People love to believe that AI ethics are this universal thing that they can just apply to their system and magically everything works. But when you start to realize that people - even within your company - have very different ideas about abstract concepts like "fairness", "diversity" or "transparency", AI ethics all of a sudden becomes very challenging for organizations.
Artificial intelligence decisions are becoming increasingly important in companies. However, an increased usage of AI also requires an engagement with ethical issues - the establishment of an ethics committee is obvious, but often leads in the wrong direction. The problem of many algorithms lies in their data sets, which due to their history do not take into account the current code of ethics and, moreover, do not correspond to the values of the corporate business model. The workshop (in English) with expert Daniel Jeffries raises awareness of value-based AI, identifies processes of data collection, and creates understanding of how algorithms use this data in decision making. The focus is on building a consistent AI ethics program for companies that can be effectively implemented and, due to its adaptability, executed sustainably.
Development of a Code of Ethics / AI Ethics Guidelines
Support in regulatory and ethical frameworks
Input about data and AI, in regard of values, transparency and fairness / „transparency by design“
Expertise in developments regarding explainable AI
Expert knowledge about risks, but mainly about chances
Technology Assessment in AI
Implementation of infrastructure and data science teams in collaboration with our partners