Key Points

Introduction

  • Papers may be retracted by an author or the journal’s editorial team.
  • Integrity concerns may be a factor in retraction.
  • There are multiple dimensions to integrity.

Rigour and Transparency

  • It is important to be transparent about where and how Generative AI has been used in your work flow
  • There are differences between the Open Source and Open AI definitions
  • Some Generative AI tools are designed to encourage engagement with the tool
  • Check the rules around Generative AI use for your choden dissemination channel

Respect and Accountability

  • The current AI boom is resulting in the building of new large scale data centres.
  • New large scale data centres are increasing the demands on energy and water supplies.
  • Machine learning relies on human workers, there is a history of poor working practices and lack of support for data workers.
  • There is a complex landscape around data protection and copyright, you will need to be aware of both your local regulations and those of any international partners you may have.

Implications for Learning

  • Shallow learning reduces attention span and hampers deep learning that requires focus and critical thinking.
  • Deep learning is focused on problem-solving and connecting various sources of new and existing knowledge.
  • GenAI carries the danger of the user being content with shallow learning.
  • Avoid shallow learning by using GenAI mindfully.

Summary

  • 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.