The Hidden Cost of Scientific Competition: When Grant Applications Cost More Than the Grants Themselves

The relentless pursuit of research funding is a defining feature of modern academia. Scientists compete not just for prestige and publication, but for the essential financial resources that make their work possible. However, this competitive system harbors a profound inefficiency, one where the cost of securing a grant can sometimes exceed the grant's value. This counterproductive threshold, known as the Szilard point, raises urgent questions about the sustainability and effectiveness of current scientific funding models.

The Szilard Point: A Critical Threshold in Research Funding

Named after the Hungarian-born physicist Leo Szilard, who satirized scientific bureaucracy in his writing, the Szilard point represents a crucial metric in cost-benefit analyses of grant funding. It describes the precise threshold where the total costs incurred during the grant application process equal or surpass the total value of the available funding. These costs are multifaceted, encompassing the time scientists invest in writing elaborate proposals, the effort peers expend in reviewing them, and the administrative overhead required to manage the entire competition. The fundamental question it poses is stark: which costs more, the research being proposed or the bureaucratic process of applying for it?

The GenAI for Africa Case Study: A System Pushed to Its Limits

A compelling illustration of this phenomenon can be found in the European Union's Horizon Europe programme. The 'GenAI for Africa' funding call, which closed in October 2025, aimed to harness generative artificial intelligence to tackle societal challenges across the African continent in agriculture, healthcare, urban planning, and education. With a total budget of €5 million (approximately US$5.8 million), the initiative attracted 215 submissions. However, only two projects were expected to be funded, resulting in a success rate of less than 1%.

When analyzing the GenAI for Africa call through the lens of the Szilard point, the potential for inefficiency becomes clear. Researchers have developed simulation tools to estimate these hidden costs. Key inputs include the significant time investment—where a median consortium coordinator spends 36 to 45 person-days per proposal—and the average consortium size of 12 to 16 partners. Factoring in varying hourly rates for academic and industry partners across Europe, the cumulative cost of preparing 215 complex, multi-partner proposals likely represents a massive investment of time and money by the scientific community itself.

The Broader Implications for Scientific Progress

The prevalence of such hyper-competitive funding environments has significant consequences. When success rates plummet below 1%, the vast majority of researchers' effort and intellectual capital is effectively wasted from a funding perspective. This creates a system that is not only inefficient but also potentially damaging to scientific morale and innovation. Researchers may become incentivized to pursue safer, more incremental projects that align with perceived funding priorities rather than high-risk, high-reward ideas that drive true breakthroughs. The process can become a circular endeavor, where publishing papers and attending conferences are viewed primarily as stepping stones to the next grant application, rather than as valuable scientific outputs in their own right.

Rethinking Resource Allocation in Science

The existence of the Szilard point forces a reevaluation of how scarce public resources for science should be allocated. The current dominant model of open competition is presented as efficient, fair, and reliable. However, alternatives exist. A more egalitarian approach would distribute smaller amounts of funding more widely. Other models might empower institutions with block grants to distribute internally or employ strict, transparent merit criteria without a competitive lottery element. The challenge lies in designing a system that maximizes scientific output and innovation while minimizing the parasitic costs of the funding mechanism itself. This is a core topic in the field of metascience, which takes a systemic, bird's-eye view of research practices to improve quality, integrity, and overall efficiency.

In conclusion, the Szilard point serves as a vital warning signal for the global scientific enterprise. While competition can drive excellence, excessive competition for dwindling resources can cross a threshold of diminishing returns. The case of the GenAI for Africa initiative suggests that some funding calls may already operate beyond this point, where the collective cost of application dwarfs the available rewards. Addressing this requires funders, institutions, and scientists to collaboratively seek more efficient models that prioritize supporting groundbreaking research over administering a costly competition. The future of scientific innovation may depend on our ability to recognize and avoid this critical inefficiency.