Human Data Interaction (HDI) is a 主播大秀 R&D programme of research that is committed to developing technologies that support digital rights in relation to personal data, and creating meaningful and accountable interactions between people, data, and digital systems.
Project from 2017 - present
Human Data Interaction (HDI) is an emerging interdisciplinary area of research that aims to put humans at the centre of the data flows in their lives by providing mechanisms for people to interact with these systems explicitly. Our HDI work is a collection of activities to help us rethink approaches to personal data that promote privacy, personal agency and public good.
Our research and development seeks to address issues and challenges by exploring new opportunities and alternatives. Our work has a strong focus on personal data but extends to include citizens鈥� interactions with broader categories of data (i.e. open/public data) as well as how production teams in the 主播大秀 use this data.
We are committed to developing digital technologies and experiences that instantiate people鈥檚 rights concerning their personal data. We aim to can support new forms of personal and public value and develop digital systems that are explainable and accountable.
Five key areas of work:
- Understanding public attitudes, concerns, and expectations around data use and automated decision making.
- Improving people鈥檚 access to personal data and creating new forms of value from this.
- Developing privacy enhancing technologies that instantiate key HDI principles and support new forms of personal and public value.
- Exploring how to make data use and its effects intelligible and meaningful to those who it concerns and impacts - extending to professionals who increasingly work with data and automated systems.
- Exploring the information, choices, controls and assistance that people need in specific everyday and professional contexts.
Why it matters
We live in a world where our interactions with digital technologies leave a trail of data and this data can be used by others in ways we are unlikely to have meaningfully consented to, or that may have unanticipated impacts on us in the future. The modern contract of trading our data for services results in a few big companies holding vast amounts of data on its users while they have limited understanding of: what data is collected about them and why; how this data is processed, shared and aggregated; what rights they have; and what recourse for action is available to them. This problematic trade-off has become the norm and has led to a catalogue of problems - not least a disenfranchised public who don鈥檛 feel they have any real understanding, say or stake in how their data is used.
Whilst some organisations may have legitimate reasons for collecting and processing personal data, or good intentions, i.e. to provide a public or useful service, the current model has been exploited by a growing data and 鈥榓ttention鈥� economy that seeks to monetise personal data for commercial gain not necessary for the benefit of individuals or the wider public.
EU regulation around personal data has been vastly strengthened under GDPR, for example through the introduction of the right to data portability, to data erasure and to an explanation when a decision has been fully automated, but there is work to be done for this to come to full fruition and become useful and meaningful to people in their daily lives.
People today increasingly deal with systems that use their personal data to make automated decisions that affect their lives. It is imperative that these systems are explainable, accountable and that we can trust that the systems are working in ways that individuals and society can understand, scrutinise, challenge and change as required.
Current Areas of Work
- Development of Technology: Experimenting with technologies like Databox - a new privacy enhancing platform that instantiates key HDI principles, exploring how they can support new forms of personal and public value.
- Design: Creating novel design patterns for consent and approaches to data portability and designing for the explainability and accountability of automated systems - exploring new workflows and processes and what information and controls people need in specific contexts and scenarios.
- Audience Research: Researching what the public understands and feels about data collection and use in specific contexts.
- Collaboration: Working with other teams across R&D and the wider 主播大秀 to identify opportunities to explore, experiment with and embed HDI approaches.
- Future Research: Collaborating with academics on interdisciplinary workshops to explore key questions and future research agendas for HDI.
Latest project, Introducing 主播大秀 Box
主播大秀 Box is a Databox-powered platform for experimenting with different models of personal data processing that addresses 主播大秀 R&D鈥檚 core priorities.
The first Box service will be a recommender that imports user data (with permission) from a range of media services, and processes it within the Databox environment to create a user profile. This can then be exported under user control to shape the suggestions offered by an enhanced media/listings application.
This will be the project's first end to end demo and will create a space to experiment with new approaches to personal data with defined use cases aimed at demonstrating new forms of audience value. Our roadmap over the next 12 months takes us towards more distinctive and ambitious new forms of value use cases, building on our existing work and partnership with the Databox team and collaborative work with colleagues across 主播大秀 Design + Engineering.
Get Involved
We want to to share our work here and collaborate with others who share our values and goals - we are already aware of many other groups and organisations actively engaged in this field. If you are working on similar projects and want to work with us, we鈥檇 love you to get in contact.
Project Team
Project updates
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Future Experience Technologies section
This project is part of the Future Experience Technologies section