AI research team authorship dispute mediation summary

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-research-ai-research-team-authorship-dispute-mediation-creators

1. What is the primary purpose of using AI to generate a CRediT-style contribution summary at the start of an authorship dispute conversation?

   1. To provide a neutral starting point for discussion based on documented contributions
   2. To automatically determine who deserves first author position
   3. To eliminate the role of senior researchers in decision-making
   4. To replace the need for team meetings about authorship

2. Which taxonomy provides the standardized roles that an AI system uses to categorize research contributions?

   1. DOI
   2. CRediT
   3. ORCID
   4. H-index

3. A research team is using AI to help mediate an authorship dispute. Which task falls outside what the AI system should be asked to do?

   1. Draft a comparison table for the meeting
   2. Decide the final authorship order
   3. Map each team member's contributions to CRediT roles
   4. Surface contributions documented in commits and drafts

4. When generating a contribution summary, how should the AI system handle a role for which evidence from different team members conflicts?

   1. Mark it with [discuss in meeting] as a contested item
   2. Give the benefit of the doubt to the senior author
   3. Remove that role entirely from the summary
   4. Assign it to whoever made the first claim

5. Why is the AI-generated contribution table described as 'starting material' rather than 'a verdict'?

   1. Because authorship decisions require human judgment about intellectual contribution and team norms that AI cannot see
   2. Because universities do not recognize AI-generated documents
   3. Because AI systems are always inaccurate
   4. Because the table may contain errors that need correction

6. What does the lesson identify as a key limitation of AI in the authorship dispute context?

   1. AI cannot access digital documents
   2. AI cannot recognize text in multiple languages
   3. AI cannot generate tables or summaries
   4. AI cannot substitute for the senior author's judgment

7. Which of the following is listed as something AI does WELL in the context of authorship mediation?

   1. Decide who deserves credit without human input
   2. Map each team member's contributions to CRediT roles
   3. Enforce copyright law automatically
   4. Resolve interpersonal conflict between team members

8. The lesson states that AI 'cannot resolve interpersonal conflict.' What is the most accurate interpretation of this limitation?

   1. AI can document contributions but cannot fix damaged relationships or rebuild trust
   2. AI is legally prohibited from discussing conflicts
   3. AI will make conflicts worse
   4. AI should not be used if team members disagree

9. What specific type of output does the lesson suggest the AI should produce to help the team meeting?

   1. A ranking of all team members
   2. A final legal document
   3. A comparison table of contributions
   4. An audio recording of the dispute

10. What is research integrity primarily concerned with in the context of authorship?

    1. Ensuring all experiments succeed
    2. Maximizing citation counts
    3. Giving appropriate credit for contributions and following ethical standards
    4. Publishing as quickly as possible

11. When the lesson says AI should 'surface' contributions, what does this mean in practical terms?

    1. AI publishes the contributions automatically
    2. AI creates new contributions that didn't exist
    3. AI identifies and presents documented contributions from available records
    4. AI decides which contributions are most important

12. A team member claims they wrote most of the introduction, but there's no documented evidence. How should this be handled in the AI-generated summary?

    1. Exclude it and note that it's contested
    2. Give them credit anyway to avoid conflict
    3. Ask the AI to investigate their personal computer
    4. Include it as stated since the team member claims it

13. What distinguishes a neutral summary from a resolution in the context of AI-mediated authorship disputes?

    1. There is no meaningful difference
    2. A resolution is longer than a summary
    3. AI cannot produce summaries, only resolutions
    4. A neutral summary presents facts for humans to discuss; a resolution makes a binding decision

14. Why is it important to base the contribution table on documented evidence rather than team members' memories or claims?

    1. The lesson requires it for legal reasons
    2. Documents are harder to forge than verbal claims
    3. Memories are always accurate
    4. Documentation provides verifiable evidence that all parties can reference and reduces dispute

15. What should happen after the AI generates the contribution table and before the final authorship order is decided?

    1. The AI should immediately publish the paper
    2. A third-party AI should verify the first AI's work
    3. Team members should discuss the table and any disputed items in a meeting
    4. The table should be discarded as unreliable