Using Skills Transparency to Unlock Equity in the AI-Driven Workplace

Workforce diversity initiatives are considered more essential than ever, as organizations increasingly acknowledge that inclusive policies nurture effective and innovative business solutions. The open and clearly defined representation of expected skills, competencies and abilities in the workplace is vital to equitable hiring and grows even more crucial when using AI in Human Resource tooling. 

Despite advancements, the underrepresentation of people of color in leadership roles persists. Latino board representation has remained essentially flat over the last two decades. By 2060, the Hispanic population is forecast to be almost 30% of the American population, but less than 5% of corporate board positions are held by Hispanics. The gender pay gap also reveals the disparity present in today’s workforce: A 2023 report by the National Women's Law Center found that women earn 83 cents for every dollar that men earn, that gap closes to 94 cents for every dollar that men earn when employers adopt transparent pay practices.  These inequalities are why interventions like skill transparency are essential.

While artificial intelligence (AI) continues to influence corporate culture, we’ve also seen a focus on the notion of more equitable workforce and talent practices. In fact, a February 2022 survey from SHRM indicated that a substantial 79% of employers leveraging AI for HR purposes are doing so to support recruitment and hiring: AI is used to develop and then screen incoming resumes, automate candidate searches or target job postings to specific groups. But these models don’t necessarily have clearly defined skills data and they can be biased based on their inputs. In the same report, 54% of organizations using these AI tools said they have faced challenges with them, specifically including issues of bias and discrimination. These challenges emphasize the need to infuse diverse perspectives, prioritize incorporating skill transparency data and ensure rigorous governance of AI models to actively counter bias and foster equity.

Skill Transparency: A Cornerstone of Equity

Skill transparency practices, such as defining measurable skills for each position, are integral to creating effective people systems. They provide HR professionals and decision-makers with clear and comprehensive information about the skills and abilities of employees and candidates, enabling more informed and data-driven decisions regarding recruitment, promotion, talent development and succession planning.

A lack of skill transparency often leads to ambiguity in hiring and promotions, and this can be exacerbated by poorly-trained AI systems that perpetuate existing biases. To help mitigate these issues, incorporate skill transparency into talent strategies. This should include the review and assessment of candidates based solely on whether they possess the skills required for a particular job, reducing subjectivity, and helping counterbalance any implicit biases or stereotypes. With a clear understanding of required skills, employees, regardless of gender or background, can determine their role fit and progression paths with equal opportunity to achieve growth and advancement. 

Incorporating skill transparency into an organization’s policies can also promote pay equity. By tying compensation to clearly-defined skills and competencies, organizations can ensure that similar roles with comparable skillsets are remunerated equally, addressing gaps like the gender pay difference.

With the advances of AI in the talent enablement space, people systems have become even more robust—but we must still exercise caution with them. An October 2022 study by the University of Cambridge in the UK found that claims by AI companies to offer objective, meritocratic assessments are deceptive. It suggested that anti-bias measures to remove gender and race are ineffective because the system-defined “ideal candidate” has historically been influenced by gender and race, and those definitions aided in the development of the AI models. This isn’t just theory; in October 2018, Amazon removed its trial automated candidate screening system intended to rate potential hires because it filtered out women for positions. Even with advanced systems, biases must be actively and deliberately countered

Skill transparency and diversity are not simply ideals to strive for or boxes to check — they are pivotal in today's AI-driven landscape. Organizations have the opportunity to harness the undeniable potential of AI while also actively addressing bias within these systems. By integrating the AI-driven insights that have been carefully modeled to eliminate bias, organizations can gain a nuanced and adaptive understanding of their employees' abilities, which supports more balanced, data-informed and equitable decision-making processes. Defining and developing measurable skills for every role ensures objectivity in recruitment, advancement and pay decisions. And fostering diversity through awareness-raising training and ongoing bias mitigation efforts can drive innovation and imbue AI with ethical considerations. A commitment to both skill transparency and diversity enables organizations to fully realize AI's promise and cultivate a workplace that champions fairness and inclusivity for all.