No Such Thing: Education in the Digital Age Greedy Algorithms, Public Goods: Rethinking AI Regulation and Education
Oct 31, 2025
Dr. Julia Stoyanovich, an expert in AI ethics and education at NYU, explores pressing topics around AI's impact on society. She highlights the need for public literacy in AI, arguing that informed citizens can better engage in technology decisions. Julia critiques the limitations of traditional engineering training and advocates for a blend of technical and social sciences in education. She introduces the 'greedy algorithm' concept to illustrate companies' conflicts of interest and shares her vision for responsible AI, emphasizing human oversight and collective action.
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AI As A Public Question
- Many decisions AI touches have no single correct answer and involve messy human trade-offs.
- Julia argues we must treat AI as a public question requiring civic argument, not just a product launch.
Limitations Of Narrow Engineering Training
- Engineering education often trains students to seek one correct, elegant solution.
- Julia says social problems require broader social science and humanities exposure to handle value trade-offs.
Teach Breadth Before Deep Specialization
- Expose technical students to social sciences and social students to analytic skills to build well-rounded citizens.
- Prioritize breadth early and allow depth later so young learners form wider perspectives.
