rishi
The long-awaited Google analysis of usage data is out! I enjoyed the paper for many reasons. Most of all, the top-level conclusions are well-chosen. They crisply articulate and evidence points many of us have been making for a while, arguably more cleanly than their OpenAI/Anthropic counterparts. - Workplace adoption is broad (many occupations) but shallow (few tasks) - AI can be used beyond white-collar work, including in physical labor. We give some nice examples in our recent EconEvals paper from @alexwan55 - Household use is a really big deal, especially for more consumer-oriented Google and OpenAI models. Michael Blank at @StanfordGSB has an excellent paper in this direction that more should read. A more modern ATUS would be even better for this type of analysis! Figure 14, the associated analyses in that section, and the guest comment from Diane Coyle were probably my favorite results in the paper. - GDP per capita predicts Google AI adoption. Based on our national exposure work with @_arulm_, I wonder if national AI exposure and/or white collar shares are better predictors, since this seems to be true of Anthropic/Microsoft/OpenAI data. Internet access as a bottleneck is a nice thing to study, aligning with recent work out of the ILO from Gmyrek et al. Europeans should attend to the issue brought about in tracking the economic impacts of AI (see page 51) "Due to conversation logging limitations, we are unable to explicitly classify API calls from European countries and any paid API usage as work/non-work ... and omit European countries from the analysis due to lack of data." - Appendix B does some nice work on validating conversational classifiers. I appreciate that the authors report the task-level classification accuracy is just 22.58%, of course acknowledging there are 18k tasks in O*NET. This point deserves a lot more focus: it would be see a collective effort to build and use standardized open-source classifiers for economic analysis of usage data. Overall, very happy with this long-awaited first work from Google on analyzing their usage data for economic purposes. Look forward to seeing them sustain and build upon this infrastructure, and working towards something more unified with the other frontier labs!
