Responsible AI-assisted coding and common training aspects

Wednesday 29 Jul 2026, 15:30 → 17:35 Europe/Zurich

61/1-009 - Room C (CERN)

Contact

 

HSF (Caterina Doglioni. Claire Antel, Michel Hernandez Villanueva, Nicole Skidmore)

Supporting parties:

EVERSE + RSQKit
EuCAIF Fair & Sustainable WG

IRIS-HEP

IML

SMASH
COMCHA

Meeting content in 3 parts:

Part 1: Collect experiences/practices around responsible AI-assisted coding in HEP software towards a loose set of suggested guidelines - Short slides per topic + discussion (1h + 20 min)
Part 2: Training plans by HSF training: Slides by HSF training following community survey + discussion (30 min)
Part 3: Discuss any new conclusions, next steps, future (10 min)

Part 1 discussions purpose and structure:

• To gather community practices, experiences, challenges and needs around AI-assisted coding in HEP.
• Slides to be presented focussed on topics listed below (one topic at a time) and based on material uploaded by community (see “homework” below).
  • Presentation format To Be Confirmed: Depending on amount of material collected, will collate slides into single deck or organisers will summarise material.
  • May additionally host short “expert” presentations on a specific expert topic.
• Presentations to be followed by open discussion.
• For duration of meeting: People can contribute to this live doc at any point.

Before meeting:

• Many communities will be coming together, so we aim to have a semi-structured discussion starting from a solid base.
• Communities will have likely held internal community discussions already.
• To that end, we hope attendees can approach common discussion with a good idea of their own community challenges and needs already.
• To thus start on a solid basis, we invite community representatives and individuals to upload ~1-2 slides per topic to agenda - if any (slides can link to further material), ideally by Fri 24th.
• We’ll nevertheless aim to be open to new directions and conclusions!
• The live doc is available for any discussions beforehand.

After meeting/for those who cannot attend:

• We continue discussions/comments on live doc, as well as document next steps where people can contribute further.

Discussion: Towards "Responsible and effective AI-assisted coding guidelines" for HEP Software

google live doc

1 Definitions and Context Setting

• Glossary(ies) to be uploaded for reference.
• Spectrum of AI-assisted tools: From “no AI” to fully automated systems [dedicated presentation from RSQKit(?) - to ask].
• National/Institute context: Policies, restrictions.
  [frame slide as ‘what are the policies and restrictions at your institute?’]
• Community context: Community opinions and impact.
  [frame slide as ‘what are community opinions, how have or might LLMs impact the community?’]
• Our community needs: e.g. Guidelines, training, building awareness.
  [frame slide as ‘what do you need the most, and why?’]

2 Practical info

• Where do good guidelines already exist.
  [frame slide as ‘list of effective guidelines’, and cite them]
• Global networks and communities.
  [frame slide as ‘add links of communities where these topics are discussed and we should keep on top of’]

3 Awareness building

• E.g. Environmental, ethical, societal, geopolitical considerations, data privacy, security.
  [frame slide as ‘main areas of concern, and why’]

4 Safe use

• E.g. securing credentials, setting up restrictions.
  [frame slide as ‘what experiences have you had, what challenges do you see, what safe practices would you suggest to a new student?’]

5 Responsible use

• E.g. Pull request etiquette, avoiding wasteful compute, respecting data of others.
  [frame slide as ‘what experiences have you had, what challenges do you see, what responsible practices would you suggest to a new student?’]

6 Commercial tools and alternatives

• Commercial versus non-commercial, closed vs open: Difference in usage and considerations.
  [frame slide as ‘what is your experience with commercial models vs local models for AI-assisted coding, and which suggestions / best practices are coming from this experience’ → expect a lot of experiences]
• Options for wider geographic distribution (e.g. European based companies).
• Support & limitations at labs, institutes (that we know of so far).
  [frame slide as ‘what tools are supported at institutes, and does it meet the needs of people?’]

7 Miscellaneous

• Topics we missed or loosely related.

8 For reflection: Acknowledgement of societal impact, future visions

• LLM technology is fast transforming (and being forced into) our workplace.
• At the moment, adoption is variable. A good fraction of community may not be using it out of principle.
• Adoption of technology has uneven playing field given financial tie.
• How do we see HEP research workflows transforming, and dictating a collaboration?

9 For reflection: How can we have a positive impact?

• From awareness building and reducing our environmental impact to funneling funding into science and building good practices: Can we transform this into concrete actions?

Discussion: Common Training Aspects

Convener: Michel Hernandez Villanueva (Brookhaven National Laboratory (US))

google live doc

10 Presentation by HSF Training

• Survey results from HSF Advisory Group
• Plans
• Discussion

11 Conclusions and next steps

As well as how to continue contributing after meeting (e.g. for those who could not attend).