This current job market is plagued by fake job postings that have been misleading American job seekers, wasting their time and distorting employment data. These deceptive listings—often created to collect résumés, inflate company growth metrics, or manipulate job market statistics—erode trust in online job platforms, create inefficiencies in the hiring process, and continue to make the job market worse for job seekers and the unemployed.

Landing a job or even an interview in the STEM field has become nearly impossible for many. And according to a report by the Federal Trade Commission (FTC) cited by CNBC, fake job scams have surged in recent years, with job seekers losing over $68 million in 2022 alone due to fraudulent employment schemes. Additionally, studies suggest that some companies post “ghost jobs” without real hiring intent to build a talent pipeline or make their financial outlook appear stronger.

As the pressure to find work increases for unemployed tech workers right now, there has been little to no issue resolution from our government representatives despite the need for a strong job market correction. Many tech workers have exhausted their unemployment benefits and remain in a very vulnerable position. New legislation around hiring fraud prevention, and potentially a new government task force, are the changes we need to see to correct this very broken job market. 

The rise of fake job postings in an already struggling economy is more than just an inconvenience to job seekers—it actively degrades work quality and exacerbates the skilled labor shortage. When qualified professionals spend time applying for nonexistent roles, they’re diverted from real opportunities where their expertise is truly needed in this country. This creates a bottleneck in hiring as companies looking for top-tier talent struggle to fill critical roles. Worse, the presence of fraudulent listings lowers trust in job boards and recruitment platforms, as we can clearly see from the sentiment on platforms such as LinkedIn, making job seekers more hesitant and prolonging hiring cycles. The end result is an inefficient job market where businesses cannot secure the skilled workers they need, slowing down innovation and productivity across industries.

For example, in manufacturing, where precision and efficiency are crucial, hiring delays caused by fake job postings have particularly damaging effects for obvious reasons. Factories and production lines rely on highly trained specialists to maintain equipment, oversee quality control, and manage supply chains. Unproductive job searches make it harder for qualified candidates to find real employers who are seeking talent. This not only extends the labor gap but also forces companies to operate with understaffed teams, leading to burnout, costly mistakes, and declining output quality. By identifying and eliminating fake job posts and unclogging the hiring pipeline, we create a more reliable hiring environment that ensures the best workers land in the right roles, strengthening both the economy and the quality of the products we rely on every day.

AI detection and reporting systems

Leveraging AI to feed data and alerts to an oversight office would be ideal in this current job climate, and it would give job seekers a better advantage of landing a job. AI-powered detection and reporting systems are emerging as crucial tools to solve this economic issue, and they should be considered. These systems could use natural language processing (NLP), machine learning (ML), and pattern recognition to identify fake job postings by analyzing repetitive or vague job descriptions, companies with no verifiable online presence, inconsistent salary or qualification expectations, and historical job-posting behavior. In combination with AI tools, a new office should be established within the U.S. Department of Labor to collect feedback from this detection system, and to investigate and penalize fraudulent hiring practices, misleading job listings, and unjustified mass layoffs.

Using AI-driven monitoring systems, this office would collect real-time feedback and alerts from job platforms to detect and deter abuse. Eventually, we would have a better idea of the actual number of jobs available on the market. This would give the government a better idea of the types of incentives needed for companies to hire workers back. By implementing these measures, policymakers can promote fair employment practices and create a more transparent job market—one that job seekers can trust. 

A need for stronger federal oversight

Regulatory bodies must take a proactive stance to ensure transparency and accountability in online job markets to correct the current job market and help Americans get back to work. A U.S. Department of Labor oversight office in each state would receive and act on alerts from an AI-powered fraud detection system that monitors job postings across major employment platforms.

Here’s how this closed-loop feedback system would work. 

Phase 1: Detection and reporting (automated and public input)

AI-powered monitoring: AI algorithms scan job boards, corporate career pages, and hiring data to detect suspicious patterns (e.g., repeated unfilled listings, unverifiable employer details, or job descriptions with misleading information).

Public reporting portal: Job seekers, recruiters, and employees can submit complaints or flag suspicious job postings and hiring practices.

Industry compliance checks: Companies above a certain hiring threshold must submit verified hiring reports periodically.

Phase 2: Investigation and validation (with U.S. Department of Labor oversight)

Risk-based assessment: AI categorizes flagged job postings and hiring trends by severity and assigns risk levels.

Human review and verification: U.S. Department of Labor compliance officers conduct manual investigations on high-risk cases, requesting supporting documentation from employers.

Employer response system: Companies must justify flagged job postings, hiring trends, or layoffs within a set timeframe to avoid penalties.

Phase 3: Enforcement and quality improvement

Penalties for noncompliance: Companies engaging in fraudulent hiring or unjustified mass layoffs face fines, hiring bans, or legal action.

Employer rating system: Verified, compliant companies receive a trust score that improves their standing on job platforms, while deceptive employers get flagged.

Incentives for fair hiring: Ethical companies receive tax benefits, federal contracts, or expedited hiring approvals.

Phase 4: Continuous improvement and policy evolution

AI model refinement: Machine learning algorithms continuously learn from new fraud patterns, improving detection accuracy.

Quarterly compliance audits: U.S. Department of Labor oversight teams assess data trends, policy effectiveness, and public complaints to refine regulations.

Transparency reports: Regular reports highlight enforcement actions, job market integrity statistics, and company compliance scores.

Mandating job verification protocols for online job boards, implementing strict penalties for companies engaging in deceptive hiring practices, and enhancing AI-driven compliance monitoring to flag suspicious job postings in real time are reforms we need now. Penalizing companies that take advantage of job seekers in need of work and rewarding companies that have fair hiring processes are steps in the right direction. Fake job postings not only frustrate job seekers but also distort economic data and undermine trust in digital hiring platforms. By leveraging these AI-driven detection systems and strengthening federal oversight, the government and private sector can work together to restore integrity in the job market.

The proposed AI-powered job market integrity system aligns with our current government mission of efficiency and would streamline oversight, reduce fraudulent activity, and ensure that job seekers and employers engage in a transparent, fair, and productive hiring process. Most importantly, we would be getting Americans back to work sooner than later.

By leveraging AI-driven fraud detection, automated reporting mechanisms, and risk-based investigations, this system minimizes wasted time and resources, enabling businesses and workers to operate within an efficient and accountable labor market. The feedback loop of detection, investigation, enforcement, and continuous improvement directly eliminates inefficiencies and ensures resource allocation, enhancing economic productivity. By penalizing fraudulent hiring practices and incentivizing fair employment, this initiative promotes a data-driven regulatory approach that strengthens workforce integrity, reduces unnecessary job market churn, and ultimately boosts economic efficiency at both state and federal levels.