How to Reduce Bias in Datasets and Algorithms w/ Michael Krupa, Cisco
In this HRchat episode Michael Krupa, Senior Director, Inclusive Growth at Cisco joins Bill Banham to talk all things HR tech. In his role at Cisco, Michael is focused on defining people & communities functional processes, operating models, and driving strategies for AI and AI ethics.
Prior to joining Cisco, Michael was a partner and CIO at Mercer. Focused on the Talent line of business, he managed a portfolio of revenue-generating HR technology solutions and drove a multi-year technology strategy.
Questions Include:
* Why and how has 'DE&I-friendly' tech become fundamental to who companies are and how they will succeed in this age of digital transformation? E.g. AI/ML solutions to help reduce bias in recruiting and job descriptions and the use of advanced analytics to provide intelligence to business leaders as they create their diversity and inclusion strategies.
* What are the 2 or 3 most dramatic shifts you see happening in the HR tech space today? What was delayed, if anything, by the pandemic?
* You're quoted as saying "the challenge for vendors and for companies creating HR technology solutions using AI and machine learning will be explainability in the algorithms and to reduce bias in the datasets and algorithms." How can HR trust AI when they can't fully grasp how the algorithms work?
* One of the most common mistakes when implementing new HR technologies is failure to explain to the employees and leaders the value or ROI of the solution. How can HR get better at this?
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