The premise
AI can structure replication protocols that codify each side's predictions, decisive-test criteria, and authorship before data collection.
What AI does well here
- Format adversarial-collaboration protocols with prediction tables.
- Draft pre-specified decisive-test criteria language.
What AI cannot do
- Resolve the substantive scientific disagreement.
- Replace negotiation between the original and replication teams.
End-of-lesson check
15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-research-ai-replication-study-protocol-r6a3-creators
What is the primary capability of AI in drafting adversarial collaboration replication protocols?
- AI can resolve substantive scientific disagreements between teams
- AI can structure protocols that codify each side's predictions, test criteria, and authorship before data collection
- AI can collect and analyze the replication data without human intervention
- AI can determine which team originally conducted the correct experiment
Which of the following must be included in a properly structured adversarial collaboration replication protocol?
- A summary of the original study's methodology
- A list of previous studies that support either team's position
- The funding sources for both teams
- Each team's prediction with point estimates and confidence intervals
Why are decisive-test criteria considered invalid if they are established after seeing the data?
- Because researchers would naturally want to publish significant results
- Because post-hoc criteria cannot provide an objective test of competing predictions
- Because funding agencies require criteria to be set before studies begin
- Because statistical software only accepts pre-registered criteria
What is a fundamental limitation of AI in adversarial collaboration replication studies?
- AI cannot format prediction tables correctly
- AI cannot generate random numbers for sampling
- AI cannot replace negotiation between original and replication teams to resolve substantive disagreements
- AI cannot perform statistical analyses
What must happen before any data is collected or analyzed in an adversarial collaboration?
- The institutional review board must approve the study
- Both teams must sign the protocol agreeing to the terms
- The replication team must obtain the original data
- A third-party statistician must be hired
What distinguishes a preregistered prediction from a standard research hypothesis?
- Preregistered predictions are written in Latin
- Preregistered predictions are publicly committed to before data collection and cannot be changed
- Preregistered predictions are only used in medical research
- Preregistered predictions must include null hypothesis significance testing
In adversarial collaboration, why do both teams provide point and interval predictions rather than just directional hypotheses?
- Because journals require specific numbers
- Because intervals allow for more precise decisive-test criteria that can objectively evaluate competing predictions
- Because point predictions are illegal in most countries
- Because AI cannot process directional hypotheses
What role does negotiation play in adversarial collaboration protocols?
- Negotiation is unnecessary because AI handles all disagreements
- Negotiation is replaced by flipping a coin
- Negotiation is essential for teams to reach agreement on predictions, criteria, and procedures before data collection
- Negotiation only happens after data is collected
What is the purpose of including an authorship and dispute-resolution plan in the replication protocol?
- To prepare for how outcomes will be handled and who receives credit before disagreements arise
- To allow the AI system to make final decisions
- To satisfy funding agency requirements
- To ensure one team gets more publications
What would be a problem if only the replication team signs the protocol but the original research team does not?
- Nothing would change; one signature is sufficient
- The AI would refuse to proceed
- The protocol lacks mutual agreement, undermining the adversarial collaboration framework and the legitimacy of any decisive test
- The study could proceed but the results would be legally binding
What is the fundamental goal of adversarial collaboration in scientific research?
- To prove one team is wrong
- To reduce the cost of research
- To increase the number of publications
- To use structured disagreement and pre-specified criteria to objectively resolve scientific disputes
Which statement best describes AI's appropriate role in adversarial collaboration protocol drafting?
- AI should format and structure the protocol while humans make substantive decisions about predictions and criteria
- AI should make the final decision on which prediction is correct
- AI should collect the data since it is more objective
- AI should be excluded from the process entirely
Why is it important that predictions in adversarial collaboration are preregistered?
- Preregistration makes the study faster
- Preregistration is required by law
- Preregistration guarantees funding approval
- Preregistration prevents researchers from changing their predictions after seeing results, maintaining the integrity of the decisive test
What is a likely consequence of skipping the protocol signing step in adversarial collaboration?
- The AI would work more efficiently
- Disputes after data collection would have no pre-agreed resolution mechanism, potentially leading to unresolved conflict
- The results would automatically be published
- The study would be faster
What is the purpose of pre-registering interpretations of possible outcomes in the protocol?
- To ensure both teams agree in advance on what each possible outcome will mean for their predictions
- To increase the sample size
- To allow researchers to interpret results however they want
- To satisfy journal requirements