Responsibility
Readings concerning moral responsibility in data science as well as some of the challenges in assessing who is morally responsible for data models and predictions.
Interactions with World
Producing Objects
Processing Objects as Data
Ordering Data as Models to Represent the World
Interpreting Models as Knowledge
| Title | Citation |
|---|---|
| Computing and Moral Responsibility | Noorman (2023) |
| Critical Questions for Big Data | Boyd & Crawford (2012) |
| Data, Responsibly | Abiteboul & Stoyanovich (2015) |
| Data Science as Political Action: Grounding Data Science in a Politics of Justice | Green (2020) |
| Thinking Responsibly about Responsible AI and ‘the Dark Side’ of AI | Mikalef, Conboy, Lundström, & Popovič (2022) |
| Locating Ethics in Data Science: Responsibility and Accountability in Global and Distributed Knowledge Production Systems | Leonelli (2016) |
| Deep Learning Meets Deep Democracy: Deliberative Governance and Responsible Innovation in Artificial Intelligence | Buhmann & Fieseler (2022) |
| Killer Robots | Sparrow (2007) |
| Amazon scraps secret AI recruiting tool that showed bias against women | Dastin (2018) |
| 70,000 OkCupid Profiles Leaked, Intimate Details and All | Woollacott (2016) |
| Automated Anti-Blackness: Facial Recognition in Brooklyn, New York | Nkonde (2020) |
| Facial Recognition Technology: The need for Public Regulation and Corporate Responsibility | Smith (2018) |
| Cultivating Moral Attention: A Virtue-Oriented Approach to Responsible Data Science in Healthcare | Ratti & Graves (2021) |
References
Abiteboul, S., & Stoyanovich, J. (2015). Data, Responsibly; ACM SIGMOD Blog. http://wp.sigmod.org/?p=1900.
Boyd, D., & Crawford, K. (2012). CRITICAL QUESTIONS FOR BIG DATA: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication &Amp; Society, 15(5), 662–679. https://doi.org/10.1080/1369118x.2012.678878
Buhmann, A., & Fieseler, C. (2022). Deep learning meets deep democracy: Deliberative governance and responsible innovation in artificial intelligence. Business Ethics Quarterly, 33(1), 146–179. https://doi.org/10.1017/beq.2021.42
Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight-idUSKCN1MK08G; Reuters.
Green, B. (2020). Data science as political action: Grounding data science in a politics of justice. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3658431
Leonelli, S. (2016). Locating ethics in data science: Responsibility and accountability in global and distributed knowledge production systems. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2083), 20160122. https://doi.org/10.1098/rsta.2016.0122
Mikalef, P., Conboy, K., Lundström, J. E., & Popovič, A. (2022). Thinking responsibly about responsible AI and “the dark side” of AI. European Journal of Information Systems, 31(3), 257–268. https://doi.org/10.1080/0960085x.2022.2026621
Nkonde, M. (2020). Automated anti-blackness facial recognition in brooklyn, new york. Harvard Kennedy School Journal of African American Policy 2019-2020, 30–36.
Noorman, M. (2023). Computing and Moral Responsibility. In E. N. Zalta & U. Nodelman (Eds.), The Stanford encyclopedia of philosophy (Spring 2023). https://plato.stanford.edu/archives/spr2023/entries/computing-responsibility/; Metaphysics Research Lab, Stanford University.
Ratti, E., & Graves, M. (2021). Cultivating moral attention: A virtue-oriented approach to responsible data science in healthcare. Philosophy and Technology, 34(4), 1819–1846. https://doi.org/10.1007/s13347-021-00490-3
Smith, B. (2018). Facial recognition technology: The need for public regulation and corporate responsibility. https://blogs.microsoft.com/on-the-issues/2018/07/13/facial-recognition-technology-the-need-for-public-regulation-and-corporate-responsibility/.
Sparrow, R. (2007). Killer robots. Journal of Applied Philosophy, 24(1), 62–77. https://doi.org/10.1111/j.1468-5930.2007.00346.x
Woollacott, E. (2016). 70,000 OkCupid profiles leaked, intimate details and all. https://www.forbes.com/sites/emmawoollacott/2016/05/13/intimate-data-of-70000-okcupid-users-released/?sh=2ac42f2f1e15; Forbes.