This is the third article in my “Digital HR Value” series. It covers the digital HR building block ‘Applification and Machine Intelligence’ from our digital HR model, with a focus on Artificial intelligence (AI). AI is changing our lives in many ways. From automation of repetitive time-consuming tasks, to the augmentation and amplification of human capabilities, AI has the potential to radically transform the way we live and work. For HR, this means not only an opportunity but also an urgency to adapt and adopt. Companies already taking advantage of AI in HR see gains in recruitment and selection efficiency, better (unbiased) decision making and improved employee experience. (Note: This FAQ list informed the article “Robo Recruiting” in Handelsblatt, that you can find here.)
In conclusion, applification and machine learning is part of the digital agenda of HR:
With this article, I am using an interview style: By ‘answering’ to FAQs around AI in HR I am trying to paint a picture of the ‘state of the union’ and what is likely to happen next.
What are the most common applications of artificial intelligence in HR? How are these employed today?
On this issue we need to distinguish between the different levels of artificial intelligence. The typical 3-step subdivision mentions (a) artificial narrow intelligence (ANI) – ANI is, for example, on par with an infant. The second stage is artificial general intelligence (AGI), an advanced level: It covers more than one field like power of reasoning, problem solving and abstract thinking, which is mostly on par with adults. Artificial super intelligence (ASI), the final stage of the intelligence explosion, in which AI surpasses human intelligence across all fields. We have not yet reached the last stage – cognitive self-learning is therefore not yet relevant, certainly not for HR divisions. However, the other two levels are already applied in HR.
a) Artificial Narrow Intelligence (ANI)
“Learning machines” on the first stage of artificial intelligence make decisions by tapping into large amounts of data and statistically validated algorithms. Classic examples are chatbots such as Siri, Alexa or Cortana – all so-called “personal assistants”. They can identify patterns in voice commands and react to them according to predefined algorithms. In HR these are employed when the initial contact with applicants is being made – often when it comes to answering standard questions about an advertised position. As chatbots they can support an ongoing interaction between recruiter and applicant during the recruiting process, in this case they quite simply increase the recruiters accessibility or the applicant.
Second field of application: „Natural Language Processing“ (NLP), this technology supports the scanning of letters of application to characterize the applicants` range and use vocabulary and his „wording“ in general. NLP can assist in writing job advertisements, by using a language which is exactly targeted towards the prefered group of applicants. Good examples are „X.ai“ for appointments or „Mya“ for answering questions about starting date, salary or recruiting process and „ClearFit“ for creating job advertisements and evaluating applications.
The applicant typically benefits by being able to interact simpler and faster with the company on a 24/7 basis. For the HR person, this use of AI means an efficiency gain.
b) Artificial General Intelligence (AGI)
On the second level of artificial intelligence networked machines can develop new models and algorithms ad hoc. In HR this technology can improve the preselection of applicants. With this second stage of artificial intelligence we can tackle an imminent and important problem of employee selection today: Unconscious prejudices. The world is full of it, as well as the world of employee selection: As a rule, people prefer “themselves and their peers” to people who are socialized differently. Personal experience with certain behaviors of others also determines a person`s judgement of others. All these subconscious prejudices can impair a good selection decision. Now, AI doesn`t know these prejudices – which might actually having exciting consequences. One example is „HireVue“ – this video interview service was originally used to increase employee selection efficiency: Candidates interviewed via video do not have to travel and do not have to synchronize their availability with the hiring manager’s busy schedules – a good, sensible tool many companies use. Now HireVue collects and stores thousands of candidate interviews for their clients on a daily basis. And by tapping into that vast amount of data, it can develop models for an automated pre-selection: What choice of words does the applicant use? Which facial expressions and gestures when answering standardized questions? And how do facial expressions and gestures fit the skills the company is looking for? In a 15-minute interview, HireVue generates and evaluates around 25,000 data points – significantly more than the 50-100 data points that a recruiter would collect and document in a classic interview. This way HireVue creates a data-driven profile of the applicant and a short list of suitable applicants without a hiring manager having to spend a second of work. And unconscious prejudices could be a thing oft he past.
SAP’s recruiting solution „SuccessFactors AI“ scans job ads for gender-specific terms that may deter the opposite sex from applying. This should help to minimize the diversity bias in recruiting and address a larger talent pool.
What has to be considered when introducing AI in an HR department?
– In times of scarce talent, it is not the most advanced AI recruitment process that solves the biggest selection problems. Our collaborations with large companies such as Bertelsmann, Bosch, BMW, Cisco, Deutsche Bahn and many others clearly demonstrate this. Any use of technology – including AI – should primarily aim at improve the candidate’s experience. Too many applicants are lost during the recruiting process. And for the best applicants we are not attractive to begin with. Any HR department should first identify all contact points (“touchpoints”) in the applicants-company-relation, then identify the most important ones. And then do everything to optimize the contact point experience.
– Critical points of contact that often stand for a poor candidate experience are: A tedious online application process, difficult availability, uninformed or unreliable recruiters and uninspiring candidate aptitude tests. If these contact points are identified and improved by employing succesful creative methods such as Design Thinking, truly interesting fields for artificial intelligence often emerge – with the clear aim to improve the candidate’s experience.
Example of a candidate journey map:
Some ways it can be done:
– One-click mechanisms for uploading Xing or LinkedIn profiles are absolutely sufficient for the actual application – these profiles are in turn automatically evaluated by first level AI.
– Chatbot-“Recruiters” are available 24 hours a day, 7 days a week – another first level AI field of activity.
– Classic, tedious application tests averaging of 100 closed questions, (“on a scale of 1 to 5, how much do you agree with the following statement”) can replaced by an unbiased, fast and modern designed video interview with open questions. This would require second level AI.
How do applicants have to prepare for the new technology?
First of all: Not at all. Remember: An applicant should fit a job. If a machine helps finding the right person – for example by avoiding unconscious prejudice – all the better.
But applicants can use artificial intelligence themselves. A simple example would be „Textio“: It provides phrasing assistance for letters of motivation – aligned to the job profile you are looking for. Recruiters can use it too: With Textio Johnson & Johnson achieved a
25% increase in the response rate of candidates approached in active sourcing.
An very widely discussed example was, almost two years ago, „EstherBot“. A female applicant, had built the chatbot – Esther – herself without any programming skills only by using free chatbot technology. „EstherBot“ could answer questions about Esther’s working life, work preferences and motivation. The applicant sent a link to her chatbot to companies she was interested in as an employer. Potential employers did not preselect Esther by telephone interview, but by talking to her chatbot.
Can computers also conduct job interviews?
Not yet, not as we know them. What is possible: Chatbots for hiring manager interaction and video interviews that can be evaluated for content, intonation, facial expressions and gestures. These technologies already offer astonishing experiences: 73% of the interviewed candidates who came into contact with the digital assistant „Mya“ thought (and stated!) they were in contact with a human recruiter – and not, as they were , with the bot).
A real job interview would require third level AI – machine awareness, which would enable an AI to continuously develop new models, new assessments and the next questions in the actual interview.
Google introduced its “Duplex” technology at the i/o conference in May 2018, it might be a forerunner of this third level of AI: „Duplex“ called at a hairdressers and a restaurant to make an appointment or reserve a table. In both cases, the person at the other end of the line did not seem to notice that she or him was talking to a computer program. Duplex sounds like a human being, he intoned, paused, and understood questions. And it spread a few “hmm” or “uh” over the conversation.
Is it possible to do the potential analysis of the existing workforce, with the help of AI?
Of course: AI-supported HR does not only work for employees who are new to the company. It can be designed to come up with predictions for any kind future behavior – and thus it would also function as a potential analysis tool.
How can machines judge possibly good leadership capacities?
Wherever unconscious prejudices affect a good decision, machines have a potential advantage. However, machine-supported decision making is only useful if it functions as valuable contact point and leaves the employee to be evaluated with a good experience,- This of course also goes for managers.
Where does this technology lead us? How will we use AI in human resources in 10 years?
10 years is a long time, it’s difficult to make an educated guess. Whether we will actually reach the third level of AI in 10 years – and machine consciousness – I don’t know. At the moment I see the AI-hype in HR dwindling a little. But we certainly will have access to more and more data on people’s behavior – this can make a lot of things possible.
Will artificial intelligence make recruiting cheaper?
Yes, very much so. As our „Candidate Journey Maps“ show – we developed them together with major international companies: We can almost completely automate the pre-selection process – and provide applicants with an even better experience than in a conventional selection process. We expect to increase efficiency by 22%. At Unilever, for example, the use of HireVue led to an increase in application completion rates from 50% to 96% for 250,000 applicants to 800 vacancies, while at the same time reducing recruitment time by 90%.
„Early adopter“ or „Wait&See“? Can you give Pro’s and Con’s on each of these stances?
A company using Level 1 AI belongs to the “Early Majority”. A company running HR on Level 2 AI can be dubbed an “Early Adopter”. Of course, the decision to integrate AI should be aligned with the recruitment requirements goals of the company. In times when talent is hard to find, the first experience I leave with applicants is crucial. According to our research, the most effective instruments for optimization will probably contain elements of artificial intelligence.
Does AI have “teething troubles” when applied to HR?
AI in HR is still in its infancy, that’s right. In the narrow field of aptitude diagnostics and potential analysis, the classic test procedures were developed by organisational psychologists in the 1970s. We have been validating these tests for 50 years and still many managers doubt the reliability of these tests. And now we replace these tests with artificial intelligence. And we will still face the problem of validation and distrust. Trust in algorithms will growing much slower than the underlying technology is going to develop. In other words: This fundamental change in HR will less be determined by the quality of ideas of computer scientists than by the acceptance of their technologies in organisations. That’s why we recommend to use AI where it serves an improved employee or applicant experience.If that works AI will undoubtedly be applied there.
Will corporations no longer need HR departments in 10 years – due to AI?
There can always occur unforeseeable innovative leaps – so-called “black swans”. But without black swans, I don’t think the HR departments will disappear. They will undergo major changes, they will become more customer orientated and data-driven. But they won’t disappear.
Which companies use artificial intelligence as a recruitment tool?
Many companies use first level AI. In cooperation with IBM, Siemens is developing a chatbot called “CARL” (Cognitive Advisor for interactive user Relationship & continuous Learning) this chatbot greets employees as well as applicants with the simple question, “How can I help you today?“ That way chatbots become a valuable “Employee Engagement” partner.
Unilever, in cooperation with Microsoft, is pursuing a very similar strategy. I think that more than half of the major Silicon Valley companies work with recruiter chatbots. And „HireVue“’s reference list is also long (e.g. GoldmanSachs, Vodafone or Nike). Many of these companies are now going to use artificial intelligence – as we suggest – in connection with candidate or employee experience. This will increase the acceptance rate of this technology.
Also, you can check out the Job Ad Working Student.
