Around the world, funding bodies are reporting huge increases in the number of researchers applying for grants . A growing scientific workforce, pressure on researchers to secure funding and surging use of artificial-intelligence models that are slashing the time needed to write credible proposals are heaping pressure on a system that can barely cope.
As application numbers rise, success rates fall . The result is a hypercompetitive funding system. Scientists waste valuable time writing grants that are unlikely to be successful. Some pursue fashionable topics to increase their chances of success, sidelining other essential research, such as replication studies.
Could agentic AI topple grant-funding systems?
Systemic change is needed. In my view, as someone who explores the benefits of coordination in science, researchers need to begin to work collectively, rather than competitively, for funding — including with their rivals.
Last year, my PhD supervisor and I set out to help 12 metascientists to collaboratively apply for funding. Collaboration typically involves colleagues from within a scientist’s networks, but our group included competitors with disparate expertise who would not usually apply for funding together.
We asked the participants to propose and evaluate potential grant topics, deciding together which of the projects would best improve science in their field. This research-prioritization process is already used to steer the direction of research by some major funders, such as the US National Institutes of Health, and in some fields that depend on large-scale shared infrastructure, such as accelerators in particle physics. It enables participants to identify challenges that they collectively deem important, including those that would be too complex or burdensome to pursue individually.
We then adapted the proposals to ensure that they included research interests shared by groups of collaborators. Collectively, the group submitted two grant proposals, both of which won funding.
How to secure philanthropic funding in a competitive climate
I think that such collective funding applications can accelerate scientific progress. Papers with a large number of authors are often more highly cited — perhaps, one study suggests, because working in large groups improves quality ( M. Thelwall et al. J. Assoc. Inf. Sci. Technol . 74 , 791–810; 2023 ). Collective research prioritization can help to unify fragmented research lines and identify fresh ways to respond to societal challenges. It also breeds consistency in terms of which measures are used and reported, allowing individual studies to be more easily combined and compared.
Individual participants benefit, too. In our group, all collaborators shared tools and existing data, and discussed ongoing projects, which avoided ‘scooping’ — when a team reports results on the same topic before a rival — and duplication of work. Participants told me that collaboration on a project that had been deemed collectively important made their work feel meaningful, increasing job satisfaction.
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Bias read (Center): The article presents a factual report without explicit ideological framing, word-choice, or emphasis that suggests a particular political leaning. It simply relays information from Bloomberg News without commentary or contextual bias.
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Nature NewsParty-alignedCenter12 days ago Don’t compete, collaborate: why collective funding applications are the futureThe article discusses the increasing competition among researchers for funding, driven by a growing scientific workforce, pressure to secure grants, and the use of AI tools that reduce proposal-writing time. It highlights the negative consequences of this hypercompetitive environment, such as wasted time on unsuccessful applications and a focus on trendy research areas at the expense of essential work like replication studies. The author advocates for a shift toward collaborative funding applications, presenting an example where 12 metascientists, including competitors, worked together to pool
Bias read (Center): The article presents a balanced discussion of challenges in scientific funding and proposes a collaborative approach without overtly favoring any particular ideological stance. It focuses on practical solutions and does not exhibit biased language or one-sided sourcing.
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