As leading scientific researchers recently put it, “artificial intelligence (AI) is facing a diversity crisis.” Besides highlighting data on the lack of representation in the field, major scientific and technological publications are increasingly sounding the alarm about the ways in which AI can “perpetuate biases” and create new technological forms of exclusion lacking “varied social-emotional and cultural knowledge.”
For today’s DEI and talent leaders, headlines like these raise serious questions about AI, the future of work, and workplace inclusion. Yet in the face of recent shifts and pullbacks in some DEI programs, this new technological terrain also presents opportunities for DEI and talent leaders to shape the conversation around inclusive workforce transformation.
What new strategies and tactics do you need to implement to safeguard workplace diversity in the face of such rapid technological transformation? Here are five key takeaways to consider as you and your organization work to drive equitable outcomes along your AI journey.
According to a May 2023 Salesforce survey of full-time desk workers, 70 percent of business leaders believe their teams lack the skills to effectively and safely utilize generative AI, while 67 percent of workers expect their employers to train them. A recent cross-industry TalentLMS survey reveals that 85 percent of HR managers are planning to address skill gaps by investing in AI learning and development.
Findings like these demonstrate the vital importance of implementing inclusive AI upskilling and reskilling opportunities, particularly when two of the top four obstacles that surveyed HR managers associated with AI trainings were algorithmic bias and AI skepticism.
Recent research by the Brookings Institution demonstrates this need by showing how inequitably AI will impact the future of work. Black and Hispanic employees face average job automation potentials of 47 percent and 44 percent, while risks for White and Asian counterparts are comparably lower at 40 percent and 39 percent. Other recently published reports on AI and the future or work add that employees in the two lowest-wage quintiles, disproportionately held by underrepresented groups, are up to 14 times more likely to need to change occupations by the end of the decade.
Workforce realities like these help explain why survey data shows clear differences in both interest and participation in upskilling among racial and ethnic groups. A recent joint study by Amazon and Gallup, for example, finds that Hispanic workers are the most likely to indicate interest in upskilling (69 percent), followed closely by Black employees (63 percent).
More broadly, as a recent HBR article argues, forward-thinking companies now “consider reskilling a core part of their employee value proposition” in an era in which the “average half-life of skills is now less than five years.” Amazon and Gallup’s upskilling survey proves the truth of such claims: nearly two-thirds of workers believe employer-provided upskilling is very important to evaluating current and potential job roles. The data clearly demonstrates that diverse talent is aware of the value of these investments.
If managed correctly, the coming AI transformation presents an opportunity for DEI and talent leaders to increase diversity and inclusive hiring. New industry partnerships with reskilling nonprofits, diverse talent networks, higher education institutions, and professional organizations are becoming critical to ensuring diverse pipelines and equitable hiring practices. Today’s technology might even help unlock solutions to a long-standing business challenge: how to match diverse talent to the right opportunities. Seramount’s newly launched Career Ascent, for example, provides a next-generation talent pipeline alternative making it easier to identify diverse talent and connect them with relevant opportunities.
It’s vital to ensure that equity gaps in adoption today don’t create an inequitable future of work tomorrow. For this reason, equitable AI adoption is quickly becoming a key component of inclusive DEI and talent strategy. Recent KPMG data on AI generation gaps, for example, shows that Millennial and Gen Z workers report much more concern about the role of AI in their careers and workplace than their Gen X or Boomer counterparts.
Strikingly, while BCG finds that frontline workers are 20 percent less optimistic about AI than their leaders, a recent Hunter Marketing report discovered adoption gaps at the top of the corporate ladder: 61 percent of surveyed male and 29 percent of female executives use AI.
Such pervasive disparities in adoption present a challenge for HR and DEI professionals seeking to build on commitments to fostering an inclusive workforce. But how to solve the problem? Interestingly, leading research in the field has shown that the process of AI adoption itself generates approval for the technology. Yet the experts also argue that adoption is governed by trust, reliability, and addressing concerns. To ensure an equitable distribution of AI’s workforce opportunities and impacts, today’s DEI and HR leaders must therefore do the hard work of auditing AI programs, building new talent networks, and evangelizing and upskilling employees.
The inconvenient truth of the AI research industry’s diversity challenge is now well known. According to Stanford University’s 2021 Artificial Intelligence Index Report, only 2.4 percent of new US resident AI PhD graduates were African American, and only 3.2 percent were Hispanic. Yet we’re only beginning to realize the full social and cultural impacts of this lack of diversity in AI research and development. A new University of Michigan research study, for example, reveals the importance of inclusive AI trainers and annotators to avoid unconscious bias.
As Stanford’s latest AI report puts it, “As the demand for AI-related skills expands, the lack of diversity in race and ethnicity, gender identity, and sexual orientation not only risks creating an uneven distribution of power in the workforce, but also, equally important, reinforces existing inequalities generated by AI systems.” Further accenting this point, a LinkedIn research partnership with the World Economic Forum found that only 22 percent of AI professionals on LinkedIn were women.
One more business-critical consideration: AI inclusion programs have themselves failed to be fully inclusive. While Seramount’s Global Inclusion Index notes that corporate attention to inclusive design is on rise, companies are currently implementing more programs to improve gender diversity than ethnic diversity in AI.
Diversifying the AI pipeline will continue to be a challenge. But with recent industry research showing that today’s business leaders are three times more likely to prefer replacement with new AI-ready talent to retraining existing workers, it’s also crucial for DEI and talent professionals to advocate for comprehensive career equity, including an equitable distribution of retraining opportunities.
In the corporate sphere, inclusive AI teams are fundamental to business success. Industry studies consistently demonstrate a strong correlation between DEI program success, inclusive talent management, and business outcomes. Nowhere does this truth ring truer than in the AI context. Today’s organizational data shows that companies with at least 25 percent of AI development employees who represent racial or ethnic minorities are more than twice as likely to be high-performers.
At the same time, it likely won’t come as a surprise to CDOs and CHROs that Pew Research data reveals that Black employees hold the greatest amount of skepticism about the use of AI in hiring and performance reviews or that Black, Hispanic, and women adults are less likely to view AI program designs as inclusive of their perspectives.
It’s therefore vital to consider the unique value proposition of such diverse thoughts and perspectives. Employee Resource Groups (ERGs) present a golden opportunity to bring diverse talent to the table for insightful discussions of AI implementation, workplace fairness, and inclusive transformation. While this work comes with significant cultural and bottom-line benefits, it also requires strategic employee listening and outside-the-box thinking.
Recent studies of AI in the workplace demonstrate that AI guides business decisions far more commonly in technology, operations, and strategy than in workforce, DEI, or ESG contexts. Yet in a recent PwC survey of “Responsible AI actions planned for 2022,” 1,000 business and technology executives involved in AI strategy ranked “Address the issues of fairness” second to last.
Now more than ever, it’s imperative to ensure that CDOs and CHROs have a seat at the table in leading discussions of AI and the future of work, from guardrails and adoption to outreach and training.
As the pace of digital transformation accelerates and the DEI and talent landscape continues to shift, turning to a trusted partner for up-to-date insights, research-informed DEI best practices, and bias-free solutions can help you unlock business success. Interested in learning more about how Seramount can partner with you to build your inclusive workplace culture of tomorrow? Contact us.