Trusting machines? Cross-sector lessons from healthcare & security: conference report

Abstract

RUSI and UKRI TAS Hub–Trustworthy Autonomous Systems Hub –have presented Trusting Machines? Cross-sector Lessons from Healthcare and Security. The conference was held between June 30th and July 2, 2021. Over three days of discussions, the conference was a forum to bring together academic experts, policy leaders and industry professionals to discuss how autonomous systems can be responsibly integrated into the healthcare and security sectors. With a focus on building trustworthy autonomous systems, the conference covered topics related to both healthcare and security research and identified development areas. The conference addressed a variety of case studies and current research challenges. Delegates presented and discussed the key global issues facing AI development, highlighting the competitive aspects, risks, and opportunities that both nations and organisations will face in the years and decades to come. As a result, keynote sessions, project presentations and workshops have been presented in accordance with the conference scope and discussed challenges, opportunities, and research problems of building trustworthy autonomous systems. The following report is intended for all those interested in the current challenges and constraints involved in AI development within these sectors. Additionally, the conference features numerous discussions regarding the potential for cross-sector lessons, therefore we welcome readers from the broader AI community who are seeking a concise summary of the global affairs in AI development and implementation.

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Identifiers

ORCID for Mohammad Naiseh: orcid.org/0000-0002-4927-5086

ORCID for Jediah Clark: orcid.org/0000-0002-1356-2462

ORCID for Mohammad Divband Soorati: orcid.org/0000-0001-6954-1284

ORCID for David Bossens: orcid.org/0000-0003-1924-5756

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