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  • BMCC/CUNY GenAI Education Paper Cited in MDPI Smart Cities Article

    Posted by Vasiliy Znamenskiy on July 7, 2026 at 11:05 am

    Dear colleagues,

    I wanted to share a small but meaningful update related to generative AI in education.

    Our paper, “Integrating Universal Generative AI Platforms in Educational Labs to Foster Critical Thinking and Digital Literacy,” has been cited in a new MDPI Smart Cities article on multimodal generative AI for construction-site management and monitoring.

    Our paper:
    https://academicworks.cuny.edu/bm_pubs/177/

    arXiv version:
    https://arxiv.org/abs/2507.00007

    Citing article:
    https://www.mdpi.com/2624-6511/9/7/114
    https://doi.org/10.3390/smartcities9070114

    I think this connection is important because it shows that GenAI education is not only about teaching students how to use AI tools. It is about teaching students how to critically evaluate, verify, and interpret AI-generated outputs.

    The new Smart Cities article applies multimodal GenAI to a real engineering context. This supports a broader educational point: AI literacy should include critical judgment, comparison of AI outputs, expert verification, and responsible interpretation.

    I would be interested to hear how other CUNY faculty are teaching students to evaluate GenAI outputs in STEM, engineering, data science, writing, or other disciplines.

2 replies
    • Keith A. Markus (he/him/his)
      Member
      July 9, 2026 at 1:47 pm

      Vasiliy,
      I did an informal poll of my students asking what they wanted their program of study to provide them regarding AI, and the ability to critically evaluate AI output was one of the top things that they reported wanting. This fining could probably be replicated more formally.

      My main focus in my courses is on the idea that if students want to be able to critically evaluate what AI produces, they need to learn to complete the task without AI first. This way, they know what is involved in correctly completing the task and what to look for in terms of possible problems with what AI produces.

      However, although I have since lost the link, my thinking was significantly impacted by a YouTuber who argued that we should not be using AI as an autonomous assistant who does things for us on its own. Instead, it is more effective to use AI as an automated interlocutor who can help us think things through in dialog with us. On this view, the main strength of AI is that, unlike a human interlocutor, it never gets tired, looses interest, or runs out of time to help. This shifts the object of assessment from an end product produced by AI to the quality of feedback and suggestions offered by AI.

      Keith

    • Vasiliy Znamenskiy
      Member
      July 9, 2026 at 2:13 pm

      Testing how a task was completed, judging whether it was completed correctly, and actually performing the task are not the same thing.

      Artificial intelligence will do some things on its own. Without that, it would not really be intelligence. How we should interact with it, what we can trust it with and what we cannot, will be shown by practice and by time.

      How much do you trust your calculator when you are trying to calculate something? You are unlikely to be able to perform the same calculations yourself that the calculator performs. At the same time, you still have a way to check whether it is calculating correctly by testing it on selected examples, or by comparing the results of two or more different calculators

      Work with artificial intelligence may develop similarly. But errors are inevitable in any case.

2 replies

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