Interview people working in AI safety and people in their lives who aren't immersed in the field to understand how AI safety work affects relationships, how career choices and beliefs are perceived, and what helps people communicate across differences in worldview.
About the project
Working on AI safety can involve decisions that are hard to explain to people who aren't immersed in the field. Someone might drop out of university, leave a stable career to take a less conventional job, move to the Bay Area leaving their home behind, or spend most of their time, including socially, around people who take catastrophic AI risk seriously.
This project will study how people working in AI safety talk about these choices with family, friends, partners, and former colleagues. Mentees will interview both people in the field and, where possible, people on the other side of those conversations to understand what creates confusion or tension and what helps people stay connected despite disagreement.
The main output will be a practical guide for people working in AI safety. The interviews should also provide useful data on how AI safety work looks to people who aren't immersed in the field: how much they understand or buy the case for it, what makes the field seem credible/strange, and where insiders may be miscalibrated about public attitudes.
Rather than teaching people how to convince their family and friends, the goal is more so to help people explain what they are doing and thinking, maintain relationships across differences in worldview, and learn from how their work and community look to people around them.
Theory of change
If working in AI safety regularly creates tension with family, friends, or previous professional communities, that can make entering and staying in the field harder. It may also push people toward relying almost entirely on the AI safety community for social support.
A practical guide grounded in real experiences could make those transitions easier. It could help people explain unusual decisions in school, career, and life, handle disagreements productively, and stay connected to people who don't share all of their assumptions. Those relationships may also help people stay grounded. Spending most of one's time around people with similar beliefs can make it harder to notice which ideas or behaviors seem unusual to people who know you well but are less immersed in the field.
This project would first test whether these problems are common enough; if they are, the final resource would focus on the situations that come up most often and the approaches people have found useful.
Your role
The project would have 3 stages (open to other approaches to scoping):
1/ Interview research
Mentees would conduct ~20 interviews:
- 12-15 people currently working or studying in AI safety
- 3-5 people who entered the field relatively recently
- 3-5 parents, partners, friends, or former colleagues of people working in AI safety, where participants are comfortable making introductions
Mentees would ask participants to reconstruct what happened in specific conversations, what they said, how the other person responded, and what they would do differently now.
2/ Synthesis
Mentees would code the interviews for recurring situations and failure modes (e.g. explaining catastrophic AI risk, explaining a university dropout / career switch decision, explaining why someone moved to an AI safety hub, talking with someone who thinks the field is alarmist or cultist, dealing with pressure to choose a more conventional career, avoiding AI safety conversations entirely, becoming socially disconnected from previous communities). The mentees would then identify which problems appear common and which responses seem to help.
3/ Public guide
The main output would be a short public guide for people entering or working in AI safety, organized around concrete situations (e.g. "My parents think I am throwing away my career", "I don't know how to explain what I do without giving a lecture", "I mostly know and spend the majority of my time with people in AI safety now"), including anonymized examples from interviews where participants give permission. A secondary output would be a short research memo summarizing the interview findings, including cases where the evidence does not support the initial hypothesis.
Prerequisites
- Strong interviewing and writing skills
- Good social judgment
- Comfort speaking with people who disagree with AI safety assumptions and ability to report those views fairly
- Familiarity with AI safety is useful, but deep technical knowledge is not required
Application question(s)
Question 1: You are interviewing the parent or close friend of someone who recently moved into AI safety. They tell you: "I support them, but I still don't really understand why they're doing this." What would you ask next? Give 5-7 questions, in the order you would ask them, and briefly explain what you are trying to learn. (300 words max)
Question 2: Suppose the first ten interviews mostly suggest that family and friends are supportive and that social friction is not much of a problem. How would you change the project? (200 words max)
About the mentor
Vy Tran
Generator Residency
Vy Tran is currently a Generator Resident, where she recently assisted the AI Futures Project (AIFP) on the launch of AI 2040: Plan A. Previously, she served as Chief of Staff of the Carnegie Mellon AI Safety Initiative (CASI).