Thinking Traps: How High-Performance Information Systems Correct Cognitive Biases in Decision-Making

Abstract

A system information technology in security, intended saddle detector and saddle correct cognitive biases, are based on intelligence artificial intelligence (AI) and algorithms advanced to analyze data from multiple sources, such as government databases, IoT, and network social. This system combats cognitive biases, such as confirmation bias, anchoring effect, and delusion of truth, through learning techniques, checking information from multiple sources, and simulation AI algorithms to analyze dates to identify faults and provide decision-making alternatives. Also, the system promotes objectivity by anonymizing sources and comparing dates through cross-checking. systems information modern, which include mechanism advanced detection and correcting cognitive biases, are essential for improving process decision-making in security nation and international integration some analysis mechanisms behavior and verification of sources help prevent the spread of misinformation and erroneous interpretations, ensuring protection efficiency against risk emerging, including attacks terrorist. Thus, the technologies of advanced data processing and correcting cognitive biases will play a crucial role in the evolution of security systems, becoming a component indispensable in an increasingly world interconnected and complex, where threats of terrorists remain a concern overall major. To combat biases, the system integrates natural language processing (NLP) techniques and analysis behavioral, reducing influences subjective on decisions. The use of some source verification mechanisms and some comparative analyses helps prevent the spread of misinformation and reduce interpretation errors.