7 things we’ve learned about computer algorithmsAlgorithms are all around us, using massive stores of data and complex analytics to make decisions with often significant impacts on humans – from choosing the content people see on social media to judging whether a person is a good credit risk or job candidate. Pew Research Center released several reports in 2018 that explored the role and meaning of algorithms in people’s lives today. Here are some of the key themes that emerged from that research.
AI Now InstituteThe AI Now Institute at New York University is an interdisciplinary research center dedicated to understanding the social implications of artificial intelligence.
Code-Dependent: Pros and Cons of the Algorithm AgeAlgorithms are aimed at optimizing everything. They can save lives, make things easier and conquer chaos. Still, experts worry they can also put too much control in the hands of corporations and governments, perpetuate bias, create filter bubbles, cut choices, creativity and serendipity, and could result in greater unemployment
Data & SocietyData & Society studies the social implications of data-centric technologies & automation.
The Gender Shades ProjectGender Shades is a preliminary excavation of the inadvertent negligence that will cripple the age of automation and further exacerbate inequality if left to fester. The deeper we dig, the more remnants of bias we will find in our technology. We cannot afford to look away this time, because the stakes are simply too high. We risk losing the gains made with the civil rights movement and women's movement under the false assumption of machine neutrality. Automated systems are not inherently neutral. They reflect the priorities, preferences, and prejudices—the coded gaze—of those who have the power to mold artificial intelligence.
Rainie, Lee and Janna Anderson, “Code-Dependent: Pros and Cons of the Algorithm Age. Pew Research
Center, February 2017. PDF: https://www.pewresearch.org/internet/wp-content/uploads/sites/9/2017/02/PI_2017.02.08_Algorithms_FINAL.pdf
Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447–453. https://doi.org/10.1126/science.aax2342
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society. https://doi.org/10.1177/2053951716679679
Just, N., & Latzer, M. (2016). Governance by algorithms: Reality construction by algorithmic selection on the Internet. Media, Culture & Society, 39(2), 238–258. https://doi.org/10.1177/0163443716643157
Granka, L. A. (2010). The Politics of Search: A Decade Retrospective. The Information Society, 26(5), 364–374. https://doi.org/10.1080/01972243.2010.511560
Gillespie, T. (2014). The Relevance of Algorithms. In T. Gillespie, P. Boczkowski, & K. Foot (Eds.), Media technologies: Essays on communication, materiality, and society (pp. 167–194). MIT Press.
Knowlton, S. A. (2005). Three Decades Since Prejudices and Antipathies: A Study of Changes in the Library of Congress Subject Headings. Cataloging & Classification Quarterly, 40(2), 123–145. https://doi.org/10.1300/J104v40n02_08