Video: AI and the Future of Work

Today, I spoke at The Atlantic Festival on AI and the Future of Work. The panel featured Kelly Trindel, Head of Industrial Organizational Science and Diversity Analytics at Pymetrics and Sean Gourley, Founder and CEO of Primer, in a wide-ranging discussion about how cross-sector collaborations can better prepare our workforce to expand alongside new and changing technologies.

Machine learning is creating breakthroughs across disciplines – automating medical procedures, expediting legal analyses, and informing our understanding of society. However, machines must be taught to recognize patterns and solve the problems we face – and, as a result, their products or outcomes are not immune to bias, ethical concerns or disparate impact. In her remarks, Deloris discussed diversity and inclusion in both the build and deployment of artificial intelligence.

One of the greatest challenges produced by machine learning is its integration into the workforce. While the skills gap is exacerbated by an education system that too commonly deprioritizes STEM curriculum, existing workers may become displaced if they cannot adapt to changing technologies and roles. Deloris noted that women and people of color are specifically vulnerable to this industrial shift, since the industries and roles in which these groups are most strongly represented have a higher likelihood of automation.

But not all AI is “bad AI,” or even exclusionary in its approach: Kelly Trindel of Pymetrics spoke about how her company uses AI to employ a wide-lens approach in assessing employees’ potential over pedigree. Another platform, Alice, uses AI to better understand the needs of diverse small business owners and connect them to the resources, networks and opportunities they need.

Reimagining the end-product of machine learning algorithms also requires prioritizing diversity and inclusion at the onset: specifically, building diverse teams to design platforms, select data sets and define variables and processes, rather than assuming a reactionary approach to disparate impact, discrimination and ethical concerns. This is where policymakers could and should come in – first by ensuring that as individuals (and their staffers) are well-versed on emerging technologies (a goal of the Tech Institute’s Tech Foundations Program), and second, by aligning with technology companies and advocacy organizations that are in the field every day.

Deloris noted that regulation has to be imagined differently for AI, but exposure to performance mandates, a review of the applicability of existing regulatory models, and new regulations around inclusive data sets could be a helpful start. However, this technology is rapidly changing and we don’t yet know where we will end up. To that end, flexibility, forward-thinking and consistent touchpoints with experts and the community are key to ensuring that technological innovations continue to grow, inclusively.

For a full recap of the day’s session, including this panel, click here. This conversation begins at the 1:33:00 mark.

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D Wilson