In this newsletter we’re going to discuss the ways Artificial Intelligence (AI) and Machine Learning (ML) are affecting the recruitment industry as well as how they affect client-side talent acquisition teams. Although AI and ML have brought lots of positive changes, it’s always a good idea to examine the possible downsides too. Examining both sides of the argument is the best way to prepare for the changes AI and ML could bring.
How Artificial Intelligence (AI) and Machine Learning (ML) are changing the recruitment industry
Both AI and ML are excellent for automating processes. There’s no denying that recruitment can feel a little time-consuming, especially when we’re in the earlier phases of sifting out unsuitable candidates. When AI and ML work to automate correctly, they give recruitment teams extra time to spend on the more important aspects of the hiring process.
Now, although all this automation is excellent in terms of efficiency, there are a few shortfalls. In order for AI and ML to automate successfully, they need to mimic the behaviours of those who would usually eliminate unsuitable candidates during the early phases of recruitment. AI and ML are technologies which have algorithms who’s sole purpose is to “learn” behavioural patterns, predict outcomes and relies heavily on the person imputing the data to ascertain what is good and reliable for its use. That person is likely to focus on what has worked well for the company in the past and if the company is trying to change their hiring process and aim to unearth niche talent pools of candidates with innovative, entrepreneurial ideas and new ways of thinking, then how would this work? As these platforms are based on historical search patterns and learned behaviour, once those behaviours are in place for the AI software to use, they’re hard to alter even when a company needs to change its approach to hiring.
AI and ML could potentially exclude highly-qualified candidates
Let’s say the behaviours inputted into autobots that exclude candidates and don’t look beyond basic flaws for human explanations. One example of this is excluding candidates with gaps in their CV’s. Unfortunately, this could result in the exclusion of highly-qualified, career rich and excellent candidates who’ve taken career breaks for secondments or parents returning to the workplace who have years of experience behind them.
The autobots filtering candidates are only as good as the person programming behaviour criteria
It’s always worth remembering that the autobots that filter candidates during a recruitment process are dependent on human programming. As such, if the person inputting behaviours isn’t overly familiar with the industry they’re representing, they could accidentally encourage inappropriate candidates through the recruitment process.
One of our best hires to date was a 24 year old with a long standing financial services client of ours in Sydney. His profile was a mix of Cisco Networking, .Net Development, Text Mining, Social Scraping and some Python within DevOps. I can almost guarantee that he would not have shown up through the use of AI and ML for a Data Analysis SME (Subject Matter Expert) within a trading environment and this is where the inquisitiveness of the human mind over a machine prompted our team to meet him and 3 years later he is still one of their best hires.
However, we can use AI and ML, we just need to use them wisely
At Kapital, we believe that there is a place in recruitment for AI and ML. However, we’re also of the mindset that we need to test software cautiously and provide the right level of human input to ensure it’s successful. This usually means finding software programs that are culturally appropriate and right for each unique recruitment process.
As an IT recruitment agency, we take a forward-thinking approach that uses software and human skills. Our consultants cover multiple technical disciplines for individual clients across industries creating “one touch points” for our clients and HR/Talent Teams, which means you can avoid the costly mistakes that come with poorly implemented AI recruitment processes.
Till next time from The Kapital Team – Recruitment Made Simple