If you are into the use of technology to support the hiring process, read the recent Wall Street Journal article about algorithmic hiring.
It offers a very real glimpse into the future of hiring. To those companies who are looking for ways to increase the efficiency and effectiveness of the hiring process, the value returned by the newest wave of advanced technology can be significant.
But it would be wrong to blindly accept that computers are poised to take over the hiring process from human hands.
As a traditionalist who also embraces change and loves technology, I straddle two sides of this issue. I believe in the value of algorithms and data to help optimize and automate decision-making. However, the role of humans in the hiring process cannot and should not be replaced.
The last book I read, The Physics of the Future by Michio Kaku, provided me with some really good perspective on this issue. This is a fantastic book in which the author, a physicist, uses factual scientific information to predict what we can expect in the near future.
The author discusses the future of the workforce and suggests that by midcentury (2030-2070) almost all lower-level jobs will be automated. He goes on to suggest that the types of jobs that will not be automated will be those that require “the one commodity that robots cannot deliver: common sense.”
The inability of machines to think creatively and to have intuition creates a limitation to their use and value. So, while the wealth of information available to us will be staggering, it will still take a human brain to digest it, evaluate it, and make decisions that cannot be programmed or made using algorithms.
I could not agree more with Kaku and when it comes to machines and hiring, we need to keep a sense of realism about what we can expect machines to do. More than anything we need to see them as a helpful tool to make experts better, not as a substitute for human intelligence.
Know this about hiring by algorithm:
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- Think Tank: Technology and What Keeps You Up at Night in Talent Acquisition (continued)
- Algorithms must be fed quality post-hire performance data to be useful. Without a stream of quality outcome data, the brainiest computer in the world will be blind to the real picture of what predicts job performance. Companies are notorious for failing to care enough to capture and use performance data. This has been a bane for us I/O psychologists for decades. The value of algorithms will be limited by the current mindset held by many corporations.
- Automated hiring has a power alley. High-volume hiring has been looking to automation for a decade or more now. High volume is the best place for automation in hiring because humans cant possibly evaluate all applicants, and have issues with consistency and objectivity. Automated hiring shines because it provides a way to quickly sort applicants and differentiate them well enough to remove the deadweight. As one deals with more complex jobs at lower volume levels, it will get harder to use algorithms and human judgment will become more important. Likely we won’t see deep penetration of algorithms beyond entry-level or mid-level jobs anytime soon.
- It will always be about informed decision-making. There is no substitute for expert judgment by humans with training, experience, and motivation. This is what we do best. The goal is to support humans with better quality information, not to try and remove us from the entire process.
- A process-based approach should be the goal. Any hiring strategy is about using the right tool for the job at the right time and collecting information that is timely, accurate, and useful. When using automated hiring, one must know where it best fits with the overall process and strategy.
- Boundaries on what constitutes usable data will soon need to be established. While the type of data that is traditionally found on application blanks is fair game, why stop there? Data such as social network use or anything that is scrapable and trackable can add to computer models and identify patterns that may predict valued outcomes. But at what cost? Privacy is the new battlefront on the web and the data used to determine suitability for hire going to be an issue. What if deep personal data patterns of data show discrimination (a very real possibility)? Will the contributing data be ruled illegal? Even if it can be shown to be job related? Our current government hiring regulations were created in 1978 (when Pong was high tech). Something will have to give in the near future.
- Our concept of validation will need to be expanded. Validation means verifying that a test (or any data used for prediction) accurately measures the job performance domain. Traditional validation is static, using a data-based snapshot in time. But these new algorithms are dynamic and ever-changing, requiring validation to be fluid. While the core concept of validation will never change, its execution will have to.
Change is not always easy, but it is always inevitable. With progress comes the need for change and the need to reshape our conceptions. We as a society are going to face many interesting battles that will test our boundaries in the near future. Hiring is but one of these battles. As with all of them the key will be to know how best to use technology while not losing sight of the value that the human mind brings to the table.