Researchers have been throwing tons of effort into getting better training data. For example, Surge AI had a revenue of over $1 billion last August, and Scale AI was probably in a similar boat.
Data industry > AI progress
Most focus on algorithmic breakthroughs, but author shows data companies with $1B+ revenue drive more efficiency than algorithmic innovations.
Reddit, Shutterstock, and News Corp are making hundreds of millions a year licensing their high-quality data to companies training AI, and those contracts are growing about 20 percent annually, according to their quarterly filings.
这一数据揭示了AI训练数据市场的巨大经济价值，表明高质量数据已成为AI公司的战略资产。传统内容公司正在转型为AI的'输入公司'，这种转变不仅改变了他们的商业模式，也重新定义了数据在AI生态系统中的核心地位。
Desirables: * data export * data import (POSSE/PESOS) * collaboration (wiki/fanclub, annotations)
Claudia Sahm. (2022, January 5). “We, as experts, have a responsibility to policymakers and everyday people to match the strength of our recommendations to the strength of our data. When I read Oster, I see a tone and conviction that far exceeds the many limitations of her data.” https://t.co/NqWwj0hi28 [Tweet]. @Claudia_Sahm. https://twitter.com/Claudia_Sahm/status/1478532000441151488
Stanford, J. (n.d.). Healthy humans drive the economy: We’re now witnessing one of the worst public policy failures in Australia’s history. The Conversation. Retrieved January 12, 2022, from http://theconversation.com/healthy-humans-drive-the-economy-were-now-witnessing-one-of-the-worst-public-policy-failures-in-australias-history-174606
Visual, F. T., & team, D. J. (n.d.). Covid-19 vaccine tracker: The global race to vaccinate. Retrieved 13 December 2021, from https://ig.ft.com/coronavirus-vaccine-tracker/
Saner, E. (2021, October 26). The psychology of masks: Why have so many people stopped covering their faces? The Guardian. https://www.theguardian.com/world/2021/oct/26/the-great-cover-up-why-the-uk-stopped-wearing-face-masks
The Data Visualizations Behind COVID-19 Skepticism. (n.d.). The Data Visualizations Behind COVID-19 Skepticism. Retrieved March 27, 2021, from http://vis.csail.mit.edu/covid-story/
GDP & main components pin EU countries.
Emails show Trump officials celebrate efforts to change CDC reports on coronavirus—The Washington Post. (n.d.). Retrieved April 12, 2021, from https://www.washingtonpost.com/health/2021/04/09/cdc-covid-political-interference/
Hale, Thomas. ‘What We Learned from Tracking Every COVID Policy in the World’. The Conversation. Accessed 26 March 2021. http://theconversation.com/what-we-learned-from-tracking-every-covid-policy-in-the-world-157721.
Gupta, Prateek, Tegan Maharaj, Martin Weiss, Nasim Rahaman, Hannah Alsdurf, Abhinav Sharma, Nanor Minoyan, et al. ‘COVI-AgentSim: An Agent-Based Model for Evaluating Methods of Digital Contact Tracing’. ArXiv:2010.16004 [Cs], 29 October 2020. http://arxiv.org/abs/2010.16004.
U.S. Census Bureau. (2021, February 4). Small Business Pulse Survey Shows Shift in Expectations from Spring to Winter. The United States Census Bureau. https://www.census.gov/library/stories/2021/01/small-business-pulse-survey-shows-shift-in-expectations-from-spring-to-winter.html?utm_campaign=20210126msacos1ccstors&utm_medium=email&utm_source=govdelivery
Goolsbee, Austan, and Chad Syverson. ‘Fear, Lockdown, and Diversion: Comparing Drivers of Pandemic Economic Decline 2020’. Journal of Public Economics 193 (1 January 2021): 104311. https://doi.org/10.1016/j.jpubeco.2020.104311.
ReconfigBehSci @SciBeh (2020) For those who might think this issue isn't settled yet, the piece include below has further graphs indicating just how much "protecting the economy" is associated with "keeping the virus under control" Twitter. Retrieved from: https://twitter.com/i/web/status/1306216113722871808
Harvard’s Chetty Finds Economic Carnage in Wealthiest ZIP Codes. (2020, September 24). Bloomberg.Com. https://www.bloomberg.com/news/features/2020-09-24/harvard-economist-raj-chetty-creates-god-s-eye-view-of-pandemic-damage
NW, 1615 L. St, Suite 800Washington, & Inquiries, D. 20036USA202-419-4300 | M.-857-8562 | F.-419-4372 | M. (n.d.). A majority of young adults in the U.S. live with their parents for the first time since the Great Depression. Pew Research Center. Retrieved September 7, 2020, from https://www.pewresearch.org/fact-tank/2020/09/04/a-majority-of-young-adults-in-the-u-s-live-with-their-parents-for-the-first-time-since-the-great-depression/
Building the New Economy · Works in Progress. (n.d.). Works in Progress. Retrieved June 16, 2020, from https://wip.mitpress.mit.edu/new-economy
GDP and employment flash estimates for the second quarter of 2020: GDP down by 12.1% and employment down by 2.8% in the euro area. (n.d.). Retrieved August 29, 2020, from https://ec.europa.eu/eurostat/web/products-press-releases/-/2-14082020-AP
Andersen, M., Maclean, J. C., Pesko, M. F., & Simon, K. I. (2020). Effect of a Federal Paid Sick Leave Mandate on Working and Staying at Home: Evidence from Cellular Device Data (Working Paper No. 27138; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27138
Bartik, A. W., Cullen, Z. B., Glaeser, E. L., Luca, M., Stanton, C. T., & Sunderam, A. (2020). The Targeting and Impact of Paycheck Protection Program Loans to Small Businesses (Working Paper No. 27623; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27623
Harris, J. E. (2020). Reopening Under COVID-19: What to Watch For (Working Paper No. 27166; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27166
Stock, James H. ‘Data Gaps and the Policy Response to the Novel Coronavirus’. Working Paper. Working Paper Series. National Bureau of Economic Research, March 2020. https://doi.org/10.3386/w26902.
Correa, R., Du, W., & Liao, G. Y. (2020). U.S. Banks and Global Liquidity (Working Paper No. 27491; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27491
Alstadsæter, A., Bratsberg, B., Eielsen, G., Kopczuk, W., Markussen, S., Raaum, O., & Røed, K. (2020). The First Weeks of the Coronavirus Crisis: Who Got Hit, When and Why? Evidence from Norway (Working Paper No. 27131; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27131
Goolsbee, A., & Syverson, C. (2020). Fear, Lockdown, and Diversion: Comparing Drivers of Pandemic Economic Decline 2020 (Working Paper No. 27432; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27432
Germany’s Capacities to Work from Home. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved August 8, 2020, from https://covid-19.iza.org/publications/dp13152/
Brown, C. S., Ravallion, M., & van de Walle, D. (2020). Can the World’s Poor Protect Themselves from the New Coronavirus? (Working Paper No. 27200; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27200
Baqaee, D., Farhi, E., Mina, M. J., & Stock, J. H. (2020). Reopening Scenarios (Working Paper No. 27244; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27244
Friedson, A. I., McNichols, D., Sabia, J. J., & Dave, D. (2020). Did California’s Shelter-in-Place Order Work? Early Coronavirus-Related Public Health Effects (Working Paper No. 26992; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w26992
Cotti, C. D., Engelhardt, B., Foster, J., Nesson, E. T., & Niekamp, P. S. (2020). The Relationship between In-Person Voting and COVID-19: Evidence from the Wisconsin Primary (Working Paper No. 27187; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27187
Dave, D. M., Friedson, A. I., Matsuzawa, K., & Sabia, J. J. (2020). When Do Shelter-in-Place Orders Fight COVID-19 Best? Policy Heterogeneity Across States and Adoption Time (Working Paper No. 27091; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27091
Papanikolaou, D., & Schmidt, L. D. W. (2020). Working Remotely and the Supply-side Impact of Covid-19 (Working Paper No. 27330; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27330
Schmitt-Grohé, S., Teoh, K., & Uribe, M. (2020). Covid-19: Testing Inequality in New York City (Working Paper No. 27019; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27019
Fatehkia, M., Tingzon, I., Orden, A., Sy, S., Sekara, V., Garcia-Herranz, M., & Weber, I. (2020). Mapping socioeconomic indicators using social media advertising data. EPJ Data Science, 9(1), 1–15. https://doi.org/10.1140/epjds/s13688-020-00235-w
Barton, C. M., Alberti, M., Ames, D., Atkinson, J.-A., Bales, J., Burke, E., Chen, M., Diallo, S. Y., Earn, D. J. D., Fath, B., Feng, Z., Gibbons, C., Hammond, R., Heffernan, J., Houser, H., Hovmand, P. S., Kopainsky, B., Mabry, P. L., Mair, C., … Tucker, G. (2020). Call for transparency of COVID-19 models. Science, 368(6490), 482.2-483. https://doi.org/10.1126/science.abb8637
Rahman, M., Ali, G. G. M. N., Li, X. J., Paul, K. C., & Chong, P. H. J. (2020). Twitter and Census Data Analytics to Explore Socioeconomic Factors for Post-COVID-19 Reopening Sentiment [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/fz4ry
Boustan, L. P., Kahn, M. E., Rhode, P. W., & Yanguas, M. L. (2020). The Effect of Natural Disasters on Economic Activity in US Counties: A Century of Data. Journal of Urban Economics, 103257. https://doi.org/10.1016/j.jue.2020.103257
Social Scientists Scramble to Study Pandemic, In Real Time. (n.d.). Association for Psychological Science - APS. Retrieved April 20, 2020, from https://www.psychologicalscience.org/news/social-scientists-scramble-to-study-pandemic-in-real-time.html
2020 Global Outlook | BlackRock Investment Institute. (n.d.). BlackRock. Retrieved April 27, 2020, from https://www.blackrock.com/corporate/insights/blackrock-investment-institute/publications/outlook
Verbruggen, R. (2020 March 24). Another COVID Cost-Benefit Analysis. National Review. https://www.nationalreview.com/corner/another-covid-cost-benefit-analysis/
Atchison, C. J., Bowman, L., Vrinten, C., Redd, R., Pristera, P., Eaton, J. W., & Ward, H. (2020). Perceptions and behavioural responses of the general public during the COVID-19 pandemic: A cross-sectional survey of UK Adults [Preprint]. Public and Global Health. https://doi.org/10.1101/2020.04.01.20050039
YouGov UK COVID-19 Monitor
Savanta Coronavirus Data Tracker
沒有看到許委員的『數位經濟基本法』原始草案全文。在討論過程中有一些問題，例如數位經濟的基本定義；對資料產業沒有處理，以至於詹先生對國家保存資料的想像可能低估技術、行政程序，導致不恰當地反映在資料保存相關條文等處，不曉得是否有修正與否。
the automatic collection of students’ data through interactions with educational technologies as a part of their established and expected learning experiences raises new questions about the timing and content of student consent that were not relevant when such data collection required special procedures that extended beyond students’ regular educational experiences of students
Useful reminder. Sounds a bit like “now that we have easier access to data, we have to be particularly careful”. Probably not the first reflex of most researchers before they start sending forms to their IRBs. Important for this to be explicitly designated as a concern, in IRBs.
the use of data in scholarly research about student learning; the use of data in systems like the admissions process or predictive-analytics programs that colleges use to spot students who should be referred to an academic counselor; and the ways colleges should treat nontraditional transcript data, alternative credentials, and other forms of documentation about students’ activities, such as badges, that recognize them for nonacademic skills.
Useful breakdown. Research, predictive models, and recognition are quite distinct from one another and the approaches to data that they imply are quite different. In a way, the “personalized learning” model at the core of the second topic is close to the Big Data attitude (collect all the things and sense will come through eventually) with corresponding ethical problems. Through projects vary greatly, research has a much more solid base in both ethics and epistemology than the kind of Big Data approach used by technocentric outlets. The part about recognition, though, opens the most interesting door. Microcredentials and badges are a part of a broader picture. The data shared in those cases need not be so comprehensive and learners have a lot of agency in the matter. In fact, when then-Ashoka Charles Tsai interviewed Mozilla executive director Mark Surman about badges, the message was quite clear: badges are a way to rethink education as a learner-driven “create your own path” adventure. The contrast between the three models reveals a lot. From the abstract world of research, to the top-down models of Minority Report-style predictive educating, all the way to a form of heutagogy. Lots to chew on.
Users publish coursework, build portfolios or tinker with personal projects, for example.
Useful examples. Could imagine something like Wikity, FedWiki, or other forms of content federation to work through this in a much-needed upgrade from the “Personal Home Pages” of the early Web. Do see some connections to Sandstorm and the new WordPress interface (which, despite being targeted at WordPress.com users, also works on self-hosted WordPress installs). Some of it could also be about the longstanding dream of “keeping our content” in social media. Yes, as in the reverse from Facebook. Multiple solutions exist to do exports and backups. But it can be so much more than that and it’s so much more important in educational contexts.
(Not surprisingly, none of the bills provide for funding to help schools come up to speed.)
nearly $8 billion prekindergarten through 12th-grade education technology software market
As usual, @AudreyWatters puts things in proper perspective.
That's why I say that data is the new oil for the digital age