Behold the Decade of Mid Tech!
The Revolution That Never Was
As I look back on the decade, I am reminded of the breathless anticipation with which I once approached the topic of A.I. with friends and colleagues. "What about A.I.?" would be the question, accompanied by a sense of excitement and wonder. I’d respond with a mix of skepticism and curiosity, asking "what’s the big deal?" only to be met with assurances that A.I. was going to change everything.
The Midness of Mid Tech
As someone who uses new technology, I can confidently say that I know mid when I see it. And what I’ve seen so far is a revolution that’s more mid than mighty. Academics have been at the forefront of this revolution, and it’s precisely because of this that I know mid when I see it.
The Threat of Mid Tech
A.I. is just one of many technologies that promise transformation through iteration rather than disruption. Consumer automation, for instance, was supposed to revolutionize the way we shop, but instead, it’s resulted in cashiers still being better at managing points of sale. A.I.-based facial recognition was supposed to make air travel more efficient, but it’s still causing privacy concerns and hasn’t particularly revolutionized the airport experience.
The Reality of Mid Tech
The economists Daron Acemoglu and Pascual Restrepo call these kinds of technological fizzles "so-so" technologies. They change some jobs, are kind of nifty for a while, and eventually become background noise or are flat-out annoying. A.I. is supposed to be more radical, but the reality is that it’s being used for far more mundane purposes. It spits out meal plans with the right amount of macros, tells us when our calendars are overscheduled, and helps write emails that no one wants.
The Parasitic Nature of Mid Tech
A.I. is a parasite that attaches itself to a robust learning ecosystem and speeds up some parts of the decision process. The problem is that A.I. has no qualms about starving its host. The political problem with A.I.’s hype is that its most compelling use case is starving the host – fewer teachers, fewer degrees, fewer workers, fewer healthy information environments.
The Danger of Mid Tech
Hype isn’t held to account for being accurate, only for being compelling. Mark Cuban, for instance, has exemplified this by imagining an A.I.-enabled world where a worker with "zero education" uses A.I. and a skilled worker doesn’t. The problem is that asking the right questions requires the opposite of having zero education. You can’t just learn how to craft a prompt for an A.I. chatbot without first having the experience, exposure, and education to know what the heck you are doing.
Conclusion
Mid tech is a threat, and its most compelling use case is starving the host. The reality of mid tech is that it’s being used for far more mundane purposes, and its promise of transformation is just that – a promise. As we look back on the decade, it’s clear that mid tech has failed to deliver on its promises. Instead, it’s left us with a sense of disappointment and disillusionment. The question is, what’s next?
FAQs
Q: What is mid tech, and how does it differ from high-tech innovations?
A: Mid tech refers to technologies that promise transformation through iteration rather than disruption. It’s characterized by modest augmentations to existing processes, rather than revolutionary change.
Q: What are some examples of mid tech?
A: Some examples of mid tech include consumer automation, A.I.-based facial recognition, and predictive analytics.
Q: What are the consequences of mid tech?
A: The consequences of mid tech include the potential for job displacement, the devaluation of expertise, and the creation of a culture that values efficiency over quality.
Q: What can be done to mitigate the negative effects of mid tech?
A: To mitigate the negative effects of mid tech, it’s essential to focus on creating a culture that values human expertise, to prioritize education and skills training, and to promote a nuanced understanding of the role of technology in society.
