Artificial Intelligence has gained significant popularity in recent years, and businesses are beginning to explore how AI can be useful. Companies are continually leveraging these technologies to optimize multiple business operations, and talent acquisition is no exception. The use of AI in candidate sourcing is becoming more widespread, enabling businesses to increase the speed and effectiveness of their recruitment processes. But with the rise and integration of AI technology in recruitment, the ethics of using such technologies have become an area of significant concern. One of the most compelling concerns is the potential for bias and discrimination in the selection of candidates. This blog post discusses how companies can use AI in candidate sourcing while avoiding bias and discrimination.

Understand the AI software: The first step in ensuring that AI is used ethically in candidate sourcing is by understanding how the machine learning algorithms work. Machine learning algorithms learn from data, and the data used to train the AI can itself be biased or discriminatory. Therefore, businesses need a more cautious approach to the recruitment software they adopt. They need to understand the methodology behind the AI sourcing software, test the software with diverse candidate data, and analyze the software’s output for any potential issues.

Eliminating biased data: The use of AI algorithms in candidate sourcing requires a large volume of data to train the software. Basing AI machine learning on biased or discriminatory data sets leads to algorithms that favor particular candidate attributes or disqualifies others based on immutable characteristics like ethnicity, gender, age, or any other protected class. To eliminate data biases, businesses must engineer the quality of data procured, thus providing high-quality and unbiased information for the algorithmic solution. Precise processes should be put in place to secure equitable data sources, ensuring that their training data sets are representative of the total population for diversity purposes.

Make use of expert human recruiters: AI-powered tools cannot replace expert recruiters. Though AI applications provide a level of automation and efficiency, human intervention and expertise remain crucial for ethical AI use. Experienced recruiters can train AI-powered sourcing software to properly identify the critical and non-critical aspects of the recruitment process. While the algorithmic solution automates specific repetitive tasks, expert recruiters can add a level of human interaction when they assess data.

Ensure Transparency: Engage candidates on how the AI-powered sourcing software works, where and how data is collected, and how it’s utilized in the recruitment process. Maintain transparency in job descriptions with regards to the use of AI and what part algorithms play in the recruitment process. Honest communication helps reassure candidates, puts them at ease, and reduces the fear and skepticism of AI-infused recruitment technology.

Regular auditing and monitoring: After fine-tuning the AI-powered sourcing software, companies should monitor the outputs of the algorithm regularly. While AI solutions are useful in candidate sourcing, biases can still persist, and periodic audits or monitoring of the algorithm will help detect any potential bias, enabling businesses to recalibrate their algorithmic tool appropriately.

Conclusion:
Recruiting with AI sourcing tools can increase speed and efficiency in the recruitment process, but it could also create bias and discrimination issues. Firms must analyze the sourcing tools and data to protect against bias and discrimination and ensure that AI-driven recruitment solutions align with the company’s culture and values. They must deploy high-quality data sources, establish AI training data sets that are representative of society, and engage experienced human recruiters. Transparency is critical, and periodic audit and monitoring may need to be conducted to ensure a perfect and bias-free recruitment process. By following the methods mentioned above, companies can use AI-powered sourcing while avoiding bias and discrimination during the hiring process.