This week’s prompt is to comment on AI tracking for eye gaze, posture, and other indicators of attention. Employers who need to follow my indicators of attention are not employers I want to work for. For me, it’s not a privacy issue, it’s a respect issue. For a professional knowledge worker, of course there are many ways to track how much work a person does. I’ve spent the last 18 years as a remote worker, and most of that as a contractor. There are ways an employer could track minute metrics of my productivity. They could look at my meetings; they could look at my Slack messages; they could look at my files. However, usually we don’t do those things. Instead, we trust that the person hired to do a job actually does the job. Some workers are slackers. We try to identify and get those folks out of the organization as much as possible. With this in mind, I am insulted by the idea of tracking my adult learners' gaze and posture. I could see a scenario in which it might work. Say I wanted to A/B test two versions of a learning experience to improve my offerings. Say that I had an AI tracking tool that was reasonably priced and easy to put in place. The tracking could provide useful information. In that scenario, learners would know they were being tracked during the test. They would also know why. That scenario requires quite a lot of effort. Both learning experiences are developed enough to test. And the AI tool is implemented. Learners are informed what is happening and why. The big question to ask is if it would be worth it. Would that information be more valuable than what we can get from other feedback? My suspicion is that the answer is no. My suspicion is that it's best to leave that type of testing of cognitive psychologists. As Clark (2020) says: If you want insights into how people actually learn, set some time aside and look at the existing research in cognitive science. You will do better looking at what the research actually says and then redesigning your online learning around that science. Remember that these scientific findings have already gone through a process of controlled studies, with a methodology that statistically attempts to get clean data on specific variables. References
Clark, D. (2020). Artificial Intelligence for Learning: How to use AI to support employee development. Kogan Page Limited.
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AuthorMichele Wiedemer has worked in software as an "accidental instructional designer" for many years. She is currently completing the MS in Learning Technologies at The University of North Texas. This blog represents reflections on specific assignments in the coursework. Archives
February 2024
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