This event was cross-posted from [LessWrong](https://www.lesswrong.com/events/bGZ8Smiha9MGNSQf5/berlin-ai-safety-meetup-march-2025)

​​​​​​Open meetup for people working on or interested in AI Safety. People new to the field welcome!

​We'll be discussing ongoing projects, research and recent papers, Namely the recent Emergent Misalignment paper.

​Subscribe to AI Safety Berlin Announcements on Telegram, Signal or Whatsapp and join the Community Chat.

RSVP here
aisafety.berlin

2

0
0

Reactions

0
0
Comments


No comments on this post yet.
Be the first to respond.
Curated and popular this week
Sam Anschell
 ·  · 6m read
 · 
*Disclaimer* I am writing this post in a personal capacity; the opinions I express are my own and do not represent my employer. I think that more people and orgs (especially nonprofits) should consider negotiating the cost of sizable expenses. In my experience, there is usually nothing to lose by respectfully asking to pay less, and doing so can sometimes save thousands or tens of thousands of dollars per hour. This is because negotiating doesn’t take very much time[1], savings can persist across multiple years, and counterparties can be surprisingly generous with discounts. Here are a few examples of expenses that may be negotiable: For organizations * Software or news subscriptions * Of 35 corporate software and news providers I’ve negotiated with, 30 have been willing to provide discounts. These discounts range from 10% to 80%, with an average of around 40%. * Leases * A friend was able to negotiate a 22% reduction in the price per square foot on a corporate lease and secured a couple months of free rent. This led to >$480,000 in savings for their nonprofit. Other negotiable parameters include: * Square footage counted towards rent costs * Lease length * A tenant improvement allowance * Certain physical goods (e.g., smart TVs) * Buying in bulk can be a great lever for negotiating smaller items like covid tests, and can reduce costs by 50% or more. * Event/retreat venues (both venue price and smaller items like food and AV) * Hotel blocks * A quick email with the rates of comparable but more affordable hotel blocks can often save ~10%. * Professional service contracts with large for-profit firms (e.g., IT contracts, office internet coverage) * Insurance premiums (though I am less confident that this is negotiable) For many products and services, a nonprofit can qualify for a discount simply by providing their IRS determination letter or getting verified on platforms like TechSoup. In my experience, most vendors and companies
 ·  · 4m read
 · 
Forethought[1] is a new AI macrostrategy research group cofounded by Max Dalton, Will MacAskill, Tom Davidson, and Amrit Sidhu-Brar. We are trying to figure out how to navigate the (potentially rapid) transition to a world with superintelligent AI systems. We aim to tackle the most important questions we can find, unrestricted by the current Overton window. More details on our website. Why we exist We think that AGI might come soon (say, modal timelines to mostly-automated AI R&D in the next 2-8 years), and might significantly accelerate technological progress, leading to many different challenges. We don’t yet have a good understanding of what this change might look like or how to navigate it. Society is not prepared. Moreover, we want the world to not just avoid catastrophe: we want to reach a really great future. We think about what this might be like (incorporating moral uncertainty), and what we can do, now, to build towards a good future. Like all projects, this started out with a plethora of Google docs. We ran a series of seminars to explore the ideas further, and that cascaded into an organization. This area of work feels to us like the early days of EA: we’re exploring unusual, neglected ideas, and finding research progress surprisingly tractable. And while we start out with (literally) galaxy-brained schemes, they often ground out into fairly specific and concrete ideas about what should happen next. Of course, we’re bringing principles like scope sensitivity, impartiality, etc to our thinking, and we think that these issues urgently need more morally dedicated and thoughtful people working on them. Research Research agendas We are currently pursuing the following perspectives: * Preparing for the intelligence explosion: If AI drives explosive growth there will be an enormous number of challenges we have to face. In addition to misalignment risk and biorisk, this potentially includes: how to govern the development of new weapons of mass destr
 ·  · 1m read
 · 
This is a linkpost for a new paper called Preparing for the Intelligence Explosion, by Will MacAskill and Fin Moorhouse. It sets the high-level agenda for the sort of work that Forethought is likely to focus on. Some of the areas in the paper that we expect to be of most interest to EA Forum or LessWrong readers are: * Section 3 finds that even without a software feedback loop (i.e. “recursive self-improvement”), even if scaling of compute completely stops in the near term, and even if the rate of algorithmic efficiency improvements slow, then we should still expect very rapid technological development — e.g. a century’s worth of progress in a decade — once AI meaningfully substitutes for human researchers. * A presentation, in section 4, of the sheer range of challenges that an intelligence explosion would pose, going well beyond the “standard” focuses of AI takeover risk and biorisk. * Discussion, in section 5, of when we can and can’t use the strategy of just waiting until we have aligned superintelligence and relying on it to solve some problem. * An overview, in section 6, of what we can do, today, to prepare for this range of challenges.  Here’s the abstract: > AI that can accelerate research could drive a century of technological progress over just a few years. During such a period, new technological or political developments will raise consequential and hard-to-reverse decisions, in rapid succession. We call these developments grand challenges.  > > These challenges include new weapons of mass destruction, AI-enabled autocracies, races to grab offworld resources, and digital beings worthy of moral consideration, as well as opportunities to dramatically improve quality of life and collective decision-making. > > We argue that these challenges cannot always be delegated to future AI systems, and suggest things we can do today to meaningfully improve our prospects. AGI preparedness is therefore not just about ensuring that advanced AI systems are alig