Science is financed mainly by national governments, but scientific knowledge rarely remains within national borders. A theorem proved in one country, a dataset assembled in another, and software maintained elsewhere […]
What Would a Truly Global Science Fund Look Like?
A truly global science fund would finance valuable research regardless of a scientist’s nationality, institutional prestige, discipline, or access to established grant networks. It would pool resources internationally, evaluate scientific […]
Could AIIM Reduce the Matthew Effect in Science?
AI Internet-Meritocracy could reduce the Matthew effect by rewarding observable scientific contributions rather than prior grants, institutional prestige, or established reputation. However, AIIM would not eliminate cumulative advantage automatically. Without […]
How AIIM Could Reward Data, Code, Proofs, and Replications Separately
Scientific funding usually treats a research paper as the main unit of achievement. This approach overlooks much of the work that makes science possible: collecting reliable data, developing research software, […]
Why Funding Agencies Should Explain Every Rejection—and How AIIM Already Does This
Scientific funding agencies should provide a meaningful explanation for every rejected application. A rejection should identify the decisive reasons, the evidence or criteria behind them, and whether the problem concerns […]
Continuous Funding: What If Scientists Were Paid After Every Useful Result?
Scientists are usually funded in large, infrequent decisions. A researcher writes a proposal, waits through peer review, and—if selected—receives enough money for a project lasting several years. Once the grant […]
Should AI Evaluate Researchers, Research Outputs, or Both?
AI should evaluate both research outputs and researchers—but not in the same way or with equal weight. Research outputs should be the primary unit of scientific evaluation. Papers, datasets, proofs, […]
How AIIM Could Detect Unsupported Scientific Claims
Scientific papers contain many kinds of statements: direct experimental findings, mathematical deductions, interpretations, literature summaries, and predictions. These statements do not all deserve the same level of confidence. AIIM could […]
Why AI Science Funding Needs Adversarial Testing
Artificial intelligence could make scientific funding faster, broader, and less dependent on institutional prestige. However, an AI system that evaluates research or distributes money cannot be trusted merely because it […]
How to Audit an AI That Distributes Research Funding
An AI system that distributes research funding should never be trusted merely because it is described as “objective,” “transparent,” or “intelligent.” It must be tested against observable evidence. A credible […]