Algorithms make better hiring decisions than experienced hiring managers. Algorithms use data, called people analytics or talent analytics, to assess how a person or group of people will perform in a workplace over the course of a employee-lifecycle. These data analytics are being used for hiring decisions, compensation, promotion. The type of information being collected and analyzed includes demographic data, education, experience, job and performance history, and compensation history; it also typically includes data such as intelligence, personality, age, and family status.
This data is being collected in a number of ways, including ways that are currently hidden from view. Consumer privacy protections are being put into place. The gold standard, the EU’s GDPR, is complex to implement. California’s Consumer Privacy Act of 2018 describes four basic rights regarding personal data:
- People have the right to know what personal data is being collected
- They have the right to know if that data is being sold or disclosed, and to whom
- They have the right to refuse the disclosure of their personal data, and
- People have the right to see and access the personal data being collected
In addition, consumers are protected from retaliation if they exercise privacy rights.
Other states are following California’s lead, and state legislatures are looking at a diverse range of personal data privacy laws. How will the implementation of these privacy laws impact the people analytics that are being used by human resources departments for hiring and other employment decisions? Will people need to choose between privacy and employment?
Civil rights protections and employment law in the United States have been in place for more than fifty years; this is because the playing field in this country is not level. Unless we have consequences set down in law, fairness and equity disappear in American workplaces. Can we build our laws regarding employment equality and civil rights into the algorithms currently analyzing data and making predictions? This is a worrisome issue, because there has already been noted a significant bias in data sets, especially the facial recognition software being used by law enforcement. People of color, especially women of color, are disproportionately excluded from these large data sets. The rate of mistaken identification is higher for these groups; and the impact of false identifications is going to fall most heavily on communities of color.
Despite concerns over employment law and civil rights, and the coming data privacy laws, many businesses are embracing people analytics in an effort to maximize the money spent on hiring and onboarding new employees. Workforce planning and predictive analytics promises to reduce the amount of turnover, fraud, and liability for harassment; and promote a model of human capital based on metrics, like the rest of the decisions a business makes. Some of the data that is being collected and included in these predictive analytics, such as age and family status, is on shaky legal ground if challenged. Other data, such as using personality tests as a data point, may provoke legal challenges in the future. Of concern is the way this data and its use in predictive analytics is not clearly understood outside of the industry.
The trend for consumers toward business is one in which consumers are demanding increased transparency, accountability, and environmental stewardship. Many workplaces are moving toward a training model for employees of ‘civility’, a type of anti-harassment training that takes a holistic approach to human interactions in a workplace. Diversity and inclusion efforts, including significant resources, are being put into play by major retailers, human services companies, and government agencies. Will people analytics support these efforts, or will they take a huge step backward when data-driven people solutions are presented to leadership?
The Future Is Now
Subjective, intuitive decision-making by experienced human resources professionals is no longer considered the best way to make employment decisions by forward-thinking companies. Critical thinking and critical problem solving remain a human process, however; and employment rights, civil rights, and privacy are important and legally-binding issues in employment decision-making. The challenge for those developing people analytics tools will be to incorporate these disparate and difficult-to-quantify issues into data collection and predictive analytics.
We would be pleased to discuss your employment concerns. Please contact us for an appointment.