Recommendation Algorithms Explainer

The Recommendation Algorithms explainer aims to demonstrate how algorithms work on social media platforms. It allows the users to simulate their experience on a social media platform, where their choices shape a personalised feed.

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Module C: Historical perspective – Free Will and Autonomy

This section considers how people’s autonomy and free will are hindered or supported by past and present KTs. By focusing on the structural level, we will examine systemic issues such as monopolies over KTs, data extraction and colonialism, labour, and political participation.

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The impact of social networks and misinformation on citizens’ opinions and attitudes

This document adopts a psychological and cognitive perspective on misinformation and disinformation, focusing on the interaction between cognitive biases, emotional motivations, social communication goals, and contemporary information environments

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Risks to individual freedoms of speech and action

Since our liberal democracies generally employ forms of representativeness to their institutions, the impact of AI on free and fair elections is also one of the key ways in which technology affects our polities. The level of acceptance of the results from the elections - the legitimacy of the outcome - rests largely on how those who end up with less power shares in the representative system see the fairness of the election process itself.

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Experiments on critical thinking, autonomy and AI

The experimental component of Module A aims to further characterise internet users' behaviours when faced with online choices potentially undermining their autonomy: how people evaluate AI-generated information and/or content selected through AI-based algorithms, and how people are influenced by AI-based algorithms in their online choices.

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