Marc Faddoul is a transdisciplinary technologist and AI researcher, expert on recommendation systems and algorithmic audit.

He is the director and co-founder of AI Forensics, a digital-rights non-profit which investigates opaque and influential algorithms.

He regularly advises regulators with technical perspectives on AI ethics and platform accountability, including though expert committees of the EU Commission, the Digital Council (CNNum) and media regulator (ARCOM), and the French General States on Information. He also testified about TikTok to the French Senate.

Marc Faddoul is often called upon to comment on AI and society by WSJ, The Guardian, Le Monde and more.

He gained experience in algorithmic auditing in academia (UC Berkeley), big tech (research collaboration with Facebook AI), and start-ups (Bloom, Jalgos).


Education

UC Berkeley School of Information - Master of Science
Transdisciplinary perspectives on societal, legal and ethical impacts of technology on society. (MIMS program)

Télécom Paris, Institut Polytechnique de Paris - Diplome d’Ingénieur
Télécom is France’s top Computer Science school. The engineering degree (undergrad + MS) covers a wide technical scope on computational systems and networks. Double-degree MS in Data Science at Eurecom.

Professional

Co-Founder & Director - AI Forensics (2021-): AI Forensics is a non profit specialized in algorithmic investigation. It was co-founded with Claudio Agosti, expanding the activities of Tracking Exposed.

Co-Director - Tracking Exposed (2021-2022): Leading the development, strategy and funding of the organization.

Associate Researcher - UC Berkeley (2019-2020): Development of novel algorithmic approaches to detect disinformation and borderline content, with Professor Hany Farid.

Research Scientist - Facebook AI (2020): Research collaboration with UC Berkeley to improve disinformation classification algorithms.

Algorithm Designer - Bloom (2018): Design an influence ranking model for social media posts.

Algorithm Designer - Jalgos (2016): Design and Implementation of data-intensive algorithmic solutions for Fortune 500 companies.

Freelance Developer (2013-17): Several projects, involving discrete optimisation, resource allocation and web semantics.

Affiliations

Selected News Featuring

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French Digital Council

Comment on platform regulation recommendations

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BFM TV

Live debate about Facebook’s societal impact after 20 years

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Washington Post

Feature of AI Forensics’ report on BingChat electoral hallucinations

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Le Monde

AI Forensics report on Amazon’s bookstore algorithms

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French Senat

Marc Faddoul’s testimony on the special commission on TikTok

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Forbes

Documentary: Bill To Ban TikTok: Why That Won’t Fix Data Privacy

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Center for Humane Technology

Podcast: TikTok’s Transparency Problem with Marc Faddoul and Tristan Harris

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The Guardian

Series: TikTok has become a global giant. The US is threatening to rein it in

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The Guardian

Series: What TikTok does to your mental health: ‘It’s embarrassing we know so little’

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The Guardian

Series: Why the app with 1bn users faces a fight for its existence

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MSNBC

TikTok’s disinformation policy ahead of the 2022 US midterms elections

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Le Figaro

Ukraine: les influenceurs, petits soldats de la guerre informationnelle

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Wall Street Journal

TikTok’s Pullback in Russia Leaves More Space for Pro-Kremlin Propaganda

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Financial Times

The truth about war is messy — just read Wikipedia

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Mozilla Foundation

A New Way to Keep TikTok Accountable

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The Guardian

TikTok was ‘just a dancing app’. Then the Ukraine war started

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Wired Italia

In Russia TikTok ha fatto un repulisti, lasciando spazio alla propaganda

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Le Monde

TikTok coupe la Russie du reste du monde en bloquant les contenus étrangers

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Le Monde

TikTok accusé d’offrir un «passe-droit» aux propagandistes du Kremlin

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Le Monde

Facebook, YouTube… les grandes plates-formes d’Internet face au défi du coronavirus

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FranceTV Info

Tiktok fait-il passer ses intérêts commerciaux avant les intérêts politiques?

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Le Monde

Interview with Marc Faddoul on YouTube’s new content moderation policy.

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Le Monde

Facebook, YouTube… les grandes plates-formes d’Internet face au défi du coronavirus

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Brookings Institution

COVID-19 is triggering a massive experiment in algorithmic content moderation. by Marc Faddoul

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O'Reilly Media

Toward Algorithmic Humility an essay by Marc Faddoul on the design of algorithmic sentencing tools and their alarming false positive rates.

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Fox Nation

Interview with Lara Logan on her documentary Privacy in the Digital Age

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BBC

TechTent: Interview with Marc Faddoul on YouTube’s new content moderation policy.

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The New York Times

Can YouTube quiet its conspiracy theorist?

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NPR

What internet outrage reveals about race and TikTok’s algorithm

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EuroNews

How white saviour ‘voluntourism’ gets you famous on TikTok

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The New York Times

YouTube Cut Down Misinformation. Then It Boosted Fox News.

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Wired

Why is TikTok creating filter bubbles based on your race?

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Forbes

Does TikTok Have A Race Problem?

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Talks & Lectures

Grand Continent Summit - Dec 23: Panel Social and Economic impact of AI, audience of heads of governments and EU institutions, and key executives and decision makers.

EU Disinfo conference - Oct 23: Keynote speaker: TikTok. Who’s there?

Nordic Media Days - May 23: Keynote speaker: What to do when algorithms rule the world?

French Senat - Mar 23: Testimony for the special commission on TikTok

International Cybersecurity Forum (FIC) - Apr 23: Auditing TikTok’s recommender system

Mozilla Festival - Mar 23: Panel: Navigating the open-source algorithm audit tooling landscape

EU Disinfo Lab conference - September 2022: Aversarial Algorithmic Audits

ARCOM - May 22: Amplification and Demotion of election related content on social media. Presentation of results to the French media regulator

Mozilla Festival - Apr 22: Gain control back on your YouTube recommendations

Webminar with EU Members of Parliment - Nov 21: Alternative Recommender Systems in the DSA: how to protect free expression, create competition and empower users

Harvard University - Oct 21: Faculty working group on Social Media Recommendation Algorithms.

Università di Milano - Pre-COP 2024 - Sept 21: The impact of Recommendation Algorithms in the Climate Crisis as part of a lecture series on climate and technology.

Université Paris Nanterre - Nov 21: Guest Lecture for Rémy Demichelis’s class Théories de l’information

Université Paris 2 Panthéon-Assas - Dec 2020, Sept 2021: Guest Lecture: Algorithmic Fairness in Digital Administrations

Conseil National du Numérique (French Digital Council) - Jun 2021: Part of the panel of contributing experts to the report Itinéraire des fausses informations en ligne and following debates.

Université Paris 2 Panthéon-Assas - Dec 2020, Sept 2021: Guest Lecturer, Primavera de Filippi’s class Digital Administrations.

US State Department - July 2020: Recommender Systems and Power Dynamics 1h30 lecture for members of the State Department and US Cyber Command, in a series hosted by Clint Watts.

UC Berkeley - GEESE Panel: The Role and Impact of Auditing Algorithms

UC Berkeley - Fall 2019: Guest Lecturer, Steve Weber’s Applied Behavioral Economics

Northeastern University - Spring 2019: Information Ethics Roundtable, paper presentation.

Selected Projects and Investigations

See our work at AI Forensics for more recent projects.

Investigating TikTok’s policy response to the Ukraine war in Russia
We monitored the evolution of TikTok’s policy in Russia as the war in Ukraine unfolded. We uncovered that TikTok blocked access to international content for its Russian users without declaring it. In a follow-up investigation, we exposed how loopholes in TikTok’s upload ban policy led the platform to be flooded by pro-Kremlin propaganda. Our report lead 6 US Senators to summon TikTok’s CEO for explanations.

YouChoose.ai: Alternative recommender systems for YouTube
YouChoose.ai is plug-in enabling users and content creators to choose and control their recommendations on YouTube.com. The current release (beta) allows content creators to choose the recommendations on their own content. The long term goal for YouChoose is to be a platform for recommender systems, empowering users to pick an accountable algorithm, aligned with their own interests.

An analysis of YouTube’s promotion of conspiratorial content
Lead author of an audit of YouTube’s recommendation engine. The study was published with the New York Times, and was cited by US Congress in a formal letter to the CEO’s of Google and YouTube. Interviews featured in le Monde and the BBC.
The analysis relied on a monitoring infrastructure paired with a machine learning classifier to detect conspiratorial content.

Uncovering physiognomic filter-bubbles on TikTok An experiment which showed how race and appearance impact recommendability on TikTok. Featured in BuzzFeed, Vox, Wired UK, Forbes

AlgoTransparency AlgoTransparency is aimed at monitoring the channels most promoted by YouTube’s recommendation engine to logged-out users.

Investigating Sniper Ad Targeting A master thesis project investigating whether and how an malign ads can be tailored and sent to a single individual. Advised by Professor Deirdre Mulligan. Introductory video here.

Auditing a Judicial Algorithm In depth-analysis of a Pretrial Risk-Assessment Tool used in the U.S to determine whether a defendant should be placed in detention before their trial. Research presented at the Information Ethics Roundtable at Northeastern University.

Cybersecurity Consulting Consulting within the Citizen Clinic for a civil-rights NGO from central-America, to help them defend against cyber-threats and state-surveillance.