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With so many examples of algorithmic bias leading to unwanted outputs and humans being, well, humans behavioural psychology will catch up to the AI train, explained Mortensen. However, Wilson warns of new questions on boundaries between personal and workplace data, spurred by such integrations. The solutions?
Key enhancements include the introduction of distributed inference capabilities within the PAI-Elastic Algorithm Service (EAS). It extracts specific information and can generate tailored reports, such as ESG reports when integrated with Alibaba Clouds Energy Expert sustainability solution.
To address this issue, this work proposes an artificial intelligence (AI) empowered method based on the Environmental, Social, and Governance (ESG) bigdata platform, focusing on multi-objective scheduling optimization for clean energy.
But before AI/ML can contribute to enterprise-level transformation, organizations must first address the problems with the integrity of the data driving AI/ML outcomes. The truth is, companies need trusted data, not just bigdata. That’s why any discussion about AI/ML is also a discussion about data integrity.
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