Data excellence: Better data for better AI

IEEE Intelligent Systems 24, 2 (2009) In the decade since then, the research community have done a lot with quantity, but quality has been left behind 16. http://lora-aroyo.org Data Quality is not only human error 20. Data Quality should consider context of use it is not easy to give Y/N answer for most of our AI tasks the answer typically depends on the context, on the task, on the usage, etc 21. http://lora-aroyo.org Data Quality should include real world diversity it is not easy to give Y/N answer for most of our AI tasks the answer typically depends on the context, on the task, on the usage, etc disagreement is signal for diversity and should be included in AI training 22. http://lora-aroyo.org Data Quality is difficult even with experts For prevention of malaria, use only in individuals traveling to malarious areas where CHLOROQUINE resistant P. falciparum MALARIA has not been reported.