artificial Intelligence is on the rise, also in human resources. But there are also disadvantages, cue Candidate-discrimination. have to Recruiter respect, think highly of.
- This is how artificial intelligence can improve working life
- Practical applications of AI software in human resources
- Artificial intelligence in recruiting and legal pitfalls
- Two examples of how AI discriminates against applicants in recruiting
- The problem of non-discriminatory algorithms: what can companies do?
- What can HR managers learn from other industries?
- The future of AI in human resources: thinking about the topic in terms of society as a whole
- Top books on the subject
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This is how artificial intelligence can improve working life
Artificial intelligence, or AI for short, has now achieved a level of awareness that goes far beyond the ITindustry goes beyond. At least since the success of ChatGPT, there are many People fascinated by the work that such systems do and which ones Tasks we can give to AI applications. Tasks that take a lot of time but require little cognitive effort are particularly suitable for this.
Artificial intelligence can also provide good services in HR work and the life of HR managers clear simplify. Thanks to elaborate algorithms, an AI can independently relatively fast Work out relationships from large data sets. An AI can also make probability predictions, which are a good help for strategic decisions. This can also be easily applied in human resources, for example in the form of a chatbot that is recurring Ask can answer and thus the Employees relieved.
Practical applications of AI software in human resources
AI has the potential to significantly improve HR productivity and efficiency, Costs to reduce, increase security and increase accuracy increase. With the help of AI HR-Managers automate everyday tasks and data-driven accuracy and speed decision making increase. With proper IT tools, HR managers can be better able to engage employees and manage their pool of applicants.
So it's no wonder that more and more companies are thinking about integrating such systems in whole or in part into their human resources departments. Finally, the right software can help HR managers identify, understand, and hire the right talent. In an increasingly competitive job market, better decisions can be made at lower cost. And the competitiveness of Company increases.
Artificial intelligence in recruiting and legal pitfalls
But despite all the euphoria: There are also a lot of legal hurdles and pitfalls to be aware of - so it is not always as easy as some entrepreneurs hope to integrate AI systems into company processes. Because even if the development of ChatGPT for sure trend-setting: Anyone who now believes that such an AI can help with the hiring process by managing applicant data at the push of a button automates invitations to the job interview and even formulated a letter of resignation, which is wrong. There are still numerous Problems with the automated Recruiting,
A very current topic, for example, is the discrimination of applicants, because artificial intelligence often adopts the discriminatory tendencies and prejudices of their creators and reinforces them, depending on the data sets with which they were trained. Companies that do not want to violate applicable law or even be sentenced to a fine should therefore obtain sufficient information about which data sets were used to train the AI software. This is made more difficult by the fact that many companies do not develop AI applications themselves from scratch, but implement ready-made systems about which they often have no further information. So you don't even know what data the application is based on, what that Risks increase a biased AI.
Two examples of how AI discriminates against applicants in recruiting
Two small case studies explain what this can lead to. The first is from Amazon: the company has been using a software system under development since 2014 that Online-Resumes searched and evaluated for potential employment. Based on CVs, an algorithm for machine Things to Learn trained to look for word patterns that indicate successful employees.
It was found that that System did not evaluate gender-neutrally during the entire development phase. The names of two all-female (college) schools and expressions beginning with “Women” have been devalued by the system. Curriculum vitae from the last 10 years, mostly from men, served as training data. This spiegelreflected the fact that men dominated the technology workforce and thus the data set was not truly neutral to begin with. And in Finland, a financial institution was fined because its AI system favored men and also discriminated against native Swedish speakers.
The problem of non-discriminatory algorithms: what can companies do?
In view of such examples, which have also become known internationally, it usually does not take long before the legislature takes action. Accordingly, in April 2021, for example, the European Commission has its Draft regulation establishing harmonized rules for artificial intelligence presented, in which it specified how companies should deal with AI systems.
In order for companies to be able to implement such regulations and laws, the programs would have to be tested during their development. For example, companies could use anti-discrimination officers to advise their employees or IT staff. These incentives could also raise awareness, so only data sets free from bias or inequality are used.
What can HR managers learn from other industries?
There is no doubt that artificial intelligence is on the rise in many industries. And with the introduction of new technologies into the working world, HR managers are certainly required to deal extensively with the current trends. However, it is important to look beyond the horizon of your own industry: HR managers can learn a lot from other industries and apply it to their own processes.
This has been the case in the financial industry for years successfully Algorithms used to evaluate chart curves and thus significantly optimize investment decisions. This report shows what this can look like Bit Index Ai experiences, which reflects user experiences with such AI software. Exactly such field reports are extremely valuable when it comes to implementing AI software in your own work processes.
The future of AI in human resources: thinking about the topic in terms of society as a whole
However, despite all the efficiency, one should not ignore the social dimension of this topic. With regard to possible discrimination, the German Anti-Discrimination Agency already published a study in 2020, in which she also deals with possible cases, also from the HR area. The study suggests a number of possible methods to prevent discrimination in algorithm-based differentiation and believes preventive efforts are the most sensible protection.
The Objective should be for employers as well as society as a whole, algorithms in Future designed to be non-discriminatory. Ultimately, it is always about defending social principles, such as striving for equality or defending the right to unrestricted individuality. Accordingly, anti-discrimination and privacy laws need to be strengthened to ensure these principles are upheld in the face of rapid advances in Big Data and AI.
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