Data and technology affect all aspects of the ±«Óãtv, from our editorial operations and outputs to how audiences can discover and access our services and content. The ±«Óãtv needs to be informed early about the editorial, ethical and social implications and impacts of uses of data and emerging technologies in order to innovate confidently and leverage these technologies in the public interest. The Responsible Innovation (RI) team works with experts across the ±«Óãtv, academia and industry to deliver timely research to help the ±«Óãtv identify, understand and respond to these challenges.
Project from 2023 - present
What we're doing
Our programme of work includes:
- Risk scanning around new and emerging technologies
- Fundamental research examining emerging issues and knowledge gaps
- Engagement and consultative/deliberative work with people likely to be impacted
- Guidance, policy and tools to help support teams in innovating responsibly
- Partnerships that promote interdisciplinarity to advance responsible innovation and technology inside and outside the ±«Óãtv
Our work focuses on these fundamental areas for the ±«Óãtv:
- Public values, data & AI
- Personalisation and the public interest
- Digital inclusion and civic participation
- Measuring public value
Examples of our work include:
- A , focus groups and a citizen jury on public views on uses of data and data management models informing the ±«Óãtv’s work into responsible data practices and new models of data stewardship.
- Interviews and participatory workshops with journalists on AI in the newsroom, informing the ±«Óãtv’s approach to engaging journalists in technology development and .
- A workshop series culminating in a looking at the ethics of AI in relation to personalisation, informing research and development into flexible media.
Why it matters
In R&D we develop, design or deploy technologies - increasingly utilising data - for the ±«Óãtv. This is part of the ±«Óãtv’s charter and remit. However, innovation is by its very nature uncertain and it's not always clear ahead of time what the effects will be. No one sets out to develop or innovate irresponsibly, but even with the best intentions, unanticipated or unintended consequences can result from these efforts. It is vital that we adopt rigorous practices, processes and methodologies that can help us understand the implications and impacts of data and technology for public service media ahead of time, so we can move confidently.
Our goals
Responsible Innovation is a collective endeavour - we achieve this by helping build capacity and capabilities to do this well at the ±«Óãtv. Our goal is to collaborate with others to deliver research, guidance and tools that can help identify, understand and respond to emerging challenges, equipping the ±«Óãtv to act and make informed decisions in a responsive fashion.
How it works
We recognise that the big challenges we face today are not technical ones but are socio-technical; they are about the relationships between people, technology and society. We approach all our work through this lens, in conjunction with the ±«Óãtv’s role and values. We adopt an anticipatory, interdisciplinary and participatory approach to examining the societal, ethical and editorial implications of data and technology:
- Anticipatory - we examine potential implications and issues ahead of time
- Interdisciplinary - we bring a social perspective to technology and innovation, drawing on interdisciplinary expertise, theories and methods to address emerging challenges
- Participatory - we engage and involve diverse groups with a focus on ensuring the views of those who will be affected by technology are part of the conversation
Outcomes
Through our research and wider engagement activity, the ±«Óãtv is better equipped with knowledge and insight to inform decisions about our use of, and approach to, existing and emerging technologies. This helps ensure that ±«Óãtv technology and innovation work continues to be responsive to ethical issues and risks, societal expectations and regulatory changes.
We’d like to further credit our ±«Óãtv collaborators and affiliated researchers (academic fellows, PhD researchers and interns) who work with the Responsible Innovation team.
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Further reading
- ±«Óãtv R&D - The ±«Óãtv’s Machine Learning Engine Principles
- ±«Óãtv R&D - Responsible Machine Learning in the Public Interest
- ±«Óãtv R&D - 5 things we learnt about the barriers we face and bridges we must build to ensure Responsible AI
- ±«Óãtv R&D - Public Service Internet
