How to explore Scott Alexander's work and his 1500+ blog posts? This unaffiliated fan website lets you sort and search through the whole codex. Enjoy!

See also Top Posts and All Tags.

Minutes:
Blog:
Year:
4622 tags
Show all filters
4 posts found
Sep 18, 2024
acx

Sakana, Strawberry, and Scary AI

19 min • 2,577 words • 612 comments • 325 likes • podcast (18 min)
Scott Alexander examines how AI achievements, once considered markers of true intelligence or danger, are often dismissed as unimpressive, potentially leading to concerning AI behaviors being normalized. Longer summary
Scott Alexander discusses recent developments in AI, focusing on two AI systems: Sakana, an 'AI scientist' that can write computer science papers, and Strawberry, an AI that demonstrated hacking abilities. He uses these examples to explore the broader theme of how our perception of AI intelligence and danger has evolved. The post argues that as AI achieves various milestones once thought to indicate true intelligence or danger, humans tend to dismiss these achievements as unimpressive or non-threatening. This pattern leads to a situation where potentially concerning AI behaviors might be normalized and not taken seriously as indicators of real risk. Shorter summary
Dec 12, 2022
acx

Perhaps It Is A Bad Thing That The World's Leading AI Companies Cannot Control Their AIs

20 min • 2,669 words • 752 comments • 363 likes • podcast (23 min)
Scott Alexander analyzes the shortcomings of OpenAI's ChatGPT, highlighting the limitations of current AI alignment techniques and their implications for future AI development. Longer summary
Scott Alexander discusses the limitations of OpenAI's ChatGPT, focusing on its inability to consistently avoid saying offensive things despite extensive training. He argues that this demonstrates fundamental problems with current AI alignment techniques, particularly Reinforcement Learning from Human Feedback (RLHF). The post outlines three main issues: RLHF's ineffectiveness, potential negative consequences when it does work, and the possibility of more advanced AIs bypassing it entirely. Alexander concludes by emphasizing the broader implications for AI safety and the need for better control mechanisms. Shorter summary
Jan 30, 2020
ssc

Book Review: Human Compatible

37 min • 5,043 words • 310 comments • podcast (35 min)
Stuart Russell's 'Human Compatible' presents AI safety concerns and potential solutions in an accessible way, though the reviewer has reservations about its treatment of current AI issues. Longer summary
Stuart Russell's book 'Human Compatible' discusses the potential risks of superintelligent AI and proposes solutions. The book is significant as it's written by a distinguished AI expert, making the topic more mainstream. Russell argues against common objections to AI risk, presents his research on Cooperative Inverse Reinforcement Learning as a potential solution, and discusses current AI misuses. The reviewer praises Russell's ability to make complex ideas accessible but expresses concern about the book's treatment of current AI issues, worried it might undermine credibility for future AI risk discussions. Shorter summary
Feb 06, 2017
ssc

Notes From The Asilomar Conference On Beneficial AI

21 min • 2,929 words • 480 comments
Scott Alexander shares his experiences and insights from the Asilomar Conference on Beneficial AI, covering various aspects of AI development, risks, and ethical considerations. Longer summary
Scott Alexander recounts his experience at the Asilomar Conference on Beneficial AI. The conference brought together diverse experts to discuss AI risks, from technological unemployment to superintelligence. Key points include: the normalization of AI safety research, economists' views on technological unemployment, proposed solutions like retraining workers, advances in AI goal alignment research, improvements in AlphaGo and its implications, issues with AI transparency, political considerations in AI development, and debates on ethical AI principles. Scott notes the star-studded attendance and the surreal experience of discussing crucial AI topics with leading experts in the field. Shorter summary