Lecture given October 18, 2018 | University of Edinburgh

1. EQUALITY AND
TECHNOLOGY:
CURRENT DEBATES
Dr. Karen Gregory
Lecturer in Digital Sociology
k.gregory@ed.ac.uk

2. Amazon HR:
■ Review the story about Amazon’s experimental hiring tool.
■ Based on your own expertise, what do you think went wrong
and why?
■ What could be done/could have been to correct for the gender
bias?
■ Discuss for ten minutes, take notes, and report back to the
class.

3. Algorithmic Bias Studies

4. Sociological Research Insights:
■ Technologies emerge and are developed and designed in social and
cultural contexts and geographies, as a result inequalities play a role.
■ Technology is human, made of human labor, social relations, flows of
money and investment interests.
■ Technology isn’t value neutral. More to the story than ”just math.”
■ Technology developments mirror social values or structural interests.
■ Using these insights, we can take a look at some current debates that are
taking place in and around the tech world.

5. Debate one: Context matters
Ojanperä, S., Graham, M., Straumann, R. K., De Sabbata, S., & Zook, M. (2017). Engagement in the knowledge economy: Regional patterns of content creation with a focus on sub-Saharan
Africa. Information Technologies & International Development, 13, 33–51.
http://geonet.oii.ox.ac.uk/blog/new-publication-engagement-in-the-knowledge-economy-regional-patterns-of-content-creation-with-a-focus-on-sub-saharan-africa/

6. ■ “To investigate the patterns of knowledge creation in the region
compared to other world regions, we examine three key metrics:
spatial distributions of academic articles (traditional knowledge
production), collaborative software development, and Internet
domain registrations (digitally mediated knowledge production).”
■ Digital divides: “Our results suggest the factors often framed as
catalysts in the transformation into a knowledge economy do not
relate to the three metrics uniformly.While connectivity is an
important enabler of digital content creation, it seems to be only
a necessary, not a sufficient, condition; wealth, innovation
capacity, and public spending on education are also important
factors.”

7. “You are not your user.”
Can one social demographic design
for a complex world?
Debate two:
People matter

8. Further reading:TheAthena Factor: Reversing the Brain Drain in Science, Engineering, and
Technology, 2008

9. Debate three:Technology has social
effects
IBM Commercial: Police Use Analytics to Reduce Crime
https://www.youtube.com/watch?v=imJ9symxCug

10. "We obtained the risk scores assigned to more than 7,000 people arrested in Broward
County, Florida, in 2013 and 2014 and checked to see how many were charged with new
crimes over the next two years.”
Significant racial disparities:
In forecasting who would re-offend, the algorithm made mistakes with black and white
defendants at roughly the same rate but in very different ways.
■ The formula was particularly likely to falsely flag black defendants as future criminals,
wrongly labeling them this way at almost twice the rate as white defendants.
■ White defendants were mislabeled as low risk more often than black defendants.”
Source: Machine Bias, Propublica, 2016: https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
When most defendants are booked in jail, they respond to a COMPAS questionnaire. Their answers are fed into the COMPAS
software to generate several scores including predictions of “Risk of Recidivism” and “Risk ofViolent Recidivism.” The COMPAS
questionnaire is here: https://www.documentcloud.org/documents/2702103-Sample-Risk-Assessment-COMPAS-CORE.html

11. Debate four:We see ourselves in our
technologies
■ The study suggests thatYelp reviews not only reflect the impacts and public perception of
gentrification, but ultimately help to determine who occupies a neighborhood as well. Indeed,
the study concludes that, “intentionally or not,Yelp restaurant reviewers may encourage,
confirm, or even accelerate processes of gentrification by signaling that a locality is good for
people who share their tastes.” Beyond persuading potential customers to visit a restaurant,
social media may in fact be part of the process of actually transforming neighborhoods.
Zukin, S., Lindeman, S. and Hurson, L. 2015. “The Omnivore’s Neighborhood: Online restaurant reviews, race, and gentrification.” Journal of
Consumer Culture.
■ SketchFactor:An app to allow users to report having seen or experienced something
“sketchy” in a particular location; these reports would then be geotagged and overlaid on a
Google map, creating a sketchiness heat map of a neighborhood or city.
Marantz, A. 2015. “When An App is Called Racist.”The NewYorker: http://www.newyorker.com/business/currency/what-to-do-when-your-
app-is-racist