Trade offs
in
Responsible Business Processes

Abstract

The need for responsible processing of data is of growing interest in various data communities, including the business process management community. Processing data in a responsible manner requires understanding the various trade-offs that need to be made to achieve optimal solution. Especially in the BPM community, it is critical to understand the role of stakeholders in having built-in trade-offs when designing a process that is both effective in achieving its goals, while processing data responsibly. In this talk, we shall have a closer look at the current state-of-the-art in responsible AI and its interpretation for the BPM community. Through an interactive activity, we shall develop an understanding of how to create trade-offs when designing a process with the collaboration of multiple stakeholders.

Bio

Avigdor Gal is the Benjamin and Florence Free Chaired Professor of Data Science and the Co-chair of the Center for Humanities & AI at the Technion - Israel Institute of Technology. He is with the Faculty of Data & Decision Sciences, where he led the design of the first engineering program in data science in Israel (and possibly the world). Gal’s research focuses on elements of data integration and process management and mining under uncertainty, making use of state-of-the-art machine learning and deep learning techniques to offer an improved data quality with about 150 publications in leading journals, books, and conference proceedings (including multiple best paper and test-of-time awards). His research is implemented, through his ties as a consultant, in multiple industries including FinTech (e.g., Pagaya). Gal actively pursues projects that involve real-world applications. He was recently a member of a MAGNET project (Israeli Innovation Authority) FoodIoT, where transfer of knowledge from academia to the food industry (including the biggest food companies in Israel) assists adopting modern data science techniques to improve their performance. Before that, Gal was involved in multiple European projects in diverse application areas such as smart cities and medicine. In recent years, with the increasing penetration of AI to all aspects of life, Gal has been involved in developing methods for embedding responsible AI in companies and government authorities through an education process that increases dialogue abilities between data scientists and other stake-holders (e.g., lawyers and regulators).