The era of AI malaise

Early days of uncertainty we experienced during COVID-19 remind us a lot of where we are now with AI. The technology is clearly here, spreading everywhere, and it is not going away. But what will it do? What effect will it have on our society? Will it make life better, or worse? How will we know? What’s the plan? Who should we even believe about the various ways possible futures may pan out?

We’re all sitting uncomfortably with AI right now. It’s coming from the top down. The CEOs of the big AI companies caution us that this technology may very well take all of our jobs. Or that if it doesn’t live up to that hype, it might just crash the economy instead.

Or maybe both things will happen.  It is a truism that investors hate uncertainty. Well! We are all investors in our own future. The promise of AI is so powerful, and so very compelling. Who among us is not in favor of curing all diseases? Who among us is not in favor of limitless clean energy or an end to the climate crisis? But right now, at least, the path immediately ahead of us looks far less appealing.

Data centers are running up our power bills and polluting our air. Robots are offering up lists of kill targets, and in some cases blowing people up on the other end of those lists. In professional conversations, it is increasingly impossible to tell if we are being over-reliant on AI or not using it enough. Slop overruns our phones and feeds. The language of social media—especially on that scourge LinkedIn—and blog posts and newsletters and even big-J journalism increasingly reads like an output from Claude. Our apps are all getting injections of AI, like it or not. Employers are shedding roles by the thousands in the name of AI efficiency. People are succumbing to its dark mirror and losing their grasp on reality. We’re told the next model is so powerful, and so potentially dangerous and terrifying, that we can’t even release it. Not yet. (But soon! Don’t worry, soon.) 

It’s buying things while we sleep. It’s discovering the structure of proteins. It’s telling children to kill themselves. It’s telling children to kill themselves. No wonder most people say AI makes them nervous. 

Is this what we signed up for? Is today the day? Did the drones wake up? Did it achieve consciousness? Is it alive? (No. Not yet. Go back to bed.)

The 21st-century average American lies in bed staring at their phone. They should be sleeping. They should read a book. They should take a melatonin. Instead they are deep in conversation with a math equation. Talking for hours and ages to melted sand.

As the novel coronavirus became covid-19 and eventually just plain covid, we learned a lot about it. We learned what to expect. We built tools that helped us track, and prevent, its spread. We created vaccines. And in time, we reopened the schools. We reopened life. 

We have not really begun to make this progress with AI. Why, for example, is this dashboard not found on a government website? Where is the large-scale industrial policy for transforming our grid to support massive data center build-outs? Where is the plan for what happens when millions of people—software engineers, paralegals, truck drivers, translators, journalists, janitors—are suddenly out of work? 

We need tools to better understand what’s coming, how it is spreading, how it is changing things. We need to be able to see its actual effect on the economy, rather than the fumbling rough sense we have now. Until we can track it, understand it, and predict it, we will be left with uncertainty and malaise, bleaching our broccoli in a cloth mask.

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