18Recombination is a major force that shapes genetic diversity. The inference accuracy of 19 recombination rate is important and can be improved by increasing sample size. However, it has 20 never been investigated whether sample size affects the distribution of inferred recombination 21 activity along the genome, and the inference of recombination hotspots. In this study, we applied 22 an artificial intelligence approach to estimate recombination rates in the UK10K human genomic 23 data set with 7,562 genomes and in the OMNI CEU data set with 170 genomes. We found that the 24 fluctuation of local recombination rate along the UK10K genomes is much smaller than that along 25 the CEU genomes, and recombination activity in the UK10K genomes is also much less 26 concentrated. The same phenomena were also observed when comparing UK10K with its two 27 subsets with 200 and 400 genomes. In all cases, analyses of a larger number of genomes result in a 28 more precise estimation of recombination rate and a less concentrated recombination activity with 29 fewer recombination hotpots identified. Generally, UK10K recombination hotspots are about 30 2.93-14.25 times fewer than that identified in previous studies. By comparing the recombination 31 hotspots of UK10K and its subsets, we found that the false inference of population-specific 32 recombination hotspots could be as high as 75.86% if the number of sampled genomes is not super 33 large. The results suggest that the uncertainty of estimated recombination rate is substantial when 34 sample size is not super large, and more attention should be paid to accurate identification of 35 recombination hotspots, especially population-specific recombination hotspots. 36 37 38 3 Author summary 39 We applied FastEPRR, an artificial intelligence method to estimate recombination rates in the 40 UK10K data set with 7,562 genomes and established the most accurate human genetic map. By 41 comparing with other human genetic maps, we found that analyses of a larger number of genomes 42 result in a more precise estimation of recombination rate and a less concentrated recombination 43 activity with fewer recombination hotpots identified. The false inference of population-specific 44 recombination hotspots could be substantial if the number of sampled genomes is not super large. 45 46 47