Report -- Allocating risk mitigation across time

owencb

I've just released a Future of Humanity Institute technical report, written as part of the Global Priorities Project.

Abstract:

This article is about priority-setting for work aiming to reduce existential risk. Its chief claim is that all else being equal we should prefer work earlier and prefer to work on risks that might come early. This is because we are uncertain about when we will have to face different risks, because we expect diminishing returns of extra work, and because we expect that more people will work on these risks in the future.

I explore this claim both qualitatively and with explicit models. I consider its implications for two questions: first, “When is it best to do different kinds of work?”; second, “Which risks should we focus on?”.

As a major application, I look at the case of risk from artificial intelligence. The best strategies for reducing this risk depend on when the risk is coming. I argue that we may be underinvesting in scenarios where AI comes soon even though these scenarios are relatively unlikely, because we will not have time later to address them.

You can read the full report here: Allocating risk mitigation across time.

I've just released a Future of Humanity Institute technical report, written as part of the Global Priorities Project.

Abstract:

This article is about priority-setting for work aiming to reduce existential risk. Its chief claim is that all else being equal we should prefer work earlier and prefer to work on risks that might come early. This is because we are uncertain about when we will have to face different risks, because we expect diminishing returns of extra work, and because we expect that more people will work on these risks in the future.

I explore this claim both qualitatively and with explicit models. I consider its implications for two questions: first, “When is it best to do different kinds of work?”; second, “Which risks should we focus on?”.

As a major application, I look at the case of risk from artificial intelligence. The best strategies for reducing this risk depend on when the risk is coming. I argue that we may be underinvesting in scenarios where AI comes soon even though these scenarios are relatively unlikely, because we will not have time later to address them.

You can read the full report here: Allocating risk mitigation across time.

I read the full report, excluding the appendices. I'm a layperson. That is, I don't expect I'll ever do direct work on existential risk mitigation, or engineering safety into machine intelligence. Further, I'm not well-versed in the technicalities of either Friendliness theory from the MIRI, or literature from academic studies of artificial intelligence.

As a layperson, I don't know how to assess how much labor is assigned to AI-soon vs. AI-later outcomes. What does AI-soon work look like? What are its features or qualities? Do you consider the MIRI's current research as 'AI-soon' labor?

I don't have the source now, but Robin Hanson mentioned on a couple past blog posts on Overcoming Bias that work on existential risk reduction isn't being done, because nobody knows how to do it. This is a rather cynical perspective, as it would not count the work of the FHI, or the MIRI, as being on existential risk reduction. I believe Dr. Hanson meant it appears no direct, or object-level work is being done. These were from a couple years ago, so his position may be different. The landscape for AI safety has changed dramatically in the last two years. Still, I wonder if it's hard to tell how much, or which, research is oriented toward "sooner" rather than "later" outcomes is because: we don't know how to do that (object-level) work.

This is a good question. To some extent I didn't want to take a position on exactly which work is appropriate for this, as that's independent of the rest of the analysis (although obviously feeds into model parameter estimates).

Something which would definitely help would be just to systematically review what might be useful for AI-soon outcomes.

Possibilities include: working to study the architecture of the more plausible candidates for producing AI; design work on containment mechanisms; producing high-quality data sets of 'human values' (in case value-le... (read more)

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Report -- Allocating risk mitigation across time

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Report -- Allocating risk mitigation across time

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