Tiffany Ge Wang is a final year doctoral candidate in Computer Science at the University of Oxford. Her research lies at the intersection of human-computer interaction (HCI) and human-centered privacy & security. Through her research, she aims to empower humans, especially those in at-risk populations, to have autonomy in their dealings with data-driven systems. She has received 7 paper awards at top-tier HCI conferences and journals, including ACM CHI and CSCW. Her research has been cited by influential organizations such as the Council of Europe, the UK ICO, the Australian ICO, and the FTC, and has been featured in news articles in El Pais, among others. She holds a bachelor's degree in Physics from the University of Oxford and an MSc in Information Science from University College London.

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AG Audience

English

60 Minutes

Saarbrücken

As ubiquitous AI becomes increasingly integrated into the smart devices that users use daily, the rise of extensive datafication, data surveillance, and monetized behavioral engineering is becoming increasingly noticeable. Sophisticated algorithms are utilized to perform in-depth analyses of people's data, dissecting it to evaluate personal characteristics, thereby making significant and impactful algorithmic decisions for them. In this evolving digital environment, smart devices are no longer just functional tools; they have become active agents in shaping experiences, transforming lives as algorithmic decisions are etching pathways for people's futures. This trend is particularly concerning for vulnerable groups such as children, young people, and other marginalized communities, who may be disproportionately affected by these technological advancements. My research in human-computer interaction focuses on reimagining these data-driven AI systems to better support user autonomy. To address these challenges, I develop tools and systems that empower users and communities, especially those most vulnerable, to control their own experiences and information directly. These include: 1) human-AI interaction tools that enhance user decision-making power, 2) AI literacy tools for a deeper, critical understanding of data-driven systems, and 3) the development of actionable strategies and frameworks for policymakers and industry leaders to ensure the ethical development and use of AI technologies.

Annika Meiser

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