Data Governance in AI - Enabled Healthcare Systems: A Case of the Project Nightingale

Asian Journal of Research in Computer Science | Vol. 17, Issue 5, Page 85-107; 2024

23 Pages Posted: 11 Mar 2024

See all articles by Aisha Temitope Arigbabu

Aisha Temitope Arigbabu

University of the Cumberlands

Oluwaseun Oladeji Olaniyi

University of the Cumberlands

Chinasa Susan Adigwe

University of the Cumberlands

Olubukola Omolara Adebiyi

Ulster University - Centre City House

Samson Abidemi Ajayi

University of Ilorin

Date Written: March 8, 2024

Abstract

The study investigates data governance challenges within AI-enabled healthcare systems, focusing on Project Nightingale as a case study to elucidate the complexities of balancing technological advancements with patient privacy and trust. Utilizing a survey methodology, data were collected from 843 healthcare service users employing a structured questionnaire designed to measure perceptions of AI in healthcare, trust in healthcare providers, concerns about data privacy, and the impact of regulatory frameworks on the adoption of AI technologies. The reliability of the survey instrument was confirmed with a Cronbach's Alpha of 0.81, indicating high internal consistency. The multiple regression analysis revealed significant findings: a positive relationship between the awareness of technological projects and trust in healthcare providers, countered by a negative impact of privacy concerns on trust. Additionally, familiarity with and perceived effectiveness of regulatory frameworks were positively correlated with trust in data, while perceptions of regulatory constraints and data governance issues were identified as significant barriers to the effective adoption of AI technologies in healthcare. The study highlights the critical need for enhanced transparency, public awareness, and robust data governance frameworks to navigate the ethical and privacy concerns associated with AI in healthcare. The study recommends adopting flexible, principle-based regulatory approaches and fostering multi-stakeholder collaboration to ensure the ethical deployment of AI technologies that prioritize patient welfare and trust.

Keywords: AI-enabled healthcare, data governance, patient privacy, regulatory frameworks, trust in healthcare, project nightingale, ethical AI development, healthcare data security

Suggested Citation

Arigbabu, Aisha Temitope and Olaniyi, Oluwaseun Oladeji and Adigwe, Chinasa Susan and Adebiyi, Olubukola Omolara and Ajayi, Samson Abidemi, Data Governance in AI - Enabled Healthcare Systems: A Case of the Project Nightingale (March 8, 2024). Asian Journal of Research in Computer Science | Vol. 17, Issue 5, Page 85-107; 2024, Available at SSRN: https://ssrn.com/abstract=4752897

Aisha Temitope Arigbabu

University of the Cumberlands ( email )

Oluwaseun Oladeji Olaniyi (Contact Author)

University of the Cumberlands ( email )

6178 College Station Drive
Williamsburg, KY 40769
United States

HOME PAGE: http://www.ucumberlands.edu

Chinasa Susan Adigwe

University of the Cumberlands

Olubukola Omolara Adebiyi

Ulster University - Centre City House

Samson Abidemi Ajayi

University of Ilorin ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
322
Abstract Views
835
Rank
183,024
PlumX Metrics