Uncategorized – AI Impacts

A policy guaranteed to increase AI timelines

A redefinition of the second is a foolproof way to increase the number of years between nearly any two events.

How popular is ChatGPT? Part 1: more popular than Taylor Swift

What does search volume tell us about public attention on ChatGPT and AI in general?

The public supports regulating AI for safety

Some survey data

Product safety is a poor model for AI governance

Relying on safety-checking after development is not sufficient.

List of sources arguing against existential risk from AI

A bibliography of pieces arguing against the idea that advanced AI poses an existential risk to humanity.

Do neural networks learn human concepts?

This page is a stub. It does not necessarily represent much of what is known on the topic. Our understanding is that the degree to which neural networks learn concepts that are potentially understandable to

April files

Katja Grace April 2021

Internal drafts for feedback

Discontinuous progress in history: an update

Katja Grace April 2020
We’ve been looking for historic cases of discontinuously fast technological progress, to help with reasoning about the likelihood and consequences of abrupt progress in AI capabilities. We recently finished expanding this investigation to 37 technological trends. This blog post is a quick update on our findings. See the main page on the research and its outgoing links for more details.

Three kinds of competitiveness

By Daniel Kokotajlo, 30 March 2020 In this post, I distinguish between three different kinds of competitiveness — Performance, Cost, and Date — and explain why I think these distinctions are worth the brainspace they

Historic trends in book production

The number of books produced in the previous hundred years, sampled every hundred or fifty years between 600AD to 1800AD contains five greater than 10-year discontinuities, four of them greater than 100 years. The last