How can the BBC deploy personalised media content recommendations responsibly?

MacLaren, James, Stewart (2024). How can the BBC deploy personalised media content recommendations responsibly? University of Birmingham. Ph.D.

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Abstract

It is well observed that recommender systems are one of the main success stories in the development of algorithmically driven technologies, and they are now adopted by many digital media companies for the personalisation of their content. The BBC is also in the process of deploying recommender systems to personalise the distribution of their media content. However, it is important that we ask how the BBC is able to deliver personalised media content recommendations responsibly, because unlike other media companies also deploying recommender systems, the BBC has a unique body of responsibilities. In this study we set out to identify what these responsibilities are and by defining responsibly as a combination of role responsibility, grounded on the BBC’s role as the nation’s primary public service broadcaster established by Parliament and accountable to the public, and legal responsibility, the sum of relevant laws and regulations, we are able to gather a clear list of the BBC’s responsibilities. I distil this list down to four core responsibilities, derived from two sources: a) political philosophy, and b) jurisprudence about the importance of speech in a democratic society, and ground them in a liberal democracy under the rule of law. These core responsibilities are to
support the place of democratic deliberation, our need for epistemic trust, our recognition of difference, and the protection of our human rights and the development of our human capabilities. By applying this framework, I am able to articulate what it means for the BBC to deploy recommender systems responsibly. In turn I will also use this framework as a tool to assess and evaluate the current BBC’s practices and operations in deploying recommenders, and ultimately to propose suggestions as to how the BBC can deploy recommenders more in line with its responsibilities.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):