[OPLIN 4cast] OPLIN 4Cast #694: Can AI algorithms predict election results better than humans?

[OPLIN OPLIN]

 OPLIN 4Cast
Email not displaying correctly? View it in your browser.
<http://www.oplin.org/4cast/>
[image: OPLIN 4Cast]

OPLIN 4Cast #694: Can AI algorithms predict election results better than
humans?
November 11th, 2020

[image: People voting and being polled] 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
   <https://www.wired.com/story/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
   <https://venturebeat.com/2020/11/06/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
   <https://www.wsj.com/articles/artificial-intelligence-shows-potential-to-gauge-voter-sentiment-11604704009>
   [*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
   <https://www.forbes.com/sites/markminevich/2020/11/02/7-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 <http://ohioweblibrary.org>:*

   - Yankoski, Michael, et al. “An AI Early Warning System to Monitor
   Online Disinformation, Stop Violence, and Protect Elections
   <https://search-ebscohost-com.proxy.oplin.org/login.aspx?direct=true&db=slh&AN=142200128&site=ehost-live>
   .” *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
   <https://search-ebscohost-com.proxy.oplin.org/login.aspx?direct=true&db=aph&AN=139408932&site=ehost-live>
   .” *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
   <https://search-ebscohost-com.proxy.oplin.org/login.aspx?direct=true&db=slh&AN=142251028&site=ehost-live>
   .” *Government Information Quarterly*, vol. 37, no. 2, Apr. 2020, p.
   N.PAG.

------------------------------
The *OPLIN 4cast* is a weekly compilation of recent headlines, topics, and
trends that could impact public libraries. You can subscribe to it in a
variety of ways, such as:

   - *RSS feed.* You can receive the OPLIN 4cast via RSS feed by
   subscribing to the following URL:
   http://www.oplin.org/4cast/index.php/?feed=rss2.
   - *E-mail.* You can have the OPLIN 4cast delivered via e-mail (a'la
   OPLINlist and OPLINtech) by subscribing to the 4cast mailing list at
   http://lists.oplin.org/mailman/listinfo/OPLIN4cast.

© 2020 Ohio Public Library Information Network
[image: Find us on Slideshare] <http://www.slideshare.net/oplin>  [image:
Find us on Facebook] <http://www.facebook.com/oplin.org>  [image: Find us
on Google+] <https://plus.google.com/107751358238995507967>  [image: Find
us on Twitter] <http://www.twitter.com/oplin>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.oplin.org/pipermail/oplin4cast/attachments/20201111/71ecaeae/attachment.htm>