NCompass Live - November 8, 2023 http://nlc.nebraska.gov/ncompasslive/ Many library users believe that when they use a search engine, they are always getting factual, unbiased, and objective results. But search engines and the algorithms that power them are not neutral. This session explores some of the racial and gender biases found in search and looks at how these biases impact search results. By examining the idea of search neutrality, we can gain a better understanding of how human beings influence, for better or worse, the creation and ongoing maintenance of search algorithms. Through examining bias in search, we can help our patrons improve their search and online information literacy. Presenter: Marcella Fredriksson, Web & Discovery Services Librarian, University of North Carolina Wilmington (UNCW). She received her BA from Boston University in 2002 and her MSLS from Catholic University in 2006. She has been at UNCW since 2016. Her research interests include improving the usability of library websites and the library search experience.

1. Racial and Gender Bias
in Search
NCompass Live
November 8, 2023
Marcella Fredriksson, Web & Discovery Services Librarian | UNC Wilmington
fredrikssonm@uncw.edu

2. Outline
● Some basic definitions
● Search neutrality
● What we believe about search
● Examples of bias
● Examples of bias in library discovery
● Conclusion

3. What is Bias?

4. Accessed 4/5/2022 from https://www.google.com/search?q=what+is+bias&rlz=1C1GCEA_enUS952US952&oq=what+is+bias&aqs=chrome.0.69i59.1648j0j1&sourceid=chrome&ie=UTF-8

5. Algorithms and
Mathematical Models

6. Accessed 4/5/2022 from https://www.merriam-webster.com/dictionary/algorithm

7. Accessed 2/27/2023 from https://www.britannica.com/science/algorithm

8. AI and Machine Learning

9. Accessed 3/7/2023 from https://cloud.google.com/learn/what-is-artificial-intelligence

10. Accessed 3/7/2023 from
https://www.google.com/search?q=machine+learning+definition&rlz=1CAOTWH_enUS862US862&oq=machine+learning+def&aqs=chrome.0.69i59j69i57.5046j0j1&sourceid=chrome&ie=UTF-8

11. The Idea of Search
Neutrality

12. Accessed 3/27/2023 at https://gs.statcounter.com/search-engine-market-share

13. Accessed 3/27/2023 from https://about.google/how-our-business-works/

14. Accessed 4/5/2022 from
https://www.google.com/search/howsearchworks/our-approach/ads-on-search/
Accessed 2/27/2023 from
https://www.google.com/search/howsearchworks/our-approach/ads-on-search/

15. Accessed 4/5/2022 from https://www.google.com/search/howsearchworks/our-approach/ads-on-search/

16. Accessed 2/27/2023 from https://www.google.com/search/howsearchworks/our-approach/

17. Accessed 4/5/2022 from https://www.google.com/search/howsearchworks/how-search-works/rigorous-testing/

18. Accessed 4/5/2022 from https://www.google.com/search/howsearchworks/how-search-works/ranking-results/

19. Accessed 4/5/2022 from https://www.google.com/search/howsearchworks/our-approach/maximize-access/

20. Accessed 2/27/2023 from https://www.google.com/search/howsearchworks/our-approach/maximize-access/

21. Accessed 2/27/2023 from https://support.google.com/websearch/answer/7368877#zippy=%2Chow-we-handle-issues-with-predictions

22. Accessed 4/5/2022 from https://support.google.com/websearch/answer/7368877#zippy=%2Cautocomplete-policies

23. Accessed 2/27/2023 from https://support.google.com/websearch/answer/7368877#zippy=%2Chow-we-handle-issues-with-predictions%2Cautocomplete-policies

24. What Do We Believe About
Search? How Do We Use
It?

25. Pew Research Center - Pew Internet & American Life Survey
In 2002:
● 52% of all Americans used search engines.
In 2012:
● 73% of all Americans used search engines
● 91% of search engine users say they always or most of the time find the information they are seeking when they
use search engines
● 73% of search engine users say that most or all the information they find as they use search engines is accurate
and trustworthy
● 66% of search engine users say search engines are a fair and unbiased source of information
● 55% of search engine users say that, in their experience, the quality of search results is getting better over time,
while just 4% say it has gotten worse
● 52% of search engine users say search engine results have gotten more relevant and useful over time, while just 7%
report that results have gotten less relevant
https://www.pewresearch.org/internet/2012/03/09/search-engine-use-2012/

26. Accessed 4/24/2022 from https://google.com and https://uncw.summon.serialssolutions.com/#!/

27. Pew Internet & American Life Survey, continued
We are confident in our search abilities:
“More than half of search users (56%) say they are very confident in their search abilities, while only 6% say they
are not too or not all confident. And the vast majority of search users report being able to find what they are
looking for always (29%) or most of the time (62%).”
Users said they had:
● learned something new or important that really helped them or increased their knowledge (86% of search
users have had this experience)
● found a really obscure fact or piece of information they thought they would not be able to find (50%)
● gotten conflicting information in search results and not been able to figure out what is correct (41%)
● gotten so much information in a set of results that you feel overwhelmed (38%)
● found that critical information is missing from search results (34%)

28. Accessed 2/27/2023 from https://www.pewresearch.org/fact-tank/2019/02/13/7-things-weve-learned-about-computer-algorithms/

29. Examples of Bias

30. Image from Goodreads.com at https://i.gr-assets.com/images/S/compressed.photo.goodreads.com/books/1519083351l/38212110._SY475_.jpg
2015: Google Photo’s autotagging feature tags
photos of two Black people as “gorillas”
● Neural networks
● Learning algorithm
● Historical data sets
● “Better recognition of dark-skinned faces”

31. Accessed 4/6/2022 from https://store.google.com/product/pixel_6?hl=en-US#p6-overview-camera

32. Accessed 7/11/2023 from https://www.nytimes.com/2023/05/22/technology/ai-photo-labels-google-apple.html

33. Image from Goodreads.com at https://images-na.ssl-images-amazon.com/images/S/compressed.photo.goodreads.com/books/1456091964i/28186015.jpg
U.S. News & World Report College Rankings
● Proxies
● Feedback Loop
● Scale

34. Accessed 3/2/2023 from https://www.chronicle.com/article/is-this-the-beginning-of-the-end-of-the-u-s-news-rankings-dominance

35. Image from Goodreads.com at https://images-na.ssl-images-amazon.com/images/S/compressed.photo.goodreads.com/books/1576795927i/42527493.jpg
● New Jim Code
● Just a glitch?
● Malcolm Ten Boulevard
● Three Black teenagers

36. Image from Goodreads.com at https://i.gr-assets.com/images/S/compressed.photo.goodreads.com/books/1492944248l/34762552.jpg
2005: Google publishes “An Explanation of
Our Search Results”
2012: Google includes a box with a link to
the explanation on the bottom of the search
results page for “Jew”
2022: No antisemitic search results are on
the first page of results for the same search.
The explanation page is not linked and no
longer accessible from the same URL.

37. Accessed 4/24/2022 from https://www.google.com/search?q=jew&rlz=1C1GCEA_enUS952US952&oq=jew&aqs=chrome.0.69i59j0i271l3.533j0j1&sourceid=chrome&ie=UTF-8

38. Accessed 3/17/2022

39. Accessed 2/27/2023 from https://www.wired.com/story/trans-researchers-want-google-scholar-to-stop-deadnaming-them/

40. Accessed 2/27/2023 from https://www.them.us/story/google-autocomplete-suggestions-transphobia-celebrities

41. Accessed 3/7/2023 from https://www.nist.gov/news-events/news/2022/03/theres-more-ai-bias-biased-data-nist-report-highlights

42. Accessed 3/7/2023 from https://www.npr.org/2023/03/02/1159895892/ai-microsoft-bing-chatbot

43. Examples of Bias in Library
Discovery Systems

44. Image from Goodreads.com at https://i.gr-assets.com/images/S/compressed.photo.goodreads.com/books/1559525198l/45899532.jpg
Summon Topic Explorer and EBSCO Discovery Service Research
Starter return factually incorrect and biased results.
● Donald Trump and Barack Obama
● Rape Culture and Rape Myths
● Muslim terrorist in the United States
● 9/11 vs. September 11 vs. September 11th

45. Conclusion

46. Accessed 4/24/2022 from https://www.cnet.com/culture/apple-google-and-other-tech-companies-work-together-in-diversity-push/

47. References and Resources
Benjamin, R. (2019) Race After Technology: Abolitionist Tools for the New Jim Code. Polity
Press.
Kantayya, S. (Director). (2020). Coded Bias [Film]. 7th Empire Media.
Noble, S.U. (2018) Algorithms of Oppression: How Search Engines Reinforce Racism. New
York University Press.
O’Neil, C. (2016) Weapons of Math Destruction: How Big Data Increases Inequality and
Threatens Democracy. Crown.
Reidsma, M. (2019) Masked by Trust: Bias in Library Discovery. Litwin Books.
Wachter-Boettcher, S. (2018) Technically Wrong: Sexist Apps, Biased Algorithms, and Other
Threats of Toxic Tech. W.W. Norton & Company.

48. Questions?
Marcella Fredriksson
Web & Discovery Services Librarian
UNC Wilmington
fredrikssonm@uncw.edu