Dates : 5 - 6 February 2024
The training is 2x1/2 day from 9:30 to 12:30
Deadline to register : 29 March 2024
Instructor: Dr. Dominik Foerschler, Managing Director | Senior Equity PartnerAudit Research Center | ARC-Institute
CPE Points : 7
Training description and goals
Generic AI is gaining momentum - proactively adapt your risk assessment and audit approaches!
The use of Generic AI and machine learning in general has increased dramatically over the past 12 months. The use of artificial intelligence (AI) raises many ethical questions and challenges. To address these, the European Commission, among others, has developed a comprehensive action plan to promote the responsible and ethical use of AI.
When it comes to transactions and active customer engagement, ethical requirements for AI include aspects such as transparency, fairness, privacy, accountability and human control. It is crucial for AI systems to disclose and explain how they work, in order to identify and minimise potential risks and biases. The fairness of AI systems means that they must not make discriminatory decisions, particularly with regard to gender, race or other protected characteristics. Data protection is of paramount importance, as AI processes and analyses large amounts of data. Responsibility for the use of AI lies with stakeholders, who must ensure that AI systems comply with ethical standards. Finally, it is essential that humans retain control over AI systems and use them as tools to support and enhance human decision-making.
• Definitions and insights into: Generic AI, Deep Learning, Machine Learning, RPA and more.
• The trajectory of Generic AI: Where is the field heading?
• Existing use cases: What practical customer interactions are emerging?
• Transparency requirements for artificial intelligence and its use.
• Risk assessment model approaches to fairness, privacy, ethical responsibility and potential discrimination.
• Human oversight: how customers review, adjust or reject AI decisions.
• Audit approaches to process security in the use of artificial intelligence.
• Risk assessment approaches to the use of artificial intelligence.
• Regulatory approaches: What needs to be considered in the future when using artificial intelligence?
• Summary and outlook
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