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Sprint projectMar 10, 2025

U Reg AI: you regulate it, or you regenerate it!

Vinaya Sivakumar, Kayla Jew, Amy Wong · Team U Reg AI

Submitted to Women in AI Safety Hackathon. Sprint projects are early-stage work by participants, not Apart Research publications.

We have created a 'choose your path' role game to mitigate existential AI risk ... at this point they might be actual situations in the near-future. The options for mitigation are holistic and dynamic to the player's previous choices. The final result is an evaluation of the player's decision-making performance in wake of the existential risk situation, recommendations for how they can improve or aspects they should crucially consider for the future, and finally how they can take part in AI Safety through various careers or BlueDot Impact courses.

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  1. The project is a simple interactive choose-your-own adventure style story , with users invested in their outcomes to provide deeper engagement with the ideas. (though it is noted that the figma project linked in the appendix only includes one pathway, despite several starting points and choices.). It would be great to see the literature that discusses the potential scenarios shown (e.g. "prioritizing safety risk increases the risk of AI systems behaving unpredictably or autonomously. As a user, I would like to understand more about the current literature on this - references to support further reading, or elaboration on the concepts would be ideal to support deeper learning, and help the learner contextualize the content.). That being said, within the context of the hackathon, an engaging experience was created, and I look forward to seeing this project evolve and iterate further.

    Additional analysis of the games mentioned (Fermi's fake, Hitchhikers guide, and existing educational gamification methods), including their format, strengths and weaknesses, would be useful for the reader to understand the pre-existing literature and inspiration. Additionally, I am keen to read more about the method of breaking down current governance and policy discourse into the scenarios chosen for the different pathways.

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  2. This was a creative solution to articulating various risk scenarios in AI! The "Choose your own adventure" style play is an engaging way to capture audience attention. I enjoyed how you also captured some personalization, such as the "Your choices suggest a preference for..." call out in the final call to action screen. It was a creative way to pull together insights from the game and push users forward on their AI safety journey.

    For future iterations, I'd recommending incorporating more in-line learnings within the scenario itself. You mentioned that these scenarios may realistically be more "near-future". Is there a way to highlight the urgency of these scenarios in real-life for a learner? The "Guidance" page is helpful, but once the game begins, this will be difficult to navigate back to. How can we further encourage or emphasize educational call-outs without losing users to context switching? Finally, there is a lot of strength in communicating how things can go right *and* wrong in AI safety. You mentioned in the accompanying paper how strong a motivator gamificiation can be for learners. How could U Reg It further gamify itself, like introducing reward models? E.g, could users collect "badges" as they navigate different scenarios, whether they play for "good" or "evil"?

    This MVP is a strong start and I loved the creativity on display here. Would be excited to play out many of the gameplays you've suggested!

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Cite this project

@misc{sivakumar2025u,
  title = {{U Reg AI: you regulate it, or you regenerate it!}},
  author = {Vinaya Sivakumar and Kayla Jew and Amy Wong},
  year = {2025},
  month = mar,
  note = {Submitted to Women in AI Safety Hackathon, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/u-reg-ai-you-regulate-it-or-you-regenerate-it}},
  url = {https://apartresearch.com/sprints/projects/u-reg-ai-you-regulate-it-or-you-regenerate-it}
}

Build something like this at the next Sprint

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