Mathsci-comm workshop, Nov 2024: Emerging themes and future directions
In November 2024 the Mathsci-comm network held its first in-person meeting at the Isaac Newton Institute for Mathematical sciences in Cambridge. It was entitled Communicating Mathematical and Data Sciences – What does Success Look Like?. This document summarises themes and future directions that emerged at the meeting. This event, as well as the Mathsci-comm network, are funded by an INI Network Grant, EPSRC grant (Ref: EP/V521929/1). The image above shows Hannah Fry, Marianne Freiberger, and Rachel Thomas speaking at the event (credit Grace Merton, INI).
Emerging themes and future directions
Two overarching messages that came through clearly on the day were that "the public" are not stupid and that to engage with your audiences you need to answer their questions, understand their priorities and speak their language.
As David Schely put it, "the limitation is our willingness and ability to engage, not the public's intelligence."
When it comes to messages reaching their desired target, and being interpreted as intended, the responsibility therefore shifts away from the audiences and lands firmly on the communicators — it's on us to make sure that whatever content we want to get across is accessible and relevant. But how do we do that and how do we know which approaches work? This is what the day was about.
Evidenced based communication
Some of the talks (eg David Spiegelhalter, Matthew Naylor, Andrew Meso) presented empirical evidence which shows that certain ways of communicating are more effective than others. Such evidence can be turned into practical dos and don'ts, such as the Five rules for evidence communication published by Spiegelhalter et al in Nature. In the case of vision science, as presented by Meso, it can inform the design of control rooms or visuals. Generally, there are lots of studies on how people perceive and process information, though many are not specifically related to the communication of maths and data science (see the resource list).
Two questions that arise from this are:
- Practical: Is it feasible, worthwhile, or necessary for the Mathsci-comm network to collate a list of evidence-based tips and guidelines, specific to maths and data science, that could be circulated widely? This could be done collaboratively, with members each reading through a collection of resources and distilling practical tips (the plus.maths.org writing guide could be a starting point). Such a list could also inform, and help develop, the comms workshops and training that many participants voiced an interest in.
- Big and bold: Generally, do we need more empirical research of this type, pertaining specifically to mathematics and data science communication? If so, how should this be done and by whom? And who should fund it? Should the Mathsci-comm network make a case for this?
Evaluation of existing comms efforts provides some evidence of this kind. It was not discussed in any detail at this event, but as Sarah Harman (EPSRC) pointed out in one of the panel discussions, thorough evaluation should always be embedded in any comms effort and shared. Questions that arise are:
- Practical: Evaluation is a tricky thing, but many people are doing it. Should we try and collate a how-to guide drawing on many people's efforts? Or does a suitable one already exist?
- Big and bold: Anecdotal evidence suggests that evaluation is still often treated as an afterthought. Is some sort of lobbying needed to alert funders (as well as communicators) to the need for thorough evaluation to be built into budgets? Can the Mathsci-comm network do this?
Involving audiences
Rachel Philips' talk on communicating treatment harms explored a way of making sure that messages get across to non-expert audiences, which is not empirical research on communications and goes beyond standard evaluation practices: involving the audience in the design of the communications from the start and in a systematic way. Since such public involvement is increasingly required by funders in the medical realm. This raises the questions:
- Practical:
- How can we (maths/data science community) benefit from learning about communications arising from patient and public engagement from the medical realm? Should the Mathsci-comm network explore this further, for example in the monthly zoom meetings?
- Can we/should we produce a how-to guide for involving the public (how to reach them, etc - see also this guide from Sense about Science and this guidance from NIHR).
- Big and bold: Should this kind of involvement of the public when designing comms be embedded, i.e. required by funders, in certain maths/data research grants?
Doing maths and data science with the public, not to the public
Philips' talk wasn't just about the one-way communication of science to non-scientific audiences, however. It was also about communication going the other way, involving the public in designing clinical trials to make sure their outcomes are relevant and to make the best of the people's knowledge (eg, about the medical conditions they live with every day).
This approach was echoed and expanded upon in Elizabeth Fearon's talk on the co-production of mathematical models in epidemiology. As Fearon (along with Veronica Bowman and Hannah Fry) pointed out, many situations that are being modelled involve people, so any model not taking account of people's behaviour is likely to less useful.
The world of co-production, along with adjacent ideas such as human centred design and patient and public involvement and engagement, appears to be a big one that is used by other areas, such as AI (one interesting source here). Questions arising from this are:
- Practical: Should we look into this further? For example, have experts in co-production talk to the Mathsci-comm network in monthly zoom meetings?
- Big and bold: Should public involvement or co-production be embedded in the mathematical sciences? Not just to create better outcomes of, for example, modelling efforts, but also to better engage the public with science, which is the aim of all comms? As Hannah Fry put it, she wants the public to feel that "maths is being done with them, not to them". If yes, should the Mathsci-comm network give a voice to this idea?
Ethical guidelines
Another theme that emerged repeatedly throughout the day is that effective communication goes hand-in-hand with ethical communication. The five rules for evidence communication published by Spiegelhalter et al are evidenced in terms of effectiveness, but also have an ethical ring to them — they are about honesty and transparency.
Two other sets of principles and standards were also mentioned: the Nolan principles for public life (mentioned by Roni Bowman) and the UK standards for public involvement (mentioned by Rachel Phillips). These too provide interesting perspectives, not just on the doing of maths and data science, but also on the communication of them, and may be worth mentioning in any resources produced by the Mathsci-comm network.
Summary and next steps
What became clear throughout the day is that the world of maths and data science comms (in the widest sense) is big, that it is active, and that it is young. All sorts of activities are going on, and many haven't been going on for a long time. It also seems like there is lots to learn from other/adjacent fields.
Comments on our online tool and form, the paper questionnaires, as well as the Slack channel also demonstrated that there's an appetite for practical tools: from how-to guides (for example on how to communicate with policy makers) to training sessions (for example on social media and podcasting/video). On an institutional level, it became clear from the panel discussion that the "mathematics community" lacks a coherent strategy or approach to comms.
Taking all this together, there seem to be three general strands the Mathsci-comm network could pursue:
- The production/collation of practical help such as how-to guides, the development of training sessions, or information on how to access them. This could be a collaborative/distributed effort. Training sessions are already being offered by some organisations (eg INI, LMS, RSS, …). It would be good to have an exhaustive list and explore options for making such training reach a larger audience, for example through online sessions, or developing self-guided online courses.
- Help to bring about a culture change for example by lobbying for the embedding of comms in university courses or research groups, for more funding for comms, or research into comms. A starting point, as already discussed, could be placing articles in relevant journals, lending them weight through joint authorship and the backing of the Mathsci-comm community.
- Find funding for follow-on workshops and continuation of the network. Our INI network grant only allows for one further in-person meeting and another year.
Acknowledgements
This document was produced with the participants of the Mathsci-comm workshop, Communicating Mathematical and Data Sciences – What does Success Look Like?, alongside members of the wider Mathsci-comm network. The workshop was held in November 2024 at the Isaac Newton Institute for Mathematical Sciences, organised with the Newton Gateway to Mathematics, and supported by an INI Network Grant.
This document was written by Rachel Thomas and Marianne Freiberger, with contributions from the following:
Shuaib Ahmed
Ajay Bater
Duncan Bradley
Celine Broeckaert
Eleanor Burch
Nigel Campbell
Kaili Clackson
Lisa Curtis
Luke Davis
Long Tung (Miranda) Ding
Helena Earl
Jessica Enright
Eleanor Fallon
Elizabeth Fearon
Julia Gog
Liza Hadley
Sam Hansen
William Kay
Joanne Kenney
Anna Khoo
Unni Irmelin Kvam
Lindsay Lee
Vinesh Maguire-Rajpaul
Katherine Mathieson
Michael McMahon
James Millar
Justin Mullins
Matthew Naylor
Rachel P
Kat Phillips
Tim Rooker
Megan Ruffle
Ameer Ali Saleem
David Schley
Jordan P Skittrall
Ann Smith