Are there such things as moral facts? If so, how might we be able to access them? Peter Singer started his career as a preference utilitarian and a moral anti-realist, and then over time became a hedonic utilitarian and a moral realist. How does such a transition occur, and which positions are more defensible? How might objectivism in ethics affect AI alignment? What does this all mean for the future of AI?

On Becoming a Moral Realist with Peter Singer is the sixth podcast in the AI Alignment series, hosted by Lucas Perry. For those of you that are new, this series will be covering and exploring the AI alignment problem across a large variety of domains, reflecting the fundamentally interdisciplinary nature of AI alignment. Broadly, we will be having discussions with technical and non-technical researchers across areas such as machine learning, AI safety, governance, coordination, ethics, philosophy, and psychology as they pertain to the project of creating beneficial AI. If this sounds interesting to you, we hope that you will join in the conversations by following us or subscribing to our podcasts on Youtube, SoundCloud, or your preferred podcast site/application.

In this podcast, Lucas spoke with Peter Singer. Peter is a world-renowned moral philosopher known for his work on animal ethics, utilitarianism, global poverty, and altruism. He's a leading bioethicist, the founder of The Life You Can Save, and currently holds positions at both Princeton University and The University of Melbourne.

Topics discussed in this episode include:

-Peter's transition from moral anti-realism to moral realism

-Why emotivism ultimately fails

-Parallels between mathematical/logical truth and moral truth

-Reason's role in accessing logical spaces, and its limits

-Why Peter moved from preference utilitarianism to hedonic utilitarianism

-How objectivity in ethics might affect AI alignment

How can humanity survive the next century of climate change, a growing population, and emerging technological threats? Where do we stand now, and what steps can we take to cooperate and address our greatest existential risks? In this special podcast episode, Ariel speaks with cosmologist Martin Rees about his new book, On the Future: Prospects for Humanity, which discusses humanity’s existential risks and the role that technology plays in determining our collective future.

Topics discussed in this episode include:

- Why Martin remains a technical optimist even as he focuses on existential risks

- The economics and ethics of climate change

- How AI and automation will make it harder for Africa and the Middle East to economically develop

- How high expectations for health care and quality of life also put society at risk

- Why growing inequality could be our most underappreciated global risk

- Martin’s view that biotechnology poses greater risk than AI

- Earth’s carrying capacity and the dangers of overpopulation

- Space travel and why Martin is skeptical of Elon Musk’s plan to colonize Mars

- The ethics of artificial meat, life extension, and cryogenics

- How intelligent life could expand into the galaxy

- Why humans might be unable to answer fundamental questions about the universe

On this month’s podcast, Ariel spoke with Paul Scharre and Mike Horowitz from the Center for a New American Security about the role of automation in the nuclear sphere, and how the proliferation of AI technologies could change nuclear posturing and the effectiveness of deterrence. Paul is a former Pentagon policy official, and the author of Army of None: Autonomous Weapons in the Future of War. Mike Horowitz is professor of political science at the University of Pennsylvania, and the author of The Diffusion of Military Power: Causes and Consequences for International Politics.

Topics discussed in this episode include:

The sophisticated military robots developed by Soviets during the Cold War

How technology shapes human decision-making in war

“Automation bias” and why having a “human in the loop” is much trickier than it sounds

The United States’ stance on automation with nuclear weapons

Why weaker countries might have more incentive to build AI into warfare

How the US and Russia perceive first-strike capabilities

“Deep fakes” and other ways AI could sow instability and provoke crisis

The multipolar nuclear world of US, Russia, China, India, Pakistan, and North Korea

The perceived obstacles to reducing nuclear arsenals

How are we to make progress on AI alignment given moral uncertainty?  What are the ideal ways of resolving conflicting value systems and views of morality among persons? How ought we to go about AI alignment given that we are unsure about our normative and metaethical theories? How should preferences be aggregated and persons idealized in the context of our uncertainty?

Moral Uncertainty and the Path to AI Alignment with William MacAskill is the fifth podcast in the new AI Alignment series, hosted by Lucas Perry. For those of you that are new, this series will be covering and exploring the AI alignment problem across a large variety of domains, reflecting the fundamentally interdisciplinary nature of AI alignment. Broadly, we will be having discussions with technical and non-technical researchers across areas such as machine learning, AI safety, governance, coordination, ethics, philosophy, and psychology as they pertain to the project of creating beneficial AI. If this sounds interesting to you, we hope that you will join in the conversations by following us or subscribing to our podcasts on Youtube, SoundCloud, or your preferred podcast site/application.

If you're interested in exploring the interdisciplinary nature of AI alignment, we suggest you take a look here at a preliminary landscape which begins to map this space.

In this podcast, Lucas spoke with William MacAskill. Will is a professor of philosophy at the University of Oxford and is a co-founder of the Center for Effective Altruism, Giving What We Can, and 80,000 Hours. Will helped to create the effective altruism movement and his writing is mainly focused on issues of normative and decision theoretic uncertainty, as well as general issues in ethics.

Topics discussed in this episode include:

-Will’s current normative and metaethical credences

-The value of moral information and moral philosophy

-A taxonomy of the AI alignment problem

-How we ought to practice AI alignment given moral uncertainty

-Moral uncertainty in preference aggregation

-Moral uncertainty in deciding where we ought to be going as a society

-Idealizing persons and their preferences

-The most neglected portion of AI alignment

Experts predict that artificial intelligence could become the most transformative innovation in history, eclipsing both the development of agriculture and the industrial revolution. And the technology is developing far faster than the average bureaucracy can keep up with. How can local, national, and international governments prepare for such dramatic changes and help steer AI research and use in a more beneficial direction?

On this month’s podcast, Ariel spoke with Allan Dafoe and Jessica Cussins about how different countries are addressing the risks and benefits of AI, and why AI is such a unique and challenging technology to effectively govern. Allan is the Director of the Governance of AI Program at the Future of Humanity Institute, and his research focuses on the international politics of transformative artificial intelligence. Jessica is an AI Policy Specialist with the Future of Life Institute, and she's also a Research Fellow with the UC Berkeley Center for Long-term Cybersecurity, where she conducts research on the security and strategy implications of AI and digital governance.

Topics discussed in this episode include:

- Three lenses through which to view AI’s transformative power

- Emerging international and national AI governance strategies

- The risks and benefits of regulating artificial intelligence

- The importance of public trust in AI systems

- The dangers of an AI race

- How AI will change the nature of wealth and power

What role does metaethics play in AI alignment and safety? How might paths to AI alignment change given different metaethical views? How do issues in moral epistemology, motivation, and justification affect value alignment? What might be the metaphysical status of suffering and pleasure?  What's the difference between moral realism and anti-realism and how is each view grounded?  And just what does any of this really have to do with AI?

The Metaethics of Joy, Suffering, and AI Alignment is the fourth podcast in the new AI Alignment series, hosted by Lucas Perry. For those of you that are new, this series will be covering and exploring the AI alignment problem across a large variety of domains, reflecting the fundamentally interdisciplinary nature of AI alignment. Broadly, we will be having discussions with technical and non-technical researchers across areas such as machine learning, AI safety, governance, coordination, ethics, philosophy, and psychology as they pertain to the project of creating beneficial AI. If this sounds interesting to you, we hope that you will join in the conversations by following us or subscribing to our podcasts on Youtube, SoundCloud, or your preferred podcast site/application.

If you're interested in exploring the interdisciplinary nature of AI alignment, we suggest you take a look here at a preliminary landscape which begins to map this space.

In this podcast, Lucas spoke with David Pearce and Brian Tomasik. David is a co-founder of the World Transhumanist Association, currently rebranded Humanity+. You might know him for his work on The Hedonistic Imperative, a book focusing on our moral obligation to work towards the abolition of suffering in all sentient life. Brian is a researcher at the Foundational Research Institute. He writes about ethics, animal welfare, and future scenarios on his website "Essays On Reducing Suffering." 

Topics discussed in this episode include:

-What metaethics is and how it ties into AI alignment or not

-Brian and David's ethics and metaethics

-Moral realism vs antirealism

-Emotivism

-Moral epistemology and motivation

-Different paths to and effects on AI alignment given different metaethics

-Moral status of hedonic tones vs preferences

-Can we make moral progress and would this mean?

-Moving forward given moral uncertainty

Why are so many AI researchers so worried about lethal autonomous weapons? What makes autonomous weapons so much worse than any other weapons we have today? And why is it so hard for countries to come to a consensus about autonomous weapons? Not surprisingly, the short answer is: it’s complicated.

In this month’s podcast, Ariel spoke with experts from a variety of perspectives on the current status of LAWS, where we are headed, and the feasibility of banning these weapons. Guests include ex-Pentagon advisor Paul Scharre, artificial intelligence professor Toby Walsh, Article 36 founder Richard Moyes, Campaign to Stop Killer Robots founders Mary Wareham and Bonnie Docherty, and ethicist and co-founder of the International Committee for Robot Arms Control, Peter Asaro.

If you don't have time to listen to the podcast in full, or if you want to skip around through the interviews, each interview starts at the timestamp below:

Paul Scharre: 3:40

Toby Walsh: 40:50

Richard Moyes: 53:30

Mary Wareham & Bonnie Docherty: 1:03:35

Peter Asaro: 1:32:40

What role does cyber security play in alignment and safety? What is AI completeness? What is the space of mind design and what does it tell us about AI safety? How does the possibility of machine qualia fit into this space? Can we leak proof the singularity to ensure we are able to test AGI? And what is computational complexity theory anyway?

AI Safety, Possible Minds, and Simulated Worlds is the third podcast in the new AI Alignment series, hosted by Lucas Perry. For those of you that are new, this series will be covering and exploring the AI alignment problem across a large variety of domains, reflecting the fundamentally interdisciplinary nature of AI alignment. Broadly, we will be having discussions with technical and non-technical researchers across areas such as machine learning, AI safety, governance, coordination, ethics, philosophy, and psychology as they pertain to the project of creating beneficial AI. If this sounds interesting to you, we hope that you will join in the conversations by following us or subscribing to our podcasts on Youtube, SoundCloud, or your preferred podcast site/application.

In this podcast, Lucas spoke with Roman Yampolskiy, a Tenured Associate Professor in the department of Computer Engineering and Computer Science at the Speed School of Engineering, University of Louisville. Dr. Yampolskiy’s main areas of interest are AI Safety, Artificial Intelligence, Behavioral Biometrics, Cybersecurity, Digital Forensics, Games, Genetic Algorithms, and Pattern Recognition. He is an author of over 100 publications including multiple journal articles and books. 

Topics discussed in this episode include:

-Cyber security applications to AI safety

-Key concepts in Roman's papers and books

-Is AI alignment solvable?

-The control problem

-The ethics of and detecting qualia in machine intelligence

-Machine ethics and it's role or lack thereof  in AI safety

-Simulated worlds and if detecting base reality is possible

-AI safety publicity strategy

How are emerging technologies like artificial intelligence shaping our world and how we interact with one another? What do different demographics think about AI risk and a robot-filled future? And how can the average citizen contribute not only to the AI discussion, but AI's development?

On this month's podcast, Ariel spoke with Charlie Oliver and Randi Williams about how technology is reshaping our world, and how their new project, Mission AI, aims to broaden the conversation and include everyone's voice.

Charlie is the founder and CEO of the digital media strategy company Served Fresh Media, and she's also the founder of Tech 2025, which is a platform and community for people to learn about emerging technologies and discuss the implications of emerging tech on society. Randi is a doctoral student in the personal robotics group at the MIT Media Lab. She wants to understand children's interactions with AI, and she wants to develop educational platforms that empower non-experts to develop their own AI systems.

In the classic taxonomy of risks developed by Nick Bostrom, existential risks are characterized as risks which are both terminal in severity and transgenerational in scope. If we were to maintain the scope of a risk as transgenerational and increase its severity past terminal, what would such a risk look like? What would it mean for a risk to be transgenerational in scope and hellish in severity?

In this podcast, Lucas spoke with Kaj Sotala, an associate researcher at the Foundational Research Institute. He has previously worked for the Machine Intelligence Research Institute, and has publications on AI safety, AI timeline forecasting, and consciousness research.

Topics discussed in this episode include:

-The definition of and a taxonomy of suffering risks

-How superintelligence has special leverage for generating or mitigating suffering risks

-How different moral systems view suffering risks

-What is possible of minds in general and how this plays into suffering risks

-The probability of suffering risks

-What we can do to mitigate suffering risks