Module B focuses on the risks AI poses for social fairness and trust: how the use of AI-based tools can generate inequality or dishonesty, particularly when human productions differ in nature (e.g. creative vs. repetitive tasks), and how such dynamics impact trust between individuals and institutions.

This document contains the Bibliography of KT4D Social Risk Toolkit Module B: AI, trust and awareness.

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).

2.1    Equality

Equality is by-and-large considered both a positive aspect of democracy, and a necessary feature for democracy. To be brief, the main benefit of equality in democracy is that it gives equal consideration to all individuals, thus each person is a free and willing self-legislator among equals.

There are both instrumental and intrinsic reasons to value democracy. In short, democracy is valuable instrumentally because