yanni's Shortform

Prediction: In 6-12 months people are going to start leaving Deepmind and Anthropic for similar sounding reasons to those currently leaving OpenAI (50% likelihood).

> Surface level read of what is happening at OpenAI; employees are uncomfortable with specific safety policies. 
> Deeper, more transferable, harder to solve problem; no person that is sufficiently well-meaning and close enough to the coal face at Big Labs can ever be reassured they're doing the right thing continuing to work for a company whose mission is to build AGI.

Basically, this is less about "OpenAI is bad" and more "Making AGI is bad". 

I like the fact that despite not being (relatively) young when they died, the LW banner states that Kahneman & Vinge have died "FAR TOO YOUNG", pointing to the fact that death is always bad and/or it is bad when people die when they were still making positive contributions to the world (Kahneman published "Noise" in 2021!).

[IMAGE] Extremely proud and excited to watch Greg Sadler (CEO of Good Ancestors Policy) and Soroush Pour (Co-Founder of Harmony Intelligence) speak to the Australian Federal Senate Select Committee on Artificial Intelligence. This is a big moment for the local movement. Also, check out who they ran after.

Something I'm confused about: what is the threshold that needs meeting for the majority of people in the EA community to say something like "it would be better if EAs didn't work at OpenAI"?

Imagining the following hypothetical scenarios over 2024/25, I can't predict confidently whether they'd individually cause that response within EA?

1. Ten-fifteen more OpenAI staff quit for varied and unclear reasons. No public info is gained outside of rumours
2. There is another board shakeup because senior leaders seem worried about Altman. Altman stays on
3. Superalignment team is disbanded
4. OpenAI doesn't let UK or US AISI's safety test GPT5/6 before release
5. There are strong rumours they've achieved weakly general AGI internally at end of 2025

I recently discovered the idea of driving all blames into oneself, which immediately resonated with me. It is relatively hardcore; the kind of thing that would turn David Goggins into a Buddhist.

Gemini did a good job of summarising it:

This quote by Pema Chödron, a renowned Buddhist teacher, represents a core principle in some Buddhist traditions, particularly within Tibetan Buddhism. It's called "taking full responsibility" or "taking self-blame" and can be a bit challenging to understand at first. Here's a breakdown:

What it Doesn't Mean:

• Self-Flagellation: This practice isn't about beating yourself up or dwelling on guilt.
• Ignoring External Factors: It doesn't deny the role of external circumstances in a situation.

What it Does Mean:

• Owning Your Reaction: It's about acknowledging how a situation makes you feel and taking responsibility for your own emotional response.
• Shifting Focus: Instead of blaming others or dwelling on what you can't control, you direct your attention to your own thoughts and reactions.
• Breaking Negative Cycles: By understanding your own reactions, you can break free from negative thought patterns and choose a more skillful response.

Analogy:

Imagine a pebble thrown into a still pond. The pebble represents the external situation, and the ripples represent your emotional response. While you can't control the pebble (the external situation), you can control the ripples (your reaction).

Benefits:

• Reduced Suffering: By taking responsibility for your own reactions, you become less dependent on external circumstances for your happiness.
• Increased Self-Awareness: It helps you understand your triggers and cultivate a more mindful response to situations.
• Greater Personal Growth: By taking responsibility, you empower yourself to learn and grow from experiences.

Here are some additional points to consider:

• This practice doesn't mean excusing bad behavior. You can still hold others accountable while taking responsibility for your own reactions.
• It's a gradual process. Be patient with yourself as you learn to practice this approach.

I don't know how to say this in a way that won't come off harsh, but I've had meetings with > 100 people in the last 6 months in AI Safety and I've been surprised how poor the industry standard is for people:

- Planning meetings (writing emails that communicate what the meeting will be about, it's purpose, my role)
- Turning up to scheduled meetings (like literally, showing up at all)
- Turning up on time
- Turning up prepared (i.e. with informed opinions on what we're going to discuss)
- Turning up with clear agendas (if they've organised the meeting)
- Running the meetings
- Following up after the meeting (clear communication about next steps)

I do not have an explanation for what is going on here but it concerns me about the movement interfacing with government and industry. My background is in industry and these just seem to be things people take for granted?

It is possible I give off a chill vibe, leading to people thinking these things aren't necessary, and they'd switch gears for more important meetings!

There have been multiple occasions where I've copy and pasted email threads into an LLM and asked it things like:

1. What is X person saying
2. What are the cruxes in this conversation?
3. Summarise this conversation
4. What are the key takeaways
5. What views are being missed from this conversation

I really want an email plugin that basically brute forces rationality INTO email conversations.

I have heard rumours that an AI Safety documentary is being made. Separate to this, a good friend of mine is also seriously considering making one, but he isn't "in" AI Safety. If you know who this first group is and can put me in touch with them, it might be worth getting across each others plans.

More thoughts on "80,000 hours should remove OpenAI from the Job Board"

- - - - 

A broadly robust heuristic I walk around with in my head is "the more targeted the strategy, the more likely it will miss the target". 

Its origin is from when I worked in advertising agencies, where TV ads for car brands all looked the same because they needed to reach millions of people, while email campaigns were highly personalised.

The thing is, if you get hit with a tv ad for a car, worst case scenario it can't have a strongly negative effect because of its generic content (dude looks cool while driving his 4WD through rocky terrain). But when an email that attempts to be personalised misses the mark, you feel it (Hi {First Name : Last Name}!).

Anyway, effective altruism loves targeting. It is virtually built from the ground up on it (RCTs and all that, aversion to PR etc).

Anyway, I am thinking about this in relation to the recent "80,000 hours should remove OpenAI from the Job Board" post.

80k is applying an extremely targeted strategy by recommending people work in some jobs at the workplaces creating the possible death machines (caveat 1, caveat 2, caveat 3, caveatn).

There are so many failure modes involved with those caveats that makes it virtually impossible to not go catastrophically poorly in at least a few instances and take the mental health of a bunch of young and well-meaning EAs with it.

A judgement I'm attached to is that a person is either extremely confused or callous if they work in capabilities at a big lab. Is there some nuance I'm missing here?

[PHOTO] I sent 19 emails to politicians, had 4 meetings, and now I get emails like this. There is SO MUCH low hanging fruit in just doing this for 30 minutes a day (I would do it but my LTFF funding does not cover this). Someone should do this!

I expect (~ 75%) that the decision to "funnel" EAs into jobs at AI labs will become a contentious community issue in the next year. I think that over time more people will think it is a bad idea. This may have PR and funding consequences too.

Three million people are employed by the travel (agent) industry worldwide. I am struggling to see how we don't lose 80%+ of those jobs to AI Agents in 3 years (this is ofc just one example). This is going to be an extremely painful process for a lot of people.

↑ comment by faul_sname · 2024-08-30T18:02:02.089Z · LW(p) · GW(p)

I am struggling to see how we do lose 80%+ of these jobs within the next 3 years.

Operationalizing this, I would give you 4:1 that the fraction (or raw number, if you'd prefer) of employees occupied as travel agents is over 20% of today's value, according to the Labor Force Statistics from the US Bureau of Labor Statistics Current Population Survey (BLS CPS) Characteristics of the Employed dataset.

For reference, here are the historical values for the BLS CPS series cpsaat11b ("Employed persons by detailed occupation and age") since 2011 (which is the earliest year they have it available as a spreadsheet). If you want to play with the data yourself, I put it all in one place in google sheets here.

As of the 2023 survey, about 0.048% of surveyed employees, and 0.029% of surveyed people, were travel agents. As such, I would be willing to bet at 4:1 that when the 2027 data becomes available, at least 0.0096% of surveyed employees and at least 0.0058% of surveyed Americans report their occupation as "Travel Agent".

Are you interested in taking the opposite side of this bet?

Edit: Fixed aritmetic error in the percentages in the offered bet

Please help me find research on aspiring AI Safety folk!

I am two weeks into the strategy development phase of my movement building and almost ready to start ideating some programs for the year.

But I want these programs to be solving the biggest pain points people experience when trying to have a positive impact in AI Safety .

Has anyone seen any research that looks at this in depth? For example, through an interview process and then survey to quantify how painful the pain points are?

Some examples of pain points I've observed so far through my interviews with Technical folk:

• I often felt overwhelmed by the vast amount of material to learn.
• I felt there wasn’t a clear way to navigate learning the required information
• I lacked an understanding of my strengths and weaknesses in relation to different AI Safety areas  (i.e. personal fit / comparative advantage) .
• I lacked an understanding of my progress after I get started (e.g. am I doing well? Poorly? Fast enough?)
• I regularly experienced fear of failure
• I regularly experienced fear of wasted efforts / sunk cost
• Fear of admitting mistakes or starting over might prevent people from making necessary adjustments.
• I found it difficult to identify my desired role / job (i.e. the end goal)
• When I did think I knew my desired role, identifying the specific skills and knowledge required for a desired role was difficult
• There is no clear career pipeline: Do X and then Y and then Z and then you have an A% chance of getting B% role
• Finding time to get upskilled while working is difficult
• I found the funding ecosystem opaque
• A lot of discipline and motivation over potentially long periods was required to upskill
• I felt like nobody gave me realistic expectations as to what the journey would be like 

Big AIS news imo: “The initial members of the International Network of AI Safety Institutes are Australia, Canada, the European Union, France, Japan, Kenya, the Republic of Korea, Singapore, the United Kingdom, and the United States.”

https://www.commerce.gov/news/press-releases/2024/09/us-secretary-commerce-raimondo-and-us-secretary-state-blinken-announce

H/T @shakeel

The Australian Federal Government is setting up an "AI Advisory Body" inside the Department of Industry, Science and Resources.

IMO that means Australia has an AISI in:

9 months (~ 30% confidence)
12 months (~ 50%)
18 months (~ 80%)

 Attention: AI Safety Enthusiasts in Wellington (and New Zealand)  

I'm pleased to announce the launch of a brand new Facebook group dedicated to AI Safety in Wellington: AI Safety Wellington (AISW). This is your local hub for connecting with others passionate about ensuring a safe and beneficial future with artificial intelligence / reducing x-risk.To kick things off, we're hosting a super casual meetup where you can:

• Meet & Learn: Connect with Wellington's AI Safety community.
• Chat & Collaborate: Discuss career paths, upcoming events, and training opportunities.
• Share & Explore: Whether you're new to AI Safety or a seasoned expert, come learn from each other's perspectives.
• Expand the Network: Feel free to bring a friend who's curious about AI Safety!

Join the group and RSVP for the meetup here
https://www.facebook.com/groups/500872105703980

I'm not sure of an org that deals with ultra-high net worth individuals (longview?), but someone should reach out to Bryan Johnson. I think he could be persuaded to invest in AI Safety (skip to 1:07:15) 

AI Safety (in the broadest possible sense, i.e. including ethics & bias) is going be taken very seriously soon by Government decision makers in many countries. But without high quality talent staying in their home countries (i.e. not moving to UK or US), there is a reasonable chance that x/c-risk won’t be considered problems worth trying to solve. X/c-risk sympathisers need seats at the table. IMO local AIS movement builders should be thinking hard about how to keep talent local (this is an extremely hard problem to solve).

TIL that the words "fact" and "fiction" come from the same word: "Artifice" - which is ~ "something that has been created".

If transformative AI is defined by its societal impact rather than its technical capabilities (i.e. TAI as process not a technology), we already have what is needed. The real question isn't about waiting for GPT-X or capability Y - it's about imagining what happens when current AI is deployed 1000x more widely in just a few years. This presents EXTREMELY different problems to solve from a governance and advocacy perspective.

E.g. 1: compute governance might no longer be a good intervention
E.g. 2: "Pause" can't just be about pausing model development. It should also be about pausing implementation across use cases

I am 90% sure that most AI Safety talent aren't thinking hard enough about what Neglectedness. The industry is so nascent that you could look at 10 analogous industries, see what processes or institutions are valuable and missing and build an organisation around the highest impact one. 

The highest impact job ≠ the highest impact opportunity for you!

 

I really like this ad strategy from BlueDot. 5 stars.

90% of the message is still x / c-risk focussed, but by including "discrimination" and "loss of social connection" they're clearly trying to either (or both);

1. create a big tent
2. nudge people that are in "ethics" but sympathetic to x / c-risk into x / c-risk

(prediction: 4000 disagreement Karma)

I always get downvoted when I suggest that (1) if you have short timelines and (2) you decide to work at a Lab then (3) people might hate you soon and your employment prospects could be damaged.

What is something obvious I'm missing here? 

One thing I won't find convincing is someone pointing at the Finance industry post GFC as a comparison. 

I believe the scale of unemployment could be much higher. E.g. 5% ->15% unemployment in 3 years.

I think it is good to have some ratio of upvoted/agreed : downvotes/disagreed posts in your portfolio. I think if all of your posts are upvoted/high agreeance then you're either playing it too safe or you've eaten the culture without chewing first.

I'm pretty confident that a majority of the population will soon have very negative attitudes towards big AI labs. I'm extremely unsure about what impact this will have on the AI Safety and EA communities (because we work with those labs in all sorts of ways). I think this could increase the likelihood of "Ethics" advocates becoming much more popular, but I don't know if this necessarily increases catastrophic or existential risks.

Not sure if this type of concern has reached the meta yet, but if someone approached me asking for career advice, tossing up whether to apply for a job at a big AI lab, I would let them know that it could negatively affect their career prospects down the track because so many people now perceive such as a move as either morally wrong or just plain wrong-headed. And those perceptions might only increase over time. I am not making a claim here beyond this should be a career advice consideration.

When AI Safety people are also vegetarians, vegans or reducetarian, I am pleasantly surprised, as this is one (of many possible) signals to me they're "in it" to prevent harm, rather than because it is interesting.

Yesterday Greg Sadler and I met with the President of the Australian Association of Voice Actors. Like us, they've been lobbying for more and better AI regulation from government. I was surprised how much overlap we had in concerns and potential solutions:
1. Transparency and explainability of AI model data use (concern)

2. Importance of interpretability (solution)

3. Mis/dis information from deepfakes (concern)

4. Lack of liability for the creators of AI if any harms eventuate (concern + solution)

5. Unemployment without safety nets for Australians (concern)

6. Rate of capabilities development (concern)

They may even support the creation of an AI Safety Institute in Australia. Don't underestimate who could be allies moving forward!

Ilya Sutskever has left OpenAI https://twitter.com/ilyasut/status/1790517455628198322

If GPT5 actually comes with competent agents then I expect this to be a "Holy Shit" moment at least as big as ChatGPT's release. So if ChatGPT has been used by 200 million people, then I'd expect that to at least double within 6 months of GPT5 (agent's) release. Maybe triple. So that "Holy Shit" moment means a greater share of the general public learning about the power of frontier models. With that will come another shift in the Overton Window. Good luck to us all.

The catchphrase I walk around with in my head regarding the optimal strategy for AI Safety is something like: Creating Superintelligent Artificial Agents* (SAA) without a worldwide referendum is ethically unjustifiable. Until a consensus is reached on whether to bring into existence such technology, a global moratorium is required (*we already have AGI).

I thought it might be useful to spell that out.

What is your AI Capabilities Red Line Personal Statement? It should read something like "when AI can do X in Y way, then I think we should be extremely worried / advocate for a Pause*". 

I think it would be valuable if people started doing this; we can't feel when they're on an exponential, so its likely we will have powerful AI creep up on us.

@Greg_Colbourn [EA · GW] just posted this [EA · GW] and I have an intuition that people are going to read it and say "while it can do Y it still can't do X"

*in the case you think a Pause is ever optimal.

I'd like to see research that uses Jonathan Haidt's Moral Foundations research and the AI risk repository to forecast whether there will soon be a moral backlash / panic against frontier AI models.

Ideas below from Claude:

# Conservative Moral Concerns About Frontier AI Through Haidt's Moral Foundations

## Authority/Respect Foundation
### Immediate Concerns
- AI systems challenging traditional hierarchies of expertise and authority
- Undermining of traditional gatekeepers in media, education, and professional fields
- Potential for AI to make decisions traditionally reserved for human authority figures

### Examples
- AI writing systems replacing human editors and teachers
- AI medical diagnosis systems challenging doctor authority
- Language models providing alternative interpretations of religious texts

## Sanctity/Purity Foundation
### Immediate Concerns
- AI "thinking" about sacred topics or generating religious content
- Artificial beings engaging with spirituality and consciousness
- Degradation of "natural" human processes and relationships

### Examples
- AI spiritual advisors or prayer companions
- Synthetic media creating "fake" human experiences
- AI-generated art mixing sacred and profane elements

## Loyalty/Ingroup Foundation
### Immediate Concerns
- AI systems potentially eroding national sovereignty
- Weakening of traditional community bonds
- Displacement of local customs and practices

### Examples
- Global AI systems superseding national control
- AI replacing local business relationships
- Automated systems reducing human-to-human community interactions

## Fairness/Reciprocity Foundation
### Immediate Concerns
- Unequal access to AI capabilities creating new social divides
- AI systems making decisions without clear accountability
- Displacement of workers without reciprocal benefits

### Examples
- Elite access to powerful AI tools
- Automated systems making hiring/firing decisions
- AI wealth concentration without clear social benefit

## Harm/Care Foundation
### Immediate Concerns
- Potential for AI systems to cause unintended societal damage
- Psychological impact on children and vulnerable populations
- Loss of human agency and autonomy

### Examples
- AI manipulation of emotions and behavior
- Impact on childhood development
- Dependency on AI systems for critical decisions

## Key Trigger Points for Conservative Moral Panic
1. Religious Content Generation
  - AI systems creating or interpreting religious texts
  - Automated spiritual guidance
  - Virtual religious experiences

2. Traditional Value Systems
  - AI challenging traditional moral authorities
  - Automated ethical decision-making
  - Replacement of human judgment in moral domains

3. Community and Family
  - AI impact on child-rearing and education
  - Disruption of traditional social structures
  - Replacement of human relationships

4. National Identity
  - Foreign AI influence on domestic affairs
  - Cultural homogenization through AI
  - Loss of local control over technology

## Potential Flashpoints for Immediate Backlash
1. Education System Integration
  - AI teachers and tutors
  - Automated grading and assessment
  - Curriculum generation

2. Religious Institution Interaction
  - AI pastoral care
  - Religious text interpretation
  - Spiritual counseling

3. Media and Information Control
  - AI content moderation
  - Synthetic media generation
  - News creation and curation

4. Family and Child Protection
  - AI childcare applications
  - Educational AI exposure
  - Family privacy concerns

I beta tested a new movement building format last night: online networking. It seems to have legs.

V quick theory of change: 
> problem it solves: not enough people in AIS across Australia (especially) and New Zealand are meeting each other (this is bad for the movement and people's impact).
> we need to brute force serendipity to create collabs.
> this initiative has v low cost

quantitative results:
> I purposefully didn't market it hard because it was a beta. I literally got more people that I hoped for
> 22 RSVPs and 18 attendees
> this says to me I could easily get 40+
> average score for below question was 7.27, which is very good for a beta test

I used Zoom, which was extremely clunky. These results suggest to me I should;
> invest in software designed for this use case, not zoom 

> segment by career stream (governance vs technical) and/or experience (beginner vs advanced)
> run it every second month

I have heaps of qualitative feedback from participants but don't have time to share it here.

Email me if interested: yanni@aisafetyanz.com.au

Is anyone in the AI Governance-Comms space working on what public outreach should look like if lots of jobs start getting automated in < 3 years? 

I point to Travel Agents a lot not to pick on them, but because they're salient and there are lots of them. I think there is a reasonable chance in 3 years that industry loses 50% of its workers (3 million globally).

People are going to start freaking out about this. Which means we're in "December 2019" all over again, and we all remember how bad Government Comms were during COVID.

Now is the time to start working on the messaging!

I’d like to quickly skill up on ‘working with people that have a kind of neurodivergence’.

This means;

• understanding their unique challenges
• how I can help them get the best from/for themselves
• but I don’t want to sink more than two hours into this

Can anyone recommend some online content for me please?

Something bouncing around my head recently ... I think I agree with the notion that "you can't solve a problem at the level it was created".

A key point here is the difference between "solving" a problem and "minimising its harm".

• Solving a problem = engaging with a problem by going up a level from which is was createwd
• Minimising its harm = trying to solve it at the level it was created

Why is this important? Because I think EA and AI Safety have historically focussed (and has their respective strengths in) harm-minimisation.

This applies obviously the micro. Here are some bad examples:

• Problem: I'm experiencing intrusive + negative thoughts
  • Minimising its harm: engage with the thought using CBT
  • Attempting to solve it by going meta: apply meta cognitive therapy, see thoughts as empty of intrinsic value, as farts in the wind
• Problem: I'm having fights with my partner about doing the dishes
  • Minimising its harm: create a spreadsheet and write down every thing each of us does around the house and calculate time spent
  • Attempting to solve it by going meta: discuss our communication styles and emotional states when frustration arises

But I also think this applies at the macro:

• Problem: People love eating meat
  • Minimising harm by acting at the level the problem was created: asking them not to eat meat
  • Attempting to solve by going meta: replacing the meat with lab grown meat
• Problem: Unaligned AI might kill us
  • Minimising harm by acting at the level the problem was created: understand the AI through mechanistic interpretability
  • Attempting to solve by going meta: probably just Governance

[IMAGE] there is something about the lack overlap between these two audiences that makes me uneasy. WYD?

A piece of career advice I've given a few times recently to people in AI Safety, which I thought worth repeating here, is that AI Safety is so nascent a field that the following strategy could be worth pursuing:

1. Write your own job description (whatever it is that you're good at / brings joy into your life).

2. Find organisations that you think need thing that job but don't yet have it. This role should solve a problem they either don't know they have or haven't figured out how to solve.

3. Find the key decision maker and email them. Explain the (their) problem as you see it and how having this role could fix their problem. Explain why you're the person to do it.

I think this might work better for mid-career people, but, if you're just looking to skill up and don't mind volunteering, you could adapt this approach no matter what stage you're at in your career.

I've decided to post something very weird because it might (in some small way) help shift the Overton Window on a topic: as long as the world doesn't go completely nuts due to AI, I think there is a 5%-20% chance I will reach something close to full awakening / enlightenment in about 10 years. Something close to this: 

Very quick thoughts on setting time aside for strategy, planning and implementation, since I'm into my 4th week of strategy development and experiencing intrusive thoughts about needing to hurry up on implementation;

• I have a 52 week LTFF grant to do movement building in Australia (AI Safety)
• I have set aside 4.5 weeks for research (interviews + landscape review + maybe survey) and strategy development (segmentation, targeting, positioning),
• Then 1.5 weeks for planning (content, events, educational programs), during which I will get feedback from others on the plan and then iterate it. 
• This leaves me with 46/52 weeks to implement ruthlessly.

In conclusion, 6 weeks on strategy and planning seems about right. 2 weeks would have been too short, 10 weeks would have been too long, this porridge is juuuussttt rightttt.

keen for feedback from people in similar positions.

I have an intuition that if you tell a bunch of people you're extremely happy almost all the time (e.g. walking around at 10/10) then many won't believe you, but if you tell them that you're extremely depressed almost all the time (e.g. walking around at 1/10) then many more would believe you. Do others have this intuition? Keen on feedback.

Two jobs in AI Safety Advocacy that AFAICT don't exist, but should and probably will very soon. Will EAs be the first to create them though? There is a strong first mover advantage waiting for someone -

1. Volunteer Coordinator - there will soon be a groundswell from the general population wanting to have a positive impact in AI. Most won't know how to. A volunteer manager will help capture and direct their efforts positively, for example, by having them write emails to politicians [EA(p) · GW(p)]

2. Partnerships Manager - the President of the Voice Actors guild reached out to me recently. We had a very surprising number of cross over in concerns and potential solutions. Voice Actors are the canary in the coal mine. More unions (etc) will follow very shortly. I imagine within 1 year there will be a formalised group of these different orgs advocating together.

Help clear something up for me: I am extremely confused (theoretically) how we can simultaneously have:

1. An Artificial Superintelligence

2. It be controlled by humans (therefore creating misuse of concentration of power issues)

My intuition is that once it reaches a particular level of power it will be uncontrollable. Unless people are saying that we can have models 100x more powerful than GPT4 without it having any agency??

Something someone technical and interested in forecasting should look into:  can LLMs reliably convert peoples claims into a % of confidence through sentiment analysis? This would be useful for Forecasters I believe (and rationality in general)

Be the meme you want to see in the world (screenshot).

[GIF] A feature I'd love on the forum: while posts are read back to you, the part of the text that is being read is highlighted. This exists on Naturalreaders.com and would love to see it here (great for people who have wandering minds like me).

I think acting on the margins is still very underrated. For e.g. I think 5x the amount of advocacy for a Pause on capabilities development of frontier AI models would be great. I also think in 12 months time it would be fine for me to reevaluate this take and say something like 'ok that's enough Pause advocacy'.

Basically, you shouldn't feel 'locked in' to any view. And if you're starting to feel like you're part of a tribe, then that could be a bad sign you've been psychographically locked in.

I went to buy a ceiling fan with a light in it recently. There was one on sale that happened to also tick all my boxes, joy! But the salesperson warned me "the light in this fan can't be replaced and only has 10,000 hours in it.  After that you'll need a new fan. So you might not want to buy this one." I chuckled internally and bought two of them, one for each room.

"alignment researchers are found to score significantly higher in liberty (U=16035, p≈0)" This partly explains why so much of the alignment community doesn't support PauseAI!

"Liberty: Prioritizes individual freedom and autonomy, resisting excessive governmental control and supporting the right to personal wealth. Lower scores may be more accepting of government intervention, while higher scores champion personal freedom and autonomy..." 
https://forum.effectivealtruism.org/posts/eToqPAyB4GxDBrrrf/key-takeaways-from-our-ea-and-alignment-research-surveys#comments

one of my more esoteric buddhist practices is to always spell my name in lower case; it means I am a regularly reminded of the illusory nature of Self, while still engaging in imagined reality (Parikalpitā-svabhāva) in a practical way.