Description: The trust gap refers to the disparity between the trust users place in artificial intelligence (AI) systems and the actual reliability of these systems. This phenomenon is crucial in the realm of ethics and bias in AI, as it reflects the disconnect between user expectations and the reality of technological capabilities. As AI becomes integrated into various fields, from healthcare to business decision-making, user trust becomes a determining factor for its adoption and effective use. However, the trust gap can arise due to several factors, such as a lack of transparency in algorithms, the presence of biases in training data, and the inability of systems to explain their decisions. This situation can lead to an over-reliance on technology, where users trust systems that may not be as accurate or fair as expected. The trust gap not only affects public perception of AI but also poses significant ethical challenges, as it can perpetuate existing inequalities and biases if not adequately addressed. In summary, the trust gap is a critical concept that underscores the need for greater transparency, accountability, and ethics in the development and implementation of AI systems.
