Eren Kurshan
Dr. Eren Kurshan is an AI researcher and technology executive focused on building AI systems for large-scale industrial use cases. Kurshan received her Ph.D. in Computer Science from the University of California, Los Angeles, as well as a Master's in Computer Science and a Bachelor of Science in Electrical Engineering. She has been leading AI, machine learning and innovation programs at Morgan Stanley, J.P. Morgan, Bank of America and IBM T.J. Watson Research Labs. She was a Visiting Fellow at Princeton's Center for Information Technology Policy (2015-2016) and served as an Adjunct Professor at Columbia University between 2014-2020. Dr. Kurshan published over 80 peer reviewed technical publications and holds ~265 patents, with approximately 125 granted. She has served as an associate editor of several IEEE and ACM journals and transactions including the Transactions on Emerging Technology, Transactions on Computers and the Journal of Emerging Technologies in Computing. She was the recipient of 2 Best Technical Paper Awards from IEEE and ACM conferences, as well as top inventor and licensing awards from Bank of America and IBM. She received 2 Outstanding Research and Corporate Accomplishment Awards from IBM for her work on system design and optimization and emerging technology development respectively. Dr. Kurshan received the "Inventor of the Year Award" from New York Intellectual Property and Law Association for her contributions in financial crime detection computer systems.
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Papers by Eren Kurshan
The leap from AI to AGI requires multiple functional subsystems operating in a balanced manner, which requires a system architec- ture. However, the current approach to artificial intelligence lacks system design; even though system characteristics play a key role in the human brain; from the way it processes information to how it makes decisions. System design is the key to alignment, one of the most challenging goals in AI. This difficulty stems from the fact that the complexity of human moral system requires a similarly so- phisticated system for alignment. Without accurately reflecting the complexity of these core moral subsystems and systems, aligning AI with human values becomes significantly more challenging.
In this paper, we posit that system design is the missing piece in overcoming the grand challenges. We present a Systematic Ap- proach to AGI that utilizes system design principles to AGI, while providing ways to overcome the energy wall and the alignment challenges. This paper asserts that artificial intelligence can be real- ized through a multiplicity of design-specific pathways, rather than a singular, overarching AGI architecture. AGI systems may exhibit diverse architectural configurations and capabilities, contingent upon their intended use cases. It advocates for a focus on employing system design principles as a guiding framework, rather than solely concentrating on a universal AGI architecture.