Ph.D. Student in Information Systems

Kanav Mor

I study how generative AI is changing news, online platforms and creative work, and what that means for the open web and for who benefits from new tools.

Heinz College, Carnegie Mellon UniversityPittsburgh, Pennsylvania

Research Curriculum vitae

About

I am a Ph.D. student in Information Systems at Heinz College, Carnegie Mellon University, advised by Rahul Telang and Avinash Collis. My research sits at the intersection of economics, information systems and public policy. I ask how publishers, platforms and creators respond to generative AI, and what their responses do to the information ecosystem the rest of us depend on.

Three questions run through my current work. How did news publishers react when AI companies began training on their content, and who else got locked out of the web as a result? Does AI assistance make musicians more productive and more creative, and does it help beginners or experts more? And when a video is disclosed as AI-generated, does its creator lose an audience?

To answer these questions I build the data myself, from web archives, platform interfaces and browser instrumentation, and combine it with causal inference designs and randomized field experiments. Before the Ph.D. I was a software engineer at Microsoft, and I hold dual degrees in Computer Science and Economics from BITS Pilani.

Economics of generative AI
Digital platforms and online media
Creative industries
Web governance and data access
Causal inference
Field experiments

Research

All research

News Behind the News: Spillover Effects of AI Crawler Blocking Among News Publishers

Kanav Mor and Rahul Telang

Working paperTo be presented at CIST 2026

Using 44 months of archived robots.txt files for major news publishers in the United States, Europe and the rest of the world, we show that the arrival of OpenAI's GPTBot in August 2023 triggered a sharp, front-loaded wave of AI-crawler blocking, strongest among paywalled outlets, and that the blocking spilled over onto crawlers with no AI function at all: archives, research tools, accessibility services and news monitors.

SSRN

Impact of AI-Assisted Music Composition on Creativity: A Randomized Controlled Trial

Kanav Mor, Rahul Telang, and Avinash Collis

Work in progressField experiment

A randomized controlled trial of AI assistance in music composition, run inside a live online composition platform. We estimate the causal effect of access to an AI assistant on how much composers produce, how good it is, and how harmonically complex it is, and we use suggestion-level interaction logs to ask whether composers accept, modify or reject what the AI proposes, and whether novices or experts gain more.

AI Disclosure Labels and Viewer Engagement on YouTube: Evidence from a Natural Experiment

Kanav Mor and Rahul Telang

Work in progressData collection ongoing

YouTube requires creators to disclose realistic AI-generated or altered content, which it marks with an "Altered or synthetic content" notice. We ask whether that disclosure costs creators their audience, tracking a large longitudinal panel of videos and exploiting the staggered timing at which disclosures appear to estimate their effect on views, likes and comments.

News

October 2026I will present News Behind the News at the Conference on Information Systems and Technology (CIST 2026) in San Francisco on October 31 – November 1.
2026News Behind the News, with Rahul Telang, is now available as a working paper on SSRN.

Contact

The best way to reach me is by email at kanav@cmu.edu.

Heinz College, Carnegie Mellon University
Pittsburgh, Pennsylvania