In this workshop, employees learn how to use artificial intelligence (AI) responsibly and in line with legal and ethical standards. The focus is on identifying and minimizing risks that can arise when using AI in companies. Participants learn how to ensure data protection, transparency and fairness in AI projects and thus comply with compliance requirements. This helps the company build trust, avoid legal pitfalls, and at the same time securely integrate innovative technologies.

The ethical use of artificial intelligence and compliance guidelines are crucial to minimizing risks and strengthening trust in AI systems. Responsible use of AI protects the company from legal and reputational damage.

Benefits for you as a company:

• Minimizing legal and ethical risks through responsible use of AI
• Ensuring compliance with data protection and compliance requirements
• Fostering customer and partner confidence in using AI
• Avoiding bad investments through transparent and equitable AI development
• Strengthening brand reputation through responsible and fair AI applications

1. What does “ethical AI” mean? Principles and values for the responsible use of artificial intelligence

• Overview of the most important compliance requirements related to AI use, in particular the EU AI regulation
• Why is ethical AI important? Risks and opportunities for companies and society
• Difference between “technical” and “ethical” compliance in an AI context

2. Key ethical principles of AI use

• Fairness: Avoiding discrimination and prejudice in AI models
• Transparency: Disclosure of algorithms, decision-making processes, and data usage
• Responsibility: Clarifying responsibilities for AI deployments and decisions
• Data protection and privacy: ensuring the privacy-compliant use of AI, protection of personal data
• Security: Ensuring the robustness of AI systems against misuse and unforeseen scenarios

3. Regulation and Governance of AI in a Business Context

• Overview of the EU AI Regulation (EU AI Act): Requirements, Risk Categorizations, and Regulatory Authorities
• Compliance with regulatory requirements for risk reduction and liability when using AI
• How companies can integrate the requirements of the regulation into their existing governance structures
• Create and implement enterprise-wide AI governance policies

4. Risks and opportunities of using AI in a compliance context

• Potential risks of using AI: Incorrect decision-making, discrimination, and lack of transparency
• Opportunities through the use of AI in compliance management: increasing efficiency, detecting anomalies, preventive measures
• Case studies and examples of failed AI implementations in compliance processes
• Best practices for identifying and minimizing risks when using AI

5. Practical approaches to minimizing risks in using AI

• How to review and regularly review AI models for fairness and bias
• Implementation of testing and monitoring mechanisms to ensure transparency and accountability
• Using Explainable AI (XAI): Improving the traceability of decisions through AI systems
• Protection against manipulation: How to take security measures to avoid cyber attacks on AI systems

6. Data protection and ethical issues in AI

• Data protection-compliant use of AI: How companies can securely process personal data
• Compliance with data protection laws such as the GDPR for AI-driven applications
• The role of data ethics: How companies can handle large amounts of data responsibly
• Maintaining privacy: Ensuring that AI systems do not reveal confidential information without authorization

7. Compliance processes for AI systems

• How companies can introduce compliance checks for AI models
• Documentation and traceability of AI decision-making processes to avoid compliance violations
• How compliance with ethical and regulatory requirements can be integrated into AI project management
• Recommendations for audits and review processes for the regular review of AI systems and algorithms

8. AI strategy and training for ethical use

• Development of a company-wide AI strategy that includes ethical principles and compliance requirements
• Preparation of a Code of Conduct for dealing with AI and its ethical use
• Training measures for employees to promote ethical principles in their daily work with AI systems
• Raising awareness of ethical issues and the importance of responsible use of AI

9. The future of ethical AI use and compliance

• How the regulation of AI is evolving and what future ethical challenges can be expected
• Technology and Innovation in AI: How Companies Can Stay Flexible While Maintaining Ethical Standards
• The role of companies in formulating global standards for ethical AI and compliance

10. Best practices and tools to promote ethical use of AI

• Practical tools to promote ethical use of AI: bias detection tools, transparency software, and auditing tools
• Recommendations for companies to support ethical AI initiatives and ensure compliance
• Case studies from companies that have successfully implemented ethical AI practices

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