From large mainframes to personal computers to the mobile devices of today, how we engage with computing has profoundly changed over the course of one generation. Each of those transitions represented a major inflection point in the ubiquity and centrality of computing — and now it’s happened again. ChatGPT signaled a whole new future, spurring artificial intelligence arms races between nations, companies and researchers. It isn’t hyperbole to say all aspects of society and industry will be impacted by advances in computing and AI. This is particularly true in prestige industries like health care, mobility, finance and entertainment, but also for less flashy areas like the trades, manufacturing and retail.
These advances will undoubtedly lead to increased productivity and usability, and more personalized services, but will also introduce new challenges. For example, smart policing using data science and AI to identify high-risk areas in which to deploy police services is a very attractive idea on its surface; however, too often these tools reinforce biases and calcify generations-old socioeconomic inequalities, leading to as much damage as good. The excitement around and rapid uptake of such technologies will need to be moderated by deeper analysis and mitigation of the unintended ramifications.
In the following paragraphs, we present three pressing questions regarding the coming impacts of AI. The list is not meant to be exhaustive. We hope it will illustrate that while computing expertise underlies AI algorithms, a broader set of knowledge is needed to apply them responsibly and effectively. By leaning into this, Michigan Tech can situate itself to be a leader in the application of AI to other domains.
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