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Data, Experiments, and Society

Module description

This module will introduce you to the ethical and epistemic issues that surround experimentation and data in the 21st century. The experimental mindset is now firmly embedded in every aspect of life. Whether it is a traditional biochemistry laboratory, a clinical trial, a political group planning a new campaign, or a social media company trying to modify user behaviour - experimentation and the data derived from it are central to all these endeavours. In this module we will investigate why experimental data matters; how experimental practice is transformed in the digital age; and address the ethical challenges that experimentation raises in everyday practice. The module has no prerequisites and is suitable for students in the social and natural sciences, the humanities, and data science.

Module aims - intentions of the module

The aim of this module is to enable you to critically reflect on the ethical and epistemic issues that experimental practice raises in various contexts. The module draws on a mixture of literature from philosophy, the natural and social sciences, and the corporate world (Google, Facebook, etc.) to build a conceptual toolbox that will allow you to perform such critical reflection. In the process you will also learn how to apply philosophical/ethical analyses to complex practical issues.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. apply a broad variety of conceptual tools for analysing the nature of experimentation in contemporary research
• 2. critically assess a case study of experimental practice

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 3. demonstrate in writing and orally competence in using major theoretical perspectives and concepts in philosophy and how they apply to real-world cases
• 4. illustrate the role and importance of detailed empirical knowledge for philosophical understanding

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 5. demonstrate ability to think, write, and argue logically both in discussions and in written assignments
• 6. reconsider your personal understanding of experimentation and its place in your own culture/discipline

Syllabus plan

Whilst the module’s precise content will vary from year to year, it is envisaged that the syllabus will cover some or all of the following themes:

• The experimental landscape - why an epistemology of experiment? Why an ethics of experiment?
• Experimental data: why does it matter?
• Reliability of experimentation: how do we know when we have “good” data?
• Doing experiments with animals: Epistemic and ethical issues raised by animal research
• Doing experiments with people: The clinical trial and the problem of randomisation
• The question of consent in the digital age
• The ethics of A/B testing - unconstrained power for private corporations?
• AI and Big Data in science: Challenge or opportunity?
• Open Science and Open Data: open to whom?

Learning activities and teaching methods (given in hours of study time)

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

Details of re-assessment (where required by referral or deferral)

Indicative learning resources - Basic reading

Bertolaso, M. and Sterpetti, F., 2020. A Critical Reflection on Automated Science. Springer International Publishing.

Iltis, A.S. and MacKay, D., 2021. The Oxford Handbook of Research Ethics. Oxford University Press.

Issenberg, S., 2012. The victory lab: The secret science of winning campaigns. Crown Publishing.

Kohavi, R., Tang, D. and Xu, Y., 2020. Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press.

Radder, H. (Ed.)., 2003. The Philosophy of Scientific Experimentation. University of Pittsburgh Press.

Salganik, M.J., 2019. Bit by bit: Social research in the digital age. Princeton University Press.

Key words search

Philosophy of Experimentation; Research ethics; Data science; Artificial Intelligence