Study guide: Reproduce Analyses and Evaluate Responsible AI
Audit draft: "12 people completed; the tool caused 80%success; it won a prize." Evidence contains 12 completed attempts of 15 and nothing else. Rewrite it and state a review route.
Ideas to explain in your own words
- An analysis can depend on data versions, code versions, libraries and configuration. Recording those inputs helps another learner reproduce a result. A matching output from unknown inputs does not establish that the same method was used. The lesson supplies fictional version labels and paper records rather than installing software.
- Re-running a method can reveal whether a result follows from its stated inputs. Different inputs or a different random setup can legitimately change output. A discrepancy should prompt investigation of the data, method and environment. Neither agreement nor disagreement automatically establishes which causal story is true.
- A generative system may produce fluent text without a reliable basis for each claim. Verification should trace claims to supplied evidence and distinguish quotation, inference and unsupported assertion. The exercise uses an original invented draft and evidence notes; no AI account or real confidential input is required.
- Responsible decision design identifies who reviews a system output, what evidence is used, and how a person can question an error. Human review is not automatically effective; it needs an actual task, authority and process. The fictional policy supplies these roles rather than claiming a compliant real institution.
Useful vocabulary
- reproducibility record
- The inputs and environment needed to repeat a method.
- generated claim
- A statement produced by a generative system.
- contestability
- A route to question and correct a decision.
Watch your reasoning
- A screenshot of a result does not preserve the method that produced it.
- Matching one number does not establish every output or real-world claim.
- Fluent wording is not proof that a reference exists or supports the claim.
- A human merely seeing an output does not prove a meaningful review occurred.
A worked review example
Input dataset labeleddata-v3. Which reproducibility input is described? The supported answer is Data revision. Record data, code, configuration and relevant environment together before comparing outputs. A screenshot of a result does not preserve the method that produced it. An analysis can depend on data versions, code versions, libraries and configuration. The supplied facts, rather than an assumed real-world detail, determine this paper case. Compare the recorded action or value with the stated rule before choosing an answer. Assigned reviewer checks cases before action. Which documented policy part is described? The supported answer is Reviewer responsibility. Specify reviewer, evidence and revision route instead of using human-reviewed as an unsupported label. A human merely seeing an output does not prove a meaningful review occurred. The supplied facts, rather than an assumed real-world detail, determine this paper case. Compare the recorded action or value with the stated rule before choosing an answer.
Make a practice plan
- Make a four-row summary, one row for each lesson, with its computing idea and one worked decision.
- Explain one tempting mistake using the actual supplied example.
- Complete the new unit review before consulting its explanations.
- Try the transfer task on paper and compare your evidence against the model response.