The incorrect suggestions by Watson are being blamed on the hypothetical data that it had to work with. “The documents — slide decks presented last summer by IBM Watson Health’s deputy chief health officer — largely blame the problems on the training of Watson by IBM engineers and doctors at the renowned Memorial Sloan Kettering Cancer Center. The software was drilled with a small number of “synthetic” cancer cases, or hypothetical patients, rather than real patient data. Recommendations were based on the expertise of a few specialists for each cancer type, the documents say, instead of “guidelines or evidence,” says the report.
An IBM spokesperson told Gizmodo that Watson for Oncology has “supported care for more than 84,000 patients” and is still learning. Seems like IBM’s Watson is not learning the right things and it could be due to the hypothetical data that is being fed to it. After all, any system based on neural network and artificial intelligence need a good amount of clean data to understand the concept it’s designed for and provide insights.
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