What AI Can’t Do Faster, Better, or Cheaper Than Humans, by Charles Hugh Smith

A lot of knowledge can’t be reduced to algorithms. From Charles Hugh Smith at oftwominds.com:

Since generative AI is adept at manipulating digital text, voice and images, many assume this automatically infers it will be adept at the entirety of human endeavor and work. But this is false logic. The same false logic leads many to assume that since a humanoid robot can jump over boxes and a specialized robot can lay flooring tiles in a giant warehouse with a perfectly flat concrete floor, robots will soon be able to do every possible kind of work.

This is a layperson’s logic based on a limited grasp of what makes tasks accessible to AI / robots. Jumping over boxes and laying flooring tiles are repeatable behaviors in a narrow context. There is little ambiguity or imperfect choices to make, and little need for dexterity in not one task but dozens of different tasks, none of which are repeatable in the long, complex slog to get job done.

Manipulating text, voice and images is easy for one reason: these are digital, not real-world. All three can be broken down to pattern matching and probability based on scraping millions of existing samples. The real world isn’t quite so easy.

Here are two small examples from my own work strengthening our 70-year old house to withstand a hurricane. The fawning videos of robots laying floor tile, etc. leave out all the important contexts of the built environment: operating on a perfectly flat floor where the work is repeatable is a narrow set of conditions that only apply to a very limited number of construction projects.

The majority of homes and buildings in the U.S. are old, and so the consequences of time, settling, decay, leaks, etc.–i.e., real life–establish unique conditions with ambiguous solutions, as there are generally several ways to do the task, and each has its costs, tradeoffs and risks.

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