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Celebrating the women of IBM AI Ethics

IBM Business Partners

Along with establishing policies and practices around AI ethics, the AI Ethics Board sponsors workstreams, which bring together experts from across the business to address key business challenges, questions and opportunities. These workstreams often include women as executive sponsors.

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Operationalizing AI Ethics Through Documentation: ABOUT ML in 2021 and Beyond

Partnership on AI

Through collaboration, we can further ensure that these documentation processes satisfy actual needs while reducing redundant workstreams between organizations. PAI is also currently engaged in multiple ABOUT ML research workstreams. Research Workstreams.

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5 Steps Every Organization Can Take to Beat the Transformation Odds (Part 2) 

Planview Blog

Tactics for workstream-level change management For the work delivery-level change management strategy, they focused on the remaining three strategies — collaborate, educate and train, and anchor the change — using the key tactics listed below, chronologically by strategy.

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Back to Basics – Step 5: Preparing for Effective Integration – Governance & Reporting

BTD Consulting

Teams in place to manage your integration workstreams? If the integration manager sees her role as mechanically consolidating and analysing workstream update reports every week, recast the role. Reporting: Visibility between integration workstreams and the wider business is critical. Integration manager to captain the ship?

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A look into IBM’s AI ethics governance framework

IBM Business Partners

An Advocacy Network: a grassroots-level network of employees across the many board workstreams who share and promote IBM’s technology ethics principles within their teams and scale AI ethics initiatives throughout the organization.

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The Future Of Value Stream Management: Harnessing The Power Of Generative AI

Planview Blog

What are the most critical dependencies of this workstream?” It automatically analyzes value stream data in real time and functions as a virtual subject matter expert by providing prompt guidance and insights. Users can engage in a conversation with the data and ask questions such as: “What is my biggest bottleneck?”

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Shedding Light on the Trade-offs of Using Demographic Data for Algorithmic Fairness

Partnership on AI

To learn more about our Demographic Data Workstream, please visit our website , where you can fill out this form to become more involved with the demographic data community at PAI. We are grateful to those who engaged with us and this work over the last year. You can also reach out to us about this white paper directly by emailing sarah.v@partnershiponai.org