You're right, it's very much context dependent, and I appreciate your incite on how this clash between psychology and computer science muddies the terms. As a CS guy myself who's just dipping my toes into NN's, I lean toward the psychology definition, where intelligence is measured by behavior.

In an artificial neural network, the algorithms that wrangle data and build a model aren't really what makes the decisions, they just build out the "body" (model, generator functions) and "environment" (data format), so to speak. If anything that code is more comparable to DNA than any state of mind. Training on data is where the knowledge comes from, and by making connections the model can "reason" a good answer with the correlations it found. Those processes are vague enough that I don't feel comfortable calling them algorithms, though. It's pretty divorced from cold, hard code.