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You are the author. AI is your assistant.

AI can:

• Improve clarity
• Suggest structure
• Help brainstorm
• Refine grammar

AI cannot:

• Take responsibility
• Ensure factual accuracy
• Replace your reasoning
• Think critically about your data

LLMs generate outputs based on statistical probability — not understanding 

AI does NOT “know” things.

It predicts likely word sequences.

This leads to:

Hallucinations

• Fake references
• Incorrect statistics
• Misrepresented conclusions
• Fabricated DOIs

Bias

• Overrepresentation of Western literature
• Bias toward positive results
• Limited representation of non-English scholarship

Knowledge cut-off

• May miss the latest studies
• Cannot replace proper literature searches

For ECRs, this is dangerous because:

• You may not yet have subject confidence to detect errors.
• Incorrect AI-generated content may pass unnoticed — until peer review.

AI is most helpful in low-risk, skill-building tasks, such as:

✔Improving grammar and readability

✔Refining awkward sentences

✔Creating a structured outline

✔Summarizing your OWN text

✔Brainstorming alternative titles

✔Generating presentation scripts from your completed work

When First-Time Authors SHOULD NOT Use AI

🚫 Writing your entire introduction
🚫Generating literature reviews from scratch
🚫Creating references without verification
🚫Uploading unpublished manuscripts into public AI systems
🚫Letting AI draft your discussion section

Why?

Because writing is thinking.

As emphasised in the training material:
Writing helps you slow down, organize, reflect, and understand

If AI writes your paper, you lose the learning process. This is especially harmful for the young authors. 

Most major publishers:

❌Do NOT allow AI as an author

AI cannot take accountability.

❌Do NOT permit AI-generated images (in most cases) 

 ⚠ Require disclosure for certain AI uses.

Policies vary across publishers.

Failure to disclose AI use can:

• Lead to manuscript rejection
• Trigger retraction
• Damage your academic reputation

There are already retraction cases where undisclosed AI use was cited as policy breach.

The guide was presented at Every Author's "Peer Review Week 2025"  in Mandarin Chinese. 

Dive into the ethical implications of AI, discussing topics like privacy, bias, fairness, transparency, and the societal impact of AI technologies. We'll examine case studies where AI has had both positive and negative effects.

Learn to critically evaluate AI applications, understand how to use AI tools effectively, and comprehend the basic principles of AI governance. This includes knowing how to ask good questions of AI systems, recognise when AI is being used, and understand its limitations.

Examine how AI is transforming academic publishing, from automated peer review to AI-assisted writing and research. We will discuss AI's role in enhancing or challenging the integrity of academic work.