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.
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.
The source, which comprises excerpts from Module A of the KT4D Social Risk Toolkit, explores the complex challenge presented by artificial intelligence to individual autonomy and free will within modern society. It introduces a comprehensive literature review focusing on how highly personalized algorithmic content curation influences personal opinions by exploiting deep-seated human cognitive biases, such as the preference for emotionally charged or explanatory information.
The purpose of this document is to provide an overview of how AI, big data and frontier technologies impact rights from the data protection perspective. The newly adopted definition of AI by the Organisation for Economic Co-operation and Development (OECD) states that “an AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that (can) influence physical or virtual environments.
Companies have significant influence over public discourse in online platforms, necessitating that the algorithms that shape these online platforms should be regulated and constrained to sufficiently consider the public interest (Susskind, 2018: 350). Perhaps the easiest way of returning control of a public good to the people would be nationalisation of large AI companies and platforms. However, this also affords the government considerable power, to tailor public discourse to their interests (Susskind, 2018: 350).
The current EU approach to AI regulation faces several challenges and limitations that need to be addressed. One of the main issues is to what degree product legislation approach is fit for mitigating more systematic and democratic risks of AI systems and the lack of resources for regulatory and enforcement agencies. Another challenge is the compatibility of the EU approach with the collective bargaining and co-determination models that are prevalent in some member states.
There are both instrumental and intrinsic reasons to value democracy. In short, democracy is valuable instrumentally because:
(1) democracy can assist us in producing laws and policies that protect the rights and interests of citizens,
(2) democracy more often than other systems produces the right laws and policies (there are epistemic benefits to democratic decision-making), and
(3) democracy can improve the people in it through increased autonomy and knowledge (Christiano and Bajaj, 2022).
Knowledge technologies, as distinct from information technologies, have been defined in the Module C of the social risk toolkit. Within KT4D, knowledge technologies are thus defined as technologies which support and contribute to the creation and dissemination of knowledge.
The aim of the first three modules of KT4D’s Social Risk Toolkit thus focuses on the individual aspects of this challenge and is multifaceted.
AI and Culture
Critical Digital Citizenship
Ethics and Trust in AI
Freedom and Manipulation
Inclusive Digital Democracy
Personal Data and User Profiling
The policy brief published by KT4D suggests that examining culture allows for a deeper understanding of societal responses to AI development.