Key facts
- HackerRank's AI interviewer, Chakra, is now generally available to customers.
- Chakra evaluates candidates on critical thinking, judgment, and "AI fluency."
- The AI interviewer observed 70% to 80% fewer suspicious-activity flags than traditional assessments.
- Chakra aims to streamline the hiring process by combining multiple interview rounds into one.
- HackerRank states Chakra scores candidates but does not make final hiring decisions.
- New York City requires bias audits for automated employment decision tools.
HackerRank has launched Chakra, an AI interviewer designed to evaluate job candidates by observing their problem-solving process and assessing critical thinking, judgment, and "AI fluency." The tool, now generally available after a six-month beta period, conducted over 500,000 interviews with companies like Snowflake, Snorkel, and Capgemini participating in testing.
Chakra aims to change the nature of job interviews by moving beyond evaluating just the final output to understanding how candidates arrive at solutions. HackerRank co-founder and CEO Vivek Ravisankar explained that with AI's ability to produce artifacts, the focus shifts to the thinking and judgment behind them. The AI interviewer presents candidates with real-world coding tasks and uses an integrated AI assistant, allowing Chakra to ask follow-up questions based on the candidate's actions.
Ravisankar stated that Chakra streamlines the hiring process, potentially replacing traditional multi-round interviews with a single AI-conducted session. Contrary to concerns about AI facilitating cheating, HackerRank reported that Chakra interviews showed 70% to 80% fewer suspicious-activity flags than traditional assessments, as candidates are less incentivized to use external AI tools secretly when AI is integrated into the interview.
While Chakra scores candidates, Ravisankar emphasized that human interviewers retain the final hiring decision. He argued that AI can apply employer-set criteria consistently, potentially reducing human bias, though he acknowledged that automated hiring tools can still inherit biases from their data and models. The use of such tools is drawing regulatory scrutiny, with New York City requiring bias audits for automated employment decision tools.