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International AI Ethics Framework Assessment

Ten cross-cutting principles covering rights, oversight, fairness, privacy, transparency, safety, accountability, societal benefit, sustainability and AI literacy.

AI Ethics by AIEI 30 questions About 15 minutes Free, no account
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Self-assessment only. Not legal advice, not an audit opinion, and not certification.

Readiness questions

Answer all 30 questions as honestly as you can. There are no right or wrong answers; an honest picture produces a useful action plan.

01

Human Rights and Ethics

01 Has your organisation adopted a written AI ethics policy or code of conduct that commits it to respecting fundamental rights, freedoms and dignity?

Critical requirement, weight 3

02 Are AI use cases screened against those ethical commitments before development or procurement begins?

Critical requirement, weight 3

03 Is there a defined route for employees or affected people to raise an ethical concern about an AI system?

Important requirement, weight 2

02

Human Oversight

04 Have you identified which AI-supported decisions are consequential enough to require human review, for example in health, finance, employment or justice?

Critical requirement, weight 3

05 Can a designated person override, pause or reverse an AI-supported decision, with that action recorded?

Critical requirement, weight 3

06 Are the people exercising oversight given the training, time and information needed to challenge an AI output rather than approve it by default?

Critical requirement, weight 3

03

Fairness and Non-Discrimination

07 Are AI systems tested for discriminatory outcomes across the groups they affect, both before deployment and periodically afterwards?

Critical requirement, weight 3

08 Are the protected characteristics and the proxy variables relevant to each AI system identified and documented?

Important requirement, weight 2

09 Is there a defined threshold at which a fairness test result blocks or halts deployment?

Important requirement, weight 2

04

Privacy and Data Protection

10 Is a valid legal basis and a specified purpose recorded for every set of personal data used to train or operate an AI system?

Critical requirement, weight 3

11 Are data minimisation, retention limits and deletion applied to AI training and inference data?

Critical requirement, weight 3

12 Can you satisfy data subject rights, including access, correction, erasure and objection, for data held in or derived from AI systems?

Important requirement, weight 2

05

Transparency and Explainability

13 Are people told, in plain language, when they are interacting with an AI system or when AI materially informs a decision about them?

Critical requirement, weight 3

14 Is the logic behind significant AI decisions documented so that it can be explained to a non-technical audience?

Critical requirement, weight 3

15 Are the intended uses, out-of-scope uses and known limitations of each AI system communicated to the people who rely on it?

Important requirement, weight 2

06

Safety, Security and Robustness

16 Are AI systems tested and validated against defined acceptance criteria before deployment?

Critical requirement, weight 3

17 Are AI systems assessed for security threats including adversarial manipulation, prompt injection and model or data poisoning?

Critical requirement, weight 3

18 Are fallback procedures defined for when an AI system degrades, fails or has to be taken offline?

Important requirement, weight 2

07

Accountability and Governance

19 Is a named person or body accountable for each AI system, with that accountability written down rather than assumed?

Critical requirement, weight 3

20 Do you maintain an inventory of the AI systems in use, including those embedded inside third-party products?

Critical requirement, weight 3

21 Are AI incidents and near-misses recorded, investigated and used to change practice?

Important requirement, weight 2

08

Societal Benefit and Responsibility

22 Is the intended societal benefit of each AI system stated and weighed against its foreseeable harms before approval?

Important requirement, weight 2

23 Are groups who may be affected by an AI system, but who are not its users, identified and consulted where the impact is significant?

Important requirement, weight 2

24 Do you decline or discontinue AI uses where the harm to people or society outweighs the benefit?

Critical requirement, weight 3

09

Environmental Sustainability

25 Do you consider the energy and compute footprint of an AI system when choosing models, providers or infrastructure?

Important requirement, weight 2

26 Is the environmental cost of training and running your AI systems measured or estimated?

Important requirement, weight 2

27 Are efficiency measures applied, such as right-sizing models, caching results, or reusing an existing model instead of training a new one?

Important requirement, weight 2

10

Awareness and AI Literacy

28 Is AI literacy training provided to staff whose work is affected by AI, at a level appropriate to their role?

Critical requirement, weight 3

29 Are the people who build or procure AI trained on your ethics principles and on the obligations that apply to them?

Important requirement, weight 2

30 Do you support workforce adaptation where AI changes roles, including reskilling or redeployment?

Important requirement, weight 2

Results are generated instantly. Self-assessment only, not an audit.