Relating Data, Recommendations, Boredom, and the ROI of AI

What do #data, #recommendations, and #boredom have to do with #AI/#MachineLearning #ROI? Surprisingly lot. #AIeconomics #AIdesign pic.twitter.com/ryX3QMtyWe
— ivanjureta (@ivanjureta) March 5, 2018
“Objective”, as in, for example, “what I’m saying is objective”, or “that statement is objective”, or “we need objective criteria when making these decisions”, is a complicated term. It takes a lot of effort to make sure it is understood as intended (or closely enough). It is therefore a costly word to use. Why is…
To say that something is able to decide requires that it is able to conceive more than the single course of action in a situation where it is triggered to act, that it can compare these alternative courses of action prior to choosing one, and that it likes one over all others as a result…
If AI is made for profit, then should its design be confidential? This choice is part of AI product strategy. The decision on this depends on the following at least. What is the relationship of each of these to AI confidentiality? Correctness: The more likely the AI / algorithm is to make errors, the more…
If an artificial intelligence system is trained on large-scale crawled web/Internet data, can it comply with the Algorithmic Accountability Act? For the sake of discussion, I assume below that (1) the Act is passed, which it is not at the time of writing, and (2) the Act applies to the system (for more on applicability,…
The Algorithmic Accountability Act of 2022, here, applies to systems that help make, or themselves make (or recommend) “critical decisions”. Determining if something is a “critical decision” determines if a system is subject to the Act or not. Hence the interest in the discussion, below, of the definition of “critical decision”. The Act defines a…