AI’s Blind Spots in Healthcare

The article serves as a crucial warning to clinicians regarding the limitations of "Dr. AI," cautioning that significant blind spots can easily mislead patients who place too much trust in its answers. A primary limitation is access: AI models are largely restricted to open-access journals, leaving approximately 75% of medical literature inaccessible due to subscription paywalls. When full text is blocked, AI often defaults to abstracts, which is highly problematic. Studies show that nearly 32% of abstracts contain errors, omissions, or "spin" that distorts conclusions, sometimes resulting in a 39% discordance between the abstract and the full report. Relying on these summaries means AI guidance can rest on shaky ground. Furthermore, identifying deep methodological weaknesses in full-text studies—such as biased designs or underpowered samples—requires domain expertise and critical appraisal skills that currently exceed AI’s abilities. For chiropractic practice, this means patients may arrive with convincing but weakly supported AI conclusions about back pain or cervical manipulation safety. Clinicians must counter this by clarifying context, ensuring decisions are grounded in sound clinical judgment, and always verifying AI claims by demanding citations and direct links to the full study.