Artificial intelligence (AI) is increasingly being used and HR can also benefit from this. However, it is important to understand in which areas AI is useful and where human intelligence is more useful.
Have you already had contact with artificial intelligence (AI) today? Surely not? Because as a user, it is impossible to recognise whether or not AI is behind a user interface. On the one hand, AI remains in the background and hides behind chatbots, search engines, voice assistants and smartphones. For example, have you asked Siri anything today? AI. Did you take a selfie with your smartphone and it recognised that it was you? AI.
On the other hand, there is often a lack of knowledge about what AI actually is. People think of horror stories of humanised computers taking over the world. Quotes like the one from Stephen Hawking "... AI ... could be the worst event in the history of civilisation"¹ do nothing to reassure the general public. And if you enter the term AI into Google, terms such as "danger" and "job killer" appear among the suggestions, but not "possibilities" or "opportunities". We also owe much of the panic to Hollywood, coupled with a great deal of ignorance.
It's no wonder that 80 per cent of managers say that their employees need to learn more about AI to feel comfortable with it.² Once employees have developed an understanding of what AI is and what it can do, they get a feel for the areas in which they can benefit from AI and make the best use of it. There are many ways to use AI in HR in particular.
What does AI do?
There is still no generally accepted definition of AI, as there is no scientific definition of the term "intelligence". This does not make it any easier for us to understand what AI is. The aim of computer science with AI is to automate intelligent behaviour. In simple terms, this means that AI is fed with data and learns independently to recognise correlations and generate an output based on them. The more data, the better. Theoretically, a similar output could also be achieved with conventional programming. However, this would require knowing the logic behind this output. For example, if I can say exactly why a recruiter selects a particular candidate. But the logic behind such decision-making processes is so complex that it is not so easy to visualise. This is where AI comes in.
What are the limits of AI?
1) Explanation: Just as we humans cannot give an answer as to how or why we make certain decisions, AI cannot.
2) Empathy: When the AI system AlphaGo defeated Ke Jie, one of the world's best Go players, in 2017, he cried with disappointment. AlphaGo, on the other hand, felt neither happiness nor the need to give Ke Jie a comforting hug.
3) Creating something completely new: For example, if AI receives a lot of images as input, it translates them into series of numbers, creates statistical correlations and creates something new with similar numbers, patterns and distributions - a new composition of something that already exists
4) Recognising prejudices: AI adopts the biases of the data it is fed and cannot recognise them as such. It also cannot foresee the consequences of the decisions it makes. For example, Amazon tried to use AI for recruitment and realised that female applicants were discriminated against because the training data contained more male applicants.⁴
What fields of application are there for AI?
Despite its limitations, AI offers many possible applications. But what exactly can it be used for? In simple terms, there are three fields of AI application. These work individually or together.
1) Categorisation: AI helps when something needs to be classified but does not always have exactly the same logic behind it. For example, it helps to recognise and categorise expense receipts. Is the Starbucks coffee now catering, public transport or accommodation?
2) Similarity calculation: If you want to compare things, AI can help you make decisions. One example of this is CV matching with the job profile. Many companies already check and pre-sort their CVs in this way.
3) Knowledge transfer: If AI is given access to various data sources, it can provide answers to questions based on the content. In some companies, this is used in Talent Management, for example. For example, a candidate can ask a chatbot what they need in order to be promoted.
How can HR use AI?
Based on the fields of application, HR can use AI in four different ways, depending on whether the focus is on emotion and empathy or rather reason and logic, and whether it is about creativity and strategy or optimisation.
1 and 2: AI can take over routine tasks
HR can hand over all repetitive tasks to AI. Depending on how important empathy is, HR can take a back seat or a front seat.
1) AI takes over: If empathy is not necessary or emotions are even a hindrance, HR can hand over tasks to AI - for example in the areas of employee services, document management, HR administration and travel and expense management. AI-supported chatbots are already the first point of contact for employees with questions. In document management, AI takes over the initial allocation of documents and fills in certain content. And perhaps in future, AI will also be able to support HR in checking salaries in salary administration.
2) AI has your back: If empathy is also required for routine tasks, AI operates as a tool in the background. In Recruitment, AI can support recruiters with an initial assessment of the CV or provide assessments of the person's character based on video data. In onboarding, AI could also take over the entire onboarding planning and an AI-supported chatbot could accompany the employee during the process.
3 and 4: AI can support HR with complex issues
When tasks become more complex and more creativity is required, humans are clearly in demand. AI can and will provide support here in the future, but is not yet ready in many areas.
3) Hand in hand: AI is already providing support in some cases for complex topics where the mind takes centre stage. The potential applications are endless, especially in the field of analytics. For example, AI calculates the probability of an employee leaving the company or assists with personnel cost planning. AI can also be used in the area of compensation. A simple system is already taking over the process for highly standardised bonus regulations. In the future, AI may also support more complex processes.
4) AI provides selective support: As soon as empathy becomes more important and the topic is complex, AI is only used very selectively and in the background. The more important creativity and empathy are, the less AI is used. However, when it comes to topics such as development, learning and performance & goals, an AI-supported chatbot can guide employees through the process and act as a sparring partner. In the case of performance & goals or succession planning, AI can provide an initial suggestion for calibration or categorisation in the performance matrix or a successor.
Do you have to disclose AI?
If there are so many possible applications and users never know whether AI is involved, what are the legal considerations? In Europe, thanks to the General Data Protection Regulation (GDPR), there is some regulation on how AI should be handled. Experts are debating the strictness of the interpretation, but everyone agrees that Articles 13 and 14 require companies to inform users and provide information as soon as AI makes decisions that have a significant impact on the user. This topic is not yet regulated in Switzerland. From a legal perspective, it therefore makes sense to comply with EU law.
What should HR do now?
- Inform yourself: AI does not appear to be a short-lived trend, but is here to stay. HR doesn't have to be an AI expert, but it should know the possibilities and limitations of AI. This will enable you to judge what makes sense and where caution is advised.
- Start with the simple issues: Start using AI for repetitive questions that require understanding. This is where you will feel the greatest effect in the first step.
- Develop specifically yourself: AI is always hidden behind a different interface or system. Before you start developing yourself, check the market to see if a solution already exists that does exactly what you need.
Sources
¹ Stephen Hawking, Web Summit technology conference in Lisbon, Portugal, 2017
² IBM Research
prof Dr Paul Lukowicz: https://www.kulturmanagement.net/Themen/Kuenstliche-Intelligenz-und-Kreativitaet-KI-als-Kultur-Geschaeftsfuehrer-der-Zukunft,2348
⁴ Reuters, Amazon scraps secret AU recruiting tool that showed bias against women ( https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-thatshowed-bias-against-women-idUSKCN1MK08G )
⁵ Kai-Fu Lee: https://www.ted.com/talks/kai_fu_lee_how_ai_can_save_our_humanity
⁶ HR Campus following Kai-Fu Lee
Artificial intelligence in HR
Artificial intelligence in HR
Authors

Anja Buser
HR Strategies

Felix Anderegg
Technology Consulting