Discrimination in Online Ad Delivery / Latanya Sweeney

A Google search for a person’s name, such as “Trevon Jones”, may yield a personalized ad for public records about Trevon that may be neutral, such as “Looking for Trevon Jones?”, or may be suggestive of an arrest record, such as “Trevon Jones, Arrested?”. This writing investigates the delivery of these kinds of ads by Google AdSense using a sample of racially associated names and finds statistically significant discrimination in ad delivery based on searches of 2184 racially associated personal names across two websites. First names, assigned at birth to more black or white babies, are found predictive of race (88% black, 96% white), and those assigned primarily to black babies, such as DeShawn, Darnell and Jermaine, generated ads suggestive of an arrest in 81 to 86 percent of name searches on one website and 92 to 95 percent on the other, while those assigned at birth primarily to whites, such as Geoffrey, Jill and Emma, generated more neutral copy: the word “arrest” appeared in 23 to 29 percent of name searches on one site and 0 to 60 percent on the other. On the more ad trafficked website, a black-identifying name was 25% more likely to get an ad suggestive of an arrest record. A few names did not follow these patterns. All ads return results for actual individuals and ads appear regardless of whether the name has an arrest record in the company’s database. The company maintains Google received the same ad text for groups of last names (not first names), raising questions as to whether Google’s technology exposes racial bias.

Sweeney, L. (2013). Discrimination in Online Ad Delivery. Communications of the ACM, 56(5), 44–54. arXiv.org version available online.

digitization: just because you can, doesn’t mean you should / Tara Robertson

In this blog post, Robertson takes a critical look at Reveal Digital’s work to digitize On Our Backs (OOB), a lesbian feminist porn magazine that ran from 1984-2004. She points out that there are ethical issues with digitizing and making print collections like OOB available online and that Reveal Digital needs more robust ethical guidelines and take-down policies. Robertson also emphasizes the importance of working with people who were featured in OOB and appear in the collection, citing their right to be forgotten.

1341761 {1341761:RHFDFY2G} 1 chicago-author-date 50 default 567 https://des4div.library.northeastern.edu/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22RHFDFY2G%22%2C%22library%22%3A%7B%22id%22%3A1341761%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A5159224%2C%22username%22%3A%22nancyloi%22%2C%22name%22%3A%22%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Fnancyloi%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Robertson%22%2C%22parsedDate%22%3A%222016-03-20%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BRobertson%2C%20Tara.%202016.%20%26%23x201C%3BDigitization%3A%20Just%20Because%20You%20Can%2C%20Doesn%26%23x2019%3Bt%20Mean%20You%20Should.%26%23x201D%3B%20%26lt%3Bi%26gt%3BTara%20Robertson%26lt%3B%5C%2Fi%26gt%3B%2C%20March%2020.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttp%3A%5C%2F%5C%2Ftararobertson.ca%5C%2F2016%5C%2Foob%5C%2F%26%23039%3B%26gt%3Bhttp%3A%5C%2F%5C%2Ftararobertson.ca%5C%2F2016%5C%2Foob%5C%2F%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22blogPost%22%2C%22title%22%3A%22digitization%3A%20just%20because%20you%20can%2C%20doesn%5Cu2019t%20mean%20you%20should%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Tara%22%2C%22lastName%22%3A%22Robertson%22%7D%5D%2C%22abstractNote%22%3A%22I%20learned%20this%20week%20that%20Reveal%20Digital%20has%20digitized%20On%20Our%20Backs%20%28OOB%29%2C%20a%20lesbian%20porn%20magazine%20that%20ran%20from%201984-2004.%20This%20is%20a%20part%20of%20the%20Independent%20Voices%20collection%20that%20%5Cu201cchronicles%5Cu2026%22%2C%22blogTitle%22%3A%22tara%20robertson%22%2C%22date%22%3A%222016-03-20T17%3A44%3A57%2B00%3A00%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Ftararobertson.ca%5C%2F2016%5C%2Foob%5C%2F%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222018-11-27T17%3A55%3A37Z%22%7D%7D%5D%7D
Robertson, Tara. 2016. “Digitization: Just Because You Can, Doesn’t Mean You Should.” Tara Robertson, March 20. http://tararobertson.ca/2016/oob/.

How We Analyzed the COMPAS Recidivism Algorithm / Mattu Larson and Angwin Kirchner

We set out to assess one of the commercial tools made by Northpointe, Inc. to discover the underlying accuracy of their recidivism algorithm and to test whether the algorithm was biased against certain groups.

1341761 {1341761:B3VQQBGS} 1 chicago-author-date 50 default 555 https://des4div.library.northeastern.edu/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%22B3VQQBGS%22%2C%22library%22%3A%7B%22id%22%3A1341761%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A787807%2C%22username%22%3A%22arrust123%22%2C%22name%22%3A%22Amanda%20Rust%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Farrust123%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Larson%20et%20al.%22%2C%22parsedDate%22%3A%222016-05-23%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BLarson%2C%20Jeff%2C%20Surya%20Mattu%2C%20Lauren%20Kirchner%2C%20and%20Julia%20Angwin.%202016.%20%26%23x201C%3BHow%20We%20Analyzed%20the%20COMPAS%20Recidivism%20Algorithm.%26%23x201D%3B%20%26lt%3Bi%26gt%3BProPublica%26lt%3B%5C%2Fi%26gt%3B%2C%20May%2023.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fwww.propublica.org%5C%2Farticle%5C%2Fhow-we-analyzed-the-compas-recidivism-algorithm%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fwww.propublica.org%5C%2Farticle%5C%2Fhow-we-analyzed-the-compas-recidivism-algorithm%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22blogPost%22%2C%22title%22%3A%22How%20We%20Analyzed%20the%20COMPAS%20Recidivism%20Algorithm%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Jeff%22%2C%22lastName%22%3A%22Larson%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Surya%22%2C%22lastName%22%3A%22Mattu%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Lauren%22%2C%22lastName%22%3A%22Kirchner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Julia%22%2C%22lastName%22%3A%22Angwin%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22blogTitle%22%3A%22ProPublica%22%2C%22date%22%3A%2205%5C%2F23%5C%2F2016%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.propublica.org%5C%2Farticle%5C%2Fhow-we-analyzed-the-compas-recidivism-algorithm%22%2C%22language%22%3A%22%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222018-09-27T10%3A58%3A30Z%22%7D%7D%5D%7D
Larson, Jeff, Surya Mattu, Lauren Kirchner, and Julia Angwin. 2016. “How We Analyzed the COMPAS Recidivism Algorithm.” ProPublica, May 23. https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm.

Critical technical practice as a methodology for values in design

Critical Technical Practice (CTP) is an approach to identifying and altering philosophical assumptions underlying technical practice. In this paper, we propose CTP as a useful method for developing value-sensitive design, complementing existing ethics-based approaches in HCI. CTP, originally proposed by Phil Agre, tightly binds technology development (as practiced in computer science) with critical reflection (as practiced in critical studies and design research), thereby uncovering and altering hidden values and assumptions in technology design. HCI, due to its interdisciplinary constitution and reflective nature, is a particularly fruitful domain for critical technical practice. We demonstrate through four case studies how critical technical practice supports the identification of values underlying design as well as the development of concrete technical alternatives.

Boehner, K., David, S., Kaye, J., & Sengers, P. (2005). Critical technical practice as a methodology for values in design. In CHI 2005 Workshop on quality, values, and choices.

Machine Reading the Primeros Libros / Hannah Alpert-Adams

By delving into the material processes of Optical Character Recognition (OCR), as well as the history of OCR tools, this article shows how the statistical models used for automatic transcription can embed cultural biases into the output. This article is particularly relevant to multilingual projects, as it unpacks the effects of OCR software that generally assumes monolingual and orhthographically simple documents.

“Early modern printed books pose particular challenges for automatic transcription: uneven inking, irregular orthographies, radically multilingual texts. As a result, modern efforts to transcribe these documents tend to produce the textual gibberish commonly known as “dirty OCR” (Optical Character Recognition). This noisy output is most frequently seen as a barrier to access for scholars interested in the computational analysis or digital display of transcribed documents. This article, however, proposes that a closer analysis of dirty OCR can reveal both historical and cultural factors at play in the practice of automatic transcription. To make this argument, it focuses on tools developed for the automatic transcription of the Primeros Libros collection of sixteenth century Mexican printed books. By bringing together the history of the collection with that of the OCR tool, it illustrates how the colonial history of these documents is embedded in, and transformed by, the statistical models used for automatic transcription. It argues that automatic transcription, itself a mechanical and practical tool, also has an interpretive effect on transcribed texts that can have practical consequences for scholarly work.”

1341761 {1341761:7VLWCZ8G} 1 chicago-author-date 50 default 537 https://des4div.library.northeastern.edu/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%227VLWCZ8G%22%2C%22library%22%3A%7B%22id%22%3A1341761%7D%2C%22meta%22%3A%7B%22lastModifiedByUser%22%3A%7B%22id%22%3A787807%2C%22username%22%3A%22arrust123%22%2C%22name%22%3A%22Amanda%20Rust%22%2C%22links%22%3A%7B%22alternate%22%3A%7B%22href%22%3A%22https%3A%5C%2F%5C%2Fwww.zotero.org%5C%2Farrust123%22%2C%22type%22%3A%22text%5C%2Fhtml%22%7D%7D%7D%2C%22creatorSummary%22%3A%22Alpert-Abrams%22%2C%22parsedDate%22%3A%222016%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%201.35%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAlpert-Abrams%2C%20Hannah.%202016.%20%26%23x201C%3BMachine%20Reading%20the%20Primeros%20Libros.%26%23x201D%3B%20%26lt%3Bi%26gt%3BDigital%20Humanities%20Quarterly%26lt%3B%5C%2Fi%26gt%3B%2010%20%284%29.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-ItemURL%26%23039%3B%20href%3D%26%23039%3Bhttp%3A%5C%2F%5C%2Fwww.digitalhumanities.org%5C%2Fdhq%5C%2Fvol%5C%2F10%5C%2F4%5C%2F000268%5C%2F000268.html%26%23039%3B%26gt%3Bhttp%3A%5C%2F%5C%2Fwww.digitalhumanities.org%5C%2Fdhq%5C%2Fvol%5C%2F10%5C%2F4%5C%2F000268%5C%2F000268.html%26lt%3B%5C%2Fa%26gt%3B.%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Machine%20Reading%20the%20Primeros%20Libros%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hannah%22%2C%22lastName%22%3A%22Alpert-Abrams%22%7D%5D%2C%22abstractNote%22%3A%22Early%20modern%20printed%20books%20pose%20particular%20challenges%20for%20automatic%20transcription%3A%20uneven%20inking%2C%20irregular%20orthographies%2C%20radically%20multilingual%20texts.%20As%20a%20result%2C%20modern%20efforts%20to%20transcribe%20these%20documents%20tend%20to%20produce%20the%20textual%20gibberish%20commonly%20known%20as%20%26quot%3Bdirty%20OCR%26quot%3B%20%28Optical%20Character%20Recognition%29.%20This%20noisy%20output%20is%20most%20frequently%20seen%20as%20a%20barrier%20to%20access%20for%20scholars%20interested%20in%20the%20computational%20analysis%20or%20digital%20display%20of%20transcribed%20documents.%20This%20article%2C%20however%2C%20proposes%20that%20a%20closer%20analysis%20of%20dirty%20OCR%20can%20reveal%20both%20historical%20and%20cultural%20factors%20at%20play%20in%20the%20practice%20of%20automatic%20transcription.%20To%20make%20this%20argument%2C%20it%20focuses%20on%20tools%20developed%20for%20the%20automatic%20transcription%20of%20the%20Primeros%20Libros%20collection%20of%20sixteenth%20century%20Mexican%20printed%20books.%20By%20bringing%20together%20the%20history%20of%20the%20collection%20with%20that%20of%20the%20OCR%20tool%2C%20it%20illustrates%20how%20the%20colonial%20history%20of%20these%20documents%20is%20embedded%20in%2C%20and%20transformed%20by%2C%20the%20statistical%20models%20used%20for%20automatic%20transcription.%20It%20argues%20that%20automatic%20transcription%2C%20itself%20a%20mechanical%20and%20practical%20tool%2C%20also%20has%20an%20interpretive%20effect%20on%20transcribed%20texts%20that%20can%20have%20practical%20consequences%20for%20scholarly%20work.%22%2C%22date%22%3A%222016%22%2C%22language%22%3A%22%22%2C%22DOI%22%3A%22%22%2C%22ISSN%22%3A%22%22%2C%22url%22%3A%22http%3A%5C%2F%5C%2Fwww.digitalhumanities.org%5C%2Fdhq%5C%2Fvol%5C%2F10%5C%2F4%5C%2F000268%5C%2F000268.html%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222018-09-27T10%3A58%3A45Z%22%7D%7D%5D%7D
Alpert-Abrams, Hannah. 2016. “Machine Reading the Primeros Libros.” Digital Humanities Quarterly 10 (4). http://www.digitalhumanities.org/dhq/vol/10/4/000268/000268.html.