Are AI Recruitment Tools Ethical And Efficient? The Pros And Cons Of ATS

Identifying the right talent remains challenging for HR professionals and recruiters. Companies rely on artificial intelligence (AI) technology to perform tasks like screening resumes and scheduling interviews. But are AI recruitment tools ethical and efficient? There are benefits and pitfalls of automated hiring practices.

AI-driven technology and applicant tracking systems (ATS) have become indispensable tools for companies worldwide. According to Predictive Hire, 55% of hiring managers have invested in AI recruitment. And most Fortune 500 companies are using AI technology to filter resumes before they get to hiring teams and recruiters.

In recent years, there has been concern over ethics and efficiency in data analytics and AI-based hiring tools. Companies that adopt applicant tracking systems run the risk of eliminating qualified candidates from the pool.

Additionally, there are growing concerns about the ethics of ATS—does AI technology widen employment gaps between demographics?

How AI Recruitment Works

AI recruiting software collects and screens hundreds of resumes. These are stored in a database for recruiters to access. Depending on the system, HR professionals can manually review resumes, but recruiters generally skim and only take about six seconds per applicant. In a competitive market, these six seconds are crucial, but many systems don’t even allow for that.

Recruitment software applies machine learning algorithms to complex recruitment data to optimize recruitment and make high-volume tasks more efficient.

Here is a breakdown of how automated recruiting works:

• Hundreds of applications are received, most of which are unqualified per the requirements input in the system.
• Intelligent screening systems identify qualified candidates within minutes, grading candidates according to keyword match, algorithms, and recruitment data.
• Some recruitment tools can interact with candidates via automated messaging, responding to questions about the position.
• Recruiters instantly schedule interviews with the candidates that ATS considers qualified, using technology to organize and track interviewees.

Benefits to Applicant Tracking Systems

When organizations utilize AI-driven technology and applicant tracking systems, they hope to find the ideal match for the open position while conserving resources.

AI tools can:

• Help hiring teams process the maximum amount of applications in a shorter time frame. Automated scheduling processes also save time for HR professionals, increasing the chance of finding quality hires.
• Filter out applicants who are not a good fit. Sifting through hundreds of resumes has a higher error rate. Recruiters can lose focus over time, missing key details that may indicate a successful hire.
• Help candidates receive a faster response time for HR teams, leading to higher acceptance rates.
• Minimize operational costs. Because ATS can run automated tasks, corporate executives and managers can focus on higher-value work.

Ethical Concerns with Applicant Tracking Systems

The Human Component

The root problem with automated processes is the lack of human intelligence; ATS can’t identify human potential or creativity. Instead, AI technology can filter out desirable talent who don’t structure their resumes or applications perfectly.\

Diversity is the biggest concern when considering whether AI is efficient and ethical. Diversity, equity, and inclusion (DE&I) are critical workforce components, and employers must address hiring biases. For example, ATS can eliminate candidates who may not have access to the resources to craft technologically perfect applications, leading to other ethical concerns.

Among many other setbacks caused by the pandemic, many women and marginalized groups have found themselves without work. While these demographics are improving, job recovery remains inequitable among marginalized communities.

Rushing to recover from devastating losses caused by COVID-19 economically, employers have not addressed the consequences of ATS and other automated hiring systems.

Machine learning algorithms often involve systematic bias, causing unethical hiring practices:

• In 2018, Amazon found their AI software downgrading applications from women, excluding candidates from all-female colleges.
• A 2018 study found that facial recognition technology such as Face++ and Microsoft AI could analyze applicants’ emotions and personality characteristics. Black men, for instance, were assigned more negative qualities than white men.
• AI-based hiring processes raise privacy and protection concerns. By law, employers cannot inquire about physical disabilities, mental health, age, gender, and marital status. However, such demographic information cannot inform hiring decisions. Still, automated systems can potentially access each applicant’s private information without their consent.

How To Limit AI Bias To Promote DE&I

New Legal Requirements

In 2021, the New York City Council voted to pass a bill requiring automated system audits. Both candidates and employees will be notified of the use of automated assessment and evaluation for hire or promotion, among other requirements. Companies using ATS can follow New York’s example by preparing for potential audits.

Auditing

• Identifying Bias: ATS is inherently “biased” against people deemed unqualified for the position. HR professionals should first identify discrepancies in outcomes between groups, i.e., race, gender, and other marginalized communities.
• Assess Justifiable Bias: Observing eliminated applications doesn’t address AI outcomes. What are the root causes of the observable differences in automated bias?
• Mitigate Bias: Documentation is vital in hiring strategies. Reports should include information about the company’s fairness objectives, disadvantages among demographic groups with ATS, root cause identification, and information about the targeted intervention.

The easiest way to promote diversity and inclusion within the workplace, especially for companies committed to using automated recruitment tools, is to use ATS to invite and boost diverse profiles.

Edit job postings to promote diverse talent and require both tracking systems and candidates to remove photographs, names, and addresses from the pool to better focus on applicant talent and potential.

The New York City law will take effect as early as January 2023. While companies can prepare for the event that similar regulations will take place in their states, hiring executives can do more to ensure that DE&I is a workplace priority.

Failure to monitor your company’s recruitment values can result in significant time, money, and reputation loss. Assessing and auditing your hiring strategies is an opportunity to consider different AI tools that will streamline the process while remaining unbiased and transparent.

Equitable recruitment and promotion processes will encourage trust and morale among the team, bolstering employee retention.