Had the opportunity to test Watson for Oncology and system provided recommendations about therapies depending on specific Electronic Medical Records of Patients with Cancer. In recommendations included the medical evidence that supported those recommendations.
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A changing environment cause that data valid to train a model (for example) is not valid anymore, impacting the accuracy of ML predictions. Example: COVID-19 changed consuming behaviors. Buying predicting models were not valid anymore in that context. Improving robustness though monitoring and human in the loop oversight
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Actually yes, because is delegating the risk to other actors. Without the proper oversight of the whole process, one by one case can be underestimated.
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Being honest and transparent about intended use of data not only today, but also when change that intention in the future. It´s possible that some users wants to be compensated because use of his data.
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Yes. Following a due diligence process that take into account legal and enforcement parts, could be an option. Of course, the mobile service provider can say NO in case the process has not been fully completed.
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¡Congratulations team! seeing our actual situation of climate change at worldwide level, a great opportunity to address it and expand it.
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Congratulations team, great use case, applicable to many challenges today in Trustworthy space. Also, great approach to solve it using LLMs, AI, analytics and SAS capabilities.
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Congratulations team, great use case, applicable to every state, municipality and country. Also, great approach to solve it using LLMs, AI, analytics and SAS capabilities.
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