this post was submitted on 07 Oct 2023
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Had a thought that deserved a separate post. Your selection of MV tasks was rather perverse for the tasks we were discussing. Identifying a pop can is definitely something that humans can do easily because pop cans were made for us to be able to easily identify them. Level the playing field and let's start looking for internal stress fractures in the superstructure of a 100' tall concrete bridge. That is something that AI drones are already being designed and deployed for. The drone can easily approach the bridge with a suite of sensors that let it see deep into the superstructure and detect future failure points. Humans would struggle to do that. I have also seen things about maintenance drones that are able to crawl on the bridge using a variety of methods (usually they are designed for specific bridges) that are able to fill cracks with sealant and ablate rust using lasers, then paint the freshly cleaned metal. The benefit of replacing a workforce with AI-driven robotics is that you can purpose-build and purpose-train the tool to do exactly what you need it to do. A robot that scurries into a crawl space to run a pipe for a plumber doesn't need to know how to do anything but recognize where it goes, what not to touch, and how much force to use when installing it. It doesn't need to identify a pop can, it doesn't need to draw a Rembrandt. All it needs to do is pull a pipe and weld it in place (and yes, I am oversimplifying a bit, I know that).
The other thing that kinda gets me is the whole "cramped spaces" safety net that I kept seeing for why this job or that was going to be safe. Designing a small, agile robot is not really a challenge. Add onto it that in many situations you could use a tethered drone to do the actual work that is much smaller and the AI brain can be sitting safely outside the situation. You could even plug it into power, so battery tech doesn't need to increase. shrug I guess I just see quite a bit of very fast advances in the tech that have a worrying trajectory to me.
All great points. I guess I need to think of this topic more from the "what is possible" mindset rather than the "this is too hard" mindset to get a fair assessment of what is coming. All while still framing it in the sense of improving worker efficiency and automating human tasks piecemeal over time.