Stony Brook University recently hosted a webinar exploring the interplay of innovation, creativity, ethics, and artificial intelligence. Titled “AI Horizons – What Does Innovation, Creativity, and Ethics Mean in the Generative AI Era?”, the event was presented by the Center of Excellence in Wireless and Information Technology (CEWIT) at Stony Brook University and the Institute of Electrical and Electronics Engineers (IEEE-USA).
The panel featured Steven Skiena from the Department of Computer Science, Margaret Schedel from the Department of Music, and Vivian Zhang, CTO at SupStat. Laura Lindenfeld moderated the discussion.
Each panelist shared insights on how AI impacts their fields. Schedel noted her focus on enhancing human creativity through AI systems. Skiena emphasized that innovation now often involves utilizing existing models rather than building new ones from scratch. Zhang discussed using algorithms to optimize processes like dental insurance claims.
Skiena highlighted large language models' potential by describing a project where his class rewrote "The Great Gatsby" without using the letter “E.” He remarked on how these models enable creative projects that were previously impossible.
Schedel described three paradigms involving AI: working alone, humans working alone, and integration between humans and AI. She noted that while AI excels at pattern recognition, it lacks goal-oriented thinking—a skill humans bring to collaborations with AI.
Zhang expressed excitement about daily new applications of AI but stressed the importance of connecting solutions effectively. Schedel raised questions about AI's role in photography competitions and proposed separate categories for AI-generated images.
During a Q&A session, audience members asked how AI might change education. Skiena expressed hope that core skills like writing and reasoning remain important despite technological advancements. Zhang suggested rethinking homework and exams as students increasingly use AI tools for initial ideas.
Skiena concluded by emphasizing understanding outcomes over merely producing artifacts with AI assistance. Zhang agreed, warning against relying solely on machines for knowledge verification.
“From what I have seen,” said Zhang regarding educational practices impacted by AI use among students, “homework and exams need to be completely redone.”
The discussion underscored both opportunities offered by generative technologies alongside challenges requiring careful consideration moving forward into an era defined largely by machine learning innovations affecting diverse sectors globally today.
— Robert Emproto