Summary

Last updated on 2026-08-12 | Edit this page

Estimated time: 50 minutes

Overview

Questions

  • What have we learned so far?

Objectives

  • Review AI concepts learned so far.

What principles have we learned?

Throughout this lesson we have considered the five dimensions of research integrity:

  1. Honesty
  2. Transparency
  3. Accountability
  4. Respect
  5. Rigour

and how these intersect with the use of Generative AI tools in the research pipeline and the development of the tools themselves.

Honesty

In all aspects of research, including:

  • Planning
  • Methods
  • Data collection
  • Credit
  • Reporting
  • Interpretation
Transparency

Promoting trust and confidence, including by:

  • Reporting full methods
  • Publishing all results
  • Sharing data, code and materials
  • Declaring conflicts of interest
Accountability

Of everyone involved in research, including:

  • Researchers
  • Institutions
  • Funding bodies
  • Publishers
Respect

For everyone & everything involved in research, including:

  • Colleagues
  • Other researchers
  • Participants
  • Animals
  • The environment
Rigour

In line with disciplinary norms, including in:

  • Appropriate methods
  • Following protocols
  • Interpreting data
  • Drawing conclusions
  • Disseminating

These five principles sit alongside the four principles defined in The Singapore Statement agreed at the 2010 World Conference on Research Integrity (WCRI):

  • Honesty in all aspects of research
  • Accountability in the conduct of research
  • Professional courtesy and fairness in working with others
  • Good stewardship of research on behalf of others
Discussion

Concept mapping

Many of the topics introduced are interconnected. Create a concept map of the key themes introduced in this lesson and how they interact.

This could be done either on paper or using Exaclidraw.

Share your drawing with the group. Are there key themes emerging across the different drawings?

Discussion

Key considerations

In this lesson we have primarily discussed the use of Generative AI with regards to the dimensions of research integrity.

Think: What would you need to consider to make an informed decision about when, where, or if to use GenAI for coding in your project(s)?

Pair: With a neighbour, discuss your key considerations. What was the same, what different.

Share: Feedback to the group on where you agreed, disagreed and why?

Key Points
  • Generative AI tools can be used both as shortcuts to complete a task and to enhance understanding.
  • The responsibility of ensuring use outputs of these tools are correct are with the user.
  • There are complex ethical, moral and legal debates about how these tools have been trained, are used and the infrastructure required to make them available to users.