5 Matching Annotations
- Aug 2023
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www.pewresearch.org www.pewresearch.org
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The big tech companies, left to their own devices (so to speak), 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
- 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.
- Epstein's organization is building two technologies that assist in combating these problems:
- reference
- seminar paper on monitoring systems, ‘Taming Big Tech -: https://is.gd/K4caTW.
Tags
- search engine bias
- quote - tilting elections
- progress trap - social media
- quote - mind control
- progress trap
- progress trap - Google
- quote - progress trap
- SEME
- quote -search engine manipulation effect
- quote - election bias
- search engine manipulation effect
- quote
- progress trap - digital technology
- quote - Robert Epstein
- progress trap - search engine
- quote SEME
Annotators
URL
-
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hackernoon.com hackernoon.com
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- 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.
-
In our early experiments, reported by The Washington Post in March 2013, 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.
- 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,
- 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
-
he Search Suggestion Effect (SSE), the Answer Bot Effect (ABE), the Targeted Messaging Effect (TME), and the Opinion Matching Effect (OME), among others. Effects like these might now be impacting the opinions, beliefs, attitudes, decisions, purchases and voting preferences of more than two billion people every day.
- for: search engine bias, google privacy, orwellian, privacy protection, mind control, google bias
- title: Taming Big Tech: The Case for Monitoring
- date: May 14th 2018
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author: Robert Epstein
-
quote
- paraphrase:
- types of search engine bias
- the Search Suggestion Effect (SSE),
- the Answer Bot Effect (ABE),
- the Targeted Messaging Effect (TME), and
- the Opinion Matching Effect (OME), among others. -
- Effects like these might now be impacting the
- opinions,
- beliefs,
- attitudes,
- decisions,
- purchases and
- voting preferences
- of more than two billion people every day.
- types of search engine bias
Tags
- Robert Epstein
- search engine bias
- democracy - search engine bias
- Google bias
- voting - search engine bias
- voting
- stats - tilting elections
- quote - monitoring big tech
- democracy - social media
- PNAS SEME study
- elections - bias
- SEME
- mind control
- search engine manipulation effect
- quote
- orwellian
- quote - Robert Epstein
- voting - social media
- elections - interference
- Washington Post story - search engine bias
- stats
- quote - search engine bias
Annotators
URL
-
- May 2015
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research.microsoft.com research.microsoft.com
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That is, the human annotators are likely to assign different relevance labels to a document, depending on the quality of the last document they had judged for the same query. In addi- tion to manually assigned labels, we further show that the implicit relevance labels inferred from click logs can also be affected by an- choring bias. Our experiments over the query logs of a commercial search engine suggested that searchers’ interaction with a document can be highly affected by the documents visited immediately be- forehand.
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