Myrdal distinguished, across his late career and most pointedly in his 1974 Nobel Prize lecture, between what he called opportunistic and honest social science. Opportunistic analysis begins with a conclusion and assembles evidence to support it. It is selective in attention — generous to confirming evidence and dismissive of disconfirming evidence — and it presents the resulting picture as though it were the product of open inquiry when it is in fact the product of motivated reasoning. Honest analysis begins with a question and follows the evidence wherever it leads, especially when the evidence leads to conclusions uncomfortable for the analyst, the analyst's community, or the analyst's funders.
The AI discourse is dominated by opportunistic analysis on both sides. The triumphalists select for success stories, adoption curves, and productivity metrics that confirm the democratization narrative. The catastrophists select for displacement data, inequality measures, and cautionary precedents that confirm the concentration narrative. Neither side is fabricating evidence.