Module 2 •The Datafied self present and future

Authored by Javiera Atenas

This module is aimed at critically exploring some key issues around data that concern us not only individually, but also, at the collective level. How we analyse and interact with data, how data is shaping our society, which are the legal frameworks around uses of data and how we can challenge the uses that are given to our data are explored.

In the first unit, the basics of data ethics are probed. In the second unit, the fundamental principles that govern what is right and what is wrong in the data cycle, from collection and production to their use are considered. The concepts of data privacy pertaining to the regulations and laws about data opening, publishing, collection, storage and management are examined. In the third unit, critical approaches to AI and algorithms are reviewed. Issues, such as opacity and bias in algorithms, as well as regulations for automated decision and predictive analytics that are underpinned by and lead to power imbalances, thus constraining opportunities for participation, are discussed. Finally, the fourth unit is focused on personal agency, where the aim is to enable citizens to contest the uses of their data with the wherewithal to challenge the advancement of data power.

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Learning Outcomes

  1. Understanding the basics of Data Ethics and Data Protection
  2. Understanding how algorithms and AI work and their impact on society
  3. Understanding the concepts of data agency and data sovereignty
  4. Acquiring abilities to manage and challenge personal and collective sensitive data
  5. Learning to manage and navigate the social aspects of data
  6. Applying basic ethical principles in research projects

Introductory media

Introduction to data ethics, Brent Mittesstadt, Alan Turing Institute


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  • Artificial intelligence (AI) intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals.
  • Data Ethics refers to systemising, defending, and recommending concepts of right and wrong conduct in relation to data, in particular, personal data
  • Personal Data is any information relating to an identifiable person.
  • Data agency is the individual’s ability to influence and shape his/her life trajectory as determined by his/her cultural and social contexts. Agency in the digital arena enables an individual to make informed decisions, where his/her own terms and conditions can be recognised and acknowledged at an algorithmic level.
  • Negotiability is the means to navigate the social aspects of data, which supports interaction between other data subjects and their policies. This enables the ongoing engagement of users so that they can withdraw from data processing either completely or in part and can derive value from data harvesting for themselves.
  • Data sovereignty is the idea that data must be subject to the laws and governance structures within the nation in which it is collected. The concept of data sovereignty is closely linked with data security, cloud computing and technological sovereignty. Also, it can be understood as the relation between data and groups of vulnerable or minority groups, which must have agency and voice-over how their data is collected, shared and portrayed.
  • Data protection is the relationship between the collection and dissemination of data, technology, the public expectation of privacy, and the legal and political issues surrounding them. It is also known as data privacy
  • GDPR The General Data Protection Regulation is a regulation in EU law on data protection and privacy in the European Union (EU) and the European Economic Area (EEA). It also addresses the transfer of personal data outside the EU and EEA areas. The GDPR's primary aim is to give control to individuals over their personal data and to simplify the regulatory environment for international business by unifying the regulation within the EU
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Recommended Readings

  1. D’Ignazio, C & Klein, L. (2020) 6. The Numbers Don’t Speak for Themselves.
  2. Taylor, L. (2017). What is data justice? The case for connecting digital rights and freedoms globally. Big Data & Society, 4(2),
  3. Taddeo, M., & Floridi, L. (2016). What is data ethics ? Philosophical Transactions. Series A, 1–5.
  4. Markham, A. N., Tiidenberg, K., & Herman, A. (2018). Ethics as methods: doing ethics in the era of big data research -Introduction. Social Media and Society, 4(3)
  5. Bhargava, Rahul (2018). The algorithms aren’t biased, we are. Medium article
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Key Complementary Resources

  1. Counting the Countless
  2. How Data Can Map and Make Racial Inequality More Visible (If Done Responsibly)
  3. Data Science Ethics Podcast
  4. We need to talk AI, comic booklet
  5. Data Feminism. D’Ignazio and Klein
  6. Bhattacharya, Ananya. n.d. Racist tweeters can be convinced to stop spreading hate—If a white man asks them to. Quartz. Accessed 25 January 2019
  7. Deva, Surya. (2020), Addressing the gender bias in artificial intelligence and automation. OpenGlobalRights (blog). 10 April 2020
  8. Yeshi (2020), Data for Black Lives. We Will Not Allow the Weaponization of COVID-19 Data. Medium article
  9. Algorithm Watch’s, bi-weekly newsletter, presents a short summary of current events and research on automated decision-making and its consequences on society.