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Leveraging Technology To Improve Diversity And Inclusion in the Workplace

June 3, 2021

Over the past few years, in the wake of movements like #MeToo, social justice concerns, and heightened media coverage, the awareness and need for workable solutions to address Diversity and Inclusion (D&I) challenges in organizations has increased, making D&I strategies in the workplace a necessity. Not only do companies establishing successful D&I policies see more positive brand awareness and better talent attraction, statistics show that these companies see significant revenue increases.

A recent discussion focused on these very topics during the Society of Industrial and Organizational Psychology (SIOP) conference held in April 2021. The panel of experts (Dr. Kizzy M. Dominguez, Eric Sydell, Mary Mescal, Dr. Kimberly Silva, Kristin Delgado, and Dr. Mei-Chuan (Mavis) Kung) weighed in on the state of the research, lessons learned, best practices, and the need for future studies.D&I Technology in Employee Talent Cycle

Utilizing technology for Diversity and Inclusion initiatives

Cultivating a diverse organization and an inclusive culture requires interventions designed to address both individual and structural bias. Technology is an important piece, as the market for D&I tech solutions designed to assist in systemic D&I approaches in organizations is accelerating rapidly. It can play a critical role in D&I success throughout the employee life cycle, most notably at these stages:

  • The early stages of attraction and selection
    Artificial intelligence-powered recruiting and selection tools can be used to remove inefficiencies from the hiring process, attract more diverse candidates, and help identify and mitigate bias in the hiring process.
  • Ongoing employee development
    Virtual reality technology is being leveraged to facilitate effective inclusion training programs to promote D&I practices among leaders and employees. Engagement and retention can be improved via platforms focused on capturing employee perceptions of the current D&I state and enhancing employee experience and communications.
  • Auditing the current structure of your organization
    Advancements in data science and D&I analytics have led to the development of tools that can execute automatic assessment of organizational diversity, identification of potential discrimination, and evaluate pay equity.

Striking a balance between human and technology contributions

However, it is important to be aware of the underlying risks associated with the use of technology to address D&I issues. Data can be influenced by biases buried deep in data sets, leading to unfair and inaccurate inferences that may exacerbate existing inequalities. Additional concerns include issues such as legality and ethics regarding decisions made by autonomous systems, threats to privacy, and the negative perceptions and fears of overreliance on technology that might be held by employees.

Organizations can minimize these risks by embracing a policy of accountability and transparency. Algorithms must be systematically monitored to assess effectiveness and bias, as does the data quality used to inform technology solutions. Solution performance should be regularly evaluated using quality metrics. Because technology is influenced by the individuals who build it, diverse teams must be involved. Most importantly, there must be a balance between technology and human involvement. The goal should not be to remove human judgment entirely from the process, only where bias is most prolific. Stakeholders and employees should be informed and engaged to ensure buy-in and commitment.

Related: Your Diversity and Inclusion Goal Should Be Allyship

Successful implementation of D&I solutions should follow a people-first approach, guided by data insights. Making D&I a core component of the entire business, not just HR, is the overall goal to ensure commitment and success of achieving a diverse and inclusive workforce.

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References

Clark, B.B, Robert, C., & Hampton, S.A. 2015. “The Technology Effect: How Perceptions of Technology Drive Excessive Optimism.” Journal of Business and Psychology, 2, DOI: 10.1007/s10869-015-9399-4.

Bruyere, S. M. 2019. “Technology Changes Everything: Inclusive Tech and Jobs for a Diverse Workforce: Pierce Memorial Foundation Report.”

Cohen, T. 2019. “How to leverage artificial intelligence to meet your diversity goals.” Strategic HR Review.

Dastin, J. 2018. “Amazon scraps secret AI recruiting tool that showed bias against women.” Reuters. Retrieved from https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G.

Garr, S. S., & Jackson, C. 2019. “Diversity & inclusion technology: The rise of a transformative market.” Red Thread Research and Mercer.

Ferdman, B. F. & Deane, B. R. (Eds.) 2014. “Diversity at work: The practice of inclusion.” San Francisco, CA: Jossey-Bass.

Floridi, L., Cowls, J., Beltrametti, M. et al. 2018. “AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations.” Minds & Machines, 28, 689–707. https://doi.org/10.1007/s11023-018-9482-5.

Rao, R., & Hill, B. 2019. “How is the Role of AI in Talent Acquisition Evolving?”

Kristin Delgado Kristin Delgado is a Managing Research Consultant at PSI. Kristin has over 15 years of experience in development, implementation, and validation of talent management solutions across a wide variety of organizational contexts. In her role, she specializes as a technical expert in assessment development, psychometrics, and data analytics. Her work at PSI has focused on test validation, computerized adaptive testing, user-centered design of mobile-first, device-agnostic assessments, measurement equivalence, test security methods, and innovative scoring methodologies that implement advanced machine learning and ideal point models. She plays a key role in research aimed at advancing creative talent management solutions. She has a keen interest in leveraging technology and computational psychometrics to enhance measurement accuracy, predictive validity, fairness, and user experience.