Academic Studies

This resource section has leant heavily on the "Platform companies and news media" section of the reading list curated by the Reuters Institute for the Study of Journalism at the University of Oxford.

The Council of Europe’s expert committee on human rights dimensions of automated data processing and different forms of artificial intelligence (MSI-AUT)

Under the supervision of the CDMSI, drawing upon the existing Council of Europe standards and the relevant jurisprudence of the European Court of Human Rights, the MSI-AUT will prepare follow up with a view to the preparation of a possible standard setting instrument on the basis of the study on the human rights dimensions of automated data processing techniques (in particular algorithms and possible regulatory implications).

MSI-AUT will also study the development and use of new digital technologies and services, including different forms of artificial intelligence, as they may impact peoples’ enjoyment of fundamental rights and freedoms in the digital age – with a view to give guidance for future standard-setting in this field. Furthermore, MSI-AUT will study the impact of civil and administrative defamation laws and their relation to the criminal provisions on defamation, as well as jurisdictional challenges in the application of those laws in the international digital environment.

Rising Through the Ranks: How Algorithms Rank and Curate Content in Search Results and on News Feeds (Open Technology Institute/New America)

Internet platforms are increasingly adopting artificial intelligence and machine-learning tools in order to shape the content we see and engage with online. Algorithms have long been deployed to rank and curate search engine results. And thanks to advances over the last decade, these algorithms also play a growing role in shaping the content we see in news feeds.

This report is the second in a series of four reports that will explore different issues regarding how automated tools are used by internet platforms to shape the content we see and influence how this content is delivered to us. The first report in this series focused on how automated tools can be leveraged to moderate content online. This second report explores how internet platforms deploy algorithms to rank and curate content in search engine results and in news feeds. The following two reports will focus on how artificial intelligence is used to optimize the target and delivery of advertisements and the delivery of content recommendations to users based on their prior consumption of content. All four of these reports also seek to explore how internet platforms, policymakers, and researchers can better promote fairness, accountability, and transparency around these automated tools and decision-making practices.

Artificial Intelligence & Human Rights: Opportunities & Risks (Berkman Klein Center for Internet & Society)

This report explores the human rights impacts of ar-tificial intelligence (“AI”) technologies. It highlights the risks that AI, algorithms, machine learning, and related technologies may pose to human rights, while also recognizing the opportunities these tech-nologies present to enhance the enjoyment of the rights enshrined in the Universal Declaration of Human Rights (“UDHR”). The report draws heavily on the United Nations Guiding Principles on Busi-ness and Human Rights (“Guiding Principles”) to propose a framework for identifying, mitigating, and remedying the human rights risks posed by AI.

Isomorphism through Algorithms: Institutional Dependencies in the Case of Facebook (2018)

Big Data & Society - ROBYN CAPLAN & DANAH BOYD

Algorithms and data-driven technologies are increasingly being embraced by a variety of different sectors and institutions. This paper examines how algorithms and data-driven technologies, enacted by an organization like Facebook, can induce similarity across an industry. Using theories from organizational sociology and neoinstitutionalism, this paper traces the bureaucratic roots of Big Data and algorithms to examine the institutional dependencies that emerge and are mediated through data-driven and algorithmic logics. This type of analysis sheds light on how organizational contexts are embedded into algorithms, which can then become embedded within other organizational and individual practices. By investigating technical practices as organizational and bureaucratic, discussions about accountability and decision-making can be reframed.

Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy (2016)

Cambridge, Massachusetts: Harvard University Press - Ariel Ezrachi & Maurice E. Stucke

Shoppers with Internet access and a bargain-hunting impulse can find a universe of products at their fingertips. In this thought-provoking exposé, Ariel Ezrachi and Maurice Stucke invite us to take a harder look at today’s app-assisted paradise of digital shopping. While consumers reap many benefits from online purchasing, the sophisticated algorithms and data-crunching that make browsing so convenient are also changing the nature of market competition, and not always for the better.

Computers colluding is one danger. Although long-standing laws prevent companies from fixing prices, data-driven algorithms can now quickly monitor competitors’ prices and adjust their own prices accordingly. So what is seemingly beneficial―increased price transparency―ironically can end up harming consumers. A second danger is behavioral discrimination. Here, companies track and profile consumers to get them to buy goods at the highest price they are willing to pay. The rise of super-platforms and their “frenemy” relationship with independent app developers raises a third danger. By controlling key platforms (such as the operating system of smartphones), data-driven monopolies dictate the flow of personal data and determine who gets to exploit potential buyers.