• Arcadia Impact
  • Measuring Automation in AI Safety Research

    Arcadia Impact
  • Why We’re Doing This

    We at the Arcadia Impact Alignment Team want to understand the state of automated research in AI safety compared with capabilities research. Right now, there's no existing way to measure this.

    Frontier labs have started publishing how much of their AI R&D is now done by AI [1][2], but they do not separate safety from capabilities. We want to take the first step towards measuring this for AI safety, and learn which tasks AIs help speed up and what the bottlenecks are. We acknowledge that measuring this accurately seems hard, but we think a scrappy point estimate will be valuable. Part of this process is figuring out how to measure this better.

    We hope these results provide AI safety researchers, strategists, and policymakers with evidence to guide research, funding, and policy. Over time, we want this to become a public baseline that tracks the capabilities–safety gap and pushes labs to report the two separately.

    Dual Use & Privacy

    We acknowledge that insights gained from this survey have the potential to speed up capabilities work. We will not release scaffolds, advice, or artifacts that we think could speed up capabilities research. All individual responses will be anonymised and kept private, and we will only publish aggregated results. If you'd rather not answer a question, especially if you think answering could cause harm, just write ‘prefer not to say’.

  • Arcadia Impact
  • Questions

  • Job Title*
  • Role type*
  • Coding experience (total overall years with and without AI assistance)*
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  • Arcadia Impact
  • Automation barriers

  • Page 2 of 4

  • Arcadia Impact
  • Distribute 100 points

    Thinking about your role as a whole, how much does each type of task contribute to the work or results you’re responsible for? We’ll use these weights to compute your overall speedup.

    Count all work that goes into producing your results, including tasks handled by AI. Don’t base your answers on how much time you personally spend on each task.

    For example, if running experiments is a significant part of your job and AI handles most of them, experiments should still receive a high share.
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  • Arcadia Impact
  • Active human time on a recent project

  • Imagine redoing your most recently finished task, project, research paper, blog post, or report.

    For each category of work, how many hours of your own active time would it take to reach the same quality of result:

    • with no AI
    • with last year’s AI
    • with today’s AI (what actually happened)
    • with the AI you expect in 6 months?

    Active hours means your own hands-on time prompting, reviewing, and fixing. Don't count time spent waiting on AI while you did something else.

    Leave a row blank if this is not a task you do for your role.

    For this question, we’d appreciate a few more minutes of your time to be as accurate as you can.

  • Answer in active human hours
    Rows
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  • Should be Empty: