When so many in-person offices went remote after the pandemic—with meetings and communications abruptly facilitated digitally—it became newly possible to collect, analyze, and leverage incredible amounts of workplace data. And with this employee data has come a major uptick in new digital tools to inform employee engagement and performance management. At the same time, organizations have been responding to new and louder calls for diversity, equity, inclusion, and belonging (DEIB) at work: persistent disparities related to who is represented within organizations, and particularly leadership roles, continued to reinforce and illustrate longstanding systemic inequities in society and organizations along lines of race, gender, sexual orientation, socio-economic status, and more. Unsurprisingly, then, tech companies have begun exploring the role that technology and the newly available data troves could play in measuring and/or enhancing organizational DEIB efforts, surveilling employees in order to enhance belonging.

Belonging goes further than inclusion: it is about feeling meaningfully connected to and part of the organization. And the importance of belonging cannot be denied. In the past, survival literally depended on building connections with others to overcome threats and stresses, and humans thus have an evolutionary need to belong. In the last few years, isolation and lack of belonging have fueled a growing mental health crisis, while the lack of belonging has been identified as a key driver behind the “great resignation.”

Is the answer AI-powered tools for workplace surveillance? What are these tools and what are the opportunities they provide? What, if any, are the unintended consequences that their use might bring? To what extent are these tools “for good” also legitimizing employee over-surveillance? Can we ensure that such DEIB tools actually advance equitable and just outcomes?

Read the full article about AI in the workplace by Genevieve Smith & Ishita Rustagi at Stanford Social Innovation Review.