Dinah RibarskyWritten by

Choosing Your Bot and Keeping Your Wits in the Process

Artificial Intelligence, Attraction & Engagement| Views: 1268

Sourcing tools powered by Machine Learning. Artificially Intelligent Chat Bots that simulate the interaction of a recruiter. Assessment tools that note voice inflections. We all hear that AI has the capacity to change the recruitment industry as we know it, but which is the right solution for you? And is your team at risk for adopting too early or too late?

Better yet, what is this stuff anyway?

Before we jump in, a quick primer on two of the key building blocks in this space – Artificial Intelligence (AI) and Machine Learning (ML). Artificial Intelligence is a generalized term for any action that would typically be reserved for a human to carry out. We engage with AI all the time in our day-to-day lives, from the spam filter working tirelessly on your inbox, to the voice-powered assistant that looks up and dials your favorite take-out spot.

Machine Learning typically functions as a layer on top of this Artificial Intelligence, helping technology become smarter and more efficient over time by learning from past experiences. Machine Learning can vary wildly from the simple to the very complex – from the products on a consumer site served to you based on your interests, to an application carrying on increasingly deep conversations with every interaction.

From here, there are all sorts of additional paths to explore – Deep Learning, Natural Language Processing and more, often working in tandem with each other. This new and rapidly growing tech category clearly holds exciting promise for many industries, but what does it mean for the recruitment space, and where and when should your team enter?

The good news is that wherever there’s an area of optimization, there’s probably AI for that. This can also mean bad news to those of us left with a feeling of malaise at the concept of too many choices. AI and Machine Learning programs can create chatbots that guide prospects through your digital footprint, automated messaging apps that keep candidates abreast of their application process, sourcing tools that point recruiters to the best talent on the web, automated scheduling apps for screening calls and in-person interviews, assessment platforms that register everything from persona type to facial expression analysis – the list goes on and on and on.

Before getting derailed (or wildly terrified) by the latest shiny AI bauble, the very first step should be an analysis of your current process, soup to nuts. How are candidates finding your jobs and taking in your company culture? What is the application process like? How are assessments and background checks conducted? What does a day in the life of a recruiter or hiring manager look like?

After you’ve mapped the full lifecycle of a candidate and how your team is currently engaged along the way, you should already be able to identify major pitfalls, time-sucks or costly actions that are taking place. If you are able to capture current ROI’s, all the better to use as a benchmark and hold your future technology accountable.

Now that you’ve identified these areas of improvement, the next step is researching the technology. Before committing to a vendor, you should be able to have a working understanding of your AI function of choice, how other organizations might be using the product (especially important when vetting a company that’s new to the space), and the level of involvement needed to have the tool work to your specifications – often an initial level of programming or “teaching” is required to deliver the responses and feedback that will align with your team’s vision or voice. Having a good sense of the landscape, either through internal research or by leveraging a partner to assist in the vetting process, is always a good idea that can help protect you from potential buyer’s remorse.

After you successfully select and implement your new technology, give yourself a pat on the back for entering the modern digital age! Be sure to monitor, test and request feedback from anyone interacting with the application – ongoing tweaks and optimizations should be expected, especially in the first few weeks.

Now that we all know the robots are officially here, the natural evolution involves us humans getting acquainted and comfortable with working alongside them. The good news remains that you and I still have our jobs…at least for the time being.

 

Dinah Ribarsky

About Dinah Ribarsky

Dinah Ribarsky is a Digital Strategist at TMP. She holds a BFA in industrial design from Massachusetts College of Art and Design and has worked in creative and marketing environments within the Boston area for the past decade. When she’s not developing digital solutions for client challenges, Dinah enjoys making art and petting animals.

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