How AI is Deciding Who Gets Hired
Science & Technology
Introduction
The Great Resignation continues, with over 11 million unfilled jobs across the United States. Many businesses are struggling to hire new employees nearly two years into the pandemic, as workforce participation remains low while job openings are soaring. In this changing landscape, the recruiting process is undergoing a radical transformation, fundamentally altered by the advent of technology.
In the past, companies received dozens of applications for a single job opening. Now, they face an influx of hundreds, sometimes even thousands. To manage this overwhelming volume, many organizations are turning to Applicant Tracking Systems (ATS) that automate candidate evaluation. Individuals who've applied for jobs recently have likely encountered technology that screens resumes, administers personality assessments, and evaluates interview performances—all without human involvement.
As this automation increases, some are challenging the accountability of AI in hiring decisions. Who is responsible when AI systems produce biased outcomes or break the law? This concern has prompted calls for Congress to step in and hold tech companies accountable for their automated processes.
There is a critical paradox here: businesses claim labor shortages, yet countless individuals are actively seeking jobs. The growing use of AI in hiring has fueled anxiety and frustration among job seekers, leading many to seek solutions to navigate this evolved job market.
The New Reality of Job Applications
A decade ago, job seekers relied on newspapers and physically mailed resumes; today, they can apply online to numerous companies simultaneously. However, this convenience has led to an avalanche of applications, prompting companies to utilize ATS to filter candidates based on preset criteria.
Gracie Sarkisian, the director of New York University’s career center, notes that applicants may face AI tools during interviews, with many Fortune 500 companies adopting these technologies. However, this automation raises critical questions about the fairness and transparency of the hiring process. Critics argue that while these software systems aim to alleviate bias, they may simply reinforce existing discrimination, as underrepresented populations often struggle to navigate AI-driven assessments.
Despite the advancements in technology, applicants remain largely in the dark about how their resumes are processed. Many habitually craft resumes to appeal to human recruiters, unaware that they often must cater to automated systems first. Ian Siegel, CEO of ZipRecruiter, emphasizes that job seekers must align their applications with AI algorithms rather than traditional human expectations.
The Algorithms and Their Impact
Automated hiring tools are not just limited to resume screening; they extend into initial interviews and assessments, implemented by major companies like Goldman Sachs and Delta Airlines. Candidates are commonly asked to participate in pre-screening activities, ranging from answering behavioral questions to engaging in gamified assessments that test their cognitive skills.
However, the nature of these evaluations raises concerns about inclusivity and cultural understanding. Jamal Eggleston, a work readiness instructor at the Hope Program, points out that AI systems often reflect biases inherent in their programming. As technology researchers continue to grapple with these issues, many applicants are finding themselves increasingly alienated by an unyielding system.
While some tech vendors provide tools to optimize resumes for ATS, equal access to these resources varies. Those unfamiliar with technology or facing other barriers remain at a disadvantage, suggesting that a significant portion of candidates are unfairly filtered out of the hiring pipeline.
The Demand for Accountability
Due to the opacity of AI algorithms, discrepancies often go unnoticed. Audits reveal algorithmic discrimination can occur silently, as seen with Amazon scrapping its AI recruitment tool for unfairly disadvantaging women and minority groups. The essence of the issue rests on the ethical application of machine learning and the data upon which these systems are trained.
In response to public concerns, the European Union and various state governments are proposing regulations to ensure transparency and fairness in AI hiring practices. The Federal Trade Commission (FTC) is also poised to hold companies accountable for their automated systems, indicating a growing recognition of the need for oversight in this area.
Ultimately, the adoption of AI-driven hiring strategies is reshaping the workforce landscape. Employers are increasingly tasked with determining the extent of automation they wish to employ in their hiring processes, as the influence of AI is already firmly entrenched in the job market.
Keyword
artificial intelligence, hiring, recruitment, Applicant Tracking Systems, bias, workforce participation, resume screening, automated assessments, transparency, accountability
FAQ
1. What is the Great Resignation?
The Great Resignation refers to the trend where a significant number of employees voluntarily leave their jobs, resulting in numerous unfilled positions across the workforce.
2. How do Applicant Tracking Systems work?
Applicant Tracking Systems (ATS) automate the collection and evaluation of job applications, scoring resumes and determining which candidates progress based on predetermined algorithms.
3. Are AI hiring tools fair?
While AI tools are designed to reduce human bias in hiring, critics argue they may perpetuate existing biases rather than eliminate them. Concerns about inclusivity and fairness are prevalent.
4. How can job seekers adapt to AI in hiring?
Job seekers should tailor their resumes to meet ATS criteria by utilizing keywords and job-specific language commonly found in job descriptions to improve their chances of being noticed.
5. What regulations are being put in place for AI hiring?
Various governmental bodies, including the FTC and the European Union, are exploring regulations intended to ensure transparency, fairness, and accountability in the use of AI for hiring.
