1. What strategies can recruiters use to ensure AI-enhanced hiring tools do not introduce bias into the selection process ?
First, recruiters must ensure the training data used in their AI-powered hiring tools is diverse and representative, reducing the risk of reinforcing existing biases. Regular audits and bias detection tests should be conducted to identify and correct any discriminatory patterns in AI decision-making. Transparency is key – recruiters should understand how AI models make decisions and be able to explain their recommendations.
Additionally, human oversight should remain integral to the hiring process, with AI serving as a support tool rather than the final decision-maker. Implementing fairness constraints in AI algorithms can help balance candidate evaluations and avoid favoring specific demographics. Employers should also continuously update AI systems to reflect evolving workforce diversity and inclusion standards. Finally, gathering feedback from candidates and hiring managers can help identify unintended biases and improve AI-driven recruitment practices.
2. How can AI help HR teams focus on evaluating the most critical skills for a specific role ?
Soft skills are often more critical than hard skills when evaluating candidates because they determine how well someone collaborates, adapts, and leads in a dynamic work environment. Unlike technical abilities, which can be taught, qualities like emotional intelligence, communication, and problem-solving are harder to develop and directly impact productivity. Additionally, as we’re increasingly relying on AI to handle more tasks on the job, the human factor is where talent can really shine.
However, soft skills are more subjective than hard skills, making them more challenging to gauge. Hiring assessments, such as Cangrade’s, have evolved to include measuring soft skills as well as hard ones, and are designed to include vital soft skills information on candidates that help determine success in their potential new role. Soft skills tests can help organizations avoid making expensive hiring mistakes by getting the right people in the door the first time.
3. How can HR teams leverage technology to combat AI “cheating” in video interviews ?
AI has changed talent acquisition and development as we know it, and organizations that fail to adapt their processes will be left behind. We should use AI tools to improve and personalize pre-hire assessments and prioritize getting the right people in the door to participate in video interviews in the first place. And for jobseekers, use AI to go beyond keyword optimization of your resumes and cover letters and do some soul-searching to understand your competencies and strengths are where those are best applied.
Preventing “cheating” in video interviews shouldn’t be isolated to just the interviewing step, but adaptive questioning and scenario-based assessments do make it harder for candidates to rely on AI-generated answers. It also helps bring soft skills to light. Human oversight ensures that flagged issues are carefully reviewed to maintain fairness in the hiring process. But what’s really more important here for employers and jobseekers to know is that AI can make anyone look good on paper, but it’s not a good predictor of long-term success.
4. How can organizations handle the increasing volume of applicants without compromising on hiring quality ?
AI is a double-edged sword: HR professionals need AI tools to mitigate candidates using AI tools or at least to understand why and how they’re using them. It’s not that AI itself is problematic, but rather how it’s used. For example, if AI is being used in a rudimentary way to screen candidates by searching for keywords, that does not help determine if a candidate will thrive in the interview or long-term on the job. On the flip side, a candidate bolstering their resume or cover letter to fit the specifics of a certain role is also not a good predictor of success.
Strategies like focusing on soft skills and using video interviews can help ensure applicants aren’t inflating their skills because it’s harder for AI to “cheat” the system. AI tools like Cangrade’s can help streamline these higher-value, but more resource- and time-intensive evaluation criteria, even with an increasing volume of applicants.
5. What new innovations could further enhance the efficiency of AI-powered video interviewing tools ?
For already overburdened HR teams, Cangrade offers AI-powered structured interview guides integrated directly into video interviewing. This helps conduct equitable interviews with auto-generated, personalized interview guides and then narrow the talent pool quickly and efficiently based on a specific role. On the candidate side, one capability that we’ve been working on, and will announce in a few weeks (or maybe by the time this interview is published), is our interview practice tool.
We designed this to help jobseekers refine their interview skills through AI-generated personalized, on-demand mock interview sessions. This new capability simulates real interview scenarios by analyzing a user’s job description and resume to generate tailored behavioral and soft skill questions dynamically. It helps interviewers get rid of the jitters and bring their best selves into the interview.
6. How can organizations balance automation with human oversight to maintain fairness and accuracy in hiring ?
AI is an extremely useful tool, but it is not and likely never will be a replacement for human workers. The balance can be achieved by prioritizing the use of co-pilot style AI tools—the type that make employees more productive but don’t attempt to take over completely. Resist the temptation to replace even junior employees with tools. Without a pipeline of junior employees, you will never have truly competent senior employees. As for accuracy and fairness, AI governance and human oversight are critical components to deploying safe and effective AI solutions.
