There's a growing trend of individuals using AI tools to fraudulently pass job interviews for remote positions, particularly in tech and data-driven roles. According to Gartner, globally, 1 in 4 job candidates will be fake by 2028 due to the rise of AI-generated profiles.
Companies today are at risk. With less oversight in the remote hiring process, along with increasingly accessible and powerful AI tools available, potential consequences such as security and data risks from unqualified individuals remain an issue. Additionally, project delays or failures due to mismatched skills, and legal or compliance issues if sensitive roles are filled fraudulently can set companies back further.
While corporate recruitment teams and staffing partners work to screen out these imposters, let’s breakdown how this happens and what can be done about it.
How job seekers use AI to cheat the hiring process:
1. Real-time AI assistance during interviews:
- Candidates use tools like ChatGPT or more advanced plugins to get real-time answers fed into their ear via smart devices during technical interviews.
- Some use teleprompters or on-screen overlays to appear knowledgeable on camera while reading AI-generated answers.
2. Voice synthesis and deepfake tools:
- In extreme cases, fake candidates use AI to mimic another person’s voice or appearance in video interviews, especially when a third party is hired to impersonate them.
3. AI-written resumes and cover letters:
- Automated tools craft exaggerated or completely fabricated work histories and skills that pass initial screenings by recruiters or applicant tracking systems (ATS).
4. Interview proxies:
- Someone else entirely (with the actual skills) interviews on behalf of the candidate. These proxies may use AI to mask their identity to match the applicant’s profile.
What can be done about it?
While AI and Deepfake technology is being used to cheat the hiring process, AI can also be used to detect job interview fraud by analyzing candidate behavior, voice, video, and language patterns to identify signs of deception or impersonation.
Here are some examples of key methods and technologies being used today:
1. Video & Voice Authentication
- Face recognition: Matches candidate's live video with official ID or application photos.
- Liveness detection: Detects whether a real person is present (vs. deepfakes or pre-recorded videos).
- Voice biometrics: Verifies the speaker’s identity based on vocal characteristics.
2. Behavioral Biometrics
- Typing patterns: In coding interviews or assessments, unique typing rhythms can be analyzed.
- Mouse movements: Patterns during assessments can indicate bot use or remote control.
3. Natural Language Processing (NLP)
- Language analysis: Detects inconsistencies, overly rehearsed answers, or use of AI-generated responses.
- Plagiarism detection: Identifies copied answers or responses generated by LLMs.
4. Environmental Analysis
- Background noise analysis: Picks up signs of coaching or someone whispering answers.
- Screen monitoring tools: Check for unauthorized apps, external monitors, or screen sharing.
5. AI-Generated Response Detection
- Text fingerprinting: Tools like Turnitin or Originality.ai can flag content likely generated by AI.
- Conversational inconsistency: Real-time monitoring tools evaluate coherence, hesitations, and unnatural phrasing.
6. Geolocation and IP Tracking
- IP consistency checks: Confirms the candidate is applying from a logical location.
- VPN/proxy detection: Flags attempts to hide identity or location.
Companies can help mitigate their risk of imposter candidates by utilizing trusted staffing partners with a deep talent pool and strong referral networks to help ensure only qualified candidates are being presented to fully remote opportunities. Contact Power-4 to learn more about how we can help you identify the right talent – remote, hybrid, and onsite – for your open positions.