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What is AI ethics?
AI ethics is a values-based reflection on the development and use of AI systems. It addresses issues of responsibility, fairness, human dignity, and societal impacts.
Unlike AI compliance (what is required by law?), ethics asks: What is right? What is good? It goes beyond legal obligations and incorporates principles such as fairness, transparency, accountability, data protection, human autonomy, and well-being.
Key ethical frameworks include the EU High-Level Expert Group Ethics Guidelines, the OECD AI Principles, IEEE Ethically Aligned Design, and the UNESCO AI Ethics Recommendation. These frameworks provide principles that must be concretely implemented within companies.
For small and medium-sized businesses, AI ethics is not a philosophical debate, but rather concrete governance questions: How do we ensure that our AI applications operate fairly, transparently, and in the best interests of users?
Best Practices for AI Ethics
These six principles help with implementation:
- Support from the top: Ethics requires clear backing from senior management.
- Concrete, not abstract: Translate principles into measurable requirements.
- Establish a diverse committee: IT, Legal, business units, HR, the works council, and external experts.
- Integrate ethics and business: Position ethics not as an obstacle, but as a quality factor.
- Conductcontinuous reviews: Ethics assessments should not be a one-time event—they should be an ongoing process.
- Seek external advice: Fresh perspectives help prevent tunnel vision.
Common Mistakes in AI Ethics
We often see these pitfalls:
- Ethics-washing: Publishing a charter without applying its principles in everyday practice. Reputational risk.
- Too Abstract: Ethical principles remain general—no concrete requirements.
- One-time effort: The committee meetsonly once—follow-up and monitoring are lacking.
- Separation from Compliance: Ethics and compliance are not integrated—resulting in duplication of effort.
- No employee involvement: Ethics is discussed only within the committee, not carried out by the team.
Ethics vs. Compliance vs. Responsible AI
A comparison of three related concepts:
- Ethics: Value-based reflection—what is right?
- Compliance: Adherence to legal requirements — what is mandatory?
- Responsible AI: Responsible practice — a combination of ethics, compliance, and technology.
Putting AI Ethics into Practice at Your Company
In a free initial consultation, we’ll review your AI applications and identify areas for ethical action—including a concrete implementation plan.
As an AI partner for small and medium-sized businesses, we put ethical principles into practice—with a charter, a committee, assessments, and monitoring.
What We Offer
- AI Consulting — Ethics Program and Governance Framework.
- Bias in the Glossary —the central ethical issue.
- AI Compliance — the legal framework.
- AI Training — Raising ethical awareness for your team.
