Artificial intelligence (AI) is often celebrated for revolutionizing endoscopic procedures—boosting detection rates and streamlining clinical workflows. But recent research is sounding a warning: could routine use of artificial intelligence be unintentionally eroding the very diagnostic skills it’s meant to augment?
Let’s unpack the emerging evidence, implications, and strategies for a balanced augmented future.
A Real‑World Study Raises Alarm Bells
A large observational study involving over 1,400 colonoscopies in Poland observed that after artificial intelligence tools were introduced, the adenoma detection rate (ADR) during non-AI procedures dropped from 28.4 % to 22.4 %, even though AI-assisted ADR stood at about 25.3 %. This roughly six percent absolute (or 20% relative) decline in detection when AI wasn’t in use suggests a concerning possibility: endoscopists may be losing proficiency when they rely too heavily on automation.
Automating, But at What Cost? Understanding De‑skilling
Experts draw parallels to the “Google Maps effect”—where overdependence on navigation tools impairs our innate sense of direction. Similarly, reliance on such automation may disrupt clinicians’ cognitive patterns: attention shifts, diminished peripheral vigilance, and altered gaze behaviors could all contribute to missed lesions. Behavioral observations even show users fixate more on AI-highlighted regions, potentially neglecting surrounding tissues.
AI’s Dual Role: Training Tool or Crutch?
Artificial intelligence isn’t solely a risk—it can elevate diagnostic skill, especially among novices. Research shows that trainee endoscopists using automation can perform on par with experienced experts in polyp detection, whereas without automation, their performance remains inferior. These dual effects highlight a delicate balance: artificial intelligence can act as a powerful training aid but, with overuse, a dangerous dependency.
Human Factors & Cognitive Pitfalls to Watch
Multiple human‑automation interaction challenges are at play:
- Automation bias: Clinicians may default to automation outputs, even when flawed.
- Alarm fatigue: Frequent or unnecessary alerts may dull responsiveness.
- Anchoring bias: Providers may inadequately adjust from automation-provided advice, even if mistake.
These patterns underscore the importance of designing automation workflows that maintain active clinician engagement, rather than encouraging disengagement.
Perspectives & Acceptance Among Endoscopists
Despite concerns, doctors generally view automation positively—most express optimism about its role in raising performance and patient care quality. However, a range of worries emerges: operator dependence, extended procedure times, high costs, regulatory ambiguity, and medico‑legal implications all rank highly among practitioners’ concerns.
Implementing Tech Wisely: Strategies to Prevent De‑skilling
How can the medical community harness AI benefits while avoiding skill erosion?
- Mandatory non‑AI practice periods: Maintaining human diagnostic capability by alternating artificial intelligence and manual procedures.
- Human‑centered AI design: Interfaces must minimize false positives, reduce cognitive load, and preserve clinician attention.
- Behavioral and training research: Study visual habits, reaction times, and long‑term skill retention post‑AI adoption.
- Balanced integration: Use automation as an assistant—not a replacement—and ensure professionals retain the ability to diagnose independently.
- Ethics, regulation & guidelines: Clear protocols must govern automation use, especially as reliance grows.
Training the Next Generation of Endoscopists
Medical training is also affected by AI’s integration. Future specialists may train in an environment where tech tools are readily available, potentially reducing opportunities to hone independent diagnostic skills. Training programs must adapt by ensuring that trainees first develop strong foundational skills without artificial intelligence assistance before gradually incorporating technology. This will help preserve their ability to function effectively with or without automated systems.
Final Thoughts: Striking the Right Balance
artificial intelligence in endoscopy is a potent ally—enhancing detection, standardizing performance, and accelerating learning. But its rising dominance brings a real risk: erosion of foundational clinical skills. The Lancet‑based research serves as a wake-up call. Responsible integration must prioritize human expertise, enforce skill preservation, and foster an ecosystem where automation and clinicians truly partner, rather than compete.
Let’s embrace innovation—but never at the cost of clinical acumen.
