We had a chance to interview Steve O’Brien, who recently joined Job.com as its new president of staffing. The former vice president of Monster.com’s Talent Fusion, Steve brings over fifteen years of diversified recruitment industry experience in agency search, boutique retained projects, global Recruitment Solutions, and Agile Recruitment Services to his new role.
He specializes in Agile Recruiting Services, integrating Talent Acquisition with Talent Management through assessment sciences, and designing predictive analytics for Talent Acquisition processes. Steve holds a Bachelor’s degree in Philosophy from The Pennsylvania State University, is married to his wife Alisha, and has two beautiful children.
You can read the complete interview below:
1. AI is revolutionizing many industries right now, and recruitment is no exception. A large number of employers are turning to AI-powered platforms like HireVue to find better-qualified candidates at the right time from the available talent pool. Can you elaborate on some of the intriguing ways companies use AI to recruit employees today?
Companies (like Job.com) are using AI to make real-time job suggestions, leveraging OSINT data helping make job application suggestions closer to employees’ desired next step and at a time closer to when they’re open to hearing them. They’re using AI to identify adjacent skills between roles helping companies and markets utilize existing talent more effectively. E.g., Did you know that the core skills and capabilities of a bookkeeper have tremendous overlap with those of a paralegal, only a paralegal pays more and has better job growth prospects across the next 10 years? Win/win for the employee, the market, and employer.
They’re using data from video interviews to help identify personality attributes that lead to better team composition and job fit. They’re tying job search data to social networks making real-time customer networking suggestions for candidates that can accelerate application review and give candidate insights from current employees of the companies that candidates are applying to. They’re enabling job matches to replace job search, so candidates can focus their time on personal development, career discovery, and exploring company brands rather than combing through pages of postings.
The net of a lot of this is like many applications of AI – helping users work with existing processes but improve their ability to manage the unmanageable amounts of data in those processes … and while they’re at it adding in delightful experiences that make users feel “seen, known, and anticipated”.
2. Most AI tools evaluate candidates on grades based on predetermined traits. Often people undergo these evaluation processes without knowing what exactly AI is grading for. Some career centers have even gone so far as to establish their own hiring AI. What is your take on this?
This application tends to be concentrated in video. The user experience for this application can be polarizing. It still results in a fairly synthetic interaction between the employer and the candidate. Companies like HireVue are endeavoring to validate personality assessments based on observable behavior, but there is further research needed. For example, an “in real life” interview is a dialogue, and a video interview is an extemporaneous speech. This feels unnatural if you anticipate an interview experience and not a speaking engagement. Career centers are spot on to prepare graduates for the many factors that will enable them to perform their best in what is currently an unfamiliar communication vehicle. I expect that the use of 1-way video (asynchronous) will evolve towards is helping companies place desirable candidates better rather than screen out undesirable applicants and towards helping TA departments (recruiters) advocate for their candidates better. E.g., a video interviewing platform Wedge is exploring “storytelling” as a user experience to help recruiters produce short highlights for interviewers on the candidates hiring managers will be meeting.
3. Although innovation in HR and recruitment is booming, more and more new AI-driven solutions for various problems are emerging. What are the major challenges today in using AI systems for hiring?
Descriptive analytics and matching are becoming more mainstream while producing novel and unexpected suggestions or insights buried in the heaps of data and user interactions are becoming the focus of next-stage technology. For example, the single most likely job an Accountant will get next is an Accounting job. Unsurprising. But according to job.com’s 60 million career records, although the single most likely job will be an Accountant – 70% of the time, an accountant will do something completely unexpected and not in accounting.
AI can help candidates explore what those unforeseen paths in the 70% look like and help them pursue them on purpose rather than by accident. AI is also helping organizations look at match and alignment from a team rather than merely an individual lens. The performance of most organizations is less tightly tied to the presence of the right people in the right job and more tied to the right people in the right jobs on the right teams. As rates of job change continue to rise and the value of “basic cognitive” (as McKinsey refers to it) capabilities decrease, predicting team cohesion will be more important for organizational performance in the next ten years than it ever has been.
4. AI can analyze data and replicate repetitive tasks to help recruiters with their response times, communications, etc. Still, some people firmly believe that AI can never take their place since it cannot see the bigger picture! What is your take? Do you think we will ever have an AI-based autonomous system in hiring?
I don’t see AI replacing humans in recruiting. However, it will pick up and automate low complexity tasks allowing time to be reallocated to very human activities such as generating agreement, persuasion, and work requiring creativity. Besides, it will restore the impact of existing teams in areas where data overload has eroded influence.
In the past five years, the average number of applicants per job and applications submitted by candidates has risen while simultaneously companies bemoan not being able to find the right talent and job seekers the right job. Some of this is captured in talent shortages, sure. We all know the STEM and nursing talent markets are imbalanced. But that doesn’t entirely explain the headlines. We also have decision overload hurting process efficiency, and AI is helping address this problem and restore fidelity to existing processes.
5. What is the future of AI and machine learning in recruitment, perhaps in the next 5-10 years?
The future holds several opportunities in recruitment.
- Allowing companies to redeploy their workforce just in time-based on adjacent skill models and current workforce predictions.
- Companies knowing in advance a team will gel and enabling that to occur faster. Providing transformation roadmaps to executives highlighting talent strategies that differentiate based on specific enterprise data for acquisition, retraining, and redeployment.
- Allowing the candidates to tell their career stories in more engaging and agile ways (instead of rewriting ten different resumes).
- Helping candidates navigate the new career lattice that has replaced our fathers’ career ladder and develop themselves in a workplace where skill demand and job titles are evolving rapidly, and helping labor markets more efficiently leverage their talent populations keeping work impactful and workers doing rewarding activities as AI comes alongside them in the workplace.
Read the full article in RoboticsBiz.com
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