Among the many ways organizations deploy Generative AI, using it as an instrument for rigorous scientific research offers unique potential for breakthrough discoveries. The scientific approach enables GenAI to create new knowledge, not just retrieve and apply existing knowledge—illuminating the 'why' behind the 'what.' A scientific approach enables GenAI to power discovery platforms—revealing underlying principles that generalize beyond individual cases.
Identify Knowledge Frontiers
Use AI to systematically map what we don't know, revealing gaps in medical understanding
Extract Novel Measures
Transform unstructured data—clinical notes, images, sounds—into quantifiable insights and predictive features
Generate Testable Hypotheses
Use pattern recognition to propose new research directions grounded in observed data
We focus on using GenAI, which is often black box, to create knowledge that is transparent and explainable.
Why Explainability Matters
- Regulatory Compliance: FDA, SEC, and industry regulators require transparent decision pathways
- Business Trust: Stakeholders need to understand AI-driven decisions affecting revenue and strategy
- Scientific Validity: Reproducibility and peer review demand interpretable methods
- Risk Management: Financial and operational decisions require clear audit trails and accountability
- Patient Safety: In healthcare, transparent predictions are ethically essential when lives are at stake
- Continuous Improvement: Explainable models reveal when patterns shift, enabling timely system updates
Diabetes Control
Expected: Lower A1c is always better
Reality: Pushing A1c too close to normal increases mortality in older adults with type 2 diabetes
App Engagement
Expected: More features increase user retention
Reality: Feature-heavy apps often have lower retention than simple, focused alternatives
Sample Size Planning
Expected: Larger sample sizes always yield better research outcomes
Reality: Beyond optimal thresholds, larger samples can detect trivial differences that aren't practically meaningful
Hospital Readmissions
Expected: Longer hospital stays ensure better recovery
Reality: Patients discharged slightly earlier often have lower readmission rates due to reduced exposure to hospital-acquired conditions
Employee Incentives
Expected: Higher bonuses always boost performance
Reality: Excessive rewards can decrease intrinsic motivation and creative problem-solving
Medication Adherence
Expected: More frequent dosing reminders improve compliance
Reality: Too many reminders create alert fatigue, actually decreasing medication adherence