ΑΙhub.org
 

How to avoid hype when promoting your AI research


by
25 October 2021



share this:
microphone in front of a crowd

Hype around AI sets inflated expectations about the technology, drives unnecessary fears and detracts from the meaningful discussions that need to happen now, about the technology actually being developed today.

The AIhub trustees have compiled a handy guide to help you avoid hype when communicating your research. Here are their 10 tips:

1. Be specific about the science and achievements

What problem is your research trying to solve? Provide context.

2. Don’t make exaggerated claims

Try to avoid unnecessary superlatives such as: “general, best, first” unless you can provide supporting context.

3. Be clear about the limitations of your experiments

Did your demonstration require external instruments that made the real world “more digital” (for example, external sensors/motion capture)?

4. Explain how things work

What data was used, what type of algorithms, what hardware? Be upfront about the computational cost.

5. Has your research been validated by the community?

Does the community support your findings, through peer-reviewed research or other means?

6. Make your headline catchy but accurate

Prioritise scientific accuracy.

7. Keep any debates scientific

Don’t bring personalities/personal attacks into the debate.

8. Don’t anthropomorphize

Avoid anthropomorphism unless the subject of the research is people.

9. Use relevant images

Use images from your research to illustrate your news. Avoid generic or stereotypical AI images (such as imaginary robots from science fiction).

10. Be open and transparent

Disclose conflicts of interest and/or funding especially if industry or personal interests are involved.

You can find all of the guidelines in this pdf document.



tags: ,


AIhub is dedicated to free high-quality information about AI.
AIhub is dedicated to free high-quality information about AI.




            AIhub is supported by:



Related posts :

monthly digest

AIhub monthly digest: January 2026 – moderating guardrails, humanoid soccer, and attending AAAI

  30 Jan 2026
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

The Machine Ethics podcast: 2025 wrap up with Lisa Talia Moretti & Ben Byford

Lisa and Ben chat about the prevalence of AI slop, the end of social media, Grok and explicit content generation, giving legislation more teeth, anthropomorphising reasoning models, and more.

Interview with Kate Larson: Talking multi-agent systems and collective decision-making

  27 Jan 2026
AIhub ambassador Liliane-Caroline Demers caught up with Kate Larson at IJCAI 2025 to find out more about her research.

#AAAI2026 social media round up: part 1

  23 Jan 2026
Find out what participants have been getting up to during the first few of days at the conference

Congratulations to the #AAAI2026 outstanding paper award winners

  22 Jan 2026
Find out who has won these prestigious awards at AAAI this year.

3 Questions: How AI could optimize the power grid

  21 Jan 2026
While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.

Interview with Xiang Fang: Multi-modal learning and embodied intelligence

  20 Jan 2026
In the first of our new series of interviews featuring the AAAI Doctoral Consortium participants, we hear from Xiang Fang.

An introduction to science communication at #AAAI2026

  19 Jan 2026
Find out more about our session on Wednesday 21 January.


AIhub is supported by:







 













©2026.01 - Association for the Understanding of Artificial Intelligence