Algorithms follow the rules every time. People don’t. What happens when you throw the legal system into the mix?
“Over and over, the goal of the game seems to be to keep the victims feeling ashamed and the documentation out of HR’s hands. Meanwhile, NDAs are used to cover tracks and keep a lid on the story.” John Sumser
What can HR do to recover from discrimination or harassment or whistleblower drama? Resident employment law attorney Heather Bussing reviews your options.
Behind the uncoded bias in AI hiring are machines participating in and perhaps even dictating hiring decisions.
Heather Bussing asks, “Can a workplace recover from discrimination or harassment or whistleblower drama?” It seems that second chances are never evenly distributed and resentments have a long half-life. What can HR do?
“How do people change their minds about discrimination? What inspires you to abandon what you believed before, then believe something different? What if the question is not what happened or how does it work? What if it’s something you just believe? Religion is a good example. Discrimination is another.” - Heather Bussing
“We are designed to connect with one another. We are also designed to be afraid of new and different things. Both aspects of our reality are important for survival.” - Heather Bussing
“While it is true that a machine can do a better job at relentlessly sticking to a narrow script, it cannot see or understand things that are not in the data. Unlike people and their unconscious biases, machines can only change their approach with new measurement and new coding. In other words, while machines may be able to address small components of unconscious bias, they cannot address all (or even most) of it.” - John Sumser
“Allowing machines to participate in and perhaps even dictate decisions in Human Resources raises a host of ethical considerations. After all, these systems control various forms of opportunity for the workforce. More precisely, they involve people’s livelihood, hopes and dreams.” - John Sumser
“Bias is always an issue with AI because the machine learning systems only know what they are taught. And what machine learning systems ‘‘learn’ is sometimes surprising or just wrong.” - Heather Bussing
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