Addressing Gender Bias in the Workplace: A New Approach

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The Peace Innovation Lab at Swoop Analytics recently conducted a study to examine gender bias in the workplace.  Highlights of the study can be found here.The Stanford Peace Innovation Laboratory (PIL) has been researching how digital media can facilitate engagement across diverse social groupings. As part of this, Peace Innovation Labs around the world are building a standard data framework to capture pervasive real-time mediated-social interaction data. This framework would be used to facilitate more peaceful outcomes, by design. rosanna“This data is fascinating in that it illustrates the power of big data to demonstrate meaningful differences in the ways in which men and women treat each other in the workplace. I would love to see how these differences in communication relate to work outcomes such as productivity, creativity, as well as raises, promotions, etc. Furthermore, these results are also consistent with the framework we have developed at Stanford Peace Innovation Lab to use mediated interaction to facilitate positive, pro-social engagement across difference boundaries.” Mark Nelson SxD Headshot - Version 2.png“The ability to measure and analyze what’s happening in any organization, right down to the individual level, in real time, is a big step toward making a previously invisible world visible. This not only allows us to measure and benchmark exactly what isn’t working. More importantly, it lets us test for interventions that measurably reduce gender bias in the workplace, by increasing positive, value-creating behavior across gender boundaries. This will eventually provide organizations with a growing suite of thoroughly proven tools to improve positive behavioral outcomes across group boundaries."As we face repeated, egregious examples of discrimination against women in the tech industry in Silicon Valley, tools like this will enable tech entrepreneurs — we call them peace entrepreneurs — to build technology interventions driven by quantitative behavioral data that measurably increase positive engagement across difference boundaries.” 

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