blog – Page 6 – AI Impacts

GoCAS talk on AI Impacts findings

By Katja Grace, 27 November 2017 Here is a video summary of some highlights from AI Impacts research over the past years, from the GoCAS Existential Risk workshop in Göteborg in September. Thanks to the folks there

Price performance Moore’s Law seems slow

By Katja Grace, 26 November 2017 When people make predictions about AI, they often assume that computing hardware will carry on getting cheaper for the foreseeable future, at about the same rate that it usually

When do ML Researchers Think Specific Tasks will be Automated?

By Katja Grace, 26 September 2017 We asked the ML researchers in our survey when they thought 32 narrow, relatively well defined tasks would be feasible for AI. Eighteen of them were included in our paper

What do ML researchers think you are wrong about?

By Katja Grace, 25 September 2017 So, maybe you are concerned about AI risk. And maybe you are concerned that many people making AI are not concerned enough about it. Or not concerned about the

AI hopes and fears in numbers

By Katja Grace, 28 June 2017 People often wonder what AI researchers think about AI risk. A good collection of quotes can tell us that worry about AI is no longer a fringe view: many big names are concerned. But

Some survey results!

By Katja Grace, 8 June 2017 We put the main results of our survey of machine learning researchers on AI timelines online recently—see here for the paper. Apologies for the delay—we are trying to avoid spoiling the newsworthiness of the

Changes in funding in the AI safety field

Guest post by Seb Farquhar, originally posted to the Center for Effective Altruism blog. 20 February 2017 The field of AI Safety has been growing quickly over the last three years, since the publication of

Joscha Bach on remaining steps to human-level AI

By Katja Grace, 29 November 2016 Last year John and I had an interesting discussion with Joscha Bach about what ingredients of human-level artificial intelligence we seem to be missing, and how to improve AI forecasts more generally. Thanks

Tom Griffiths on Cognitive Science and AI

This is a guest post by Finan Adamson, 8 September 2016 Prof. Tom Griffiths is the director of the Computational Cognitive Science Lab and the Institute of Cognitive and Brain Sciences at UC Berkeley. He

What if you turned the world’s hardware into AI minds?

By Katja Grace, 4 September 2016 In a classic ‘AI takes over the world’ scenario, one of the first things an emerging superintelligence wants to do is steal most of the world’s computing hardware and repurpose it to running the AI’s