Creating Resilient Student Experiences with Heuristic Based Monitoring (hBM) Solutions While Balancing Concerns about Privacy, Ethics and Bias


Time: 1-1:45PM EST



Dr. Sherry Bennett, Board Member, The Data Coalition, Chief Data Scientist, DLT-TD Synnex, Adjunct Faculty, SNHU

Elham Tabassi, Chief Of Staff, NIST - Information Technology Laboratory, Member of The White House National Artificial Intelligence (AI) Research Resource Task Force

Michael Knight, Chief Digital Officer, Intellisite


The use of AI applications by higher education institutions, seeking to create superior student experiences and bolster student success, is widely debated.  On the one hand, students and privacy advocates highlight the intrusiveness associated with collecting personal data, not to mention issues of bias, required to build and run these applications; while innovators seeking to modernize academic operations and learning experiences are resolved to drive digital transformation.   As the pandemic exposes the need for agile operations to promote continuity and resilience in student support and learning, Heuristic Based Monitoring (hBM) systems arguably have a role to play. 

As many higher education institutions begin to use AI solutions, the issues of ethics, bias, privacy, etc. will continue to grow and be of great concern.  These concerns require mediation so that the benefits of AI can be realized. The National Institute of Standards and Technology (NIST) is leading an effort to create an “AI framework” which can play an integral role in this process. 

In this panel we will discuss what hBM systems are using a real use case example in higher education, and issues and considerations for leveraging these types of applications.  In addition, we will learn what the NIST AI framework is and where the initiative stands to date.  We will conclude with a discussion regarding the importance of the AI framework and how it has a role to play in accelerating the adoption of AI technologies in education and the United States more generally.


There is no need to register for this individual session, to register for Datapalooza go here.