Women in AI: From Algorithms to Action: Living in the AI Era

Her research explores the entanglements between algorithms, digital infrastructures and social and political life, with interests in cultural imaginaries of AI, feminist epistemologies, and the temporalities of algorithmic media. She is the author of two monographs, IF…THEN: Algorithmic Power and Politics (Oxford University Press, 2018) and Facebook (Polity Press, 2021). Currently she leads three projects on media silences, reimagining AI, and the monitorial citizen, and serves as Principal Investigator of HumAIn, a new five‑year research hub at the Faculty of Humanities (funded through 2029).

After completing her PhD at NTNU in 2023, she was awarded a post‑doctoral position at the University of Copenhagen — first at the Center for Tracking and Society, and from 2025 at CAISA, Denmark’s national center for AI in society. Her research explores how data-driven technology reshapes power and democracy, with a special focus on public administration and the Nordic welfare state. She works as a Postdoc at the National Center for AI in Copenhagen and works as a project manager and analyst at the independent Danish think tank Tænketanken Digital Infrastruktur.

Julie is Head of Engineering at TOM, an AI-native waste management company focused on improving how waste is measured and handled. She works on developing and scaling the company’s technology platform, turning complex challenges into practical, robust solutions with real-world impact.

She holds an MSc in Cybernetics and Robotics from NTNU and has a background in software development across both large industrial organizations and startups. Her experience spans building reliable systems and bringing products from idea to implementation.

A passionate and results-oriented Principal Researcher at DNV with extensive experience in research. Highly motivated by creating knowledge that tackles real-world challenges, particularly using AI and machine learning for improved decision-making in high-risk scenarios. Her current focus is on Assurance of AI, ensuring responsible and trustworthy AI implementation. Beyond research, she is a strong advocate for Diversity, Equity, and Inclusion (DEI) in STEM fields.

Ingrid Kristine Glad, Professor in Statistics and Data Science, UiO (Moderator)

Professor Ingrid Kristine Glad is a leading figure in Statistics and Data Science at the University of Oslo, and the director of Integreat, Norway's center of excellence in Machine Learning and AI. Her research spans high-dimensional regression, anomaly detection in data streams, and Bayesian inference, bridging theoretical advances with practical applications in genomics and industrial settings. She serves as Chair of the Abel Board (2022-2026) and is a member of the NORA Board.

Kushagri Tandon, PhD candidate, UiO

Kushagri Tandon is a PhD Research Fellow in Statistics and Data Science at the University of Oslo. Her work sits at the intersection of data, climate, and uncertainty, where she studies rainfall and extreme weather using data-driven approaches. She is particularly interested in how complex patterns in climate data can be modelled to better reflect real-world conditions, using examples from Norway. Alongside her research, she is engaged in public-facing science communication and contributes to the Integreat Insights blog series at UiO, including the article Debunking AI Myths and is an avid reader who writes about books in her spare time.