Informations complémentaires : https://ifp.u-paris2.fr/fr/publication-ifp-le-manuel-de-journalisme

This article describes and discusses how normative journalistic roles are formulated across Europe. The material was obtained from the 2012–2016 wave of the Worlds of Journalism Study, a comparative study designed to assess the state of journalism throughout the world. The advantage of this study over similar undertakings in the past is that we did not confront journalists with ready-made statements but invited them to tell us, in their own words, what they thought the major roles of journalists in their countries ought to be. Open responses of more than 10,200 journalists from twenty-seven European countries yielded 12,860 references. Results show that the most important roles refer to the domain of political life, especially the informational-instructive and the critical-monitorial functions—a finding that is consistent across the twenty-seven countries investigated. Beyond this shared global vision, it is, however, possible to point out some national specificities, keeping in mind that even if the core of the normative roles remains somewhat universal, a detailed comparison of those roles in their cultural context allows us to grasp some differences in their hierarchy and their meaning.

Permalink for the paper : https://journals.sagepub.com/doi/10.1177/1940161221994093

Algorithmic decision making is used in an increasing number of fields. Letting automated processes take decisions raises the question of their accountability. In the field of computational journalism, the algorithmic accountability framework proposed by Diakopoulos formalizes this challenge by considering algorithms as objects of human creation, with the goal of revealing the intent embedded into their implementation. A consequence of this definition is that ensuring accountability essentially boils down to a transparency question: given the appropriate reverse-engineering tools, it should be feasible to extract design criteria and to identify intentional biases. General limitations of this transparency ideal have been discussed by Ananny and Crawford (New Media Soc 20(3):973–989, 2018). We further focus on its technical limitations. We show that even if reverse-engineering concludes that the criteria embedded into an algorithm correspond to its publicized intent, it may be that adversarial behaviors make the algorithm deviate from its expected operation. We illustrate this issue with an automated news recommendation system, and show how the classification algorithms used in such systems can be fooled with hard-to-notice modifications of the articles to classify. We therefore suggest that robustness against adversarial behaviors should be taken into account in the definition of algorithmic accountability, to better capture the risks inherent to algorithmic decision making. We finally discuss the various challenges that this new technical limitation raises for journalism practice.

Link to the paper : http://link.springer.com/article/10.1007/s00146-021-01159-3

Link to the full-text version : https://rdcu.be/cgI0h