{"id":109754,"date":"2025-09-04T13:45:07","date_gmt":"2025-09-04T11:45:07","guid":{"rendered":"https:\/\/www.hiig.de\/?p=109754"},"modified":"2025-09-04T14:17:16","modified_gmt":"2025-09-04T12:17:16","slug":"emotionless-competition-at-work","status":"publish","type":"post","link":"https:\/\/www.hiig.de\/en\/emotionless-competition-at-work\/","title":{"rendered":"Emotionless competition at work: When trust in Artificial Intelligence falters"},"content":{"rendered":"\n

In many companies, people are already working side by side with artificial intelligence (AI). Systems such as ChatGPT, DALL\u00b7E or specialised analytical tools support decision-making, provide creative input or take on complex tasks \u2013 often faster and more accurately than their human colleagues. Yet this very superiority comes at a price. Our research shows that trust in AI falters when people feel inferior in direct comparison. The reason is simple. People compare themselves \u2013 with colleagues and with machines. And this comparison is emotional. Those who find themselves outperformed by AI begin to doubt not only their own abilities but also the technology itself. Paradoxical as it may sound, the machine\u2019s superiority can weaken trust in it. Rather than fostering collaboration with AI, the willingness to use it then declines. Companies introducing AI systems should be aware of this dynamic.<\/strong><\/p>\n\n\n\n

When AI systems take on tasks previously reserved for humans, they are expected to do above all one thing: make everyday work more efficient and ease the workload of employees. Expectations are high. Companies hope for more precise decisions, fewer mistakes and new ways to streamline processes. Even today, algorithms analyse data, screen applications or propose creative solutions.<\/p>\n\n\n\n

At first glance, this sounds like clear progress \u2013 a powerful new tool to complement and ease our work. Many people and organisations therefore place their trust in the performance of AI. The underlying principle seems straightforward: the better the machine, the greater the trust.<\/p>\n\n\n\n

This perspective has so far also dominated research. Studies show that people are willing to collaborate with AI when they perceive it as competent (Choung et al., 2023). However, most of the focus has been on absolute performance \u2013 in other words, on how good the technology is in itself. At first sight this seems plausible. Yet it overlooks an important aspect: people are not neutral observers. They assess their own performance in relation to others. And this applies even when the comparison is with a machine.<\/p>\n\n\n\n

When AI becomes too powerful<\/strong><\/h2>\n\n\n\n

Our study<\/a> therefore takes a fresh look at this logic and shifts the perspective. It does not simply ask how capable AI is. It also considers how it performs in comparison with humans \u2013 and what consequences this \u201csocial comparison\u201d entails.<\/p>\n\n\n\n

To explore this, we conducted an experiment. At its core was the question of how people experience direct comparison with AI. We were particularly interested in one issue: how willing are employees to collaborate with AI as a colleague, especially once they realise the algorithm delivers better results than they do?<\/p>\n\n\n\n

Relative comparison rather than absolute performance<\/strong><\/h2>\n\n\n\n

To better understand how people respond to particularly powerful AI systems, we conducted a vignette experiment with 797 participants. This is a well-established method in behavioural research, in which individuals read short, realistic scenarios and imagine themselves in the given situation.<\/p>\n\n\n\n

In our case, participants were asked to imagine they had just finished a poker tournament. They were then told whether they had performed equally well or worse than either a human or an AI opponent. Afterwards, they were asked how willing they would be to collaborate with this counterpart on a completely different and unrelated task.<\/p>\n\n\n\n

The study revealed two key effects:<\/p>\n\n\n\n

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  1. General enthusiasm for AI<\/strong>: Regardless of the comparison outcome, participants were overall more willing to imagine working with an AI than with a human. This general openness towards AI is an encouraging sign. In research, this phenomenon has been described as \u201calgorithm appreciation\u201d (Logg et al., 2019).<\/li>\n\n\n\n
  2. Superiority of AI can undermine trust<\/strong>: However, as soon as it became clear that the AI had outperformed them, trust in the system dropped sharply (Benbasat & Wang, 2005). This was true even when the context was merely a game of poker that had no connection to the subsequent task. What was particularly striking was that trust in the AI\u2019s goodwill and integrity decreased, but so too did perceptions of its competence \u2013 even though it had demonstrably performed better than human counterparts.
    <\/li>\n<\/ol>\n\n\n\n

    Social competition with algorithms?<\/strong><\/h2>\n\n\n\n

    The explanation lies in social psychology. People do not interpret superiority \u2013 even that of a machine \u2013 in a neutral way. They react emotionally. Those who feel inferior often experience negative emotions such as envy, self-doubt or a threat to their self-esteem (Smith, 2000). These emotional reactions spill over into their evaluation of AI as an interaction partner, even though it is of course not human. The system is no longer perceived as a neutral tool but as a social actor \u2013 akin to a human competitor.<\/p>\n\n\n\n

    Social comparisons are deeply ingrained in human behaviour. We constantly measure ourselves against others, often unconsciously. When we fare poorly in such comparisons, we frequently perceive it as a threat to our self-esteem. To cushion this negative feeling, many people resort to a typical defence mechanism: they withdraw, emotionally or even literally, from the superior counterpart (Tesser, 1988).<\/p>\n\n\n\n

    What is new, however, is that this mechanism is also triggered by AI systems. Even though we know that AI assistants have no \u201cfeelings\u201d or \u201cintentions\u201d, we treat them in social comparison much like human beings.<\/p>\n\n\n\n

    What companies can learn<\/strong><\/h2>\n\n\n\n

    If AI triggers not only technical but also psychological dynamics, companies need to adopt a sensitive approach to its introduction. Powerful systems offer enormous potential, but they can also have unintended side-effects \u2013 particularly when they are perceived less as tools and more as competitors.<\/p>\n\n\n\n

    To maintain trust in the technology and ensure successful collaboration between humans and machines, companies should take active steps. <\/p>\n\n\n\n

    Three approaches can help:<\/p>\n\n\n\n