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

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 feedback from others on whether the thinking behind it makes sense – I decided to write a shorter summary. While I am […]

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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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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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A reply to Thomas Metzinger’s BAAN thought experiment

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 the goal of assisting us with ethical deliberation. Being superior to us in its understanding of how our own minds function, the […]

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Uncertainty smoothes 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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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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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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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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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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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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