Nik Claesen, managing director of the European Association of Research Managers and Administrators, speaking at the body’s 2023 annual conference in Prague.Credit: Josef Rabara
The European Association of Research Managers and Administrators (EARMA) is the continent’s representative body for those working at the “interface between research funding organisations and the scientific community”. Its members often act as a bridge between researchers and public-funding agencies, charities, companies and governments. They help scientists to bid for grants, to organize projects and collaboration networks, and to demonstrate impact.
EARMA seeks to increase awareness of the work done by research managers and administrators, and is engaged in a major project, the European-Union-funded RM Roadmap, to more clearly identify and demonstrate the worth of these professions to science. It also helps its members get to grips with the rapid technological, political and systemic changes affecting universities.
One of the most pressing challenges is artificial intelligence (AI). At EARMA’s 2023 annual conference, held in Prague in April, its managing director Nik Claesen stressed that within five years, AI could be writing better grant proposals in five minutes than delegates in the hall might manage in a year.
Nature Index spoke to Claesen about what AI might mean for research management, and how far the profession has progressed in being a recognized force for good in science.
What are the main challenges for research management and administration over the next five years?
We might be about to see a boom in research management because of how complex the research system has become, and the need for more people to deal with that complexity. At the same time, we’re seeing AI come on to the scene. The pace of change in how research is funded and conducted is going to increase, and being able to adapt to that will be crucial for research managers.
How can AI be most usefully applied to research management, at least in the short term?
Quite a lot of people are already using it in grant-proposal writing. Why spend hours refining the text if you can bring it to a point where you need to refine it less? But AI could be used in all sorts of applications. In data management, for example, it could make the connections to other research projects where data might be useful.
Are people in research management apprehensive about AI and whether it will replace jobs?
Definitely that apprehension is there. I personally see it as more of an opportunity than a big threat. If we look at grant-proposal writers for example, is AI going to be able to take on that role? In my opinion, yes, but will that change how grant proposals are written, leading to, for example, a scenario in which people who are writing proposals will use AI to write better ones? Or do we go to a completely different model where the researcher or research managers, or both, are interfacing directly with an AI from the funder, bypassing the need for a research proposal in the form of a PDF that we know today?
Does there need to be some transparency about declaring the use of AI in writing a grant proposal?
Yes. But there also needs to be a policy about whether it is allowed, encouraged or discouraged. There need to be some rules around it, which to my knowledge there aren’t, really.
In the past ten years, how far has research management come in demonstrating its importance?
There has been a big leap in recognition over that time. I think that most well-informed people understand the value and necessity of research management, so that is huge progress. Some policymakers and funders have known about its importance for 20 or 30 years, but it’s always been dependent on local circumstances. At the European or global level, I think now there’s much more visibility and awareness. People see that research managers are a tool, an enabler, a facilitator, so that researchers have time to do research.
Who is still not giving research management due recognition?
For me, the main changes that need to be made are at the governmental level, at ministries, because it is hard for their staff to understand the role of research management, given that it is such a niche activity.
In most European governments now, is there an understanding that research managers improve efficiency, or are these roles seen as ones that can go first during cutbacks?
I think that argument is ongoing. For me, cutting research management is a little counterintuitive. The tasks are still there to be done, even if you cut jobs, and then the researcher is going to have to do them, faced with ever-increasing complexity. But that is a difficult conversation to have at the political level and one that doesn’t win elections.
Are there quantitative ways of demonstrating the impact of research management?
It is very difficult to show the value added by research management. We’re trying to look at this within the RM Roadmap project. It is a nuanced, difficult, technical discussion which is tricky to translate to the wider public. We are working on it. Establishing which elements of research outcomes are the fruits of research management is the hard thing.
Is there enough development and training to help new research managers?
That is one of the key things that needs to improve. In some of the most developed systems, there is decent training, but across the board, it is far below the level it should be at. Quite a large proportion of people are dropped into the job and really don’t have an appropriate way to learn. They have to try and make it up as they go along.
This interview has been edited for length and clarity.
