First and Last Name/s of Presenters

Lindsey TortoraFollow

Mentor/s

Professor Bora Kwon

Participation Type

Poster

Abstract

Bias in recruitment has long hindered progress toward equitable and inclusive workplaces. Traditional hiring practices are often shaped by unconscious human biases, prompting the emergence of artificial intelligence (AI) as a potential solution for fairer, data-driven decision-making. However, research shows that AI tools trained on historical data may inherit and even amplify existing biases, raising critical concerns about transparency and fairness (Binns, 2018; Cowgill, Dell’Acqua, & Deng, 2021; Raghavan et al., 2020). This study explores whether AI can truly deliver bias-free hiring or if that remains a myth. By examining current research and industry applications, the study investigates the intersection of AI and diversity, equity, and inclusion (DEI), evaluating how algorithmic hiring affects representation and fairness in the workplace. The primary objective is to assess both the opportunities and limitations of AI in recruitment, offering evidence-based recommendations for organizations to responsibly implement AI while maintaining ethical oversight. Ultimately, the study emphasizes that AI can support DEI goals only when developed and deployed with intentionality, transparency, and continuous human oversight.

College and Major available

Welch College of Business, Finance BS, Management BS

Academic Level

Undergraduate student

Location

Digital Commons & West Campus West Building University Commons

Start Day/Time

4-25-2025 12:00 PM

End Day/Time

4-25-2025 2:00 PM

Students' Information

Lindsey Tortora

Major: Finance & Business Management

Minor: Human Resource Management

Honors Student

Year of Graduation: 2025

Winner, Most Scholarly Impact or Potential 2025 Award

Winner, Dean's Prize: Welch College of Business & Technology 2025 Award

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

Prize Categories

Best Multidisciplinary Research or Collaboration, Most Scholarly Impact or Potential, Most Transformative for Social Justice, Best Visuals, Most Creative, Best Writing

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Apr 25th, 12:00 PM Apr 25th, 2:00 PM

Tech Meets Inclusion: Investigating AI’s Role in Fair and Diverse Hiring

Digital Commons & West Campus West Building University Commons

Bias in recruitment has long hindered progress toward equitable and inclusive workplaces. Traditional hiring practices are often shaped by unconscious human biases, prompting the emergence of artificial intelligence (AI) as a potential solution for fairer, data-driven decision-making. However, research shows that AI tools trained on historical data may inherit and even amplify existing biases, raising critical concerns about transparency and fairness (Binns, 2018; Cowgill, Dell’Acqua, & Deng, 2021; Raghavan et al., 2020). This study explores whether AI can truly deliver bias-free hiring or if that remains a myth. By examining current research and industry applications, the study investigates the intersection of AI and diversity, equity, and inclusion (DEI), evaluating how algorithmic hiring affects representation and fairness in the workplace. The primary objective is to assess both the opportunities and limitations of AI in recruitment, offering evidence-based recommendations for organizations to responsibly implement AI while maintaining ethical oversight. Ultimately, the study emphasizes that AI can support DEI goals only when developed and deployed with intentionality, transparency, and continuous human oversight.

 

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