AI Safety Research

Katja Grace

Research Associate

Machine Intelligence Research Institute

katjasolveig@gmail.com

Project: AI Impacts

Amount Recommended:    $49,310

Project Summary

Many experts think that within a century, artificial intelligence will be able to do almost anything a human can do. This might mean humans are no longer in control of what happens, and very likely means they are no longer employable. The world might be very different, and the changes that take place could be dangerous.

Very little research has asked when this transition will happen, what will happen, and how we can make it go well. AI Impacts is a project to ask those questions, and to answer them rigorously. We look for research projects that can shed light on the future of AI; especially on questions that matter to people making decisions. We publish the results online, and explain our research to a broad audience.

We are currently working on comparing the power of the brain to that of supercomputers, to help calculate when people will have enough hardware to run something as complex as a brain. We are also checking whether AI progress is likely to see sudden jumps, by looking for jumps in other areas of technological progress.

Technical Abstract

‘Human-level’ artificial intelligence will have far-reaching effects on society, and is generally anticipated within the coming century. Relatively little is known about the timelines or consequences of this arrival, though increasingly many decisions depend on guesses about it. AI Impacts identifies cost-effective research projects which might shed light on the future of AI, and especially on the parts of it that might guide policy and other decisions. We perform a selection of these research projects, and publish the results as accessible articles in the public domain.

We recently made a preliminary estimate of the computing performance of the brain in terms of traversed edges per second (TEPS), “a supercomputing benchmark” to better judge when computing hardware will be capable of replicating what the brain does, given the right software. We are also collecting case studies of abrupt technological progress to aid in evaluating the probability of discontinuities in AI progress. In the coming year we will continue with both of these projects, publish articles about several projects in progress, and start several new projects.