Characterizations of Data and Data Science
Readings on how to characterize data, data science, artificial intelligence, and data science ethics.
Interactions with World
Producing Objects
Processing Objects as Data
Ordering Data as Models to Represent the World
Interpreting Models as Knowledge
| Title | Citation |
|---|---|
| Data and Society: A Critical Introduction | Beaulieu & Leonelli (2021) |
| Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon | Boyd & Crawford (2012) |
| What Distinguishes Data from Models? | Leonelli (2019) |
| Raw Data is an Oxymoron (Introduction) | Gitelman (2013) |
| On Being a Data Skeptic | O’Neil (2013) |
| The Epistemological Foundations of Data Science: A Critical Review | Desai, Watson, Wang, Taddeo, & Floridi (2022) |
| Artificial Intelligence: A Guide for Thinking Humans (Chapter 1) | Mitchell (2020) |
| The Invention of Ethical AI: How Big Tech Manipulates Academia to Avoid Regulation | Ochigame (2019) |
| Digital Ethics as Translational Ethics | Danks (2022) |
| The Trouble with Algorithmic Decisions: An Analytic Road Map to Examine Efficiency and Fairness in Automated and Opaque Decision Making | Zarsky (2016) |
| What is Computer Ethics? | Moor (1985) |
| What is Data Ethics? | Floridi & Taddeo (2016) |
References
Beaulieu, A., & Leonelli, S. (2021). Data and society: A critical introduction (First). SAGE Publications Ltd.
Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15, 662–679.
Danks, D. (2022). Digital ethics as translational ethics. https://doi.org/10.4018/978-1-7998-8467-5.ch001
Desai, J., Watson, D., Wang, V., Taddeo, M., & Floridi, L. (2022). The epistemological foundations of data science: A critical review. Synthese, 200. https://doi.org/10.1007/s11229-022-03933-2
Floridi, L., & Taddeo, M. (2016). What is data ethics? Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences, 374, 20160360. https://doi.org/10.1098/rsta.2016.0360
Gitelman, L. (Ed.). (2013). "Raw data" is an oxymoron. London, England: MIT Press.
Leonelli, S. (2019). What distinguishes data from models? European Journal for Philosophy of Science, 9. https://doi.org/10.1007/s13194-018-0246-0
Mitchell, M. (2020). Artificial intelligence: A guide for thinking humans. Picador.
Moor, J. H. (1985). What is computer ethics? Metaphilosophy, 16(4), 266–275. https://doi.org/10.1111/j.1467-9973.1985.tb00173.x
O’Neil, C. (2013). On being a data skeptic. O’Reilly Media.
Ochigame, R. (2019). How Big Tech manipulates academia to avoid regulation. https://theintercept.com/2019/12/20/mit-ethical-ai-artificial-intelligence/.
Zarsky, T. (2016). The trouble with algorithmic decisions: An analytic road map to examine efficiency and fairness in automated and opaque decision making. Science, Technology, and Human Values, 41(1), 118–132. https://doi.org/10.1177/0162243915605575