Glossary

AI Ethics

What is AI Ethics?

AI ethics deals with the moral questions surrounding the development and use of AI: fairness and discrimination, transparency and explainability, data protection, responsibility for errors, safety and the effects on work and society. For organisations it becomes concrete in guidelines, risk assessments, human oversight and honest communication about AI's limitations. Example: before a CV screening tool is introduced, it is checked for whether it disadvantages particular groups.

Topics

Ethics
Responsibility
Fairness

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Related terms

Bias

In AI, bias refers to a systematic distortion of results. It often stems from unbalanced or historically skewed training data, but also from model design or how a question is framed. A well-known example: an applicant screening tool that learns from past hiring decisions can perpetuate existing disadvantages. In statistics, bias also means the deviation of an estimate from the true value. Countermeasures include diverse data, regular audits and human decisions on personnel matters.

AI ethics
Fairness
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AI Transparency

AI transparency means disclosing when AI is involved, which data and sources its results are based on, and how decisions are reached. This includes labelling AI content, traceable source references, logs and documented changes. Transparency builds trust, makes troubleshooting easier and is partly required by law, for example by the EU AI Act's transparency obligations, under which people should be able to tell that they are interacting with an AI.

Transparency
Trust
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Explainability

Explainability (explainable AI, XAI) describes how well one can understand why an AI system reached a particular result. It covers methods that show which inputs influenced a decision most, as well as practical aids such as source references and logs. Explainability matters for trust, troubleshooting and regulation – for example when a bank has to justify why an application was declined.

XAI
Transparency
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AI and Human Rights

The term describes how AI systems can affect human rights such as privacy, equal treatment, freedom of expression or fair proceedings, both positively and negatively. Risks arise, for instance, from discriminatory decisions, mass surveillance, biometric identification or a lack of means to challenge decisions. International frameworks such as the Council of Europe's Framework Convention on AI and the EU AI Act address these issues. Organisations respond with impact assessments, transparency and human oversight.

Ethics
Fundamental rights
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