by Sylvain Parasie, médialab
It is hard – if not impossible – to discuss the role of journalism in democracy today without mentioning the Internet, social networks and algorithms. Most of the ills afflicting contemporary journalism – weakening business models, declining quality of information, citizen confusion amid information overload, growing media dependence on audience measurement, etc. – seem to be closely linked to the evolution of digital technologies.
In my book Computing the News, Data Journalism and the Search for Objectivity (Columbia University Press, 2022), I took a step back to examine journalists who do not consider digital technologies as a threat, but rather as an opportunity to ‘save’ journalism and enable it to fulfil its democratic mission.
I set out to study ‘data journalism’ – a movement that emerged in the late 2000s as a broad set of journalistic practices based on data collection and computation. In many countries, its advocates see it as an opportunity for the media to better contribute to democratic debate in several ways: (1) by providing citizens with online applications that enable them to make ‘better decisions’ – voting for a candidate, choosing a child’s school, a doctor, etc.; (2) by helping to monitor institutions and governments based on publicly available data; (3) by analysing complex or systemic phenomena that cut across society; (4) by expanding media coverage to events that affect minorities. The novelty here is not so much the different conceptions of the democratic role of journalism – which are quite traditional – as the considerable expectations placed on the technology.
The social sciences have critically examined the media’s claim that data journalism enhances their objectivity. While some researchers deem these practices likely to increase the credibility and influence of journalists, others see them as an illusory attempt to restore the authority of journalism by giving it a scientific façade. Holding data journalism to its goal of being more objective, I sought to identify the rules that journalists and their organisations should follow to better fulfil the aforementioned promises.
The central argument of my work is that computational practices are more likely to increase the democratic contribution of journalism if journalists adjust their collective rules. These rules are no longer adapted to news production. When a newsroom becomes a ‘centre of calculation’ that collects data to analyse it and turn it into news products, journalists become dependent on a large number of human and non-human actors: data providers (administrations, associations, etc.), digital resources (statistical models, algorithms, etc.), and data processing experts and practitioners (web developers, data scientists, social science researchers, etc.).
This change in the division of labour disrupts the professional ethics of journalists, who face many questions: How to ensure the quality of the data? How to ascertain that the data does not reflect the perspective of some actors to the detriment of others? What are the professional qualities that a data journalist needs to demonstrate? How should data processing be distributed within and beyond the news organisation? To what extent does the dissemination of data enable the public to become aware of or mobilise around a particular issue?
Computing the News is an examination of how journalists’ professional ethics change as they engage in computational practices. I interviewed journalists, developers, data scientists and technology managers at established media outlets such as the Chicago Tribune, U.S. News & World Report, Center for Investigative Reporting, Le Monde, Libération, L’Express, and Paris-Match, and more specialised ones such as EveryBlock.com and OWNI. I also studied several contemporary data journalism projects that the profession has hailed as significantly contributing to the democratic debate – by reframing the perception of earthquake risk in California; enriching the debate around minority homicides in Los Angeles; and strengthening public scrutiny of candidate speeches in the 2017 French presidential election.
The book starts by showing that data journalism appeared well before the rise of the Internet, eliciting interest from parts of the profession on both sides of the Atlantic. At the end of the 1960s, a new movement formed within American journalism: Computer-Assisted Reporting, which sought to use computers and quantitative social sciences to reestablish a journalistic authority challenged by the protest movements of the 1960s. Investigative journalists developed a set of rules inspired by the social sciences that specified the conditions under which statistical data processing would likely strengthen journalistic authority in the public debate: the data should not be at the origin of the investigation; it should be verified and have no intrinsic journalistic value. Then, in the 1980s, American and French journalists separately started to produce rankings of schools and hospitals, with the goal of increasing their transparency. On both sides of the Atlantic, these calculations caused major tensions within and outside of the profession, as journalists contended with the harmful consequences of their calculations on institutions and their users.
The Internet’s rise has greatly increased the media’s interest in digital data by facilitating access to more data and computing tools. It has also confronted journalists with unfamiliar data concepts. For example, citizen movements advocating for open data promoted the idea that citizens can access data themselves to do their own analysis, challenging the well-established view that journalists should select the events worthy of public scrutiny. The objectivist approaches of ‘data scientists’, who postulate that data encapsulate a truth about the world, also question established ways of producing journalistic knowledge.
This raises a fundamental question: how to create a professional ethic enabling journalists to contribute more to the democratic debate through data? The study of several critically acclaimed projects on both sides of the Atlantic allowed us to outline a ‘ethic of reflexivity’.
This ethic includes a set of rules to ensure that journalists integrate the actions of everyone who contributes to the data production, calculation, and interpretation. It also involves organising work in such a way to protect against the risk of taking data at face value as a reflection of an objective reality. By limiting the division of labour on data within their organisation – between reporters and data scientists – the media would be able to better maintain collective vigilance over data quality. This ethic would also affect the relationship between journalists and their publics. Since data dissemination alone does not suffice to raise citizens’ awareness of a problem, let alone solve it, journalists should also adapt their rules. More specifically, they should start by partially renouncing their role as gatekeepers, and by agreeing to no longer select the events that merit coverage (a central element of their professional identity). At the same time, they should help their audiences express themselves on specific issues by creating spaces for discussion and providing citizens with more general interpretations of the issue at hand.
Finally, this book outlines another role that sociology can play in relation to journalism and its current transformations. Rather than cast doubt on journalists’ claims to objectivity, sociology can offer them resources to reconcile technology with their professional values. The challenge is to strengthen a central but weakened democratic institution.
Sylvain Parasie is a sociology professor and researcher, affiliated to the médialab. Since 2010, his work has focused on how digital technologies are transforming ways to inform, debate, and engage in the public space. He is especially interested in how data is displacing established ways of producing and consuming journalistic information in the United States and France. His research also focuses on digital methods.
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