Explaining prediction models to adress data science ethics in business and society

Artificial Intelligence (AI) is having an increasingly large impact on society and is already used in several high stakes decision domains as finance, justice and healthcare. This also means that it is of high importance to ensure that the decisions of the AI system are aligned with ethical objectives. In my research, I will focus on the ethical areas of transparency, fairness and privacy. Transparency relates to how well the AI model and its predictions can be understood by individuals. Fairness of an AI model deals with not discriminating against any sensitive group (for example women or a particular ethnic group), while privacy requires respect for personal data. I will link these ethical ects with the field of Explainable AI, Counterfactual Explanations in particular, and several validation domains in business, such as tax fraud, HR analytics and credit scoring. The main contribution of my research will be to develop new methodologies to improve and validate these ethical issues when using Explainable AI.

Keywords:DATA SCIENCE

Disciplines:Operations research and mathematical programming, Data mining, Machine learning and decision making, Business economics