Summary of Diversity and Inclusion in Ai For Recruitment: Lessons From Industry Workshop, by Muneera Bano et al.
Diversity and Inclusion in AI for Recruitment: Lessons from Industry Workshop
by Muneera Bano, Didar Zowghi, Fernando Mourao, Sarah Kaur, Tao Zhang
First submitted to arxiv on: 9 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Medium Difficulty Summary: This study investigates how Diversity and Inclusion (D&I) guidelines can be effectively implemented in AI-driven online job-seeking systems, aiming to promote fairness and inclusive hiring practices. The authors conducted a co-design workshop with a multinational recruitment company focusing on two AI-driven recruitment use cases, applying user stories and personas to evaluate the impacts of AI on diverse stakeholders. The results show that the co-design workshop successfully increased participants’ understanding of D&I in AI. However, translating awareness into operational practice posed challenges, particularly in balancing D&I with business goals. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty Summary: This study is about making sure artificial intelligence (AI) systems for job searching are fair and treat everyone equally. Right now, many companies use AI to help them find the best candidates, but this can sometimes lead to unfair hiring practices. The researchers worked with a big company that uses AI for recruitment and asked them to think about how they could make their system more inclusive. They found that people need more guidance on how to make sure AI is fair and doesn’t discriminate against certain groups. |
