As the dust continues to settle from last week’s elections, pundits are blithely repeating the perception that polling is broken, as polls again failed to predict accurately the closeness of the race. But science is messy, particularly when human behavior is involved. A prediction is a hypothesis of probability, and if the pollsters got it wrong, then they’ll examine their models to see if they can formulate better hypotheses. But is there an alternative to calling people up and asking them whom they intend to vote for? Perhaps AI algorithms can draw new insights from alternative data sets. There’s always the risk, though, that flawed algorithms will just magnify the errors in data that already plague us.
- An Election Forecaster Reflects: We Have Too Many Polls [Wired] “The question here, though, is whether polling and forecasting are a waste of time and resources, given that, at least in this election, we could’ve done better with no polls at all. We should be able to study this using our forecasting model. It’s Bayesian, meaning that it combines information from past elections, a fundamentals-based forecast, and polls during the campaign.”
- How AI predictions fared against pollsters in the 2020 U.S. election [VentureBeat] “Firms like KCore Analytics, Expert.AI, and Advanced Symbolics claim algorithms can capture a more expansive picture of election dynamics because they draw on signals like tweets and Facebook messages. But in the aftermath of the 2020 election, it’s still unclear whether AI proved more or less accurate than the polls.”
- Artificial Intelligence Shows Potential to Gauge Voter Sentiment [Wall Street Journal] “Expert.ai’s system projected that Democratic presidential nominee Joe Biden would win 50.2% of the popular vote and Republican President Donald Trump would get 47.3% of the vote, a 2.9 percentage-point margin. As of Friday afternoon, Mr. Biden had 50.5% of the popular vote compared with Mr. Trump’s 47.8%, a 2.7 percentage-point margin.”
- 7 Ways AI Could Solve All Of Our Election Woes: Out With The Polls, In With The AI Models [Fortune] “If we look to AI and innovation, we can see the future of election day. No long lines, no waiting on ballots to be dumped and counted. No wondering if your mailed or absentee vote was counted and counted correctly. Instantaneous, secure and 100% accurate results.”
From the Ohio Web Library:
- Yankoski, Michael, et al. “An AI Early Warning System to Monitor Online Disinformation, Stop Violence, and Protect Elections.” Bulletin of the Atomic Scientists, vol. 76, no. 2, Mar. 2020, pp. 85–90.
- Zhang, Mali, et al. “Election Forensics: Using Machine Learning and Synthetic Data for Possible Election Anomaly Detection.” PLoS ONE, vol. 14, no. 10, Oct. 2019, pp. 1–14.
- Singh, Prabhsimran, et al. “Can Twitter Analytics Predict Election Outcome? An Insight from 2017 Punjab Assembly Elections.” Government Information Quarterly, vol. 37, no. 2, Apr. 2020, p. N.PAG.