Effective Altruism Forum
EA Forum

Hide table of contents
Comment Permalink
Manuel Allgaier3
0
0

I'm excited you're doing this! This seems helpful to fill this gap in AIS field building. 

(I'm late to the party, just saw this now in a newsletter)
 

Reply
See in context
by Agustín Covarrubias 🔸, Topaz
2 min read 2

79

AI safetyCareer choiceOpportunities to take actionResearch training programsAI safety groupsAnnouncements and updatesBuilding the field of AI safetyOrganization updates
Frontpage

TL;DR

  • We’re announcing Kairos, a new AI safety fieldbuilding organization focused on the early career talent pipeline.
  • We’re the new home for two programs:
    • FSP, which provides semester-based mentorship for organizers of AI safety university groups
    • SPAR, a program that pairs early career individuals to work on three-month AI safety research projects alongside experienced mentors
  • We’ve opened applications for the next round of FSP (starting in December 2024) and expressions of interest for SPAR (starting in February 2025).

Announcing Kairos

We’re excited to announce the launch of Kairos[1], a new AI safety fieldbuilding organization focused on strengthening the early career talent pipeline. Kairos will serve as the new institutional home for two existing programs: the Supervised Program for Alignment Research (SPAR), a mentorship program now on its fifth iteration, and the Fieldbuilder Support Program (FSP), a program in its second iteration.

We believe that growing and strengthening the infrastructure for AI safety talent is among the most promising fieldbuilding efforts, so we’re now focused on improving what we think are critical and neglected segments of the pipeline. We’re also planning to run a number of smaller, targeted support programs for AI safety groups. We hope to share more about our broader plans in the coming months.

Fieldbuilder Support Program (FSP)

FSP is a mentorship program (recently spun off of CEA’s Groups Team) that supports university AI safety group organizers in establishing and running their groups. During the program, organizers get paired with mentors who guide them through defining their group’s strategy and planning their semesters, as well as following up on their progress. The program has an initial period of three weeks, but most participants go on to be mentored for their entire semester.

Applications are now open!

  • The program will run from December 5th, 2024, through to the next semester
  • Each interested group organizer must apply separately
Apply here by November 15

We’re also looking for experienced existing or former group organizers to participate as paid mentors for the program. See here for details.

Supervised Program for Alignment Research (SPAR)

SPAR is a virtual, part-time research program that connects early-career individuals with experienced AI safety researchers. Participants work on 3-month projects in both technical and governance areas, with mentees typically committing 5-20 hours per week.

Expressions of interest are now open!

  • The program will run from February 10th to May 17th, 2025
  • Mentor applications will open in early November
  • Mentee applications will open in December
Express your interest here

If you're interested in contributing to AI safety field-building, whether as a student, professional, mentor, or researcher, we encourage you to get involved with our programs.

  1. ^

     Kairos is an ancient greek word meaning  “the critical moment” or the “the right moment to act”. Thanks to @Nicholas Marsh for coming up with the name.

79

1
0

Reactions

1
0
Mentioned in
Load more (5/6)
Comments2


Sorted by
New & upvoted
Click to highlight new comments since:
tzukitchan11
3
0
4

can’t think of better fit people to run these important programs! 🥳 congrats on the announcement launch, and cheers to more future projects under the Kairos banner!

Reply
Manuel Allgaier3
0
0

I'm excited you're doing this! This seems helpful to fill this gap in AIS field building. 

(I'm late to the party, just saw this now in a newsletter)
 

Reply
More from Agustín Covarrubias 🔸
48
Anthropic's submission to the White House's RFI on AI policy
Agustín Covarrubias 🔸
· · 1m read
7
7
292
Kelsey Piper's recent interview of SBF
Agustín Covarrubias 🔸
· · 2m read
155
155
54
UK announces early warning system for pandemics
Agustín Covarrubias 🔸
· · 1m read
0
0
View more
Curated and popular this week
Paul Present
 ·  · 28m read
 · 
Note: I am not a malaria expert. This is my best-faith attempt at answering a question that was bothering me, but this field is a large and complex field, and I’ve almost certainly misunderstood something somewhere along the way. Summary While the world made incredible progress in reducing malaria cases from 2000 to 2015, the past 10 years have seen malaria cases stop declining and start rising. I investigated potential reasons behind this increase through reading the existing literature and looking at publicly available data, and I identified three key factors explaining the rise: 1. Population Growth: Africa's population has increased by approximately 75% since 2000. This alone explains most of the increase in absolute case numbers, while cases per capita have remained relatively flat since 2015. 2. Stagnant Funding: After rapid growth starting in 2000, funding for malaria prevention plateaued around 2010. 3. Insecticide Resistance: Mosquitoes have become increasingly resistant to the insecticides used in bednets over the past 20 years. This has made older models of bednets less effective, although they still have some effect. Newer models of bednets developed in response to insecticide resistance are more effective but still not widely deployed.  I very crudely estimate that without any of these factors, there would be 55% fewer malaria cases in the world than what we see today. I think all three of these factors are roughly equally important in explaining the difference.  Alternative explanations like removal of PFAS, climate change, or invasive mosquito species don't appear to be major contributors.  Overall this investigation made me more convinced that bednets are an effective global health intervention.  Introduction In 2015, malaria rates were down, and EAs were celebrating. Giving What We Can posted this incredible gif showing the decrease in malaria cases across Africa since 2000: Giving What We Can said that > The reduction in malaria has be
Neel Nanda
 ·  · 1m read
 · 
TL;DR Having a good research track record is some evidence of good big-picture takes, but it's weak evidence. Strategic thinking is hard, and requires different skills. But people often conflate these skills, leading to excessive deference to researchers in the field, without evidence that that person is good at strategic thinking specifically. I certainly try to have good strategic takes, but it's hard, and you shouldn't assume I succeed! Introduction I often find myself giving talks or Q&As about mechanistic interpretability research. But inevitably, I'll get questions about the big picture: "What's the theory of change for interpretability?", "Is this really going to help with alignment?", "Does any of this matter if we can’t ensure all labs take alignment seriously?". And I think people take my answers to these way too seriously. These are great questions, and I'm happy to try answering them. But I've noticed a bit of a pathology: people seem to assume that because I'm (hopefully!) good at the research, I'm automatically well-qualified to answer these broader strategic questions. I think this is a mistake, a form of undue deference that is both incorrect and unhelpful. I certainly try to have good strategic takes, and I think this makes me better at my job, but this is far from sufficient. Being good at research and being good at high level strategic thinking are just fairly different skillsets! But isn’t someone being good at research strong evidence they’re also good at strategic thinking? I personally think it’s moderate evidence, but far from sufficient. One key factor is that a very hard part of strategic thinking is the lack of feedback. Your reasoning about confusing long-term factors need to extrapolate from past trends and make analogies from things you do understand better, and it can be quite hard to tell if what you're saying is complete bullshit or not. In an empirical science like mechanistic interpretability, however, you can get a lot more fe
Ronen Bar
 ·  · 10m read
 · 
"Part one of our challenge is to solve the technical alignment problem, and that’s what everybody focuses on, but part two is: to whose values do you align the system once you’re capable of doing that, and that may turn out to be an even harder problem", Sam Altman, OpenAI CEO (Link).  In this post, I argue that: 1. "To whose values do you align the system" is a critically neglected space I termed “Moral Alignment.” Only a few organizations work for non-humans in this field, with a total budget of 4-5 million USD (not accounting for academic work). The scale of this space couldn’t be any bigger - the intersection between the most revolutionary technology ever and all sentient beings. While tractability remains uncertain, there is some promising positive evidence (See “The Tractability Open Question” section). 2. Given the first point, our movement must attract more resources, talent, and funding to address it. The goal is to value align AI with caring about all sentient beings: humans, animals, and potential future digital minds. In other words, I argue we should invest much more in promoting a sentient-centric AI. The problem What is Moral Alignment? AI alignment focuses on ensuring AI systems act according to human intentions, emphasizing controllability and corrigibility (adaptability to changing human preferences). However, traditional alignment often ignores the ethical implications for all sentient beings. Moral Alignment, as part of the broader AI alignment and AI safety spaces, is a field focused on the values we aim to instill in AI. I argue that our goal should be to ensure AI is a positive force for all sentient beings. Currently, as far as I know, no overarching organization, terms, or community unifies Moral Alignment (MA) as a field with a clear umbrella identity. While specific groups focus individually on animals, humans, or digital minds, such as AI for Animals, which does excellent community-building work around AI and animal welfare while
Recent opportunities in AI safety
35
Center on Long-Term Risk: Summer Research Fellowship 2025
Center on Long-Term Risk
· · 1m read
0
0
28
Apply to the Cambridge ERA:AI Fellowship 2025
Harrison 🔸
· · 3m read
0
0
24
Last week to apply for the Futurekind AI Fellowship! (deadline: April 1)
Jay Luong
· · 1m read
0
0
View more