Responsible Data Science - technical & societal issues

Data science is an emerging discipline that offers both promise and peril. Responsible data science refers to efforts that address both the technical and societal issues in emerging data-driven technologies. Dr. Lise Getoor is a computer scientist, professor and research director of the UC Santa Cruz D3 Data Science Research Center and strategic partner of Omny IQ. She is well known for her theoretical work that integrates logic and probability to reason collectively and holistically about context in structured domains. In this video presentation, 

she will describe some of the opportunities and challenges in developing the foundations for responsible data science. How can machine learning and AI systems reason effectively about complex dependencies and uncertainty? Furthermore, how do we understand the ethical and justice issues involved in data-driven decision-making? There is a pressing need to integrate algorithmic and statistical principles, social science theories, and basic humanist concepts so that we can think critically and constructively about the socio-technical systems we are building. 

Dr. Lise Getoor is a professor in the Computer Science Department at UC Santa Cruz and the director of the UC Santa Cruz D3 Data Science Center. Her research areas include machine learning and reasoning under uncertainty; in addition she works in data management, visual analytics and social network analysis. She has over 200 publications and extensive experience with machine learning and probabilistic 

modeling methods for graph and network data. She is a Fellow of the Association for Artificial Intelligence, an elected board member of the International Machine Learning Society, serves on the board of the Computing Research Association (CRA), among other titles.  She has received her PhD from Stanford University.

Categories

All
AI Machine Learning
Market Dynamics
Product
Wi-Fi Analytics

RSS Feed