Decoding Democracy: Politics, Data and AI

Join a forward-thinking discussion with leading experts as we dissect the transformative impact of Artificial Intelligence, Large Language Models (LLMs) and Data on the analysis of politics and the political landscape itself. From AI's growing role in policy drafting and voter targeting to the weaponization of disinformation, the foundations of democracy are being challenged and reshaped.

Our panel of distinguished speakers will cut through the hype to explore critical questions, including:

· How can AI help us to decode political images?

· What new forms of data journalism are enabled through AI and how does this change politics reporting?

· Can AI be harnessed to strengthen democratic engagement and policymaking?

Invited speakers include Associate Professor Roxana Radu (Jesus College, University of Oxford), Dr Linda Li (London School of Economics) and Joey D'Urso (The Times). The panel will be moderated by Professor Ralph Schroeder (OII, University of Oxford). Discover the opportunities and potential risks on the cutting edge of technology and power.

This event is part of the Cheng Kar Shun Digital Hub Programme in partnership with the Oxford Internet Institute.

The networking reception will include vegetarian, vegan and gluten-free snack options and allergens will be clearly labelled. If you have any additional dietary requirements or allergies, please do contact ZGlnaXRhbGh1YiB8IGplc3VzICEgb3ggISBhYyAhIHVr and we are happy to help.

FIND US

This event will take place in the Cheng Kar Shun Digital Hub at Jesus College, Oxford. The Hub entrance is on Market Street (opposite Wagamama). The Hub is accessible, with automatic double doors at the entrance and lifts to and from the main lower ground floor event space.

If you have any accessibility requirements, please do contact ZGlnaXRhbGh1YiB8IGplc3VzICEgb3ggISBhYyAhIHVr and we are happy to help.

*Filming and photography will be taking place during the event. If you do not wish to be photographed or filmed, please notify a member of the Hub team on arrival.

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