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  • From screen to skin

    From Skin to Screen Bodily Intgrity in the Digital Age

    Nov. 20, 2024
    Júlia Keserű

    Research examines the collection of “body-centric data” which has experienced a dramatic surge since the COVID-19 pandemic and the rise of sophisticated AI tools.

  • Page from Incomplete Chronicles. AIMZ report.revised_0(1)

    Incomplete Chronicles: Unveiling Data Bias in Maternal Health

    Nov. 18, 2024
    Min’enhle Ncube

    An ethnographic research into the datasets powering maternal healthcare app “DawaMom” used across Zambia and other Southern African countries

  • Public AI cover photo

    Public AI

    Sept. 30, 2024
    Mark Surman, Nik Marda, Jasmine Sun
    Responsible technology

    A vision for a robust ecosystem of initiatives that promote public goods, public orientation, and public use throughout every step of AI development and deployment.

  • RH-thumbnail-03

    Unveiling the Potential of a Conversational Agent in Developer Support: Insights from Mozilla’s PDF.js Project

    July 10, 2024
    Marco Castelluccio
    Open source

    This paper presents an investigation into whether AI can be leveraged to assist developers and guide open source community members. It introduces DevMentorAI, an LLM-based tool that uses a RAG approach to answer developer questions, which is then evaluated with a case study on Mozilla's PDF.js proje

  • aapti

    Strengthening Data Ecosystems in Indian Schools

    June 10, 2024
    Manvi Parashar, Poorvi Yerrapureddy, Astha Kapoor

    Educational data collection and analysis can both improve and introduce risks to India’s sprawling education system. Findings follow a nine-month investigation by Mozilla and Aapti Institute, supported by USAID.

  • Openness Framework Paper v6

    Towards a Framework for Openness in Foundation Models

    May 21, 2024
    Mozilla, Columbia University
    AI fairness, accountability, and transparency

    This paper presents a framework for grappling with openness across the AI stack. The paper surveys existing approaches to defining openness in AI models and systems, and then proposes a descriptive framework to understand how each component of the foundation model stack contributes to openness.

  • RH-thumbnail-03

    Mind the Gap: What Working With Developers on Fuzz Tests Taught Us About Coverage Gaps

    April 24, 2024
    Christian Holler, Jason Kratzer, Andy Zaidman, Alberto Bacchelli, Marco Castelluccio, Carolin Brandt
    Privacy, security & tracking
  • AIIDB thumbnail

    AI Intersections Database

    April 18, 2024
    Mozilla Insights, Kenrya Rankin
    AI bias & discrimination / AI fairness, accountability, and transparency / Community building / Digital inclusion / LGBTQIA+

    The AI Intersections Database maps intersections between the key social justice and human rights areas of our time and documented AI impacts and their manifestations in society.

  • Stress-test-ad-libraries-report-graphics

    Full Disclosure: Stress testing tech platforms’ ad repositories

    April 16, 2024
    Claire Pershan, Amaury Lesplingart
    Ads transparency / Elections

    Mozilla called on Check First to test the ad transparency tools maintained by 11 of the world's largest tech companies. These tools aim to let researchers, watchdogs, and members of the public understand how commercial communications influence the information space and affect society.

  • CCTM

    Technical Readout - Columbia Convening on Openness and AI

    March 27, 2024
    Mozilla, Columbia University
    Openness and AI

    Key technical takeaways from a convening focused on exploring what "openness" means in the AI era.

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