The 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 the (non-) presence of 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.

翻译：生成式AI的迅猛发展已渗透至社会的各个角落——包括新闻环境。随着生成式AI应用日益广泛，人们对个人及社会层面的影响产生诸多担忧，包括虚假信息与错误信息、歧视以及社会矛盾激化等问题。然而，关于预测生成式AI影响的研究仍处于起步阶段，且多局限于技术开发者和/或研究人员的视角。本文旨在拓宽视野，捕捉三个利益相关群体（新闻消费者、技术开发者、内容创作者）对生成式AI潜在负面影响的预期，以及应对这些影响的缓解策略。研究方法上，我们采用场景写作法，并在问卷调查（n=119）中运用参与式前瞻方法，深入探究认知多样化的未来想象。通过主题分析法对场景进行定性分析，系统梳理生成式AI对新闻环境的潜在影响、可能的缓解策略，以及各利益相关者在引发和缓解这些影响中的角色。此外，我们测量了受访者对特定缓解策略（即《欧盟AI法案》草案第52条建议的透明度义务）的看法。我们比较不同利益相关群体的结果，并详细阐述各群体预期影响中存在（或缺失）的差异性。最后，我们讨论了场景写作与参与式前瞻作为生成式AI影响评估工具箱的实用性。