Responsible Machine Learning in the Public Interest

Published: 1 January 2018

主播大秀 Research & Development is working with colleagues across the 主播大秀, as well as academic and expert institutions, to develop Machine Learning - and data-enabled technologies more generally - in ways that reflect and uphold core 主播大秀 values and support the 主播大秀 in delivering its remit.

Project from 2018 - present

Three people look at a wall of photographs

Why it matters

Machine learning (ML) has transformative potential for across various sectors such as health, education, media and transport - but this disruptive potential brings with it a set of societal challenges and raises important questions about the broader social implications and consequences of the technology.

The 主播大秀 is currently developing machine learning applications and capabilities, and 主播大秀 Research & Development is exploring potential future applications of artificial intelligence (AI) in the media. The risk of unintended societal consequences from ML has been well illustrated by recent where ML has been shown to make decisions that are or. The opacity of many of these systems further complicates this problem, and there is a lack of clarity in many cases as to where resides in these complex socio-technical systems. The 主播大秀 is committed to anticipatory, evaluative and proactive research to advance machine learning in the public interest.

Just as our broadcasting and journalism services are built on a number of fundamental principles, based on our public mission (...) the AI services that we build will have these same principles at their heart'

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This work programme aims to deepen our knowledge of the key challenges facing the media industry, with a specific focus on public service broadcasting to help keep the 主播大秀 at the forefront of debates, developments and best practice. Our research agenda aims to develop an approach to ML where , among others - are embedded and preserved in future development, application and evaluation of machine learning technologies and systems and automated systems more generally.

Current areas of work

Responsible AI and public service media
Intelligible AI by design
Public service approaches to personalisation and recommendation systems
Public understandings of AI and attitudes/expectations about the use of AI in the media

Following the 2017 主播大秀 conference on Artificial Intelligence and Society, 主播大秀 R&D, in collaboration with key across the 主播大秀, conducted scoping work into current debates about ethics and machine learning. We attended several key events, including at the Royal Society, the organised by TechUK, and we conducted a comprehensive literature review on the topic. This work culminated in a scoping report on the topic: 'The case for ethical machine learning at the 主播大秀'. This scoping work informed to the and made recommendations for a 主播大秀 research agenda to advance work in this area.

These recommendations have now been formalised into the following programme of research:

Responsible AI and Public Service Media: We are building case studies of ML at the 主播大秀 to identify issues and necessary responses to help ensure fairness, transparency and accountability in workflows and systems. We are also supporting academic research into AI, media and bias to inform our work around responsible AI in the public sector.
Intelligible AI: We are interviewing industry stakeholders about ML and AI systems at the 主播大秀, and we are exploring key requirements for explainability.
Public Service Personalisation: We are investigating approaches to public service recommendations and personalisation that align with 主播大秀 values, for example, by fostering principles of diversity exposure. This extends to considering new ways to articulate and measure public service value in these systems.
Audience Research: We are researching audience understandings, attitudes and expectations around automated decisions, ML and the media.
Convening an internal and external debate: We are working with key people across the wider 主播大秀 to convene internal discussion forums and helping our colleagues in the 主播大秀 Blue Room and 主播大秀 Academy organise the 'AI, Society and the Media' conference, including an 'AI, media diversity' networking event hosted by the 主播大秀 women in STEM network.

How to get involved

This is a 主播大秀 Research & Development programme of work done in collaboration between . Our approach is interdisciplinary and collaborative. If you are actively working in this area and want to share this work with us or think there might be opportunities to collaborate, we want to hear from you.