The tech world is still buzzing with terms like AI and automation, however, landing a job is getting tougher. Artificial intelligence (AI) is shaking things up, making it hard for technical recruiters to tell who’s really good at coding and who’s cheating. Recent trends have shown that some candidates have been using AI to pass technical interviews, tricking companies into thinking they’re better than they actually are. This article will break down a few of the problems recruiters face, how candidates pull off these tricks, and a couple of simple ways to fix it.

How AI Helps Candidates Trick the System

AI tools are giving candidates a hidden advantage. In online interviews, some use AI off-camera to write code or explain answers, according to reports. It’s happening so much that big tech companies are thinking about bringing back in-person interviews to curb it. Recruiters notice clues: perfect answers with no explanation, long pauses before a spot-on response, or trouble when a question changes a little. The cheating can be sneaky and hard to catch by hiring managers who also may be looking at dual screens while interviewing.

Tricks Candidates Use

Here’s how some candidates try to rig the system:

• Live AI Boost: They type the problem into an AI tool during the interview and use its answer.
• Ready-Made Replies: They get AI to solve common questions ahead of time and repeat them like it’s their own idea.
• Hidden Screens: In online interviews, they peek at AI on another device, pausing to grab the info.
• Smart-Sounding Explanations: AI can explain code, so they sound like they know more than they do.

These moves work because online setups let candidates hide what’s really going on by focusing their cameras further away to prevent noticeable eye and head movements that pull their attention away from the screen.

AI cheating creates havoc for technical recruiters:

1. Hidden Skills: If someone uses AI to produce great code, recruiters can’t tell if they are proficient in what they do or if they are merely sourcing their answers from ChatGPT. (This could become a real issue after they start a job, where they will be performing real tasks and solving harder issues versus just copying random code sets).
2. Trust Issues: Cheating makes companies doubt everyone, even honest people - which isn’t fair. Also, using AI tools could open the door to internal procedures and information that, most of the time, is protected under NDAs.
3. Critical Thinking: AI can handle set problems, but if hiring managers switch things up, cheaters stumble and at times spend days trying to create code. Spotting this early requires quick eyes and a strong set of skills and criteria.
4. Bring Back the Old Days: Old ways, like whiteboarding, might not be an efficient solution for big groups but it can certainly give hiring managers a true understanding of someone’s abilities. 
5. Is It Wrong?: Some say using AI is smart, not cheating, since most tech folks love AI anyway. Others call it unfair. Recruiters will need to figure out what’s acceptable vs. non-acceptable. 
6. Speed: Managers can sometimes sympathize with candidates when it comes to creating lines of standardized code that saves them time while working on more critical functionality within a web application. AI tasks that change UI code may be viewed as more acceptable.

Easy Fixes for Recruiters

Recruiters can try these approaches to minimize deviations:

1. Watch Them Code Online: Use tools to see candidates code live. Ask them to share their screen and keep their camera on. Pay attention to keystrokes and the sound of the keyboard.
2. In-Person Coding: Bring candidates to the office to write code on a whiteboard.
3. Review Their Projects: Review candidates’ portfolio work online, like on GitHub, to see what they’ve done over time. Or ask them to share a project they have built on their own.
4. Change the Questions: Ask fresh problems or tweak them mid-interview. Make candidates explain how they think to spot AI help.
5. Repeat a Question: Repeating a question later in the interview to see if they give the exact word for word answer.
6. Work Together: Pair them with someone to code as a team. It shows how they think and talk, not just what they write.
7. Spotting Tools: Use software to catch odd typing or copied answers.
8. More Than Code: Ask about teamwork or ideas. AI doesn't do a good job of faking human reasoning by asking questions such as “why is that the best approach? Or why did you choose that approach?”

Moving Forward: Keeping It Honest

Hiring needs to keep up with AI in a reasonable fashion. Some argue using AI should be okay since companies use it to streamline tasks. But most agree it’s about finding people with ethics and who can solve problems, not just copy answers. The focus should be on how someone thinks—AI can’t copy that.

With smart tools and classic know-how, tech recruiters can stay alert as they look to hire real talent. It’s a tricky spot, but it’s also a chance to make hiring better and fairer for all, while avoiding the misuse of AI that leads to a lack of authenticity and a decrease in the overall performance of each individual by relying on AI tools.