10 Machine Learning Ethics Mini-Essays

4. Artificial Stupidity.

Machine Learning Ethics assignment, Question #4, “Artificial Stupidity”, for York University CSML1000 “Machine Learning in the Business Context”, Fall 2019.

How can we guard against mistakes?

In order to guard against mistakes, any system must have robust human oversight. This idea will be explored in Question #7. While guarding against mistakes is always critical, it is essential that we learn what Artificial Stupidity is, what conditions or processes lead to its creation, and how we can avoid wasting untold human potential upstream and downstream from its creation. Squandering resources on an Artificial Stupidity would be a mistake. Setting one loose and letting people live with the consequences would be another mistake. In an interview about the book Rebooting AI[6], Gary Marcus says

But right now AI is dangerous, and not in the way that Elon Musk is worried about. But in the way of job interview systems that discriminate against women no matter what the programmers do because the techniques that they use are too unsophisticated. I want us to have better AI. I don’t want us to have an AI winter where people realize this stuff doesn’t work and is dangerous, and they don’t do anything about it.

Gary Marcus

Marcus believes that Classical AI, which is more of a rules-based framework for building cognitive models, can play a role in transcending Artificial Stupidity. “The machine-learning stuff is pretty good at learning from data, but it’s very poor at representing the kind of abstraction that computer programs represent. Classical AI is pretty good at abstraction, but it all has to be hand-coded, and there is too much knowledge in the world to manually input everything. So it seems evident that what we want is some kind of synthesis that blends these approaches.” An AI system that was capable of understanding when its own decisions were going off the rails because of a subtle shift in the data would still require human oversight. Butit would require less intervention and fewer mistakes would be made.