ΑΙhub.org
 

Science communication for AI researchers – an AIhub tutorial at IJCAI-ECAI 2022


by
20 May 2022



share this:
microphone in front of a crowd

We’re pleased to announce that we will be giving a tutorial on science communication for AI researchers at IJCAI-ECAI this year. This will be held in person on 25 July (the afternoon session). If you are attending the conference and fancy finding out how you can communicate your research to a general audience in different formats, then please do sign up to join us.

About the tutorial

One of the challenges facing the field of AI is its portrayal in the media, which leads to misconceptions among policy makers, business leaders, and the general public alike. By communicating about AI in a clear, informed, and measured manner we can help to combat the flow of misinformation and convey the reality of today’s technology.

We will guide participants on how to quickly shape the story of their AI research. We’ll focus on how to structure this research story to form a blog post. Participants will learn how to explain their research to a general audience in a clear and concise manner. We will also touch on how to find suitable images and how to avoid hype when promoting research.

The presenters
Carles Sierra – Artificial Intelligence Research Institute (IIIA) of the Spanish National Research Council (CSIC)
Lucy Smith – Managing Editor, AIhub
Agenda
  1. Understand the importance of AI communication
    • Find out why AI communication is so important and how this can increase the impact of your research, inspire the next generation, and lead to new projects.
  2. Different ways of doing science communication
    • There are many ways to communicate your work, ranging from social media to full articles, from podcasts to comics. We will cover a few of these. For those that do not feel comfortable communicating their work themselves, we’ll guide you on how to best reach out to science communicators who may be able to share your story for you.
  3. Finding your story
    • How to produce a short summary of your research – we will take a step-by-step, guided approach to show you how to build a structured outline of your research story. This outline of the key points of a research story could be used to communicate work on a social media platform, such as Twitter.
    • How to expand your outline to write a complete post – the next step is to expand the structured outline to form a complete post. We’ll give guidance, with worked examples, on how to do this.
  4. How to find and use suitable images.
    • Articles about AI in the media tend to be accompanied by images of blue brains, white robots, and flying maths – usually completely unrelated to the content being reported. We will guide on how to source, use, and credit suitable AI images to accompany your work.
  5. How to avoid hype when communicating your research
    • 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. We will present some guidelines on how you can best avoid the hype when promoting your work.

Find out more on our tutorial webpage.



tags:


Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

Disappearing lakes and AI are helping scientists map Arctic permafrost thaw in near‑real time

  18 Sep 2026
Researchers created an interactive website to track permafrost thaw across the Arctic.

How much can fair budget-division rules resist manipulation?

The authors write about their award-winning IJCAI-ECAI paper: "Approximate Strategyproofness in Approval-based Budget Division".

AI dives into a sea of data, from plankton to pollution

  16 Sep 2026
“Faster and cheaper monitoring means problems like plankton decline, litter accumulation, oil spills and coral degradation can be picked up and acted on sooner."

Interview with Yash Saxena: how is external knowledge used in AI systems?

  15 Sep 2026
What happens to information from external sources as it moves through an AI system?

When AI art has no author: Study finds generated images often can’t be traced to training data

  14 Sep 2026
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.

AI in nature conservation: powerful tool or dangerous shortcut?

  11 Sep 2026
AI provides opportunity for future biodiversity conservation but introduces risks .

Improving the process for large-scale recommender systems: an interview with Haruka Kiyohara

  10 Sep 2026
Credit-assigned policy gradient for early stage retrieval in two-stage ranking.

The Machine Ethics podcast: Data Collective with E.M. Lewis-Jong

Ben chats to E.M. Lewis-Jong about the promise of AI and making human connection easier, speech recognition and supporting linguistic diversity, making useful technologies that have a purpose, and more.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence