Can technology-based hiring algorithms reproduce queerphobic biases under a neutral facade?
Technology-based hiring algorithms are designed to analyze applicant data and match it with job openings. They aim to make the recruitment process more efficient and less prone to human errors like unconscious bias.
They may have some limitations that can lead to reproducing queerphobic biases under a neutral façade. In this article, we will explore how such biases occur, their impact on LGBTQ+ individuals, and ways to mitigate them.
How Technology-Based Hiring Algorithms Work
Technology-based hiring algorithms use data science techniques to analyze large datasets. They extract relevant features from resumes and applications, identify patterns, and match them with job requirements. The algorithms evaluate skills, experience, education, and other factors that help predict job performance. They also compare candidates against each other based on these criteria.
Queerphobia in Recruiting
Queerphobia refers to discrimination or prejudice against people who identify as lesbian, gay, bisexual, transgender, or nonbinary. It is an active form of oppression that affects all aspects of life, including employment opportunities. According to recent research, queerphobic attitudes prevail among heterosexual workers and managers, leading to lower wages and fewer promotions for LGBTQ+ employees.
38% of LGBTQ+ workers reported experiencing workplace discrimination based on sexual orientation or gender identity in 2019.
Reproducing Queerphobic Bias Under a Neutral Façade
Technology-based hiring algorithms can reproduce queerphobic bias by focusing on irrelevant characteristics or favoring certain groups over others.
They may give more weight to traditional masculine or feminine traits like leadership or teamwork, which are associated with heteronormativity. These biases become embedded in the algorithm's learning process, reinforced by previous hires, and replicated across diverse industries.
Impact on LGBTQ+ Individuals
Reproducing queerphobic bias under a neutral façade has significant implications for LGBTQ+ individuals seeking employment. They face greater barriers in finding jobs, getting promoted, and advancing their careers. This leads to higher rates of unemployment and underemployment, increased stress, and decreased job satisfaction. The impact is even worse for minority subgroups within the LGBTQ+ community, such as transgender individuals or those living with HIV/AIDS.
Mitigating Queerphobic Bias
To mitigate queerphobic bias in technology-based hiring algorithms, organizations must take proactive steps:
- Review the algorithm's design and ensure it does not perpetuate stereotypes or favor specific demographics.
- Incorporate diversity metrics into the hiring process, including sexual orientation and gender identity.
- Train managers and recruiters to recognize implicit biases and counter them actively.
- Partner with LGBTQ+ advocacy groups to identify best practices and promote inclusivity.
Technology-based hiring algorithms can help companies make more informed decisions about candidates.
They need careful design and monitoring to avoid reproducing queerphobic biases that disproportionately affect marginalized communities. By addressing these issues, we can create a more equitable workplace where all employees thrive based on their skills and contributions.
Can technology-based hiring algorithms reproduce queerphobic biases under a neutral façade?
Technology-based hiring algorithms can be designed to reduce queerphobic biases that result from human prejudices and stereotypes, but they may not always succeed in doing so. These systems rely on data to make decisions about candidates, and if this data is biased, it will perpetuate those biases in their decision-making processes.