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What the hack? – Fostering diversity through tinkering with algorithms and digital tools

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Dan Verständig
Dan Verständig

What the hack? – Fostering diversity through tinkering with algorithms and digital tools - presented at the ECER 2018 in Bolzano

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Dan Verständig dan.verstaendig@ovgu.de @danvers What the hack? Fostering diversity through tinkering with algorithms and digital tools 4th September 2018 – ECER 2018, Bolzano
Starting with a brief overview on diversity and algorithmic systems, to clarify essential terms and the conceptual framework. Diversity Conceptual framing What are the specific characteristics of algorithmic bias and how to address it in the context of education and diversity. Digital Diversity Diversity and algorithmic bias 3 Proposals on how to address algorithmic bias in order to foster diversity in a digital world. Conclusion and discussion on expectations as well as limitations. Finding a path Looking into black boxes
Diversity
Jason Brown
RAFFI YOUREDJIAN
REUTERS/Konstantin Chernichkin
CityofStPete
Sozialhelden
Matt Johnson
Paco Gómez Amich
Sozialhelden
Johnny Silvercloud
Digital Diversity Christian Colen
What the hack? – Fostering diversity through tinkering with algorithms and digital tools
“When we realize that we are not talking about algorithms in the technical sense, but rather algorithmic systems of which code is only a part, their defining features reverse: instead of formality, rigidity, and consistency, we find flux, revisability, and negotiation.” - Seaver 2014 -
bias algorithmic
Vic.
Preexisting sparkleice
Technical James Stuart
Emerging Japanexpertana.se
What the hack? – Fostering diversity through tinkering with algorithms and digital tools
https://twitter.com/seyyedreza/status/935291317252493312/
Implementing values?
pulp stem Rippled surface
Finding a path ais3n
Friedman & Nissenbaum (1996, p. 334) https://dl.acm.org/citation.cfm?id=230561
#1 awareness
1. What values do digital tools and algorithmic architectures embody? 2. Do algorithmic architectures unfairly discriminate against specific individuals or groups? 3. Is there any transparency on the values embodied?
Bolukbasi, Chang, Zou, Saligrama & Kalai (2016) https://arxiv.org/abs/1607.06520
#2 auditing
GotCredit
#3 collaboration
Adapted Assets (Icons, Hints, Imagery) Maps Layer (OpenStreetMap, GoogleMaps) Adapted Layer (Addons, Third-Party Data) Build on given tools
findwheelchairaccessibleplaces
Luis Perez
Where to go? markusspiske
Dan Verständig dan.verstaendig@ovgu.de @danvers https://pixelspace.org danverstaendig Thank you.
• boyd, d. (2017). “Did Media Literacy Backfire?”. Journal of Applied Youth Studies 1(4). • Bolukbasi, T.; Chang, K.-W.; Zou James Y.; Saligrama V. and Kalai A. (2016). Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. http://arxiv.org/abs/1607.06520. • Eubanks, V. (2018). Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York: St. Martin's Press. • Friedman, B. & Nissenbaum, H. (1996). „Bias in computer systems“. In: ACM Transactions on Information Systems 14.3, S. 330–347. • Kitchin, R., Dodge M. (2014). Code/Space: Software and Everyday Life (Software Studies). Cambridge, Mass und London, England: MIT Press. • Nissenbaum, H. (2001). How computer systems embody values. Computer, 34(3), 120-119. • O’Neal, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Crown Publishing. • Sandvig, C., Hamilton, K., Karahalios, K., & Langbort, C. (2014). Auditing algorithms: Research methods for detecting discrimination on internet platforms. Data and discrimination: converting critical concerns into productive inquiry, 1-23. • Seaver, N. (2014). Knowing Algorithms. working paper on the issues that outsiders face in knowing things about algorithms, delivered at Media in Transition 8 • Seaver, N. (2017). Algorithms as culture: Some tactics for the ethnography of algorithmic systems. Big Data & Society, 4(2), 2053951717738104. • Stalder, F. (2018). The digital condition. Cambridge, UK; Medford, MA, USA: Polity Press. • Verständig, D. and Biermann, R. (in press). Zwischen Bias und Diversität – Bildung und Diversity im Kontext algorithmischer Strukturen. In Kergel, D. and Heidkamp, B. Digital Diversity und Bildung: Wiesbaden: Springer VS. • Verständig, D. (2017). Bildung und Öffentlichkeit – Eine strukturtheoretische Perspektive auf Bildung im Horizont digitaler Medialität. Magdeburg: Universität, Diss. References
Images ݺߣ Author 4 Jason Brown https://flic.kr/p/e62U9Z 5 RAFFI YOUREDJIAN https://flic.kr/p/dkA4Nk 6 REUTERS/Konstantin Chernichkin 7 CityofStPete https://flic.kr/p/vsqtN5 8 Sozialhelden https://flic.kr/p/mU67DV 9 Matt Johnson https://flic.kr/p/CwCifH 10 Paco Gómez Amich https://flic.kr/p/ftaFMS 11 Sozialhelden https://flic.kr/p/r58JKm 12 Johnny Silvercloud https://flic.kr/p/pMhL7J 13,14,16 Christiaan Colen https://flic.kr/p/x9G5bQ 17 Vic. https://flic.kr/p/cARSkU 18 sparkleice https://flic.kr/p/of4zFN 19 James Stuart https://flic.kr/p/UpMthm 20 Japanexperterna.se https://flic.kr/p/sBTNY4 26 ais3n https://flic.kr/p/eYvAVP 31 GotCredit https://flic.kr/p/TcaZyN 35 Luis Perez https://flic.kr/p/YkH4R8 36 markusspiske https://pixabay.com/en/fog-road-highway-tar-1819147/

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What the hack? – Fostering diversity through tinkering with algorithms and digital tools

  • 1. Dan Verständig dan.verstaendig@ovgu.de @danvers What the hack? Fostering diversity through tinkering with algorithms and digital tools 4th September 2018 – ECER 2018, Bolzano
  • 2. Starting with a brief overview on diversity and algorithmic systems, to clarify essential terms and the conceptual framework. Diversity Conceptual framing What are the specific characteristics of algorithmic bias and how to address it in the context of education and diversity. Digital Diversity Diversity and algorithmic bias 3 Proposals on how to address algorithmic bias in order to foster diversity in a digital world. Conclusion and discussion on expectations as well as limitations. Finding a path Looking into black boxes
  • 15. “When we realize that we are not talking about algorithms in the technical sense, but rather algorithmic systems of which code is only a part, their defining features reverse: instead of formality, rigidity, and consistency, we find flux, revisability, and negotiation.” - Seaver 2014 -
  • 17. Vic.
  • 28. 1. What values do digital tools and algorithmic architectures embody? 2. Do algorithmic architectures unfairly discriminate against specific individuals or groups? 3. Is there any transparency on the values embodied?
  • 33. Adapted Assets (Icons, Hints, Imagery) Maps Layer (OpenStreetMap, GoogleMaps) Adapted Layer (Addons, Third-Party Data) Build on given tools
  • 38. • boyd, d. (2017). “Did Media Literacy Backfire?”. Journal of Applied Youth Studies 1(4). • Bolukbasi, T.; Chang, K.-W.; Zou James Y.; Saligrama V. and Kalai A. (2016). Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. http://arxiv.org/abs/1607.06520. • Eubanks, V. (2018). Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York: St. Martin's Press. • Friedman, B. & Nissenbaum, H. (1996). „Bias in computer systems“. In: ACM Transactions on Information Systems 14.3, S. 330–347. • Kitchin, R., Dodge M. (2014). Code/Space: Software and Everyday Life (Software Studies). Cambridge, Mass und London, England: MIT Press. • Nissenbaum, H. (2001). How computer systems embody values. Computer, 34(3), 120-119. • O’Neal, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Crown Publishing. • Sandvig, C., Hamilton, K., Karahalios, K., & Langbort, C. (2014). Auditing algorithms: Research methods for detecting discrimination on internet platforms. Data and discrimination: converting critical concerns into productive inquiry, 1-23. • Seaver, N. (2014). Knowing Algorithms. working paper on the issues that outsiders face in knowing things about algorithms, delivered at Media in Transition 8 • Seaver, N. (2017). Algorithms as culture: Some tactics for the ethnography of algorithmic systems. Big Data & Society, 4(2), 2053951717738104. • Stalder, F. (2018). The digital condition. Cambridge, UK; Medford, MA, USA: Polity Press. • Verständig, D. and Biermann, R. (in press). Zwischen Bias und Diversität – Bildung und Diversity im Kontext algorithmischer Strukturen. In Kergel, D. and Heidkamp, B. Digital Diversity und Bildung: Wiesbaden: Springer VS. • Verständig, D. (2017). Bildung und Öffentlichkeit – Eine strukturtheoretische Perspektive auf Bildung im Horizont digitaler Medialität. Magdeburg: Universität, Diss. References
  • 39. Images ݺߣ Author 4 Jason Brown https://flic.kr/p/e62U9Z 5 RAFFI YOUREDJIAN https://flic.kr/p/dkA4Nk 6 REUTERS/Konstantin Chernichkin 7 CityofStPete https://flic.kr/p/vsqtN5 8 Sozialhelden https://flic.kr/p/mU67DV 9 Matt Johnson https://flic.kr/p/CwCifH 10 Paco Gómez Amich https://flic.kr/p/ftaFMS 11 Sozialhelden https://flic.kr/p/r58JKm 12 Johnny Silvercloud https://flic.kr/p/pMhL7J 13,14,16 Christiaan Colen https://flic.kr/p/x9G5bQ 17 Vic. https://flic.kr/p/cARSkU 18 sparkleice https://flic.kr/p/of4zFN 19 James Stuart https://flic.kr/p/UpMthm 20 Japanexperterna.se https://flic.kr/p/sBTNY4 26 ais3n https://flic.kr/p/eYvAVP 31 GotCredit https://flic.kr/p/TcaZyN 35 Luis Perez https://flic.kr/p/YkH4R8 36 markusspiske https://pixabay.com/en/fog-road-highway-tar-1819147/