In our last discussion on the risks of depending too much on AI, we shed light on its potential downsides. This essay explores the underlying psychological reasons behind our tendency to over-rely on AI. So why do we trust AI so much?

1. Perceived Omniscience of AI
One of the primary reasons for the over-reliance on AI is its perceived omniscience. AI systems are often seen as more knowledgeable and professional than humans due to their ability to process and analyze vast amounts of data far beyond human capacity. This perception is rooted in Milgram’s psychological principle of “authority bias,” where individuals tend to be extremely influenced and comply with authority figures or entities. In the case of AI, its vast data handling capability is mistakenly perceived as an all-encompassing knowledge base, leading to an overestimation and reliance on its capabilities.

2. Stability and Consistency Foster Trust
The stability and consistency of AI-generated answers play a significant role in building trust. Unlike humans, who may provide varied responses based on their current state of mind, level of fatigue, or personal biases, AI offers stable and consistent outputs. This reliability is comforting from a psychological standpoint, as predictability is closely linked to trustworthiness. People are naturally inclined to trust sources that provide stable and consistent information, reinforcing the reliance on AI systems.

3. Perceived Objectivity of AI
AI’s lack of personal interests or biases further contributes to its over-reliance. In contrast to human decision-makers, who may be influenced by personal gains, emotions, or prejudices, AI operates on algorithms and data, ostensibly making it more objective. This perception of objectivity is appealing, as it aligns with the desire for fair and unbiased decision-making. However, it overlooks the fact that AI algorithms can inherit biases from their training data or the perspectives of their developers, challenging the assumption of absolute objectivity.

4. Clarity and Conciseness Enhance Perceived Professionalism
The manner in which AI presents information—typically clear, concise, and straight to the point—further reinforces its perceived reliability and professionalism. Humans are naturally inclined to associate confidence and competence with individuals who communicate clearly and succinctly. For instance, consider the difference between two individuals presenting a business proposal: one delivers a straightforward, well-articulated pitch, while the other struggles to find the right words, frequently pausing and using fillers like “uh” and “um.” The former is perceived as more confident and competent, a psychological effect that similarly applies to the clear and direct outputs provided by AI.
According to the Elaboration Likelihood Model” (ELM), people tend to perceive well-articulated information as more credible and trustworthy. The ELM describes two routes through which information is being processed. The central route focuses on the content of the message, and the peripheral route focuses on cues of professionalism. Articulated arguments, use of high or academic language, and perfect grammar are some cues of professionalism that lead individuals to perceive the message as more credible or the source as more knowledgeable, regardless of the actual accuracy of the information presented.

Conclusion
The over-reliance on AI in business can be attributed to a complex interplay of psychological factors, including the perceived omniscience of AI, the stability and consistency of its outputs, its perceived objectivity, and the clarity and conciseness of its communication. While AI offers undeniable advantages, recognizing the psychological underpinnings of our trust in technology is crucial for maintaining a balanced perspective, ensuring that human judgment and ethical considerations remain central to business decisions in the AI era.