Decoding AI: Terminology You Need to Know for Your Next Job Application

It’s a heck of a time to be alive, dear reader. The world as we know it is changing at a pace so rapid that anyone born before the turn of the last century could reasonably claim they’ve blinked, and oh, look at that, we’re already in the midst of Industry 4.0 (read: the Fourth Industrial Revolution). Characterised by the leaps and bounds in technological integration, it shouldn’t surprise anyone that Artificial Intelligence (AI) has taken centre stage in this next stage of our society’s economic evolution. AI has found its way into almost every job sector. Naturally, it’s riding shotgun in the tech and software industries, but it’s also starting to permeate healthcare, transport, finance, manufacturing, marketing, and even sports. In order to keep up with the times, you, dear reader, must unlock new vocabulary and reimagine language for the benefit of utilising AI to your advantage in your search for your ideal job.

Whether you feel that you are up-to-date with the rollercoaster ride that is AI development or you are a complete newbie to the lingo, there is something worth learning for everyone here. Because guess where else AI is being used prolifically… go on, dear reader, guess. That’s right: hiring and recruitment. Recent data shows that as many as 88% of companies worldwide use AI for initial screening. This is, of course, a natural progression for popular industries and companies, which receive applications to the tune of millions of candidates each year. We wouldn’t want to try to read that many cover letters either, so the automation and employment of AI tools to do some of the legwork seems reasonable.

The key to standing out in such an enormous crowd is understanding the function of the AI tool, what it is looking for, and being able to speak to it. Luckily, Whoops Word has taken the time to collate a little dictionary for you! (You’re so welcome, dear reader!)

1.        Big Data

Simply put, big data is a term used to refer to extremely large and complicated sets of data that humans can’t manage via traditional methods like spreadsheets. Thanks to big data services being able to collect and store all types and volumes of data, candidate information has become more accessible than ever for recruiters.

“How does this affect your job application?” I hear you asking, dear reader. Well, a quick meander through any search engine will reveal that the top companies to work for around the world – and we’re talking Google, Amazon, Canva, the “Big Four Banks,” and the like – have millions of applicants every year. And AI, unlike the average hiring manager, can handle that enormous volume of data.

And it doesn’t stop at the documents you voluntarily supply for the application. Big data can be collected from anywhere online. AI can collect and store information about you from previous employer performance metrics and even social media. If you think AI is above a cheeky Facebook stalk, you’re wrong, dear reader. Big Brother is watching, George Orwell had that much right.

2.        Data Mining

So, if companies collect and store these huge mountains of information, how do they find the valuable stuff amongst all the rubbish and noise? Well, dear reader, that’s what data mining is for. Data mining involves identifying and understanding relevant information through patterns and test modelling.

Data mining goes hand in hand with big data. It’s about comparing candidate information with the characteristics of previous successful employees. As well as reviewing your online employment history, the reels you liked on Instagram last month, and your resume and cover letter, AI can use data mining tools to build a picture of whether your personal ethos and work ethic align well with a company.

By combining these powers of resume parsing and desirable (and undesirable) candidate qualities, data mining identifies “red flags” and inconsistencies in your application to identify and reject high-risk candidates early in the process. Hooray for efficiency, right?

3.        Generative Artificial Intelligence (AI)

Prospective employers can use generative AI to match applicant information to job descriptions. Recruiters use experts from within their company (or a consultant) to instruct generative AI on what criteria their ideal candidates should fulfil for a specific role, and the AI fairies go “yes, boss!” and get to comparing that rubric with candidate application data. The closest matches get shortlisted, while those missing the most get the dreaded auto-rejection email (which is often also written by the generative AI – have you ever noticed how soulless those emails are? *Shivers with distaste*).

Companies use AI to scan, sort, and rank your applications, and then, for the interview-worthy candidate, they can use generative AI to create customised interview questions. This is particularly relevant for behavioural, situational, competency-based, and technical questions, which generative AI can tailor to your specific background based on your job history, key skills, and personality. It's creepy but flattering, we suppose.

4.        Large Language Model (LLM)

LLMs are an impressive development in the AI world. They power AI chatbots, which large enterprises are starting to use for first-round interviews and preliminary screening processes. These chatbots use language similar to how people talk to each other and learn communication styles from the humans they chat with.

LLMs are fast learners who can interpret the language used in your application, such as your use of professional language and industry terminology. They can synthesize this information to make assumptions about your “soft skills.” Your “soft skills” are attributes that are generally difficult to quantify. However, they are essential to effective communication, teamwork, and harmoniously solving problems. An LLM will make assumptions about your interpersonal skills based on natural language trends in your application documents and other interactions with you. The irony of an AI making assumptions about your people skills is not lost on us, dear reader…

5.        Natural Language Processing (NLP)

AI uses NLPs, similar to LLMs, to tear apart your application documents and analyse your language use to try to quantify personality, tone, and professionalism. An NLP will use these data points for comparative analysis and play a game of matchy-match with the language in your application and the keywords in the job description and rubric that a recruiter has supplied it with.

AI can also use an NLP to assess an applicant’s language proficiency. Much like your high school English teacher, NLP assesses your writing for grammar, vocabulary sophistication, and ability to satisfy a recruiter’s criteria through written communication.

Many of these AI tools are intertwined and work together to provide companies with maximal optimization. If all of that has put you on edge, dear reader, we don’t blame you. Luckily, here at Whoops Word, we have a detailed understanding of how the recruitment process works and how to optimize your resume and cover letter for both the bots and the humans involved in the recruitment world. You can contact us for more information.