7 July 2020

Reducing long-term risks from malevolent actors

Summary Dictators who exhibited highly narcissistic, psychopathic, or sadistic traits were involved in some of the greatest catastrophes in human history.  Malevolent individuals in positions of power could negatively affect humanity’s long-term trajectory by, for example, exacerbating international conflict or other broad risk factors. Malevolent humans with access to advanced technology—such as whole brain emulation […]

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22 February 2019

Risk factors for s-risks

Traditional disaster risk prevention has a concept of risk factors. These factors are not risks in and of themselves, but they increase either the probability or the magnitude of a risk. For instance, inadequate governance structures do not cause a specific disaster, but if a disaster strikes it may impede an effective response, thus increasing the damage. Rather than considering individual scenarios of how s-risks could occur, which tends to be highly speculative, this post instead looks at risk factors – i.e. factors that would make s-risks more likely or more severe.

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3 July 2018

Challenges to implementing surrogate goals

Surrogate goals might be one of the most promising approaches to reduce (the disvalue resulting from) threats. The idea is to add to one’s current goals a surrogate goal that one did not initially care about, hoping that any potential threats will target this surrogate goal rather than what one initially cared about. In this post, I will outline two key obstacles to a successful implementation of surrogate goals.

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29 March 2018

A framework for thinking about AI timescales

To steer the development of powerful AI in beneficial directions, we need an accurate understanding of how the transition to a world with powerful AI systems will unfold. A key question is how long such a transition (or “takeoff”) will take.

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1 March 2018

Commenting on MSR, Part 2: Cooperation heuristics

Published on the CLR blog, where researchers are free to explore their own ideas on how humanity can best reduce suffering. (more) Summary This post was originally written for internal discussions only; it is half-baked and unpolished. The post assumes familiarity with the ideas discussed in Caspar Oesterheld’s paper Multiverse-wide cooperation via coordinated decision-making. I […]

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20 February 2018

Using surrogate goals to deflect threats

Agents that threaten to harm other agents, either in an attempt at extortion or as part of an escalating conflict, are an important form of agential s-risks. To avoid worst-case outcomes resulting from the execution of such threats, I suggest that agents add a “meaningless” surrogate goal to their utility function.

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14 November 2017

Self-improvement races

Just like human factions may race toward AI and thus risk misalignment, AIs may race toward superior abilities by self-improving themselves in risky ways.

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2 November 2017

Commenting on MSR, Part 1: Multiverse-wide cooperation in a nutshell

Published on the CLR blog, where researchers are free to explore their own ideas on how humanity can best reduce suffering. (more) This is a post I wrote about Caspar Oesterheld’s long paper Multiverse-wide cooperation via coordinated decision-making. Because I have found the idea tricky to explain – which unfortunately makes it difficult to get […]

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21 September 2017

S-risk FAQ

In the essay Reducing Risks of Astronomical Suffering: A Neglected Priority, s-risks (also called suffering risks or risks of astronomical suffering) are defined as “events that would bring about suffering on an astronomical scale, vastly exceeding all suffering that has existed on Earth so far”.

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18 September 2017

Focus areas of worst-case AI safety

Efforts to shape advanced artificial intelligence (AI) may be among the most promising altruistic endeavours. If the transition to advanced AI goes wrong, the worst outcomes may involve not only the end of human civilization, but also astronomical amounts of suffering – a so-called s-risk.

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10 August 2017

A reply to Thomas Metzinger’s BAAN thought experiment

Published on the CLR blog, where researchers are free to explore their own ideas on how humanity can best reduce suffering. (more) This is a reply to Metzinger’s essay on Benevolent Artificial Anti-natalism (BAAN), which appeared on EDGE.org (7.8.2017). Metzinger invites us to consider a hypothetical scenario where smarter-than-human artificial intelligence (AI) is built with […]

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21 July 2017

Uncertainty smooths out differences in impact

Suppose you investigated two interventions A and B and came up with estimates for how much impact A and B will have. Your best guess is that A will spare a billion sentient beings from suffering, while B “only” spares a thousand beings. Now, should you actually believe that A is many orders of magnitude more effective than B?

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17 July 2017

Arguments for and against moral advocacy

This post analyses key strategic questions on moral advocacy, such as: What does moral advocacy look like in practice? Which values should we spread, and how? How effective is moral advocacy compared to other interventions such as directly influencing new technologies? What are the most important arguments for and against focusing on moral advocacy?

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30 June 2017

Strategic implications of AI scenarios

Efforts to mitigate the risks of advanced artificial intelligence may be a top priority for effective altruists. If this is true, what are the best means to shape AI? Should we write math-heavy papers on open technical questions, or opt for broader, non-technical interventions like values spreading?

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26 June 2017

Tool use and intelligence: A conversation

This post is a discussion between Lukas Gloor and Tobias Baumann on the meaning of tool use and intelligence, which is relevant to our thinking about the future or (artificial) intelligence and the likelihood of AI scenarios.

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20 June 2017

Training neural networks to detect suffering

Imagine a data set of images labeled “suffering” or “no suffering”. For instance, suppose the “suffering” category contains documentations of war atrocities or factory farms, and the “no suffering” category contains innocuous images – say, a library. We could then use a neural network or other machine learning algorithms to learn to detect suffering based on that data.

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19 June 2017

Launching the FRI blog

We were moved by the many good reasons to make conversations public. At the same time, we felt the content we wanted to publish differed from the articles on our main site. Hence, we're happy to announce the launch of FRI’s new blog.

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21 November 2016

Backup Utility Functions: A Fail-Safe AI Technique

Setting up the goal systems of advanced AIs in a way that results in benevolent behavior is expected to be difficult. We should account for the possibility that the goal systems of AIs fail to implement our values as originally intended. In this paper, we propose the idea of backup utility functions: Secondary utility functions that are used in case the primary ones “fail”.

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14 August 2016

Identifying Plausible Paths to Impact and their Strategic Implications

FRI’s research seeks to identify the best intervention(s) for suffering reducers to work on. Rather than continuing our research indefinitely, we will eventually have to focus our efforts on an intervention directly targeted at improving the world. This report outlines plausible candidates for FRI’s “path to impact” and distills some advice on how current movement building efforts can best prepare for them.

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7 June 2016

Our Mission

This is a snapshot of the Center on Long-Term Risk’s (formerly Foundational Research Institute) previous "Our Mission" page. The Foundational Research Institute (FRI) conducts research on how to best reduce the suffering of sentient beings in the long-term future. We publish essays and academic articles, make grants to support research on our priorities, and advise […]

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