When I saw the movie Her (Joaquin Phoenix and Scarlett Johansson, 2013), a romantic story between Theodore and a conscious operating system named Samantha it seemed an unlikely science fiction story back then. Well now, AI has infiltrated our lives in every imaginable way, and it is here to stay. It is important to think about how healthcare delivery is changing and may continue to change because of this technology.
First the good part:
Superior diagnostic accuracy: Artificial Intelligence has been demonstrated to have high accuracy in diagnostic imaging, disease diagnosis, and treatment planning. In many instances where it has been tested, it has exceeded human performance in specific tasks like diabetic retinopathy screening and melanoma detection.
Physician support for clinical decision making: AI-powered tools can analyze huge database in seconds and identify diagnosis and thus improve decision making abilities of physicians.
Improved patient engagement: AI sources can provide vast amount of patient education, and can train patients to self monitor and in some cases provide proactive interventions.
Can improve access to care: through telemedicine, mobile diagnostics, and wearable health technologies, AI can improve access to care when live healthcare providers may not be available.
Can improve efficiency in administrative tasks: can automate and streamline complicated tasks such as revenue cycle management, appointment scheduling, clinical documentation, reducing overhead cost, and minimizing human error.
The concerning part:
Privacy risk: AI systems require vast amounts of sensitive patient data, increasing risks of breach in privacy.
Bias: AI accuracy depends of available data, so bias can infiltrate in training datasets for underrepresented or marginalized populations, and potentially lead to further healthcare inequities and disparities in diagnostic accuracy across different patient groups.
Errors:Most AI tools lack evaluation through randomized controlled trials, and their effectiveness depends heavily on the human-computer interface, user training, and deployment setting
Ethical and regulatory issues include unclear accountability when adverse events occur, lack of transparency in AI decision-making (“black box” problem), and fragmented regulatory frameworks globally
Job displacement concerns persist, reduced professional autonomy, and AI’s inability to deliver empathic care.
Risks of skill degradation among trainees who become overly dependent on AI assistance.
No matter what side of the fence AI’s overall impact falls, we are in for quite a ride in healthcare in the time of AI.