Essential skills for using generative AI

20 2023 September
John C Ickis
No. 23, September-October 2023. 

Based on his research on the psychology of artificial intelligence (AI) and learning, Oguz Acar, professor of marketing and innovation at King's College, London and research affiliate at the Innovation Science Laboratory at Harvard University, has defined 4 skills that , in his opinion, students should learn to use generative AI effectively—published in “Are Your Students Ready for AI?” Below, I share with you these skills and some reflections on them.

The first skill is a thorough understanding of the problem to be solved. Students who already have experience with the case method will have already acquired this skill and will have an advantage in its application. 

This skill should not be confused with the ability to interact with the AI ​​until you reach the correct question, known as “prompting.” This skill is the deep analysis that is done to define the approach and scope of the problem. before de prompting. It is what allows us to communicate more precisely what is expected from generative AI.

The second skill is exploration, which means searching for the generative AI tool that is most appropriate for the task or problem you want to solve. ChatGPT is very useful for the instructor as an academic assistant in general, whether in designing his syllabus or preparing his teaching plan. Tools such as Microsoft Bing or Google Bard, according to Acar, can help in information searches. And there are new tools coming out every day.

To strengthen students' exploration skills, Prof. Acar recommends asking them to search for AI tools for their next course assignment or project, and select the one that fits best, taking into account its attributes, functions, possible benefits and limitations. They must document and justify their decisions.

The third skill is critical thinking: the ability to identify and remove AI-generated content that is biased, inaccurate, or incorrect—one of the main limitations of ChatGPT, noted by Prof. Florian Federspiel in the last issue of this blog. But this limitation can be turned into a learning opportunity, according to Acar, with exercises in the application of this skill, which is learned with the case method, to evaluate the information generated by AI.

The fourth skill is reflection, the ability to examine your own feelings in relation to AI. Do you see it as a tool, useful, but with the limitations of any instrument that has imperfections? As a threat to their own identity, in the case of an aspiring great writer or designer who rejects the idea of ​​seeking help from AI?

Although it has certain elements in common with critical thinking, reflection is different. It's about the ability to examine yourself, your beliefs, and your behaviors—to be able to differentiate your thoughts from the products of AI.

These 4 skills are precisely those that the case method aims to strengthen. The use of AI is not only consistent with this method; the two can and should reinforce each other. Prof. Acar's experience with activities that develop these skills has produced notable improvements in the quality of his students' work. Wouldn't case discussion be the best activity?

-John C. Ickis

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