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AIGovSpec · the question card
Eleven questions for any AI decision
AI governance is the field of inquiry and practice concerned with how societies should shape the incentives, institutions, infrastructures and safeguards around AI to share its benefits broadly, prevent and address harm, and maintain the capacity to change course as today’s choices become tomorrow’s conditions.
- 1What outcome is being shaped?What would be different for people if this works, and what pattern is it meant to change?
- 2What incentives currently produce or reinforce that outcome?Who gains from doing things the current way, and what pushes people toward that?
- 3Which institution has the authority to act?Who here can actually say yes, no or stop, and who has to live with the result?
- 4Does that institution have the capacity, independence, expertise, legitimacy, and accountability to act?Could they really act: do they have the time, skills, independence and trust, and who holds them to account?
- 5What infrastructure does the mechanism depend on or reshape, and who controls it?What does this depend on, such as data, devices, internet access or a supplier, and who controls that?
- 6What safeguards translate the objective into practice?What would stop things going wrong, notice when they do, and limit the damage, and who would do that?
- 7Where in the AI lifecycle does the intervention operate?At what stage does this act: from research and data, through building, buying and use, to checking, fixing problems and switching off?
- 8Who decided, on what authority, and who was not represented?Who made this choice, who gave them the right to, and whose voice was missing?
- 9Who bears the costs and risks, and who captures the benefits?Who pays or carries the risk if it fails, and who benefits if it works?
- 10What happens when the mechanism or technology scales across organizations, sectors, or borders?What changes if many schools, clinics or organisations do the same thing, across sectors or across borders?
- 11What becomes difficult to reverse if governance arrives too late, and how will the governance mechanism itself be revised if it turns out to be wrong?What would be hard to undo later, and how would we notice and change course if we got this wrong?
Where governance acts
- Incentives: What behavior does the system reward?
- Institutions: Who has authority, capacity, and accountability?
- Infrastructures: What is AI built on, and who controls it?
- Safeguards: What actually prevents, detects, or limits failure?
Four tests for each
- Power: Who has the ability to shape the system, set terms, control infrastructure, or define the problem?
- Legitimacy: By what authority are decisions made, who is represented, and who can contest them?
- Distribution: Who captures the benefits, who bears the costs and risks, and who is excluded?
- Adaptability: Can the governance mechanism learn, revise itself, and recover when its assumptions prove wrong?
Answer with evidence, or write “unknown”: each unknown is a question to take to someone responsible. aigovspec.com/analyze · Dataset 0.7.0 · CC BY 4.0 · Research preview, independent review pending.