On the missing benchmarks layer and a potential solution

Computer Science > Artificial Intelligence [Submitted on 4 Aug 2026] On the missing benchmarks layer and a potential solution Francis F Daniel, Mauro Ibañez, Francis Perelman, Marian Basti Latin America is missing a foundational layer for native AI development: the benchmark layer. The benchmark layer does two things no other layer can - it audits AI systems against regional social requirements and it directs AI optimization in economically relevant environments. Without it, public institutions cannot independently evaluate foreign AI systems, and companies cannot optimize AI systems to solve local problems with SOTA performance. The cost of the missing layer is dual: a loss of auditability and a loss of optimization direction over a technology that is increasingly critical infrastructure. We propose an EvalsHub, with LatamBoard as its first regional instance - an open, task-first benchmark infrastructure where universities, public institutions, professional communities, and companies can publish, execute, compare, and maintain evaluations across models, workflows, and agents. Built once, measured forever - re-run by institutions as new AI systems ship and by industry teams after every system change. Open by design and incentive-driven by construction. Comments: 9 pages Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2608.02996 [cs.AI]   (or arXiv:2608.02996v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2608.02996 Focus to learn more Submission history From: Francis F Daniel [view email] [v1] Tue, 4 Aug 2026 01:26:03 UTC (11 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)