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A computer doesn’t know all the ins and outs of your company and culture
AI bias exists. AI alone cannot improve diversity hiring
In the world of talent acquisition, automation should be a recruiter’s best friend. It sources more candidates faster than is humanly possible, creates personalized outreach messages, and analyzes and reviews performance and output. All of which frees you up to work on more meaningful tasks, like your recruitment strategy, candidate engagement, and internal communication.
Of course, a robot can’t do everything a human can. Where can AI alone fall short for a recruiter? First, while AI can quickly source a slew of relevant candidates via basic filters, many candidates will inevitably come through that aren’t the right fit for the position you’re trying to fill. A computer doesn’t know all the ins and outs of your company and culture, so basic filters allow a starting off point, but still lead to a lot of sifting and sorting internally, costing you time and lowering your bandwidth.
Another common issue with standalone AI sourcing is incorrect contact information. Information like email addresses are often being pulled from a database that might not be updated in real time. And incorrect contact information could lead to major issues. A high number of email bounce backs can have a significant impact on your IP and sender reputation, which in turn affects your deliverability (ability to get your emails into the recipient’s inboxes). A low sender score could divert your emails to candidates’ spam folders, or even cause your email account to become suspended. Bottom line, too many bounce backs is bad for business, and something you want to avoid in your recruiting process.
Finally, many believe that a major benefit of AI over humans is that robots can’t discriminate. But this is not totally accurate. AI bias exists, and is defined as the underlying prejudice in the data that’s been used to create AI algorithms. Remember, AI is created by humans, and humans are inherently biased, thus leading to biased AI. A prime example is what happened at Amazon in 2015. Their model was trained to vet applicants based on patterns observed in resumes submitted to the company over the previous ten years. As most of those applicants had been male, Amazon unknowingly and accidentally created an AI recruiting tool that discriminated against women. AI alone cannot improve diversity hiring.
But we know that you don’t have the time to weed through hundreds of noisy profiles, deal with dozens of bounced-back emails, or ensure that diversity hiring is as unbiased as possible. That’s why having a “human in the loop” is so essential to the automated recruitment process. That’s why Fetcher is an important part of your tech stack -- or should be.
Fetcher’s aptly named, “human in the loop” feature mitigates the issues that come with using sourcing automation. Our highly-qualified internal team of recruiters trains and monitors data to deliver you qualified candidates that meet all your pre-set criteria. Other sourcing tools don’t use ‘humans in the loop,’ and instead leave you with a simple database scrape (i.e. a ton of semi-qualified candidates that haven’t been properly vetted). The nature of a database scrape means you’ll get more candidates quickly, but, is it really worth it if it means you need to spend hours verifying their information and weeding out unqualified prospects?
Quality over quantity is key. Only a real person can determine a good vs. a great candidate. Using Fetcher, you can select specific candidate criteria with a click of a button. This information will be filtered directly with our AI. But Fetcher goes one step further, by also providing a textbox for the criteria that doesn’t fit as neatly into structured data forms digestible by algorithms. This criteria is checked by our humans in the loop. They verify the candidates that make it to your inbox are meeting all of your standards, even those ‘non-filterable’ asks. It’s necessary to have checks and balances between machines and humans. Blending the two is ideal. That’s Fetcher.
Fetcher also ensures contact information (including candidates' personal email addresses) is correct with a 98% accuracy rate. While Fetcher’s AI pulls the initial relevant batch of candidates, our team members take it one step further to filter out any errors, so you don’t have to, saving you valuable time and curbing deliverability issues upfront. And with Fetcher’s full-service, recruiting automation platform, you’ll have deliverability stats right at your fingertips. Not only will you be able to send custom emails directly from our platform, but you’ll also be able to analyze, review, and optimize results in real time.
Our ‘human in the loop’ also helps ensure a strong diversity hiring strategy. Fetcher prides itself on delivering you a diverse selection of applicants via AI, and our team of humans is there as backup in case abnormalities in the AI’s results are detected. This allows errors or bias to be caught quickly and curbed effectively, thus avoiding issues similar to the one Amazon faced a few years back.
We know you’re busy, and while AI has increased productivity for recruiters in all industries, there are still setbacks if you don’t have that ‘human in the loop’ layered into your strategy. Don’t waste your time sourcing from a database scrape that should have already been curated for you, or looking for alternate emails after bounces. We’ve got you covered! Fetcher’s approach is practical, taking the best qualities of AI and human work and blending them together to deliver you a top-notch, qualified, diverse talent pool.
Our mission is to help you engage talent that will transform your business aspirations into reality. Great talent is hard to find - that's why we offer a talent sourcing platform that not only gets your brand in front of the right candidates but also gives you a competitive edge in talent acquisition.
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