RNA editing, the post-transcriptional recoding of RNA molecules, has broad potential implications for gene expression. Several recent studies of human transcriptomes reported a high number of differences between DNA and RNA, including events not explained by any known mammalian RNA-editing mechanism. However, RNA-editing estimates differ by orders of magnitude, since technical limitations of high-throughput sequencing have been sometimes overlooked and sequencing errors have been confounded with editing sites. Here, we developed a series of computational approaches to analyze the extent of this process in the human transcriptome, identifying and addressing the major sources of error of a large-scale approach. We apply the detection pipeline to deep sequencing data from lymphoblastoid cell lines expressing ADAR1 at high levels, and show that noncanonical editing is unlikely to occur, with at least 85%-98% of candidate sites being the result of sequencing and mapping artifacts. By implementing a method to detect intronless gene duplications, we show that most noncanonical sites previously validated originate in read mismapping within these regions. Canonical A-to-G editing, on the other hand, is widespread in noncoding Alu sequences and rare in exonic and coding regions, where the validation rate also dropped. The genomic distribution of editing sites we find, together with the lack of consistency across studies or biological replicates, suggest a minor quantitative impact of this process in the overall recoding of protein sequences. We propose instead a primary role of ADAR1 protein as a defense system against elements potentially damaging to the genome.