AI significantly influences trust in robots, acting as both a catalyst for confidence and a potential source of apprehension. On one hand, advanced AI can foster trust by enabling robots to perform complex tasks reliably, adapt to new situations, and even demonstrate human-like interaction capabilities, making them seem more competent and predictable. Technologies like Explainable AI (XAI) are crucial, allowing users to understand a robot's decision-making process, thereby enhancing transparency and reducing the "black box" effect that often erodes trust. Conversely, the inherent complexity and opacity of some AI systems can undermine trust, especially when robots exhibit unexpected errors, biases, or behaviors that users cannot readily comprehend or anticipate. Concerns over data privacy and the potential for AI system vulnerabilities also contribute to public skepticism, highlighting the critical need for robust security measures. Ultimately, building trust requires a delicate balance: leveraging AI's power for enhanced performance while ensuring transparency, predictability, and user understanding in robotic interactions. More details: https://orbita-adler.ru/redirect?url=https://infoguide.com.ua/