Public Engagement Emerges as Key Factor on “AI in Healthcare Development”

Artificial intelligence (AI) stands at the forefront of contemporary debates, marked by a lack of consensus in its definition. Professor John McCarthy, a key figure in AI’s founding, defines it as ‘the science and engineering of making intelligent machines.’ In other perspectives, AI is portrayed as the evolution of computer algorithms to perform tasks aligned with human intelligence, including learning and problem-solving.

The application of AI in medical and healthcare domains has surged in recent years, with notable examples such as AI imaging in radiology and the use of medical robots like Da Vinci’s robotic surgery system. These technologies leverage big data and deep learning to enhance diagnostic accuracy and streamline medical processes. 

A systematic review and qualitative meta-synthesis, conducted using the meta-aggregation approach by the Joanna Briggs Institution (JBI), delved into the public’s attitudes and perceptions towards medical AI. The study, spanning from September 2021 to January 2022, adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations.

The review employed a comprehensive three-step method: an initial limited search on Medline and CINAHL, a detailed analysis of articles’ titles, abstracts, and index terms, and an extensive search across various databases. The inclusion criteria encompassed studies published in English and Chinese, without restrictions on publication dates. 

The meta-synthesis incorporated twelve qualitative studies, resulting in 39 findings categorized into 12 groups and distilled into three synthesized findings. The analysis highlighted the public’s recognition of the convenience and benefits of medical AI. However, it also underscored prevalent concerns regarding its implementation, such as issues related to personal privacy, data security, and regulation.

Public opinions on enhancing the credibility and acceptability of AI were also noted, providing valuable insights for future research, development, and application of medical AI. The pervasive use of AI in healthcare, spanning disease screening, diagnosis, risk warning, adjuvant therapy, and intelligent healthcare, was evident in the studies included in the analysis.

Additionally, AI’s role extended to the research and development of new drugs and the response to the COVID-19 pandemic. The accumulation of vast medical data and improvements in hardware computing capacity facilitated the establishment of data-driven deep learning systems. This advancement enables medical AI to address the diverse needs of the public in healthcare more efficiently and with higher quality. 

Despite the public’s acknowledgment of the advantages of medical AI, concerns arise from the ‘black-box’ attributes of machine learning (ML) and deep learning (DL) technologies. These systems lack the ability to explain the rationale behind their predictions, raising ethical and transparency issues.

While the meta-synthesis followed a rigorous design and adhered to the JBI meta-aggregation approach, limitations were acknowledged. The inclusion of studies published only in English and Chinese may introduce language bias, and variations in participants’ experiences with medical AI underscored the need to consider experience as a variable in future research. 

One prominent concern highlighted by the meta-integration was the public’s right to informed consent. The study suggests that medical institutions establish management systems to guide AI usage, ensuring the public’s right to informed consent, particularly for institutions with their data infrastructure.

Furthermore, health institutions are advised to comprehend the performance of their medical AI platforms, clarify their role in the diagnostic and treatment process, prevent over-reliance by medical staff, and ensure treatment safety. 

In essence, the meta-synthesis reveals that, from the public perspective, medical AI has significantly enhanced modern medical and healthcare practices. However, it has also introduced numerous social and ethical challenges. The study proposes recommendations to promote the application of medical AI from the public’s viewpoint.

Recognizing the public’s perception as a crucial driving force for the development of medical AI, the study emphasizes the importance of addressing public concerns and leveraging their insights for the continuous improvement of medical AI. Striking a balance between legal governance and ethical constraints is crucial in maximizing the advantages of AI while upholding social values such as security, fairness, and justice. 

The study provides a comprehensive understanding of the intricate dynamics surrounding medical AI, shedding light on both its transformative benefits and the ethical considerations it necessitates. It advocates for a holistic approach that involves the public in shaping the development, operation, and management of medical AI, ensuring a harmonious integration that prioritizes both technological advancements and societal values. 

Journal Reference  

Wu C, Xu H, Bai D, Chen X, Gao J, Jiang X. Public perceptions on the application of artificial intelligence in healthcare: a qualitative meta-synthesis. BMJ Open. 2023 Jan 4;13(1):e066322. doi: 10.1136/bmjopen-2022-066322.