I barely skimmed this so criticism is unfair, but... it could be a criticism of many "working papers." There's a type of euphemization that's been irking me in

I barely skimmed this so criticism is unfair, but... it could be a criticism of many "working papers." There's a type of euphemization that's been irking me in recent years: The vague everyone. No one ever talks about X. "Data largely determines performance, fairness, robustness, safety, and scalability of AI systems [44, 81]. Paradoxically, for AI researchers and developers, data is often the least incentivized aspect, viewed as ‘operational’ relative to the lionized work of building novel models and algorithms" Do they mean that projects (at google? in society?) under resource "data work?" Do people get paid less. Do they mean incentives in academia? Do they mean that companies specialising in these areas are less successful? That universities have priorities wrong? Just for the meander... at the top level, the economy does seem to be valuing data work highly. Adwords & Amazon marketplace antitrust cases suggest that "data work" is at the core of these mega businesses. TSLA's current valuation is partially based on tesla's exclusive dataset. In at least some very substantial examples, data work is very highly valued while models are seen as a temporary advantage... IE it looks like the market (some industrie) expects models/algorithms to be commoditized while the datasets are expected to be valuable intellectual property. The authors do really have some insights here. A lot of "AI project" post mortems do find "data work" was underestimated. I guess that means it's underappreciated by definition. But... I think it would have gone someplace more concrete if they had started someplace more concrete.