Upskilling and Reskilling have never been more critical as technological and economic transformations in the digital age have greatly changed the demand for global labor. As a result, the need for reliable certification of new skills is also growing.
Given the rapid expansion of global certification and licensing testing, a wave of services used to help candidates spoof testing procedures naturally took place. These dual approaches not only pose a threat to the integrity of the skill market, but may also pose a risk to human security. Some licensing tests involve important practical skills, such as driving or operating heavy machinery.
In cases where companies started cheating with real human agents, they introduced measures to prevent this – for online exams, candidates began to be asked to keep cameras while they took the exam. But now, DeepFake technology (i.e., high-reality audio and video that are often indistinguishable from real life) poses a novel threat to test security. Ready to use online tools waving Genai to help candidates escape and let human agents test them.
By manipulating videos, these tools can trick companies into thinking When there is actually someone behind the screen, the candidate is taking the exam (i.e., the proxy test is performed). Popular services allow users to swap faces with other people’s faces via webcams. The accessibility of these tools undermines the integrity of certification testing, even when the camera is used.
Other forms of Genai and deep strikes pose a threat to testing security. Large Language Models (LLMS) are at the heart of the global technology competition, with tech giants such as Apple, Microsoft, Google and Amazon, as well as Chinese competitors such as DeepSeek, making big bets on them.
Many of these models make headlines for their ability to pass prestigious high-risk exams. Like Deepfakes, bad actors have wielded LLM to exploit weaknesses in traditional testing safety specifications.
Some companies have started offering browser extensions to launch AI assistants that are hard to detect, allowing them to access answers to high-risk tests. The less complex use of the technology still poses a threat, including no candidates for using AI applications found during the exam.
However, new testing safety procedures can provide ways to ensure the integrity of the exams for these methods.
How to reduce risk when reaping the benefits of generating AI
Despite Genai cheating on numerous and rapidly growing applications in testing, the testing security industry is still conducting parallel races.
The same technology for threat testing can also be used to protect the integrity of the exam and provide companies with increasing assurance that the candidates they hire are eligible for the job. As threats continue to change, solutions must be creative and take a multi-layered approach.
One innovative way to reduce the threat posed by Genai is the sales of dual cameras. This technology requires Using the candidate’s mobile device as the second camera, a second video feed is provided to detect cheating.
By gaining a more comprehensive understanding of the candidate’s testing environment, Proctor can better detect multiple monitors or external devices that may be hidden outside of a typical webcam view.
Since the software relies on face-to-face exchanges, it can also make it easier to mask the proxy tests when detecting the use of masquerade tests. Perceptions of the whole body can reveal the difference between dark colors and the person sitting on the exam.
Subtle tips such as lighting or mismatch in facial geometry are more pronounced when compared in two separate video feeds. This makes it easier to detect deep strikes that are usually flat two-dimensional representations of the face.
The added benefit of dual camera options is that it effectively connects candidates’ phone calls, meaning it cannot be used for cheating. By using AI, the dual-camera strategy can even be further enhanced, improving detection of real-time video feed cheats.
AI effectively provides a “second set of eyes” that can keep paying attention to live videos. If the AI detects abnormal feed activity of the candidate, an alert is sent to the human supervisor, and they can then verify that the test regulations are violated. This additional layer of oversight provides added security and allows thousands of candidates to be monitored through other security protections.
Is the person who is born blessing or curse?
With the advancement of high-skilling and reshaping revolutions, ensuring testing of novel cheating methods has never been more important. From covering up the deep smoke of the exam agent to using LLM to provide answers to test questions, the threat is real and accessible. But the same is true for the solution.
Fortunately, as Genai continues to move forward, testing security services are addressing challenges and have been at the forefront of the AI arms race against bad actors. By adopting innovative approaches to detect cheats using Genai, test security companies can effectively deal with these threats, from dual-camera mass production to AI-enhanced surveillance.
These methods reassure the business that the training program is reliable and that the certification and license are real. By doing so, they can promote professional growth for their employees and enable them to stand out in new positions.
Of course, the nature of artificial intelligence means that the threat to test security is dynamic and evolving. Therefore, as Genai improves and poses a new threat to test integrity, it is crucial that security companies continue to invest in leveraging their development and refine innovative, multi-layered security strategies.
Like any new technology, people will try to wield AI for bad and good purposes. However, by leveraging this technology, we can ensure that certification remains reliable and meaningful, and that trust in the workforce and its capabilities remains strong. The future of exam safety is not only about keeping up, but also maintaining a leading position.
