Rita Wouhaybi, Ph.D., has an urgent call-to-action to ensure diversity and inclusion in a time of advanced analytics and machine learning: the culture of tech leadership needs to change as fast as the technology itself is changing. These leaders can accomplish this, she says, through advocacy, mentorship, and networks — which she examines in detail in a new audio lesson available on Giide through MediaVillage.
Wouhaybi, principal engineer at Intel and a leading female technologist, asserts that a diverse and inclusive society needs more resilient networks — and to achieve that resiliency, leaders need to draw from the commitment and community ties observed in human social networks. She cites the idea of Six Degrees of Separation as an example of the power of a human social network in action.
With more than 100 patents to her name, Wouhaybi's experience makes her uniquely suited to explore the intersection of tech leadership, machine learning, and analytics in the context of inclusivity. Along with a master's in neural networks and a doctorate in distributed networking, Wouhaybi's early start-up experience leading a team of 32 engineers prepared her for her role as chief architect of Intel's Internet of Things, Cloud and Machine Learning platforms.
One of her key responsibilities is bringing machine learning to factories. She notes that factories using machine learning have increased their efficiency through more timely detection of defects and higher quality products. Many factories now rely on locally accessible data that is faster to act on, enabling managers to change course as needed.
This type of intelligence is just one example of why Wouhaybi is optimistic about the potential of analytics and machine learning to have a transformational impact not only on business, but also in our everyday lives. Consider, she posits, adding more intelligence to mobile devices, so they can do computing themselves instead of in the cloud.
Wouhaybi warns, however, that analytics and machine learning used even with unintended bias, can have dire consequences. That's why who designs new a technology is as important as the tech itself.
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