Talented Tools
Airlines training AI-based recruitment automation with adjacency-based strategies help the workforce & society
(Image by Prod5)
When you search the term “professor style”, Google Images returns exclusively middle-aged white men. You get similar results for a “successful manager” search. By contrast, a search for “housekeeping” returns pictures of women.
This shows how algorithms have “learned” that professors and managers are mostly white men, while those who do housekeeping are women. And by delivering these results algorithms do amplify existing biases and beliefs.
Now that we are listening in to tone, speech patterns, and facial expressions, we are opening up pandora’s box cultural inputs and AI-generated selections.
For this very reason we should look carefully at AI-based tools used in recruitment, workforce planning and organization design.
Read on to learn more and/or join for free.
Airlines
62% of people are currently still considering a career change. While this is not that easy once you’re in the airline industry, 58% of people are taking courses that are outside their current role, according to Gartner.
What companies like Unilever are doing is to build workforce readiness by having people spend 20% of their time in another role. They are looking at skills growth life cycles to focus on growing skills that will become core skills in future roles. But it takes time to take skills to maturity.
So, quite literally, the future is right now.
Even more so that the average number of skills required for roles has grown from 17.1 to 21.8 between 2018-2022, shared Gartner in a webinar last month.
Nonetheless, looking outside, there are no hidden pockets of talent left for many digital skills, so even airlines are looking at skills adjacency strategies. That is, they look at skills people have that are fairly similar in nature and could be schooled to fit specific roles (like quantitative skills applied to planning or RM).
During and following the pandemic, many companies started automating the CV screening and video interviews using artificial intelligence-based tools. Airlines like Air Canada, Delta, United and European carriers use these technologies, too.
Certainly there are significant benefits to be had from this. Some say it speeds up the hiring process by 90%. This is mostly related to the speed of information processing.
That’s great when you get too many resumes or need to sift through thousands of candidates. You need help.
But, video interviews don’t necessarily put people at ease. And this has to be factored into the analysis of recorded video responses, even though the candidate gets to redo it as often as they want. (Although some have time limits to complete once you start.)
HireVue is a company that analyses the language and tone of a candidate’s voice and records their facial expressions as they are videoed answering identical questions. It is also common to use the tech and apply it to pre-recorded interviews on the recruiter’s platform.
It has been used around the world for several years. And in the USA, some 700 companies, including Vodafone, Hilton and Urban Outfitters have tried it out.
For airlines, it’s not that common (yet).
But it leaves many wondering about how this works across genders, ethnicities and cultures and whether it stands in stark contrast to DEI.
How training the AI works properly, for instance.
On that note, the AI is built on algorithms that assess applicants against its database of about 25,000 pieces of facial and linguistic information.
But what went in, you might say?
Well, these pieces are compiled from previous interviews of “successful hires” , that is the people that have shown to be good at their respective jobs.
You see the room for error and bias there. But it’s a start.
The 350 or so linguistic elements include criteria like a candidate’s sentence length and the speed they talk, but also the use of passive and active words. Then the thousands of facial features that provide inputs are the smiling, eyebrow raising, the amount the eyes widen or close together with spoken words, brow furrowing, and chin raising.
But there are important risks we should be wary of when outsourcing job interviews to AI.
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Imperfect society
The main issue with outsourced recruitment to AI is that the data on which the algorithms learn to evaluate and judge candidates is based on society.
And society is imperfect.
It is based on existing sets of beliefs that have a whole range of various kinds of biases, inequalities, discrimination, and prejudices. And at that, many subtle ones that are not obvious to us, but get carried forward in automation using this data.
So the core stumbling block the intelligence of AI hits is how much the solutions are -by design -overly conservative, leaving little room for innovation and social progress.
In addition, sociologists (like Pierre Bourdieu) and anthropologists (e.g. Margaret Mead) often find that inequalities are reproduced based on the way we perceive ourselves, our self-confidence, and the chances in life we foresee based on our upbringing.
Also, confidence is often related to people having a “sense of one’s place” which typically creates divisions between rich and less cultural capital. And that is then shown in body language when we speak.
Or even the way we use and focus our eyes. We may express more fear, higher levels of stress during an interview, or it may suppress our natural confidence. Either way, it will be ranked differently by the AI.
So, back to the AI and the data, this technology will initially reinforce what has always been done in society, especially if you look at past hire data. It also means that companies are most likely to hire the same types of people that they have always hired.
And the risk is that they are all from the same set of backgrounds.
Algorithms leave little room for subjective appreciation, for risk-taking or for acting upon a feeling that a person should be given a chance.
In addition, this technology may lead to the rejection of talented and innovative people who simply do not fit the profile of those who smile at the right moment or have the required tone of voice. And this may actually be bad for businesses in the long run as they risk missing out on talent that comes in unconventional forms.
More concerning is that this technology may also inadvertently exclude people from diverse backgrounds and give more chances to those who come from privileged ones.
As a rule, they possess greater economic and social capital, which allows them to obtain the skills that become symbolic capital in an interview setting.
What we see here is another manifestation of the more general issues with AI. Technology that is developed using data from our existing society, with its various inequalities and biases, is likely to reproduce them in the solutions and decisions that it proposes.
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Adding value
Ethical AI is already looking at what potential regulation may come in terms of how data is used to make predictive decisions. And at how bias creeps in or can be removed.
One way through which we can improve this is by adding room for subjective appreciation, and for risk-taking. This could allow the AI to act on a “feeling” that a person should be given a chance.
And how it can do that is by using an adjacent-skills and adjacent-attitudes strategy. But is also entails using a diverse workforce, if available, to train the data. Airlines like Emirates, Etihad, Qatar and some Middle-East based low cost airlines are uniquely positioned to take advantage of this.
In a nutshell, it means that those skills that are complimentary and attitudes that can almost be substituted for each other ‘get through the gate’. It means adding a layer of linguistic and facial analyses that removes bias.
This may help people to become more confident staring at their laptop’s camera when they do their next job interview.
Let the best skilled-match win, but let it not depend on distractions. That’s my main DEI message.
By the same token, it means that a search on Google can produce results with male housekeeping staff or female professors or other identity expressions from different ethnical backgrounds.
It appears that the world is moving toward this, and so should recruitment.
Wishing you all a wonderful day, and greetings from rainy Montréal.
Ricardo
Montreal, Tuesday, 2 May 2023
Feel free to contact me for questions, comments, or a chat:
ricardo(at)pomonaadvisors(dot)com
my general email has changed to: info(at)ricardopilon(dot)com