Best Practices to Reduce the HR Biases by Using AI
Companies often advertise their diversity initiatives. However, hidden biases during recruitment limit candidate options. This bias is highly prevalent in the workplace, affecting various business decisions. Consequently, social stereotyping may occur in the workplace, resulting in biases that can negatively impact decisions related to recruitment, hiring, promotion, advancement opportunities, retention, and evaluations.
In recent years, there has been an increase in more nuanced methods to test individuals for unconscious bias, such as the implicit association test, since it has been established that unconscious bias is a more significant problem for businesses than conscious bias.
Factors Contributing to Bias
Several factors contribute to biases and the way we make decisions:
● Perception: how we view people and perceive the world.
● Attitude: how we respond to certain people.
● Behavior: how friendly/receptive we are.
● Attention: the aspects of a person to which we pay the most attention.
● Active Listening: how much we hear what certain people say.
● Micro-affirmations: how much or how little we comfort certain people in certain situations.
Post-Pandemic Bias
As of late, it has been observed that the pandemic has made unconscious bias more apparent because we have fewer opportunities to interact in person. There is a feeling of Zoom fatigue among many of us. Instead of asking, "How was your day" at the water cooler or coffee pot at work, we want to begin Zoom, have our meeting, and leave. We don't take the time to connect, so we're more prone to bias in that sense. In the meantime, this raises whether the virtual hiring process will exacerbate unconscious bias or mitigate it. This is where AI comes into the picture.
Hiring Bias and AI
How biased will AI Decisions be compared to Human Decisions? How might AI impact these issues?
By using artificial intelligence, biases can be identified and reduced. However, there is also a need to improve AI systems themselves - by including how it uses the data collected, deployed, and maintained. Doing so helps prevent them from perpetuating human and societal biases or creating bias and related challenges of their own. AI can reduce humans' subjective interpretation of data since machine learning algorithms are trained to consider only the variables that increase their predictive accuracy based on training data. In addition, some evidence shows that algorithms can improve decision-making, causing it to become fairer in the process.
AI helps the HR department gain insight into employee referrals by looking into the kinds of candidates employees refer to and the most successful ones. It can also analyze performance data from previous referrals and identify candidates similar to successful employees.
Technology can also reduce the effects of unconscious bias on hiring teams by helping organizations conduct structured interviews more effectively. Artificial intelligence has various applications that can help recruiting teams hire faster, wiser, and more impartially, from self-screening candidates to conducting the most compelling interviews and assessments. In addition to significantly reducing recruiter administrative work, AI improves the candidate experience, improves the "match" between applicants and vacancies, and removes any unconscious biases people might otherwise have when making hiring decisions. So, AI can reduce unconscious bias and significantly speed up the hiring process through automation and best match candidates by analyzing their online presence.
Major Areas where AI is Contributing in Recruiting Process:
● Attracting talent and screening several resumes
● Reduction of bias and promotion of diversity
● Responding to applications and answering candidate queries
● Detect attrition patterns
● Schedule management
Is Human Judgment Still Needed in Hiring to Reduce Bias?
Definitions and statistical measures of fairness may be helpful. Still, they do not consider the social contexts into which an AI system operates or how the data were collected. Therefore, it is essential to consider when and in what form human judgment is needed. What are the criteria for deciding when a system has sufficiently minimized bias to be used publicly? Additionally, in which situations is it acceptable to make fully automated decisions? No algorithm can resolve such questions. No machine can determine the correct answers; it requires human judgment and methods, including social sciences, law, and ethics, to develop standards to use AI ethically and without bias.
Conclusion:
There is no doubt that AI is an efficient technology that can help with numerous HR functions; however, some functions still require human intervention. Human control is still needed to guarantee that AI does not replicate or introduce new biases based on the data we provide. By ranking and grading prospects and then analyzing the demographic breakdown of those candidates, recruiting AI algorithms can be evaluated for bias. The good news is that if AI does reveal a bias in your hiring, you'll have the opportunity to address it. We can use our human judgment and knowledge, aided by AI, to determine how to correct any biases and enhance our procedures. Human resource leaders can integrate AI with numerous HR functions to ensure effective AI and Talent Management, resulting in retaining top talent and attracting new talent.
In recent years, there has been an increase in more nuanced methods to test individuals for unconscious bias, such as the implicit association test, since it has been established that unconscious bias is a more significant problem for businesses than conscious bias.
Factors Contributing to Bias
Several factors contribute to biases and the way we make decisions:
● Perception: how we view people and perceive the world.
● Attitude: how we respond to certain people.
● Behavior: how friendly/receptive we are.
● Attention: the aspects of a person to which we pay the most attention.
● Active Listening: how much we hear what certain people say.
● Micro-affirmations: how much or how little we comfort certain people in certain situations.
Post-Pandemic Bias
As of late, it has been observed that the pandemic has made unconscious bias more apparent because we have fewer opportunities to interact in person. There is a feeling of Zoom fatigue among many of us. Instead of asking, "How was your day" at the water cooler or coffee pot at work, we want to begin Zoom, have our meeting, and leave. We don't take the time to connect, so we're more prone to bias in that sense. In the meantime, this raises whether the virtual hiring process will exacerbate unconscious bias or mitigate it. This is where AI comes into the picture.
Hiring Bias and AI
How biased will AI Decisions be compared to Human Decisions? How might AI impact these issues?
By using artificial intelligence, biases can be identified and reduced. However, there is also a need to improve AI systems themselves - by including how it uses the data collected, deployed, and maintained. Doing so helps prevent them from perpetuating human and societal biases or creating bias and related challenges of their own. AI can reduce humans' subjective interpretation of data since machine learning algorithms are trained to consider only the variables that increase their predictive accuracy based on training data. In addition, some evidence shows that algorithms can improve decision-making, causing it to become fairer in the process.
AI helps the HR department gain insight into employee referrals by looking into the kinds of candidates employees refer to and the most successful ones. It can also analyze performance data from previous referrals and identify candidates similar to successful employees.
Technology can also reduce the effects of unconscious bias on hiring teams by helping organizations conduct structured interviews more effectively. Artificial intelligence has various applications that can help recruiting teams hire faster, wiser, and more impartially, from self-screening candidates to conducting the most compelling interviews and assessments. In addition to significantly reducing recruiter administrative work, AI improves the candidate experience, improves the "match" between applicants and vacancies, and removes any unconscious biases people might otherwise have when making hiring decisions. So, AI can reduce unconscious bias and significantly speed up the hiring process through automation and best match candidates by analyzing their online presence.
Major Areas where AI is Contributing in Recruiting Process:
● Attracting talent and screening several resumes
● Reduction of bias and promotion of diversity
● Responding to applications and answering candidate queries
● Detect attrition patterns
● Schedule management
Is Human Judgment Still Needed in Hiring to Reduce Bias?
Definitions and statistical measures of fairness may be helpful. Still, they do not consider the social contexts into which an AI system operates or how the data were collected. Therefore, it is essential to consider when and in what form human judgment is needed. What are the criteria for deciding when a system has sufficiently minimized bias to be used publicly? Additionally, in which situations is it acceptable to make fully automated decisions? No algorithm can resolve such questions. No machine can determine the correct answers; it requires human judgment and methods, including social sciences, law, and ethics, to develop standards to use AI ethically and without bias.
Conclusion:
There is no doubt that AI is an efficient technology that can help with numerous HR functions; however, some functions still require human intervention. Human control is still needed to guarantee that AI does not replicate or introduce new biases based on the data we provide. By ranking and grading prospects and then analyzing the demographic breakdown of those candidates, recruiting AI algorithms can be evaluated for bias. The good news is that if AI does reveal a bias in your hiring, you'll have the opportunity to address it. We can use our human judgment and knowledge, aided by AI, to determine how to correct any biases and enhance our procedures. Human resource leaders can integrate AI with numerous HR functions to ensure effective AI and Talent Management, resulting in retaining top talent and attracting new talent.
