• for: quote, quote - Robert Epstein, quote - search engine bias,quote - future of democracy, quote - tilting elections, quote - progress trap, progress trap, cultural evolution, technology - futures, futures - technology, progress trap, indyweb - support, future - education
• quote
  • The big tech companies, left to their own devices , have already had a net negative effect on societies worldwide.
  • At the moment, the three big threats these companies pose
    • aggressive surveillance,
    • arbitrary suppression of content,
      • the censorship problem, and
    • the subtle manipulation of
      • thoughts,
      • behaviors,
      • votes,
      • purchases,
      • attitudes and
      • beliefs
    • are unchecked worldwide
• author: Robert Epstein
  • senior research psychologist at American Institute for Behavioral Research and Technology
• paraphrase
  • Epstein's organization is building two technologies that assist in combating these problems:
    • passively monitor what big tech companies are showing people online,
    • smart algorithms that will ultimately be able to identify online manipulations in realtime:
      • biased search results,
      • biased search suggestions,
      • biased newsfeeds,
      • platform-generated targeted messages,
      • platform-engineered virality,
      • shadow-banning,
      • email suppression, etc.
  • Tech evolves too quickly to be managed by laws and regulations,
    • but monitoring systems are tech, and they can and will be used to curtail the destructive and dangerous powers of companies like Google and Facebook on an ongoing basis.
• reference
  • seminar paper on monitoring systems, ‘Taming Big Tech -: https://is.gd/K4caTW.

• for: titling elections, voting - social media, voting - search engine bias, SEME, search engine manipulation effect, Robert Epstein
• summary
  • research that shows how search engines can actually bias towards a political candidate in an election and tilt the election in favor of a particular party.

• for: search engine manipulation effect, SEME, voting, voting - bias, voting - manipulation, voting - search engine bias, democracy - search engine bias, quote, quote - Robert Epstein, quote - search engine bias, stats, stats - tilting elections
• paraphrase
• quote
  • In our early experiments, reported by The Washington Post in March 2013,
    • http://www.washingtonpost.com/opinions/could-google-tilt-a-close-election/2013/03/29/c8d7f4e6-9587-11e2-b6f0-a5150a247b6a_story.html?ref=hackernoon.com
  • we discovered that Google’s search engine had the power to shift the percentage of undecided voters supporting a political candidate by a substantial margin without anyone knowing.
  • 2015 PNAS research on SEME
    • http://www.pnas.org/content/112/33/E4512.full.pdf?with-ds=yes&ref=hackernoon.com
    • stats begin
    • search results favoring one candidate
    • could easily shift the opinions and voting preferences of real voters in real elections by up to 80 percent in some demographic groups
    • with virtually no one knowing they had been manipulated.
    • stats end
    • Worse still, the few people who had noticed that we were showing them biased search results
    • generally shifted even farther in the direction of the bias,
    • so being able to spot favoritism in search results is no protection against it.
    • stats begin
    • Google’s search engine 
      • with or without any deliberate planning by Google employees 
    • was currently determining the outcomes of upwards of 25 percent of the world’s national elections.
    • This is because Google’s search engine lacks an equal-time rule,
      • so it virtually always favors one candidate over another, and that in turn shifts the preferences of undecided voters.
    • Because many elections are very close, shifting the preferences of undecided voters can easily tip the outcome.
    • stats end

We applied two scenarios to compare how these regular agents behave in the Twitter network, with and without malicious agents, to study how much influence malicious agents have on the general susceptibility of the regular users. To achieve this, we implemented a belief value system to measure how impressionable an agent is when encountering misinformation and how its behavior gets affected. The results indicated similar outcomes in the two scenarios as the affected belief value changed for these regular agents, exhibiting belief in the misinformation. Although the change in belief value occurred slowly, it had a profound effect when the malicious agents were present, as many more regular agents started believing in misinformation.

Smith, B. (2021, November 29). Inside the ‘Misinformation’ Wars. The New York Times. https://www.nytimes.com/2021/11/28/business/media-misinformation-disinformation.html

Chang, H.-C. H., Chen, E., Zhang, M., Muric, G., & Ferrara, E. (2021). Social Bots and Social Media Manipulation in 2020: The Year in Review. ArXiv:2102.08436 [Cs]. http://arxiv.org/abs/2102.08436

Yang, K.-C., Pierri, F., Hui, P.-M., Axelrod, D., Torres-Lugo, C., Bryden, J., & Menczer, F. (2020). The COVID-19 Infodemic: Twitter versus Facebook. ArXiv:2012.09353 [Cs]. http://arxiv.org/abs/2012.09353

Identifying social media manipulation with OSoMe tools. (2020, August 11). https://www.youtube.com/watch?v=1BMv0PrdVGs&feature=youtu.be

Journal of Computational Social Science. Springer. Retrieved June 10, 2020, from https://www.springer.com/journal/42001/updates/17993070

Haelle, T. (2020, May 8). Why It’s Important To Push Back On ‘Plandemic’—And How To Do It. Forbes. https://www.forbes.com/sites/tarahaelle/2020/05/08/why-its-important-to-push-back-on-plandemic-and-how-to-do-it/