Ilya Shmidt, Head Of Operations at Careerist, a learning platform where Edtech meets SaaS in job placement.
Artificial intelligence and machine-learning technologies have now become powerful enough to truly transform how we live, work and interact with the world around us. They’re changing everything, whether it be gaming, e-commerce, cybersecurity or space exploration—and tech recruiting is no exception.
At my company, a learning and job placement platform, we work with AI very closely in our recruiting process. I’ve seen firsthand how AI can be used to help streamline many of the administrative tasks involved in hiring, which allows recruiters to focus on more strategic activities. From my perspective, the future of tech recruiting is likely to be heavily influenced by the continued development and adoption of AI and machine learning technologies.
Using AI In Recruiting
Recruiters can use AI and machine-learning algorithms in many ways, including:
• Improving job descriptions: AI tools can help identify bias in job descriptions—such as gendered language, words that might discourage older applicants or phrases that imply a racial bias—and then suggest possible alternatives.
• Sourcing candidates: These tools can automate the searching of job boards and internal databases, recommend openings to past applicants, reach out to potential candidates and match interested professionals with the most suitable positions for them. In addition, chatbots can answer candidates’ questions about the role before they apply. This approach can allow for a more accurate matching of potential candidates with open jobs.
• Screening resumes: One of the most time-consuming tasks in the tech hiring process is screening and filtering candidates. AI screening tools can help speed up this process by extracting and analyzing critical information from each resume, narrowing down the candidate pool and allowing recruiters to focus only on applicants with high potential. AI solutions can also rank resumes based on objective qualifications such as experience, skills and education.
• Assessing skills: AI-based tools also allow hiring professionals to measure a candidate’s technical competencies and soft skills through solutions such as questionnaires or online, gamified assessments. Gathered data can then be analyzed by AI algorithms and transformed into insights about a candidate’s strengths and weaknesses.
• Running background checks: AI solutions can aggregate the professional backgrounds of tech candidates from multiple sources and provide recruiters with a comprehensive report on a candidate’s skill sets and experience.
• Conducting preliminary interviews: Interview builders allow recruiters to create a list of questions specific to each role and generate evaluation guidelines. Interview robots powered by conversational AI technology are then able to conduct initial interviews and shortlist applicants based on predefined criteria. Video interview platforms can also analyze the content of a candidate’s answers along with hidden information such as their choice of words or tone of voice in order to provide valuable insights to hiring managers.
Ethical Matters
While it can provide many helpful advantages, let’s not forget that AI is still only a tool. It can be used for good; however, it can be quite the opposite if businesses don’t commit to using it ethically.
For example, as employers, we know we can’t ask a candidate about their political preferences or sexual orientation. However, some screening tools can get such sensitive data indirectly and without consent from applicants. They can scrape their social media postings, perform a linguistic analysis of their writing samples, analyze nonverbal clues from video interviews and create a comprehensive report on each applicant in a matter of minutes. Your responsibility is to ensure these capabilities are not employed in such a way that would cross ethical lines. You must respect each individual’s privacy, collect only the data you absolutely need and strictly follow employment laws.
Another major concern is that bias can develop in AI solutions over time, even if they were initially completely bias-free. After all, computer models learn from humans and historical data. For example, if, in the past, a company hired mostly men for software development positions, there is a risk that AI recruitment tools will give a higher rating to male candidates compared to female candidates with the same qualifications. That’s why AI systems must be transparent. You need to be able to check how it came to a particular result and why Candidate A is a better fit than Candidate B. This way, you can identify potential problems early and fix them promptly.
Tips for Using AI in Recruiting
Companies can take proactive steps to ensure they use AI tools in the hiring process both effectively and ethically by following the steps below.
1. Define your goals.
Whether it’s improving candidate quality or eliminating biases, you need to understand your main objectives in order to choose the right tools and to know how to measure their effectiveness over time.
2. Commit to being transparent.
Decide what information about applicants you need to collect, and ensure it is job-relevant. Disclose to candidates that you are using AI technologies in recruitment, and gain consent for processing their data.
3. Plan regular audits.
You need to regularly check your tools for compliance with ethics and relevant laws. If you’re using a vendor’s solutions, ask about their auditing framework. If it’s an internally built tool, consider hiring an external auditor.
Final Thoughts
AI-based technologies can significantly streamline the process of hiring tech employees. These tools can speed up the sourcing of qualified candidates, simplify the screening process, make interviewing more efficient and more. They can’t fully replace human expertise, however, and it’s critical that companies learn how they can leverage this technology ethically in order to be successful.
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