AI & Digital Health Guides
AI and digital-health tools can be useful while still introducing uncertainty, verification problems, privacy tradeoffs, or overconfident claims. These guides focus on what a tool is actually doing, what evidence supports it, and how much reliance is appropriate for the stakes of the task.
AI & digital health
Practical explanations of health technology, AI, wearables, and responsible interpretation.
AI Health Advice: What It Can Help With and Where It Needs Guardrails
A balanced guide to AI health advice: useful tasks, important limitations, privacy and bias concerns, and how to match reliance to the stakes of a decision.
Evidence-informed analysisCan AI Personalize Exercise Programs? What Good Personalization Requires
AI can adjust exercise programs, but meaningful personalization requires good inputs, a clear objective, feedback, and rules that distinguish signal from noise.
Product checklistHow to Evaluate a Health App’s AI Claims Before You Trust Them
A practical checklist for evaluating AI claims in health and fitness apps: intended use, validation, data, personalization, uncertainty, privacy, and risk.
System walkthroughHow Wearables Turn Sensor Data Into Health and Fitness Advice
A step-by-step explanation of how wearable sensors become familiar metrics such as sleep, calories, recovery, stress, and readiness, and where uncertainty enters.
Practical explainerWhat Is Digital Health? Apps, Wearables, Telehealth, AI, and More
A practical explanation of digital health, including apps, wearables, telehealth, AI, remote monitoring, and how to judge what a tool is actually for.
Academic AI
Research-focused guides to AI policies, citation verification, literature reviews, summaries, and scientific judgment.
Can You Use AI in Graduate School? Start With the Rules for the Specific Task
A practical framework for graduate students evaluating whether AI use is permitted for a course, assignment, thesis, research task, or professional activity.
Verification workflowHow to Fact-Check AI-Generated Citations Before They Enter Your Research
A step-by-step method for checking whether an AI-generated citation exists, matches its claimed source, and actually supports the statement attached to it.
Workflow analysisCan AI Help With a Literature Review? Useful Tasks, Risks, and Boundaries
Where AI can assist a literature-review workflow, where it can introduce errors, and why search coverage, source verification, and synthesis still require explicit methods.
Reliability guideHow Reliable Are AI Research Summaries?
Why an AI summary can sound accurate while missing study design, qualifiers, effect sizes, limitations, or even factual details, and how to verify one efficiently.
Research workflow frameworkUsing AI for Research Without Outsourcing Scientific Judgment
A task-based framework for deciding which research activities can be assisted by AI and which still require direct human judgment, verification, or domain expertise.