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Generative AI’s change management challenge

CIO Business Intelligence

Despite headlines warning that artificial intelligence poses a profound risk to society , workers are curious, optimistic, and confident about the arrival of AI in the enterprise, and becoming more so with time, according to a recent survey by Boston Consulting Group (BCG). A lot has happened since that last survey on attitudes to AI in 2018.

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Responsible AI can revolutionize tax agencies to improve citizen services

IBM Big Data Hub

But the rates of exploration of AI use cases and deployment of new AI-powered tools have been slower in the public sector because of potential risks. Driving innovation for tax agencies with trust in mind Tax or revenue management agencies are a part of the public sector that might likely benefit from the use of responsible AI tools.

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6 business risks of shortchanging AI ethics and governance

CIO Business Intelligence

Even if the AI apocalypse doesn’t come to pass, shortchanging AI ethics poses big risks to society — and to the enterprises that deploy those AI systems. The following real-world implementation issues highlight prominent risks every IT leader must account for in putting together their company’s AI deployment strategy.

Risk 145
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Highlights from the Strata Data Conference in New York 2018

O'Reilly on Data

Watch " Managing risk in machine learning.". Amber Case covers methods product designers and managers can use to improve interactions through an understanding of sound design. The answer to life, the universe, and everything: But can you get that into production? Von Neumann to deep learning: Data revolutionizing the future.

IoT 140
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Are You Ready for Some IRM? Gartner’s 2018 Security & Risk Summit Events Span the Globe

John Wheeler

1) State of Risk Management, 2018 . Risk management continues to be an area of growing maturity and investment for most organizations, as the risk landscape becomes increasingly complex and interconnected. 2) How IRM Fits Into a Digital Risk Management Solution Stack.

Risk 40
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Machine Learning Product Management: Lessons Learned

Domino Data Lab

It focuses on his ML product management insights and lessons learned. If you are interested in hearing more practical insights on ML or AI product management, then consider attending Pete’s upcoming session at Rev. I was fortunate to see an early iteration of Pete Skomoroch ’s ML product management presentation in November 2018.

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Data Governance and Metadata Management: You Can’t Have One Without the Other

erwin

When an organization’s data governance and metadata management programs work in harmony, then everything is easier. Therefore, most enterprises have encountered difficulty trying to master data governance and metadata management, but they need a solid data infrastructure on which to build their applications and initiatives.

Metadata 135