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The year 2020 was more disruptive than anyone could’ve predicted. For HR, it meant we had to turn on a dime and adopt processes and new ideas at an accelerated pace. What once was a multiple-year transition plan into digital HR now had to be executed in just a few months with limited resources.

Surprisingly to some, although not so much for those of us who have been observing the relentless adoption of agility as a core value in the industry, HR was a shining beacon of adaptability. Those who had embraced the cutting-edge of technology transformed entire companies, with their large workforces and complex projects, into fully operational remote enterprises.

There are many paradigm shifts working in tandem that enabled this transformation. Chief among them. The recognition of skills as the currency of talent.

And AI is playing a key role by allowing computers to do what used to be a uniquely human endeavor, understand the skills possessed by a candidate, as well as the skills required to perform a job, and pairing candidates and jobs together.

In the second part of our recent deep-dive webinar into AI, we explored how Avature AI works, the benefits and the downsides of different approaches to AI and what companies can expect to achieve by embracing AI matching.

AI Matching: The Art of Recognizing Similar Skills

Technology has a very interesting quirk: What is often trivial to humans takes years of research and development to replicate with a computer (e.g. language). And what is trivial for a computer is often straight out impossible for humans (e.g. large mathematical operations).

Humans are very good at spotting the similarity of things. In fact, much of AI is just trying to emulate our uncanny ability to recognize what makes two things similar and to create categories based on that.

A child will quickly learn what a chair is after looking at a few chairs, even if other chairs are different in an infinite number of ways, they will pick up on what makes a chair a chair and identify new ones in the future with little to no difficulty.

It’s only in the last few years, with the right combination of machine learning techniques and computational power, that we’ve finally begun to crack the puzzle. And this has enabled software companies to develop groundbreaking solutions across a myriad of industries.

For HR, perhaps the biggest impact will be on talent acquisition and talent management. Candidates and employees are unlike each other in a million ways, but now we can teach our algorithms to spot the commonalities in regard to their abilities to solve problems that arise in different jobs, i.e.their skills.

Finding the Right Person for the Job, and More

The same underlying technology that powers our semantic engine is capable of analyzing resumes and infer what skills candidates possess. Think of it like resume parsing turned to eleven.

At the same time, our ontology knows what skills are necessary to perform a specific job. Knowing these two things allows our systems to put two and two together. Of course, people exist in a spectrum, so our system calculates a matching score. This matching score represents how likely a person is to be a good fit.

Buy that’s not all. Because the Avature platform can assess the skill-similarity between jobs or people, it can help you in unexpected ways. For example, you can ask the system to rank candidates or employees based on how similar their skillset is to another person’s.

Banner of Avature's e-book on talent sourcing and a link to the landing page to download it.

Say, for instance, that George is a great employee that has performed admirably as an AI developer, you can ask Avature to find people with skills similar to George’s.

You can also find roles that are similar to each other (that require similar skills to do properly). For example, this can be very useful when constructing recruitment marketing campaigns, because it gives you a curated list of roles that are worth targeting.

Avoiding Biases and Black-box Pitfalls

Artificial and human intelligence are not competing against each other—they’re growing stronger together. The better your talent acquisition teams are, the more effective AI is; and the more effective AI is, the more it helps your teams be better. It’s a virtuous cycle.

The power of AI lies in cutting down the number of people your recruiters have to manually consider and evaluate, by generating a short-list of candidates that are likely to be a good fit, you ensure that your recruiters’ abilities to spot and identify the best people are not wasted screening or interviewing candidates that definitively lack the necessary skills.

Our ontology was built on a wealth of data, however, lessons learned by AI elsewhere have their limitations, at the end of the day no two companies are the same. Therefore, the true potential of AI lies in learning what works for your organization.

To achieve this, you need a system that is not just intelligent but also under your control. Most tech companies take a black-box approach to machine learning, meaning you can’t change or visualize how AI weights different things. This can result in bias becoming ingrained in your processes.

The potential benefits of machine learning are incredible. You just need to ensure there are systems in place that can stop the spread of systemic bias.

Avature AI uses a white-box approach, at all times your HR teams can see and change what are the variables our algorithms are considering. This makes it basically impossible for errors to remain undetected for years, as it happened at Amazon.

AI is Just One More Weapon in Your Arsenal

It’s always important to remember that new AI solutions, like skill inference and skill matching, are only some of the many pieces needed to solve the talent puzzle. To overcome their challenges and come up ahead in the talent game, companies need holistic strategies that go beyond what happens when a candidate applies.

Recruitment marketing, employer branding, talent pipelines, nurturing long-term relationships, among many other areas, will continue to grow in importance. Finding ways of combining all these different areas into a unified strategy that is effective at identifying, attracting and hiring the talent you need will ultimately be the key to success.

This is where Avature is in a privileged position, from day one our platform was designed to be modular and to enable agility. We keep expanding into new fields, mostly encouraged by our clients, who often see a challenge and know they could solve it using Avature. The same applies to AI, which grows and evolves with our clients’ needs.

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