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Social and ethical implications of AI, big data and algorithms (Module)

Module description

This one-week intensive teaching module is especially designed to provide students from a range of academic backgrounds with a critical understanding of prime social and ethical implications of AI, big data and algorithms in the wider domain of health care. In doing so, it will enable students to engage critically with theory, policy and practice associated with multidisciplinary approaches to responsible research and innovation, of key importance at a time when increasingly, embedding principles and practice of collective responsibility into research and innovation becomes a mandatory requirement of major funding bodies and an essential part of corporate social responsibility.

The module will use a case-based approach to examine a series of key social and ethical issues associated with artificial intelligence, big data and algorithms, such as transparency, bias, fairness, trust, privacy, accountability, inclusion and safety. It will introduce the students to different conceptual approaches and theoretical standpoints used to anticipate, reflect on, engage with, and act upon, these issues (e.g. sociology of expectations; bioethics; technological determinism and transhumanism; foresight and futures studies; user-led and participatory design; public(s) engagement; gender, intersectionality and diversity studies), and it will bring these together to explore critically practice and policy of responsible research and innovation.

Staff information

Christine Aicardi

Teaching pattern

5 x 2-hours lectures over one week

Module assessment - more information

The assessment consists in 1 x 3,000 words essay. Students will be required to analyse key social and ethical issues of AI, big data and algorithms, and critically discuss them and their short to medium term potential implications in relation to a particular domain of application in healthcare. They will make use of methodological approaches and concepts studied in the module. Formative assessment will be ongoing throughout the module, based on feedback from the group and class discussions. For their assignment students will answer one essay question from a choice of 4-5.

Key information

Module code

Credit level 7

Assessment coursework

Credit value 15

Semester summer session 3

Study abroad module No