This paper puts forward an argument that while exploring and pushing the boundaries of what generative artificial intelligence (GenAI) can achieve, we should not lose sight of its erosion on core human capacities. This paper provides explanations from a cognitive perspective, how human creativity is at risk of being compromised by GenAI, as we continue to outsource such cognitive tasks to GenAI. The use of GenAI is disruptive because it does not lend itself easily to scrutiny, and much of its decision-making is a black box and as such is in constant need for human oversight. The paper suggests that we can leverage on GenAI’s strengths to address its potential harm and illustrate this using creativity as the discussion point. The choice of creativity is rather straightforward: it was not long ago hailed as something that is uniquely human, but recent advances in GenAI technologies had threatened this claim. For example, artefacts produced by GenAI in the creative industries are now indistinguishable from those of human creation. This paper focuses on GenAI use in promoting creativity engineering education, an area where past attempts were not met with much success. In addition, impact of GenAI on creativity is already extensively studied in non-engineering disciplines where we have much to learn from. One important aspect is the greater emphasis on importance of creation process in addition to creative product. The approach made use of a mental model developed by the author that showed how use of GenAI can be scrutinized at several levels to ensure that it can be responsibly used in teaching and learning. A key feature of the model is the use of CDIO Core Standards to provide human-in-the-loop oversight on GenAI responses. This has the dual benefits of ensuring that the processes enhance core human capacity while the engineering products demonstrate strict adherence to professional standards in meeting ethical and safety obligations. The paper shares an idea of moving forward to use the approach outlined in this paper to enhance faculty contribution to innovative teaching and learning by addressing challenges that are “unknown unknowns” via working collaboratively with GenAI.
