Data Science?

https://engagement.virginia.edu/learn/20240831-data

Prometheus’s Fire or a Monkey’s Paw?

The presentation started off with a DALL-E-generated image of Prometheus with his fire overlooking a horde of humans holding torches of fire looking up. The idea was to display data science in a positively, a technology which it makes humanity freer, positioning it as from the realm of Gods.

This way of painting data science is a bit disingenuous considering its potentials and ongoing challenges. Fire was made in the realm of God. Data science is patently devised by us, humanity. The implication being that it can only be as good as any other human activity. Akin to the development of psychology; Data Science is fated to encounter the same qualms.

Lessons from Psychology & Data

AP Psych teaches heuristic bias, sampling bias, and representative bias. These concepts can be mapped into the current discourse on why models fail: 1. relying on variables that don’t measure the phenomena (or can the phenomena even be converted to a metric), 2. the current dataset does not accurately portray the phenomena, and 3. consequently overfit to what the model data has.

Eventually it all coalesces into Fundamental Attribution Error: assuming the behavior of some individual is related to the appearance. In the same light, the point of the correlation vs. causation concept highlights the more conceptual aspect of FAE which is that two variables can be correlated, but not necessarily cause each other. And if the problem of other minds has to say anything, there is already an existing epistemic gap between any observed behavior and the reasoning that went behind it (regarding using ai to predict human behavior).1

Seminar Notes


Citations

Eronen, M. I., & Bringmann, L. F. (2021). The Theory Crisis in Psychology: How to move forward. Perspectives on Psychological Science, 16(4), 779–788. https://doi.org/10.1177/1745691620970586

McCarthy, J., & Hayes, P. (1981). Some Philosophical Problems from the Standpoint of Artificial Intelligence. In Elsevier eBooks (pp. 431–450). https://doi.org/10.1016/b978-0-934613-03-3.50033-7


"The first task is to define even a naive, common-sense view of the world precisely enough to program a computer to act accordingly. This is a very difficult task in itself."

  1. This epistemic gap has already been detailed by McCarthy (the founder of the ai field) and I feel like modern practitioners have forgotten about his work which I will cite below. ↩