The unstated disagreement that underpins safety debates
The AI safety movement needs normies
A broader base may be the only way for the AI safety field to get what it wants
Safety isn’t safety without a social model (or: dispelling the myth of per se technical safety) — AI Alignment Forum
As an AI researcher who wants to do technical work that helps humanity, there is a strong drive to find a research area that is definitely helpful so…
How a single tweet transformed the AI safety debate
Most people think AI is risky, but they don’t agree what to do next.
A new writing series: Re-envisioning AI safety through global majority perspectives | Brookings
Chinasa T. Okolo previews a new writing series that will re-envision AI safety through global majority perspectives.
Who decides when AI is too dangerous?
Anthropic asked for AI regulation, but not like this.
AI safety and the data center backlash
Planting a flag for AI safety as a place where we won’t abjectly bullshit you
AI Safety Is Mostly A Sex Cult In Berkeley, California
We might some day have “AI Safety”, as a science or policy area, that is not primarily a sex cult in Berkeley, California, but it does not currently exist.
Curriculum | AI Safety — ARENA
Explore the ARENA curriculum for AI safety education, covering fundamentals, transformers, reinforcement learning, and evaluations, with resources for educators and learners.
Safety Co-Option and Compromised National Security: The Self-Fulfilling Prophecy of Weakened AI Risk Thresholds
Risk thresholds provide a measure of the level of risk exposure that a society or individual is willing to withstand, ultimately shaping how we determine the safety of technological systems. Against the backdrop of the Cold War, the first risk analyses, such as those devised for nuclear systems, cemented societally accepted risk thresholds against which safety-critical and defense systems are now evaluated. But today, the appropriate risk tolerances for AI systems have yet to be agreed on by global governing efforts, despite the need for democratic deliberation regarding the acceptable levels of harm to human life. Absent such AI risk thresholds, AI technologists-primarily industry labs, as well as "AI safety" focused organizations-have instead advocated for risk tolerances skewed by a purported AI arms race and speculative "existential" risks, taking over the arbitration of risk determinations with life-or-death consequences, subverting democratic processes. In this paper, we demonstrate how such approaches have allowed AI technologists to engage in "safety revisionism," substituting traditional safety methods and terminology with ill-defined alternatives that vie for the accelerated adoption of military AI uses at the cost of lowered safety and security thresholds. We explore how the current trajectory for AI risk determination and evaluation for foundation model use within national security is poised for a race to the bottom, to the detriment of the US's national security interests. Safety-critical and defense systems must comply with assurance frameworks that are aligned with established risk thresholds, and foundation models are no exception. As such, development of evaluation frameworks for AI-based military systems must preserve the safety and security of US critical and defense infrastructure, and remain in alignment with international humanitarian law.
AI Safety Is a Narrative Problem · Special Issue 5: Grappling With the Generative AI Revolution
This op-ed explores power and narrative dynamics around AI. Drawing on pop-culture references, the professional experiences of the author and examples from 2023’s “Great AI Safety Hype Roadshow,” this piece draws on the literary criticism technique of practical criticism to consider how speeches and announcements from both Silicon Valley executives and research scientists to interrogate the media-friendly nature of p(doom) discourse—which focuses on the existential risks of AI (PauseAI, 2023)—and its likely consequences. The complexities of AI and its numerous social impacts can be difficult for even the most expert analyst to unpack. In spite of this, the potential of “existential threats” has successfully cut through to become a mainstay of mainstream media coverage over the last year. This piece will make the case that this is an effective narrative conceit that has achieved a number of ends that traditional science communication tends to find difficult, if not impossible, to achieve. Firstly, it is easy to understand. Simplification of this nature—that removes jargon and complexity and focuses on a single outcome—is much easier to fit on a TV rolling news ticker or on the cover of a tabloid newspaper than more well-balanced, representative opinions. Secondly, it inherits prior assumptions from well-known dramatic forms. P(doom) plays to stories familiar from Greek tragedy through to Marvel movies, in which lone male heroes battle ineluctable forces. Thirdly, it is imbued with urgency and so becomes difficult to ignore.
AI Safety Is a Narrative Problem · Special Issue 5: Grappling With the Generative AI Revolution
This op-ed explores power and narrative dynamics around AI. Drawing on pop-culture references, the professional experiences of the author and examples from 2023’s “Great AI Safety Hype Roadshow,” this piece draws on the literary criticism technique of practical criticism to consider how speeches and announcements from both Silicon Valley executives and research scientists to interrogate the media-friendly nature of p(doom) discourse—which focuses on the existential risks of AI (PauseAI, 2023)—and its likely consequences. The complexities of AI and its numerous social impacts can be difficult for even the most expert analyst to unpack. In spite of this, the potential of “existential threats” has successfully cut through to become a mainstay of mainstream media coverage over the last year. This piece will make the case that this is an effective narrative conceit that has achieved a number of ends that traditional science communication tends to find difficult, if not impossible, to achieve. Firstly, it is easy to understand. Simplification of this nature—that removes jargon and complexity and focuses on a single outcome—is much easier to fit on a TV rolling news ticker or on the cover of a tabloid newspaper than more well-balanced, representative opinions. Secondly, it inherits prior assumptions from well-known dramatic forms. P(doom) plays to stories familiar from Greek tragedy through to Marvel movies, in which lone male heroes battle ineluctable forces. Thirdly, it is imbued with urgency and so becomes difficult to ignore.
The AI safety vibe shift
Once a fringe obsession of Bay Area rationalists, existential risk is suddenly all anyone is talking about
The Locally Optimal Discursive Posture — LessWrong
Longtime lurker, first-time poster. • I want to address a section of a recent essay of mine that has gotten some attention within the AI safety commu…
How to Deploy AI Agents for Safety
