Talking about AI/ChatGPT in HR and recruitment

I’m going to focus this onto ChatGPT and Artificial Intelligence and how it's going to impact on recruitment and HR with details relevant if you are reading this from the hiring side, or as a candidate. I'm sure this will interest members, as I recently heard on the High Performance Podcast... Every company is a recruitment company! 

What Impact will AI have on scientific staffing? The major impacts on staffing will be in speed with hopefully the same level of quality. For example AI powered algorithms will sift through large numbers of applications and I think initially it'll impact most on the Candidate Screening and Selection. 

Algorithms already do assist in sifting through a large volume of applications and resumes to identify the most qualified candidates and have done for over a decade. By analysing keywords, skills, qualifications, and experience, these algorithms quickly and efficiently shortlist candidates. The impact of which is in saving time and resources for recruiters. Some platforms we use like CV Library score candidates a % and Reed give us a 'Relevancy' ordering. AI will normalise this even further I feel and people will expect to be algorithmically ordered based on wider factors in the following 5 main areas. 

I'm going to keep this blog to the 5 positive points below which I feel are most pertinent. However one caveat - clearly people don't always 'enjoy' feeling automated. I personally will say 'agent' over and over again if I call my bank or cell/mobile service provider! 

Whether people actually want this is different to it physically existing, as any early adopters of Google Glass or HD DVD players will attest. Here we go: 

1. Skills Assessment: AI will be able to dig a bit deeper into skills assessment by using various methods such as online tests, simulations, or interactive platforms. These assessments can help evaluate candidates' technical knowledge, problem-solving abilities, and critical thinking skills, providing more objective and standardised measures of competency. Any Talent Acquisition Professional will tell you these can be the hardest elements of a recruitment campaign to put together (and run well) but are a thing of beauty when they work out. Using AI here feels very logical. 
2. Data-driven Candidate Matching: Who loves sifting through hundreds of CV's every single day? Ok I actually really do, nice coffee bit of Mike Oldfield on the headphones and I'm away. However, AI algorithms can analyze job requirements and candidate profiles to identify the best matches. By considering factors such as educational background, skills, experience, and cultural fit, AI can provide data-driven recommendations to recruiters, increasing the likelihood of finding candidates who are well-suited for specific scientific roles. However, this is based on the quality going in. Our advice is, as always, write a good CV, expect a good response! You can get the famous LiCa Scientific CV guide from us anytime by emailing admin@licasci.com 
3. Talent Discovery: We're quite excited by the idea that AI-powered platforms can proactively search for potential candidates by scanning professional networks, research databases, and academic publications. These platforms could help identify individuals with specialised skills or expertise for example people who have co authored research papers or given talks at conferences in skill fields that didn't make it onto the CV/Resume and would be in the 'blind spot' category so might be otherwise overlooked. I'm curious about how this could expand the pool of qualified candidates.
4. Bias Reduction: There are always unconscious biases inadvertently influencing the recruitment process. We can't pretend otherwise and this element of 'de humanising' is probably going to be the most beneficial. AI algorithms can help mitigate bias by focusing on objective criteria and reducing human subjectivity. However, it's important to ensure that the AI systems themselves are designed and trained to be unbiased and not perpetuate existing biases! 
5. Natural Language Processing (NLP) for Resume Parsing: Heard of this? Don't fret it's not a massive area however it might become one! NLP techniques can be employed to extract relevant information from resumes or CVs, enabling better categorisation and matching of candidates with specific skill sets. This streamlines the initial screening process and improve the accuracy of candidate evaluation. What does this mean for you? It means adding skills to the CV but also will begin to affect your day to day descriptions of how you describe your 'job'. I'm going to introduce another phrase into your life then I promise I'm done "Part Of Speech" this will be the ability to assign tags to parts of speech (nouns, verbs, adjectives) and then parse these into a database. This will be coming into phone screening at some point so perhaps in a few years, this impacts on the best use of words and phrases in a phone/video interview for example.

I have always felt our job in recruitment is a transfer of emotions. For example, I can look at a candidates situation and see how my clients role will be of huge benefit and convey this to them in an honest, logical and practical manner. Last week I noticed a candidate had listed wild swimming as a hobby, so suggested a thriving coastal SME to them which they loved the idea of (having initially asked me for Manchester based jobs). We love building this level of personal exitement and spotting these gaps in peoples thinking. 

Recruitment is a contact sport you can't build excitement in a chat room or on LinkedIn messenger. As another candiate put it to me, I wanted to hear him 'laugh or cry'. However, before the phone call / meeting even happens we need to be locating the person and I feel this will be where the most significant gains will be made. 

I hope this statement ages well, and, I'm quite looking forward to seeing how AI impacts on our ability to do that we do best which is finding people jobs and careers that they love. As Mike Oldfield says... Only Time Will Tell.