Best AI tools for Detecting Dishonest Responses during Online Interviews

The hiring process has quietly become one of the biggest victims of AI misuse.

Candidates now walk into interviews or rather, video calls - with ChatGPT windows open, whispering prompts into hidden earbuds, or using deepfake overlays that mimic someone else’s face or voice.

This is a real story of candidate doing fraud during an interview - recently shared on linkedin

What used to be a conversation about skills is now a cat-and-mouse game of truth vs. technology.

Recruiters know something is off. Candidates sound too fluent. Answers are too polished. There’s a pause before every response - almost as if a model is thinking, not a person.

This is the new hiring reality. And to restore trust, a new generation of AI integrity tools is emerging - built to detect dishonest responses, proxy participants, and AI-generated behavior in real time.

The Complication

Traditional proctoring tools were built for exams, not interviews.

They detect if someone left the tab - not if someone else is speaking on behalf of the candidate.

What makes dishonest responses in interviews particularly hard to detect is:

• Multi-modal deception - Candidates can fake not just answers, but tone, facial expressions, and even voice.

• Subtle AI assistance - People use earphones connected to another person or real-time GPT whispering tools.

• Deepfake overlays - Video masking tools can swap faces, making identity checks unreliable.

• Scripted responses - AI tools generate perfect yet context-misaligned answers that recruiters often mistake for competence.

These aren’t theoretical problems anymore. They’re showing up in day-to-day interviews across industries, especially in high-value remote hiring.

AI Tools Fighting Dishonesty in Interviews

Here are some of the most promising AI tools that detect dishonest responses during video interviews - each approaching the problem differently.

1. Sherlock

Best for: Hiring Managers and Recruiting teams who want an enterprise-grade, Forensic-grade AI proctor inside live interviews.

Sherlock is considered a leader in the Interview Fraud Detection category

How it works:

Sherlock joins your Zoom, Teams, or Google Meet as an invisible AI agent. It watches for suspicious behavior - like mismatched lip movements, multiple faces, tab switches, whispering, or unusual speech latency - and flags potential fraud or AI-assisted responses.

It uses multi-modal analysis (video, audio, transcript) and builds behavioral signatures for every candidate.

Why it stands out:

Sherlock doesn’t just detect anomalies; it learns what honesty looks like for each user. It also auto-summarizes interviews and creates a “trust score” alongside the skill score.

2. HireVue

Best for: Structured AI interviews and large-scale screening.

How it works:

HireVue uses AI to analyze verbal and non-verbal cues in candidate responses. It looks at tone, sentiment, pauses, and gaze direction to infer authenticity and engagement.

Limitation:

While powerful for structured one-way interviews, it’s less effective for real-time proxy fraud or deepfake detection.

3. Sapia.ai

Best for: Chat-based honesty detection.

How it works:

Sapia uses linguistic and psycholinguistic AI to detect unnatural writing patterns and AI-generated text in chat interviews.

It can spot over-optimized or “machine-styled” phrasing patterns that betray ChatGPT-type responses.

4. Reejig

Best for: Ethical AI scoring with fairness focus.

How it works:

Reejig builds ethical, auditable AI systems that help organizations identify skill patterns while ensuring bias-free evaluation. While not a fraud-detection tool per se, its explainable AI framework adds a trust layer to assessment analytics.

5. Deepware / Reality Defender

Best for: Detecting deepfakes and face-swaps.

How it works:

These tools scan live or recorded video streams for manipulation artifacts - pixel-level inconsistencies, temporal warping, and synthetic noise that indicate tampering.

They’re becoming a vital part of background verification and identity assurance stacks.

6. AuthBridge

Best for: Identity verification in the hiring process.

How it works:

While not built for “dishonest response” detection, this tool ensures that the person interviewed is the same person whose credentials were submitted — closing the loop on identity fraud before interviews even begin.

The New Standard of Interview Integrity

The future of interviews isn’t about catching cheaters - it’s about re-establishing trust in conversations between humans.

AI will soon be present on both sides of the table - candidates using it to assist, companies using it to detect and interpret.

The right path isn’t paranoia; it’s precision.

By layering AI tools like Sherlock into your workflow, you can separate human honesty from machine fluency, ensuring that interviews remain what they were meant to be - a truthful exchange of competence, not computation.

TL;DR Summary

In the age of AI, trust will become the ultimate hiring currency.

The companies that adopt AI integrity layers early won’t just prevent fraud — they’ll hire more confidently, scale faster, and protect the one thing that can’t be automated: human authenticity.