Towards more Ethical and Human Centric Artificial Intelligence: Overview of New SFSU Graduate Certificate in Ethical Artificial Intelligence
Artificial Intelligence (AI) methods are rapidly gaining in importance in many critical applications in medicine, business, autonomous cars, banking, law, loan approvals, rental approvals etc. However, these AI methods are inherently complex and often difficult to understand and explain, often contain inappropriate biases, and hence result in challenges to their adoption and validation and may even cause discrimination. These concerns received increased attention among scientists, but also among the general public and politicians, as evidenced in increased press and public attention to these issues worldwide. These issues have led to the discussion of the need for more ethical considerations of AI and motivated us to launch SFSU multi-college Graduate certificate in Ethical AI involving Computer Science, Business and Philosophy. In this seminar we will first overview issues related to AI Ethics: what AI ethics is, why it might be important and the needs to enforce AI Ethics, detect and correct bias and make AI systems more explainable and transparent. We will then overview just launched SFSU Graduate Certificate in Ethical AI https://cs.sfsu.edu/graduate-certificates/graduate-certificate-ethical-a... which aligns well with SFSU mission of addressing social justice.
Dr. Kleinrichert obtained her Ph.D. from the University of South Florida, Tampa in Philosophy with a focus on Business Ethics. Her prior business career included risk management and human resources in the insurance, banking and tech recruiting sectors. She also has served as Chair of the College of Business' annual Business Ethics Week (2007-2017), is founder of the Ethics & Compliance Workshop series, co-developed the Business Certificate in Ethics & Compliance and the MBA Emphasis in Ethics & Compliance., and is the former Director, Center for Ethical & Sustainable Business at SF State University. She has focused her academic career in the areas of business ethics and compliance, corporate social responsibility (CSR), sustainability, and women social entrepreneurs. She is the current Interim Dean of the College of Business at SF State.
Dr. Montemayor obtained his PhD in Philosophy with a Certificate in Cognitive Science from Rutgers University, and a JD (Law degree) from the Autonomous National University of Mexico’s Law School. He joined the faculty at San Francisco State University in the summer of 2009, and is currently Professor of Philosophy and Associate Chair of the Philosophy Department at SF State University. His research focuses on the intersection between philosophy of mind, epistemology and cognitive science, particularly on issues related to consciousness, attention, and time perception. He remains interested in human rights, which was the topic of his Law thesis, and has recently published on legal epistemology. He serves on the Editorial Board of Problema, a legal philosophy journal.
Dr. Petkovic obtained his Ph.D. at UC Irvine, in the area of biomedical image processing. He spent over 15 years at IBM Almaden Research Center as a scientist and in various management roles. His contributions ranged from applications of computer vision, to multimedia and content management systems. Dr. Petkovic received numerous IBM awards for his work and became an IEEE Fellow in 1998 and IEEE LIFE Fellow in 2018 for leadership in content-based retrieval area. Dr. Petkovic also had various technical management roles in Silicon Valley startups. In 2003 Dr. Petkovic joined CS Department as a Chair and also founded SFSU Center for Computing for Life Sciences in 2005. Currently, Dr. Petkovic is the Associate Chair of the SFSU Department of Computer Science and Director of the COSE Computing for Life Sciences. With colleagues from SFSU College of Business and Department of Philosophy, Prof. Petkovic is leading new SFSU cross-college graduate certificate program in AI Ethics. Research interests of Prof. Petkovic include Machine Learning with emphasis on Explainability.