Explain Which AI You Mean, Please?
The term ‘AI’ has gotten overplayed. Similar to the term ‘data science’ from 5 years ago, the word ‘AI’ is used everywhere by everybody. It has become the umbrella term for anything tech-related or tech-adjacent. AI, as a discipline, has also gone through a series of metamorphoses. AI isn’t strictly in the natural/physical science arena anymore. It has also suffered a litany of fractures. The mass adoption of ‘AI’ has diluted its purported faultlessness. I don’t *really* know what someone means when they say AI. As a data educator, I’ve mentally placed AI as part of the data analysis box. So at times I wonder if some people are saying AI , but *really* contending with data analysis and management issues. I therefore use data and AI together 9 times out of 10.
By now, we all have had more conversations about AI than we care to remember or recount. I usually sit silently for a few minutes to allow the organic discussion to flow. I’ve realized over the past 2 years that it’s critically important to listen to how the majority of the room is understanding AI and in what sector/domain context, e.g., AI tool uses for educators as a learning complement versus navigating AI tool misuse by their learners as an educator. My listening phase is quite active as I’m running through a list of questions (not necessarily in this order or all of them for every AI conversation):
