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Abstract
How do you get citizens/media consumers to voluntarily choose to expose themselves to diverse content? Is there a role for government in helping people make diverse choices? Professor Helberger addresses these questions by suggesting "diversity by design" as an antidote to the ironic fact that broadband media abundance actually makes it more difficult for users to choose diversely. She presents four conceptualizations of diversity policy: marketplace of ideas ("external diversity"); public sphere ("internal diversity"); personal autonomy ("individual choice"); and random exposure ("serendipity"), and suggests concrete design principles to guide regulators in implementing them. However, she notes, in the end it remains for the user to decide.

Abstract
How do you get citizens/media consumers to voluntarily choose to expose themselves to diverse content? Is there a role for government in helping people make diverse choices? Professor Helberger addresses these questions by suggesting "diversity by design" as an antidote to the ironic fact that broadband media abundance actually makes it more difficult for users to choose diversely. She presents four conceptualizations of diversity policy: marketplace of ideas ("external diversity"); public sphere ("internal diversity"); personal autonomy ("individual choice"); and random exposure ("serendipity"), and suggests concrete design principles to guide regulators in implementing them. However, she notes, in the end it remains for the user to decide.

Controlling access to content -- Access-controlled broadcasting and the free flow of information -- Conditional access and general competition law -- Conditional access and telecommunications law

By helping the user find relevant and important online content, news recommenders have the potential to fulfill a crucial role in a democratic society. Simultaneously, recent concerns about filter bubbles, fake news and selective exposure are symptomatic of the disruptive potential of these digital news recommenders. Recommender systems can make or break filter bubbles, and as such can be instrumental in creating either a more closed or a more open internet. This document details a pitch for an ongoing project that aims to bridge the gap between normative notions of diversity, rooted in democratic theory, and quantitative metrics necessary for evaluating the recommender system. Our aim is to get feedback on a set of proposed metrics grounded in social science interpretations of diversity.

Exposure diversity is a relatively new and as yet to be explicitly formulated objective of contemporary media policy. While it holds certain potential—in particular in the messy digital space characterized by abundance and exponentially increased user choices—it comes with certain risks too. The role of public service media in ensuring exposure diversity is an underexplored yet important topic of media policy and law. This article introduces the special section on public service media and exposure diversity in the International Journal of Communication and outlines the key motivation behind it. It briefly presents the main contributions and a summary of their arguments, as well as the red line that holds them together.

AbstractThe tremendous rise of generative AI has reached every part of society—including the news environment. There are many concerns about the individual and societal impact of the increasing use of generative AI, including issues such as disinformation and misinformation, discrimination, and the promotion of social tensions. However, research on anticipating the impact of generative AI is still in its infancy and mostly limited to the views of technology developers and/or researchers. In this paper, we aim to broaden the perspective and capture the expectations of three stakeholder groups (news consumers; technology developers; content creators) about the potential negative impacts of generative AI, as well as mitigation strategies to address these. Methodologically, we apply scenario-writing and use participatory foresight in the context of a survey (n = 119) to delve into cognitively diverse imaginations of the future. We qualitatively analyze the scenarios using thematic analysis to systematically map potential impacts of generative AI on the news environment, potential mitigation strategies, and the role of stakeholders in causing and mitigating these impacts. In addition, we measure respondents' opinions on a specific mitigation strategy, namely transparency obligations as suggested in Article 52 of the draft EU AI Act. We compare the results across different stakeholder groups and elaborate on different expected impacts across these groups. We conclude by discussing the usefulness of scenario-writing and participatory foresight as a toolbox for generative AI impact assessment.

Personalized recommendations in search engines, social media and also in more traditional media increasingly raise concerns over potentially negative consequences for diversity and the quality of public discourse. The algorithmic filtering and adaption of online content to personal preferences and interests is often associated with a decrease in the diversity of information to which users are exposed. Notwithstanding the question of whether these claims are correct or not, this article discusses whether and how recommendations can also be designed to stimulate more diverse exposure to information and to break potential 'filter bubbles' rather than create them. Combining insights from democratic theory, computer science and law, the article makes suggestions for design principles and explores the potential and possible limits of 'diversity sensitive design'. ; Peer reviewed