ResearchReportExternalBody 372 views 116 downloads
Exploring the potential for automation and artificial intelligence in the regulation of the health and social care professions in the United Kingdom
Swansea University Author: Marty Chamberlain
PDF | Version of RecordDownload (322.18KB)
This horizon scanning Wellcome Trust funded project was tasked with exploring the impact of currentadvances in computing and information processing, in the field of professional regulation in the UnitedKingdom.Although key advances in mathematics, information processing, machine learning, automation...
No Tags, Be the first to tag this record!
This horizon scanning Wellcome Trust funded project was tasked with exploring the impact of currentadvances in computing and information processing, in the field of professional regulation in the UnitedKingdom.Although key advances in mathematics, information processing, machine learning, automation andartificial intelligence are beginning to disrupt and transform traditional practices in health and social carein the United Kingdom, the project found that the same cannot be said in relation to the field of professionalregulation.At present, the focus of the regulatory reform agenda has been on promoting a more joined-up, risk-adverseand public-interest focused model of ‘right touch’ regulation. However, the project concluded that thisagenda will not by itself enable regulators to embed current and future developments in automation andmachine learning within their organisational structures.The fractured and decontextualized nature of the current regulatory data lake means that despite their recentefforts to develop their respective intelligence and insight agendas to improve the predictive risk templatesused to identify threats to public safety, at present regulators possess a very low level of readiness in relationto the information capture and analysis systems required by algorithmic digital technologies.It is the key recommendation of the project that action be taken to standardize current regulatory datawarehouse information capture and processing systems, with a view to support the development of a shareddata lake between regulators. Furthermore, this warehouse should be curated by an independent statutorybody, such as the Professional Standards Authority, to meet public-interest expectations and GDPRrequirements, particularly in relation to the future development of regulatory predictive risk-templates.
Briefing Report - Project funded by the Wellcome Trust
Regulation, Computing, Information Processing, Big Data
Faculty of Humanities and Social Sciences