I am a transdisciplinary researcher and technologist.

I have carried research in academia (UC Berkeley), big tech (Facebook AI) and start-up environments (Bloom, Jalgos).

I went from building algorithms to analysing their biases and impact on society. I am now investigate algorithmic biases, with a focus on social media recommender systems.

Below is a selection of my works that have been featured across the media, including the New York Times, le Monde, O’Reilly, the Brookings Institute

Research & Projects

Former Projects

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.

Professional Experience

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.

Talks & Lectures

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 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.


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

Télécom Paris - Diplome d’Ingénieur
Télécom is France’s top Computer Science school. The engineering degree (undergrad + MS) captures a broad technical understanding of computational systems and networks. Double-degree MS in Data Science at Eurecom.

In the news

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Le Monde

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

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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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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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The New York Times

YouTube Cut Down Misinformation. Then It Boosted Fox News.

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Why is TikTok creating filter bubbles based on your race?

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Does TikTok Have A Race Problem?

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