One of the most critical decisions that an HR professional makes is to hire the right candidate. Online assessments are one of the major parts of the recruitment process.
From technical skills to problem-solving and even personality traits, these assessments provide a peek into the potential of a candidate. But now that we are rapidly moving toward remote hiring and digital skills tests, the question is, how does one ensure that these online assessments are valid?
Learn about proctoring, the process of invigilating a candidate in an assessment to make sure that they abide by all the rules. With the rise of online hiring, two types have emerged: human proctoring and AI proctoring. Both come with their own strengths and weaknesses and knowing those is important so you can make the right choice for your hiring process.
In this blog, we’ll compare human proctoring and AI proctoring, examining how each works, their benefits, drawbacks, and the best use cases.
Summarise this post with:
What is proctoring and why does it matter?
Proctoring is the act of supervising or monitoring candidates during an assessment to ensure they’re adhering to guidelines and not engaging in dishonest behavior like cheating.
In the context of hiring, ensuring fair and honest assessments is important, as it helps you make well-informed decisions about candidates’ capabilities.
With online assessments now the norm for many organizations, it is critical to have a system in place to monitor candidates remotely in order to maintain the integrity of the evaluation.
Without proper proctoring, employers run the risk of having inaccurate results that don’t reflect a candidate’s true abilities.
Types of proctoring: Human vs AI
There are two common kinds of proctoring: human and AI. Let’s investigate both of them more closely.
Human proctoring
Human proctoring is the traditional method, whereby a real person oversees the candidate during their assessment. This can be done either in-person or remotely, but for remote assessments, human proctors usually observe via live video.
How does human proctoring work?
In a typical human proctored setup, the candidate logs into the assessment platform where they are observed by a proctor through video. The proctor is on the lookout for suspicious activities, such as the candidate looking away from the screen, using unauthorized resources, or receiving help from another person. If the proctor suspects cheating or rule violations, they can intervene or flag the behavior for review.
A significant aspect of human proctoring is the real-time interaction between the proctor and the candidate. If a candidate faces technical issues or needs clarification about the test, they can directly communicate with the proctor. The proctor can also ask the candidate to adjust their camera to ensure they are in a secure environment.
Advantages of human proctoring
1. Real-time oversight
Human proctors provide live, real-time monitoring, meaning they can react instantaneously to any suspicious behavior. In case of an attempt to cheat or violate the rules, a proctor will immediately intervene to warn the candidate or shut down the test.
2. Personal touch
Having a real person monitor the test can make candidates feel at ease. This is especially true for high-stakes testing, where candidates can appreciate the option to ask questions or resolve issues right then and there. This can create a better overall experience.
3. Flexibility
Human proctors can adapt to different situations and handle complex issues that AI systems might miss. For example, if a candidate’s camera malfunctions, a human proctor can troubleshoot in real time.
Disadvantages of human proctoring
1. Higher costs
Human proctoring can be quite expensive. Hiring trained proctors, especially for a vast number of assessments that you need to monitor, can start adding up quickly. On average, the cost of a live proctor can range from $30 to $70 per candidate depending on the platform and service.
2. Limited scalability
Human proctoring doesn’t scale well. As your hiring volume increases, you’ll need more proctors, which can lead to logistical challenges and increased costs. This makes it harder to manage large-scale assessments.
3. Potential for human error
Despite being trained, human proctors are still prone to errors. They can miss suspicious behavior due to fatigue or distraction. In fact, research has shown that humans can miss up to 30% of cheating incidents during remote assessments due to human oversight limitations.
AI proctoring
AI proctoring is an application of artificial intelligence and machine learning algorithms for monitoring candidates sitting for assessments. It detects the behavior patterns of candidates and reports suspicious activities such as cheating and rule violations, without human intervention.
How does AI proctoring work?
AI proctoring uses complex algorithms to ensure analysis of multiple data points throughout the examination. It can track eye movement in respect to a candidate, detect if the candidate is looking away from the screen, monitor facial expressions, and even background noise. The most complex of these systems can even record keystrokes or flag if more than one person is present in the candidate’s environment.
For instance, AI can detect if a candidate opens a new browser window or if they’re using a second device. If suspicious activity is detected, the AI flags it for further review, either by a human proctor or the HR team.
Advantages of AI proctoring
1. Cost-effective
AI proctoring is also cheaper than human proctoring. Though it is highly expensive to establish AI systems, it is cheaper per candidate, especially when hundreds of thousands or millions of candidates are involved. The estimate for AI proctoring has been from $1 to $5 for one candidate and this is much less expensive than human proctoring at $30 to $70 for one candidate.
2. Scalability
AI systems are scalable. They can manage hundreds or thousands of candidates simultaneously, and they are best for large-scale recruitment when the organization needs to analyze many applicants within a short time. If you are recruiting through a mass recruitment drive, AI proctoring can help you streamline the whole process.
3. Objective and consistent
AI systems are objective and work according to data. It works strictly as per defined rules, thereby having consistent monitoring of all the candidates. Being non-human, AI is devoid of personal bias or fatigue. So, large-scale assessments may benefit from it rather than humans.
4. Instant feedback
AI proctoring gives instant feedback on any suspicious activity, which is reviewed by HR teams immediately. This allows for quicker decision-making and identifies potential cheating or security breaches without waiting for a lengthy review process.
Disadvantages of AI proctoring
1. Privacy concerns
AI proctoring is also connected to facial recognition, eye-tracking, and even background scanning. This, therefore, has a negative implication on the candidates’ privacy. According to the national privacy commission study conducted in 2023, 58% of candidates feel uncomfortable with AI proctoring due to the invasiveness of the technology.
2. Technical issues
Such systems rely very much on the technological infrastructure that powers their execution but sometimes err in judging a candidate’s moves. As pointed out, an individual looking away to reflect before entering his responses onto the computer could raise some false positives among candidates who must feel unnecessarily threatened or unfairly measured.
3. Limited human interaction
AI proctoring is excellent in monitoring but lacks the human factor. Problems may not easily be solved during the test session, and questions will not be clarified immediately. This unavailability of real-time human intervention is frustrating especially for less IT-savvy candidates.
Key differences between human and AI proctoring
Let’s compare human proctoring and AI proctoring on some critical parameters.
Human proctoring vs. AI proctoring

When to choose human proctoring vs AI proctoring?
When to choose human proctoring
- For high-stakes assessments where human judgment is needed.
- When personal interaction and a supportive candidate experience are priorities.
- If you have a smaller pool of candidates and can manage the additional cost and logistical challenges.
When to choose AI proctoring
- For large-scale hiring events or mass recruitment drives.
- When you need a cost-effective, scalable solution for monitoring assessments.
- If the assessment is more standardized, with less need for human intervention.
How can Testlify help overcome cheating in AI-driven assessments?
The main challenge for organizations using automated tools to evaluate the skills of candidates with accuracy and fairness is cheating in AI-driven assessments. With companies increasingly relying on platforms such as Testlify for pre-hire assessments, it is imperative that the integrity of the process is maintained. Advanced features designed to prevent cheating ensure that assessments are conducted in a secure, unbiased environment.
Here are some of the ways Testlify helps curb cheating and ensure a trustworthy assessment process:

Real-time proctoring and monitoring
Testlify uses a multi-layered proctoring method to ensure candidates stay focused and honest during the assessment. Real-time video monitoring, screen tracking, behavioral analysis, and AI-driven flagging systems work in tandem to catch suspicious behavior. With testlify, candidates receive a secure environment for evaluation, thereby minimizing cheating risks and making the results of the assessment authentic.
Testlify allows photo capture during different stages of the assessment process to verify candidate identity. It is one part of a much more comprehensive security system that prevents impersonation or receiving unauthorized help. Moreover, all proctoring features of testlify are in line with the EEOC guidelines, thus ensuring that all assessments are carried out without any bias.
Face detection and full-screen mode
Testlify’s face detection feature actively tracks candidates to make sure they appear on camera for the entire duration of the test. If a candidate tries to look away from the screen or leave their seat, the system flags this behavior as suspicious.
Along with this, Testlify’s full-screen mode prevents candidates from switching tabs, opening new windows, or searching for answers online. If any of these actions are detected, the AI immediately flags the session for further review by the HR team.
Session and screen recording
Testlify’s session and screen recording features Will provide a detailed visual record of the candidate’s actions during the assessment. By capturing everything that the candidate does, from screen activities to keyboard inputs, testlify ensures that no suspicious behavior goes unnoticed.
Hiring managers can then review these recordings to make fair and informed decisions. This creates an extra layer of transparency and accountability, making the entire process more reliable.
Advanced plagiarism detection
The use of advanced plagiarism detection algorithms ensures the candidate responses get cross-checked with vast databases of publicly available content. Databases comprise popular websites, such as stack overflow and GitHub, along with academic papers.
This makes Testlify use a database that’s internal to their system with past assessments for verifying originality work from the candidate. Thus, candidates would have to present something original instead of copying or reproducing an answer.
Moreover, testlify scans the response in real time, flags the contents if it finds any similarity to public sources. The detection at this real-time stage ensures the genuineness of the process and helps to judge the candidate on the merit of his or her knowledge and skills.
Adaptive and randomized tests
One of the most effective ways to reduce cheating is to make assessments dynamic and non-predictable. Testlify does this by using adaptive and randomized testing methods.
The system assigns unique, randomly generated questions to each candidate, thereby reducing the possibility of sharing answers or external help.
You can also change the difficulty level of the assessment based on the role and candidate, so that the test remains challenging and relevant.
Candidate behavior analysis
Testlify’s AI does not just analyze the candidate’s answers. It also observes their behavior in the test. There are several patterns analyzed to find potential cheating behavior, such as:
Timing and pacing: Testlify follows how much time is taken to answer each question by the candidates. If the candidate answers all questions in a few minutes, this could be an indication that the candidate is not interested or is cheating by getting assistance from someone.
Inconsistent patterns of response: The system picks up on the inconsistency in the responses, like a sudden shift in the skill level or the reasoning ability that May indicate use of external resources.
Keystroke patterns: The platform monitors mouse movements and keystrokes, picks up unusual patterns that may suggest someone else is using the same device or the candidate is cheating.
It analyses these behaviors in real time to help HR teams identify potential cheaters and maintain a fair testing environment.
Limited test attempts
Advanced test control features by testlify ensure that candidates cannot manipulate the results by taking the assessment multiple times. The platform makes use of IP tracking and browser lockdown features to prevent candidates from restarting the test solely to improve their scores.
By enforcing a strict single-attempt rule, Testlify ensures that each candidate’s performance reflects their true abilities, without the possibility of gaming the system.
To learn more about Testlify’s anti-cheating and proctoring features
Conclusion
Both human proctoring and AI proctoring are useful in the hiring process. Human proctoring provides real time supervision and individual attention; hence recommended for short, important assessments. By contrast, AI proctoring is affordable, able to handle a large volume of assessments, and is unbiased in its approach.
Your choice will depend on the size and complexity of hiring your process, the type of candidates you are assessing, and the overall experience you wish to give. In many cases, a hybrid approach—using AI for large-scale assessments and human proctors for high-stakes tests—might be the most effective solution.
By understanding the strengths and weaknesses of each approach, you can make a more informed decision that aligns with your organization’s hiring goals, ensuring you select the best candidates while maintaining the integrity of your skills assessments.

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