[acc-cca-l] Fwd: [Air-L] Upcoming CFP Deadline (Oct 25): Governing the Algorithmic Distribution of News

[Sara Bannerman]

Just a reminder about the upcoming CFP deadline for our edited collection.

Editors: Sara Bannerman (McMaster University) and James Meese (University
of Technology Sydney)

In January 2018, Facebook declared that it would no longer prioritise news
content in its NewsFeed. Instead, it would surface posts from 'friends and
family', with the goal of bringing 'people closer together' (Mosseri,
2018). Facebook had stopped promoting particular forms of news before (like
clickbait headlines) but they had always retained a broad commitment to
distributing news content. However, the change in 2018 represented a major
pivot for a platform that had increasingly become a central intermediary
for online news distribution. In response, digital-first publications, who
had staked their business model on Facebook's ability to surface news to
audiences, started to lay off staff in significant numbers. These new
disruptive news enterprises (like Buzzfeed and Mic) were supposed to usher
in a new future for news. However, it appeared that their business models
were as unstable as those of their print predecessors.

These recent developments have not gone unnoticed by governments.
Policymakers and politicians across the world are starting to examine the
role that platforms and algorithms play in the distribution of news.
Inquiries in Australia, the United Kingdom, Canada and elsewhere have
explored the consequences of the algorithmic distribution of news.
Alongside these national inquiries, a broader international discussion has
focused on the apparent rise in disinformation and the increasingly
partisan nature of political discourse. This discussion has intensified
recently, leading to the formation of an International Grand Committee on
Big Data, Privacy and Democracy composed of elected officials from
governments around the world.

This edited collection will respond to this international policy moment and
examine the challenges posed by the algorithmic distribution of news. It
will critically assess recent media policy developments in this space and
explore the broader economic, political and industrial transformations
associated with algorithmic distribution. In doing so, we aim to offer a
comprehensive account of this moment of institutional change, which has
significantly altered the distribution and consumption of news (see Nielsen
2018).

The book will be split into two sections. The first section will consist of
thematic chapters (5 - 6,000 words) and the second section will feature
shorter case studies (3 - 4,000 words) describing and analysing recent
policy developments related to algorithmic distribution in particular
countries. We are currently in discussions with interested publishers and
seeking contributions for both sections.

Possible topics include (but are not limited to):

- International governance of the algorithmic distribution of news,
including the formation and operation of the International Grand Committee;

- Measures to support media diversity in light of algorithmic distribution,
including measures to support local, Indigenous, alternative, independent,
ethnic, women's and minority news media;

- Case studies of countries (for section two): how have particular
countries approached regulatory problems in light of the algorithmic
distribution of news?

- Subsidies and tax exemptions that respond to the algorithmic distribution
of news;

- Discussions of regulations intended to ensure the objectivity and/or
transparency of search and recommendation algorithms;

- Regulatory measures that respond to layoffs and closures of news outlets;

- Intersections between copyright law and news aggregation (such as the
EU's Article 11, the 'Google News tax;'

- The relationship between news, platforms, and competition law;

- Regulation of targeted advertising in relation to news;

- Histories of early forays into online (or social) news distribution;

- Analyses of innovative forms of news distribution;

- Civic risks associated with algorithmic distribution (or online
engagement);and

- Detailed analyses of relevant inquiries or reform proposals.

If you are interested in contributing to either section, please send a
short chapter or case study proposal (of about 400 words) and a biography
(150 words) by the 25th of October 2019 to james.meese at uts.edu.au and
banners at mcmaster.ca



Apologies for cross-posting


-
James Meese
Senior Lecturer
Digital and Social Media
School of Communication
Faculty of Arts and Social Sciences
T. +61 (02) 9514 2955
PO Box 123. Broadway NSW 2007 Australia

UTS acknowledges the Gadigal People of the Eora Nation and the
Boorooberongal People of the Dharug Nation upon whose ancestral lands our
campuses now stands.

We would also like to pay respect to the Elders both past and present,
acknowledging them as the traditional custodians of knowledge for these
lands.

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