Most patients on board with radiology AI, though job loss, data privacy are top concerns

Most patients are on board with utilizing artificial intelligence in radiology, though some have concerns about data privacy and job displacement, according to a new a new analysis. 

AI’s rapid advancement has generated significant debate among patients and healthcare professionals. One researcher sought to gauge public sentiment, analyzing social media posts on Reddit and X (formerly Twitter). The study included over 1,000 posts logged between 2019 and 2024, with the results published Sept. 23 in the journal Cureus [1]. 

The sentiment analysis revealed that about 55% of comments expressed positive perceptions around AI in medical imaging, “emphasizing its potential to enhance diagnostic accuracy and efficiency.” Meanwhile, about 35% expressed neutral feelings about AI in radiology while 10% were negative, unearthing concerns about job loss, ethics and privacy. 

“As AI continues to evolve and its applications in medical imaging expand, addressing these concerns will be crucial for ensuring its responsible and effective use,” Mansour Almanaa, PhD, a faculty member and assistant professor in the radiology department at King Saud University in Saudi Arabia, wrote Monday. “The identified themes emphasize the importance of developing clear regulatory frameworks and ethical guidelines that ensure patient safety and data security. Equally important is the need for ongoing education and training for healthcare professionals, enabling them to adapt to AI's evolving role in medicine. By fostering a collaborative approach between technology developers, healthcare providers, and policymakers, the medical community can navigate the challenges posed by AI, ultimately leveraging its potential to improve patient care and advance the field of medical imaging.”

To perform the analysis, Almanaa searched the two social media platforms for 20 different phrases including “radiology,” “computed tomography,” “AI,” and “medical imaging.” He used the Python program to winnow nearly 4,000 posts down to the final tally, eliminating hundreds of duplicates and unrelated messages. Meanwhile, the public sentiment analysis was performed using the VADER (Valence Aware Dictionary and sEntiment Reasoner) tool in Python, designed to detect attitudes expressed in social media. 

Ethical and privacy issues were frequently mentioned, Almanaa noted. These included the transparency of AI decision-making processes and accountability for artificial intelligence-generated errors. 

“The biggest issue is legal liability,” one social media user wrote. “If a human radiologist makes a bad diagnosis, it falls on them and their license. If AI makes a mistake, it falls on the software designer, as well as the hospital which decided to replace human radiology. That can be significantly more expensive as a lawyer could argue negligence on the part of the hospital to rely on such services.”

Users also shared concern about AI potentially replacing human radiologists and other healthcare professionals. However, the sentiment analysis indicated that the theme of “job displacement” also produced positive comments. Many social media users recognized “the potential for AI to complement and enhance the work of radiologists rather than replace them entirely.” 

“Workflow efficiency” was another “prominent” theme, with social media users noting that AI has the potential to automate routine tasks such as image sorting and preliminary analysis. This could allow radiologists to focus more on complex cases and reduce overall workload. Almanaa additionally highlighted “trust and reliability” as a “critical” common thread, with users often questioning the dependability of this technology.

“The dilemma of AI and data reliability is something that still makes me uneasy about AI,” one individual wrote. “Machine learning is a fantastic technology, and I think we should embrace it, but we have to address the elephant in the room: What if the data we feed it with is incorrect, unreliable, or deliberately wrong?”

Almanaa believes the study findings have implications for future research and practice.

“The predominantly positive sentiment towards AI in medical imaging suggests a general acceptance of its potential benefits. However, the significant concerns about ethical issues, data privacy, and job displacement need to be addressed to foster broader acceptance and trust,” he wrote. “Future research should focus on developing and implementing robust ethical guidelines and regulatory frameworks to ensure the responsible use of AI in healthcare. Additionally, there is a need for continuous education and training for radiologists and other healthcare professionals to adapt to the evolving landscape of AI technologies.”