ScenarioAI moral status inquiry and conditional welfare governance

AI Moral Status Researcher

Also called Artificial Moral Status Researcher · Model Welfare Researcher

An AI Moral Status Researcher would investigate what evidence could bear on whether AI systems have experiences or interests. The role depends on how AI develops, and it would matter if a company faced credible questions it could not answer.

What they do

The researcher would turn a vague question into work that can be tested. They would set out criteria that different theories of mind propose, and say what each would predict about a given system. They would design experiments, read model internals research and behavioural studies, and separate what is shown from what is assumed. They would write competing hypotheses with clear falsifiers. They would also record where evidence runs out. They would brief engineers, policy staff and leadership in plain language, and talk with outside researchers and institutions about shared criteria. No validated measurement toolkit would be assumed, so much of the work is judgement under uncertainty.

What a strong hire delivers

In the first months, a strong hire would deliver a research framework that lists the live hypotheses about AI moral status, the evidence each would need, and the findings that would count against each. They would produce a clear statement of what current evidence cannot settle. They would also leave the team with shared vocabulary, a short reading map, and a sensible view of which studies are worth running.

How you can tell they are good

Ask them to take one claim, such as a system reporting an inner state, and show how they would test it and what would change their mind. Strong people state their uncertainty precisely, name falsifiers unprompted, and explain theories fairly, including ones they reject. Be wary of confident answers in either direction, or of fluent philosophy with no testable step.

Why it is hard to fill

If this role emerged, the people would be extremely scarce. The field is very small today, titles vary, and almost nobody has done it as a job. The skills sit across philosophy, cognitive science and machine learning, and few people hold all three. Candidates must also be careful in public and calm under disagreement, which narrows the pool further.

Where to find them

Today they would come from philosophy of mind and ethics, cognitive science, neuroscience of consciousness, and machine learning research with an interpretability bent. Some would sit in academic groups or small research institutes. Others would be in frontier labs, research governance or policy teams. Look for people who have published on moral uncertainty and also worked with technical staff.

Interview questions for an AI Moral Status Researcher

  1. Describe a time you worked on a question with no agreed method of measurement. How did you make progress?

    A strong answer shows how they framed the question, chose proxies, and stated limits. They should name what they did not claim. Worry if they describe false certainty or avoid saying where the work fell short.

  2. How would you separate a model's claim about its inner states from evidence that it has any?

    They should cover training effects, imitation of human text, behavioural tests, and internal evidence. Good answers distinguish what each source can show. Worry if they treat self-reports as either proof or worthless.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are looking for a researcher to examine what evidence could bear on whether AI systems might have experiences or interests. The work assumes no answer in advance. You would build clear frameworks, test them against evidence, and be exact about what we do not know.

What you will do

  • Develop a research framework with competing hypotheses and falsifiers
  • Translate theories of mind into testable criteria for AI systems
  • Design and review experiments relevant to these questions
  • Record the limits of current evidence clearly and openly
  • Brief technical and non-technical colleagues in plain language
  • Engage with outside researchers and institutions on shared criteria

What you will bring

  • Demonstrated work on philosophy of mind, consciousness science or moral uncertainty
  • Experience designing studies or arguments that could be shown wrong
  • Working understanding of how modern machine learning systems are built and studied
  • Clear writing that separates evidence from assumption
  • Ability to engage fairly with views you disagree with
  • Comfort working without established measurement tools

Nice to have

  • Experience with interpretability or model behaviour research
  • Background in research governance or policy
  • Experience coordinating across institutions

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Depends on a scenario

Institutional consideration of AI moral status

What AI would need to do
Credible evidence or sustained uncertainty prompts questions about possible AI experiences or interests.
What organisations would need to decide
Research bodies or legitimate institutions create formal assessment and governance processes.
What would rule it out
No credible evidence, consensus criteria or institutional mandate develops.

We give no date. The role becomes real if both conditions hold.

Skills that matter

  • Frontier scenario analysisAdvancedExplore conditional outcomes without claiming predictions
  • Experimental designAdvancedChoose comparisons that identify credible effects
  • Institutional and international coordinationWorkingAlign actors and processes across jurisdictions
  • Technical communicationWorkingExplain evidence and limitations to relevant readers

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert. Scenario roles describe responsibilities that depend on stated conditions; they are not forecasts.

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