18 citations · 59 across the 10 of their papers we have counts for
10 papers
Identifying Roles, Requirements and Responsibilities in Trustworthy AI Systems
Iain Barclay, Will Abramson
Artificial Intelligence (AI) systems are being deployed around the globe in critical fields such as healthcare and education. In some cases, expert practitioners in these domains a…
Providing Assurance and Scrutability on Shared Data and Machine Learning Models with Verifiable Credentials
Iain Barclay, Alun Preece, Ian Taylor +2
Adopting shared data resources requires scientists to place trust in the originators of the data. When shared data is later used in the development of artificial intelligence (AI)…
Tokenising behaviour change: optimising blockchain technology for sustainable transport interventions
Iain Barclay, Michael Cooper, Alun Preece +2
Transport makes an impact across SDGs, encompassing climate change, health, inequality and sustainability. It is also an area in which individuals are able to make decisions which…
A framework for fostering transparency in shared artificial intelligence models by increasing visibility of contributions
Iain Barclay, Harrison Taylor, Alun Preece +3
Increased adoption of artificial intelligence (AI) systems into scientific workflows will result in an increasing technical debt as the distance between the data scientists and eng…
Towards a Modelling Framework for Self-Sovereign Identity Systems
Iain Barclay, Maria Freytsis, Sherri Bucher +3
Self-sovereign Identity promises to give users control of their own data, and has the potential to foster advancements in terms of personal data privacy. Self-sovereign concepts ca…
Certifying Provenance of Scientific Datasets with Self-sovereign Identity and Verifiable Credentials
Iain Barclay, Swapna Radha, Alun Preece +2
In order to increase the value of scientific datasets and improve research outcomes, it is important that only trustworthy data is used. This paper presents mechanisms by which sci…
Quantifying Transparency of Machine Learning Systems through Analysis of Contributions
Iain Barclay, Alun Preece, Ian Taylor +1
Increased adoption and deployment of machine learning (ML) models into business, healthcare and other organisational processes, will result in a growing disconnect between the engi…
Towards Traceability in Data Ecosystems using a Bill of Materials Model
Iain Barclay, Alun Preece, Ian Taylor +1
Researchers and scientists use aggregations of data from a diverse combination of sources, including partners, open data providers and commercial data suppliers. As the complexity…
A Conceptual Architecture for Contractual Data Sharing in a Decentralised Environment
Iain Barclay, Alun Preece, Ian Taylor +1
Machine Learning systems rely on data for training, input and ongoing feedback and validation. Data in the field can come from varied sources, often anonymous or unknown to the ult…
Defining the Collective Intelligence Supply Chain
Iain Barclay, Alun Preece, Ian Taylor
Organisations are increasingly open to scrutiny, and need to be able to prove that they operate in a fair and ethical way. Accountability should extend to the production and use of…