Prudence in Using AI

in Scientific Publishing

By Mohammad AlMarzouq

Agenda

  • Prudence in
    • AI Capabilities
    • AI to write research
    • AI in the editorial process
  • General advice and lessons learned

Prudence in AI Capabilities

What is AI?

  • Any machines performing tasks that mimic human intelligence
  • Machine learning and deep learning are popular subfields of AI
  • Processes large datasets for insights
  • Evolves with new data

Important Concepts

  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Deep Learning (DL)

Artificial Intelligence (AI)

  • Broad concept of machines performing tasks in a way that mimics human intelligence.

Machine Learning (ML)

  • Subset of AI where machines learn from data without being explicitly programmed for specific tasks.

Deep Learning (DL)

  • Advanced subset of ML using neural networks with many layers to analyze data, recognize patterns, and make decisions.

Evolution of Programming

  • Conventional Programming
  • Machine Learning Programming
  • Deep Learning Programming

Conventional Programming

  • Programmer defines rules and instructions for the computer to follow.
  • Data is processed based these rules

Machine Learning Programming

  • Programmer trains model
    • Chooses algorithms
    • Provides data
    • Selects important features
  • Models
    • Learns patterns from data
    • Make predictions

Deep Learning Programming

  • Programmer trains model
    • Chooses complex neural network algorithms
    • Provides large dataset
  • Models
    • Learns complex patterns
    • Finds important features
    • Make predictions

What is Causing all this Excitement?

  • Deep Learning AI models
  • Specifically, Deep Learning models that can produce human-like content
    • These are called Generative AI models
    • They can generate text, images, music, and more
    • ChatGPT is an example

Does AI Think on Its Own?

  • No! people might think it does because:
    • Has astonishing capabilities
    • Limited programming effort
      • Mostly training on data
    • Unexplainable black box

AI as a Black Box

  • Challenges in understanding AI decision paths
    • Makes it unpridinctable
  • Efforts towards explainable AI
    • You can prompt the AI to explain its output
  • Balancing trust with transparency in AI systems
  • Educating users on AI capabilities and limitations

Examples of astonishing Capabilities

  • Recognizes complex patterns unseen by humans
  • Utilizes vast data to make insightful or precise predictions
  • Output not distinguishable from human’s

However, AI

  • Lacks original creativity
  • Relies on training data, could be biased
  • Lacks consciousness and self-awareness
  • Lack ability to recognize right from wrong
    • Beware of hallucinations
  • Requires human oversight

Key Takeaways

  • Generative AI produces human-like content
  • Recombines and generates new content from training data
  • Lacks consciousness and creativity
  • Requires human oversight

Prudence in AI to Write Research

You Have Been Using AI for Sometime in Research

  • Plagiarism checkers
    • iThenticate, Turnitin, etc.
  • Grammar and language checkers
    • Grammarly, Word, etc.
  • Translation tools
    • Google Translate, DeepL, etc.
  • Search engines
    • Google, Bing, etc.

What Changed?

  • AI impact is more observable with Generative AI
  • It can now:
    • Draft research papers and articles
    • Create and refine research questions and outlines
    • Simplify complex explanations
    • Produce and analyze data
    • Summarize papers and reviews
    • Review and edit papers
    • and more

ChatGPT

  • Latest tool to have a significant impact

What is ChatGPT?

  • Type of generative AI by OpenAI
    • It generates content
  • Mimics human-like text responses
  • Trained on diverse internet text
    • Based on Deep Learning
  • Continuously updated for relevance
    • Latest version is ChatGPT-4

How to Use ChatGPT

How to Use ChatGPT

  • Write prompts
    • Describing what you want
    • Give an example of what you want
    • Give document and ask for summary or refinement
  • Engage in conversation to refine output
    • Ask to refine output
    • Ask to explain how output is generated

Obvious Use Case by Researchers

  • Writing paragraphs, sections, or complete papers
  • O’Connor, S. & ChatGPT. (2023). Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse? Nurse Education in Practice, 66, 103537. https://doi.org/10.1016/j.nepr.2022.103537

Risks

  • Will AI Replace researchers?
    • Unlikely to happen given limitations of AI
  • Will researchers misrepresent AI-generated content as their own?
    • More likely, content will be unoriginal and not reliable
    • Refining the output likely to take more effort than writing it from scratch
  • Will researchers become too reliant on AI?
    • Likely, risk is deskilling and loss of expertise
    • Can be mitigated with guidelines and training

More Productive Uses of AI in Research

  • Summarize articles
  • Explain or simplify complex concepts
  • Analyze or visualize data
  • Generate empirical data from documents
  • Generate synthetic data for testing models
  • Generate/translate research instruments
  • Improve wording or paragraph
  • Draft outlines and research questions
  • and more

Beware of

  • Ignoring AI-generated content’s need for validation
    • Always validate, experience in subject matter is crucial
  • Relying on AI to produce new content
    • It’s a tool, not a replacement
    • Write the content, ask AI to refine it
  • Not reporting to editors how AI was used in publication
    • We are still trying to understand how AI is used in research
    • Policies and guidelines are still evolving
  • Relying on first produced output
    • Engage in conversation to refine output
    • AI as a tool becomes more effective as you learn to use it

Exploring Other Tools

  • Elicit
  • Consensus
  • Researchrabbit
  • SciSpace
  • Litmaps
  • Scite
  • Trinka
  • Scholarcy
  • iThenticate

Key Takeaways

  • AI can be a powerful tool in research, that has been used for a while
  • New tools like ChatGPT are making AI more impactful
  • Other useful tools are available
  • AI should complement human expertise, not replace it
  • Guidelines on use of AI in research are still evolving

Prudence in AI in the Editorial Process

  • Role of editorial boards
    • Think about the role of AI in the editorial process
    • Establish guidelines and policies for AI use
      • Transparency will be a minimum requirement
    • Educate authors and reviewers on AI use
  • Utilizing AI in the editorial process
    • Assist in screening submissions
      • Avoid over-reliance on AI, likely to reject creative and innovative submissions
    • Enhance peer review process
      • Summarize and compare reviews
      • Use AI as the third reviewer
    • Improve communication language
      • Enhance feedback/reports to be polite and constructive
      • I would advise against using AI to write your reviews
        • Same reasons as using AI to write research

New Challenges

  • Undetectable plagiarism
  • AI doctored/generated data
  • Change in predatory practices
  • Possible overwhelming of conventional review process
    • AI generated papers passing initial screening threshold

Solutions

  • New tools to detect AI-generated content
  • Embrace AI tools and become familiar with their capabilities
  • Adoption of Open Science practices
    • Open data, open access, open peer review
  • Be transparent about AI use

Conclusion

  • AI’s potential to transform scientific publishing is immense
  • Responsible use and ethical considerations are paramount
  • Collaboration between AI and human expertise is key
  • Continuous evaluation of AI’s impact and evolution
  • Transparancy in use is necessary in moving forward
  • AI is a tool, not a replacement
    • Rather than jobs disappearing, more likely people not using it in their jobs will disappear

Thank You!