We Aren’t Ready to Live in a World of Algorithmic Enchantment

Six years ago, I was a relatively content college professor at a small liberal arts college. I did (and do) find joy in using knowledge to help students enter, as philosopher Michael Oakeshott once said, “the conversation of (human)kind.” I read some. I wrote some. I graded some. I was on too many committees. But I also groused over the lack of tomato production in my garden. I struggled to form a B chord on the guitar. I tried in vain not to get injured in my Saturday morning “legends” pick-up soccer game. I built an unaesthetic but functional potting bench. I regularly lost to my wife and kid at Boggle.

Fast forward to today and I’m often suspicious and edgy. The world seems to be moving faster than I can cognitively grasp. I can sometimes feel myself getting a bit manic trying to make sense of arcane concepts like the “dark enlightenment,” the latest iteration of “mixture of experts” reinforcement learning or the new corporate tech merger or sale that is further consolidating a consolidated industry.

As a political scientist trained primarily in public policy analysis, I don’t feel equipped to understand the gathering “AI storm.” When I was in graduate school, rational-choice theory was the primary approach to doing policy analysis. The assumption in these models was that humans were rational actors who could formulate preference, conduct full information searches, evaluate options and arrive at an optimal outcome. If humans could do this, so could those that work in government. Policy analysis was hence the study of maximizing costs and minimizing benefits.