What "AI" Means in This Course | AI Learning Guide

The list on this page is deliberately short, because the useful meaning of AI here is narrow. Pattern finding is the search for regularities in data too large to read by hand. Prediction turns a pattern into a ranked guess about a new case — a guess that tells people where to look first, not what will certainly happen. Automation takes over the repetitive, rule-based work that never stops arriving. The note underneath is the part people skip: the output is only as good as the data behind it, and none of this removes the need for human judgment.

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Three capabilities, and what each is good for

Pattern finding: scanning large collections of past trials or patient records for regularities that are impractical to spot by hand.
Prediction: using those regularities to estimate something about a new case, such as dropout risk or slow enrollment at a site.
Automation: performing repetitive, rule-based tasks — consistency checks, data extraction, formatting — continuously and without fatigue.

Two boundaries to keep in mind

AI changes what people spend their time on, not whether judgment is needed. And every output is only as good as the data behind it: sparse, inconsistent, or biased records produce patterns and predictions with the same problems.