alignment

Robert Miles gives a remastered introduction to AI safety, adapted from a talk in London. It lays out why advanced AI could go wrong and answers common objections.

Veritasium's Derek Muller gives a Perimeter Institute livestream on how AI might change teaching and learning. He draws on past technology shifts and cognitive science to argue that learning requires effortful repetition.

Technosociologist Zeynep Tufekci argues that the machine-learning systems used to serve ads also decide what political and social information people see. She explains how opaque algorithms can nudge, segment and manipulate users, and warns that the real danger is powerful people using AI to control populations.

Tristan Harris and Aza Raskin of the Center for Humane Technology present why current AI capabilities pose catastrophic societal risks. They argue companies are racing to deploy without adequate safety, and that institutions must adapt. It was given before GPT-4's launch.

Charles Stross's 34C3 talk on how science fiction gets the future wrong. He argues that corporations are slow, human-powered AIs that optimize for profit, and that regulation lags behind accelerating technology.

Joscha Bach's 35C3 talk offers an AI perspective on the soul, covering perception, mental representation, agency, consciousness and selfhood as things that can arise in a computational system like the brain.

Novelist Daniel Suarez warns in a TED talk about autonomous robotic weapons and drones. He argues that taking the decision to kill out of human hands threatens democratic accountability and calls for a ban.

Brandon Sanderson's keynote on AI-generated art, arguing that the artistic process and the journey matter more than the finished product. He explains why he rebels against generative AI in creative work.

A Munk Debate on the proposition that AI research and development poses an existential threat. Yoshua Bengio and Max Tegmark argue for it, and Melanie Mitchell and Yann LeCun argue against.

Andrew Ng speaks at the Stanford MSx Future Forum about how AI is transforming industry after industry, comparing its impact to electricity. The talk also touches on evil-AI worries, jobs and basic income.

Chris Stucchio presents the ethical principles behind algorithmic decision making and shows with examples from lending, criminology and education that they cannot all be satisfied at once. The talk frames AI fairness as a set of quantitative tradeoffs.

Sal Khan of Khan Academy gives a TED talk on how AI could transform education, with a personal tutor for every student and a teaching assistant for every teacher. He demos Khanmigo, including features where the AI reasons before responding.

Sam Harris argues in a TED talk that we will build superhuman AI and have not grappled with the risk of creating something that may treat us the way we treat ants. He makes a logical case for taking AI risk seriously.

Bryan Cantrill's Monktoberfest 2023 talk takes on AI doomerism, weighing the theoretical existential risks against the reality on the ground. He takes a skeptical but thoughtful view of how to balance AI's potential against its risks.

Demis Hassabis of DeepMind speaks at Google Zeitgeist, saying human-level AI is decades away but the debate should start now. He covers DeepMind's focus on game-playing agents.

OpenAI cofounder Greg Brockman explains the design principles behind ChatGPT and demos unreleased plug-ins at TED 2023. In the follow-up, TED head Chris Anderson presses him on the timeline of development and the risks of releasing such a tool.

A short pre-recorded talk by Rich Sutton for the World AI Conference in Shanghai arguing that succession from humanity to AI is inevitable. He lays out his view of that transition.

Sam Altman accepts the 2023 Hawking Fellowship at the Cambridge Union and speaks about OpenAI, AGI and AI safety, recorded November 1, 2023. It includes his comments on what is left for AGI and on discovering new physics.

A panel from the Beneficial AI 2017 conference moderated by Max Tegmark, with Elon Musk, Stuart Russell, Kurzweil, Hassabis, Harris, Bostrom, Chalmers and others. They discuss likely outcomes of human-level AGI and what outcomes are desirable.

Ray Kurzweil presents his book How to Create a Mind at Google, on reverse engineering the brain and using that understanding to build intelligent machines. He shows his graphs of exponential technological progress.

Emery Berger explains why performance is hard to measure and deliver on modern hardware, showing how code layout and alignment can swamp optimization effects. He presents Stabilizer for statistically sound evaluation and Coz, a causal profiler.