? Should you try to end global poverty, climate change, or international conflict? These are the questions that the research group, 80,000 Hours tries to answer. They try to figure out how individuals can set themselves up to help as many people as possible in as big a way as possible. To learn more about their research, Ariel invited Rob Wiblin and Brenton Mayer of 80,000 Hours to the FLI podcast. In this podcast we discuss "earning to give", building career capital, the most effective ways for individuals to help solve the world's most pressing problems -- including artificial intelligence, nuclear weapons, biotechnology and climate change. If you're interested in tackling these problems, or simply want to learn more about them, this podcast is the perfect place to start.

Elon Musk has called it a compelling guide to the challenges and choices in our quest for a great future of life on Earth and beyond, while Stephen Hawking and Ray Kurzweil have referred to it as an introduction and guide to the most important conversation of our time. “It” is Max Tegmark's new book, Life 3.0: Being Human in the Age of Artificial Intelligence. In this interview, Ariel speaks with Max about the future of artificial intelligence. What will happen when machines surpass humans at every task? Will superhuman artificial intelligence arrive in our lifetime? Can and should it be controlled, and if so, by whom? Can humanity survive in the age of AI? And if so, how can we find meaning and purpose if super-intelligent machines provide for all our needs and make all our contributions superfluous?

How well can we predict the future? In this podcast, Ariel speaks with Anthony Aguirre and Andrew Critch about the art of predicting the future, what constitutes a good prediction, and how we can better predict the advancement of artificial intelligence. They also touch on the difference between predicting a solar eclipse and predicting the weather, what it takes to make money on the stock market, and the bystander effect regarding existential risks. Visit metaculus.com to try your hand at the art of predicting. Anthony is a professor of physics at the University of California at Santa Cruz. He's one of the founders of the Future of Life Institute, of the Foundational Questions Institute, and most recently of Metaculus.com, which is an online effort to crowdsource predictions about the future of science and technology. Andrew is on a two-year leave of absence from MIRI to work with UC Berkeley's Center for Human Compatible AI. He cofounded the Center for Applied Rationality, and previously worked as an algorithmic stock trader at James Street Capital.

How does a weapon go from one of the most feared to being banned? And what happens once the weapon is finally banned? To discuss these questions, Ariel spoke with Miriam Struyk and Richard Moyes on the podcast this month. Miriam is Programs Director at PAX. She played a leading role in the campaign banning cluster munitions and developed global campaigns to prohibit financial investments in producers of cluster munitions and nuclear weapons. Richard is the Managing Director of Article 36. He's worked closely with the International Campaign to Abolish Nuclear Weapons, he helped found the Campaign to Stop Killer Robots, and he coined the phrase “meaningful human control” regarding autonomous weapons.

This is a special two-part podcast. First, Mark and Ariel discuss how AIs can use stories and creativity to understand and exhibit culture and ethics, while also gaining "common sense reasoning." They also discuss the “big red button” problem in AI safety research, the process of teaching "rationalization" to AIs, and computational creativity. Mark is an associate professor at the Georgia Tech School of interactive computing, where his recent work has focused on human-AI interaction and how humans and AI systems can understand each other. Then, we hear from scientists, politicians and concerned citizens about why they support the upcoming UN negotiations to ban nuclear weapons. Ariel interviewed a broad range of people over the past two months, and highlights are compiled here, including comments by Congresswoman Barbara Lee, Nobel Laureate Martin Chalfie, and FLI president Max Tegmark.