Category:Protocols and Algorithms

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New section, created July 2017: how do protocols and algorithms increasingly govern our world, for good or ill; and how we can change it, for example through Design Justice


Anouk Ruhaak:

"Many of the new data governance models being pioneered today rely on some notion of collective governance and consent.

These include

  1. Data Trust (where trustees govern data rights on behalf of a group of beneficiaries),
  2. Data Commons (where data is governed as a commons),
  3. Data Cooperatives (where data is governed by the members of the coop) and consent champions (where individuals defer some of their data sharing decisions to a trusted institution)."



"We need to ask then not only how algorithmic automation works today (mainly in terms of control and monetization, feeding the debt economy) but also what kind of time and energy it subsumes and how it might be made to work once taken up by different social and political assemblages—autonomous ones not subsumed by or subjected to the capitalist drive to accumulation and exploitation."

- Tiziana Terranova [1]

Anjana Susarla on the New Algorithmic Divide

"Many people now trust platforms and algorithms more than their own governments and civic society. An October 2018 study suggested that people demonstrate “algorithm appreciation,” to the extent that they would rely on advice more when they think it is from an algorithm than from a human. In the past, technology experts have worried about a “digital divide” between those who could access computers and the internet and those who could not. Households with less access to digital technologies are at a disadvantage in their ability to earn money and accumulate skills. But, as digital devices proliferate, the divide is no longer just about access. How do people deal with information overload and the plethora of algorithmic decisions that permeate every aspect of their lives? The savvier users are navigating away from devices and becoming aware about how algorithms affect their lives. Meanwhile, consumers who have less information are relying even more on algorithms to guide their decisions." {

Privacy is a Public Good

"How do we manage consent when data shared by one affects many? Take the case of DNA data. Should the decision to share data that reveals sensitive information about your family members be solely up to you? Shouldn’t they get a say as well? If so, how do you ask for consent from unborn future family members? How do we decide on data sharing and collection when the externalities of those decisions extend beyond the individual? What if data about me, a thirty-something year old hipster, could be used to reveal patterns about other thirty-something year old hipsters? Patterns that could result in them being profiled by insurers or landlords in ways they never consented to. How do we account for their privacy? The fact that one person’s decision about data sharing can affect the privacy of many motivates Fairfield and Engel to argue that privacy is a public good: “Individuals are vulnerable merely because others have been careless with their data. As a result, privacy protection requires group coordination. Failure of coordination means a failure of privacy. In short, privacy is a public good.” As with any other public good, privacy suffers from a free rider problem. As observed by the authors, when the benefits of disclosing data outweigh the risks for you personally, you are likely to share that data - even when doing so presents a much larger risk to society as a whole." - Anouk Ruhaak [2]

Key Resources

Key Articles

Key Books

  • Recursivity and Contingency. By Yuk Hui. Rowman & Littlefield International (2019)

[6]. Recommended by Bernard Stiegler: "Through a historical analysis of philosophy, computation and media, this book proposes a renewed relation between nature and technics." For details see: Towards a Renewed Relation Between Nature and Technics.

Pages in category "Protocols and Algorithms"

The following 141 pages are in this category, out of 141 total.