Artificial Intelligence and Cognitive Biases: Understanding Human Judgment in Climate Change Communication

The current research examines cognitive biases and climate communication based on artificial intelligence (AI), as well as their linkage to public climate change message comprehension or engagement. Such cognitive biases as optimism, anchoring, and confirmation bias may cause people to misperceive climate messages, tending to undermine risks and lack motivation to change their pro-environmental behaviors. These relationships were studied using a quantitative research design. The sample size of participants was 280 people who are actively seeking climate information over the Internet using digital sources, such as social networks, news websites, and AI-based software. Stratified random sampling strategy was employed so as to cover a wide range of demographic unevenness, in terms of age, sex, education level and career. Structured questionnaires would be used to obtain measurable data that would be analyzed by use of statistical techniques in order to determine association, predictive effects and group differences. The results show that AI technologies can enhance knowledge and inspire pro-environmental attitude, yet their performance can be affected by overcoming cognitive bias and scrupulousness in message delivery. Perception can be interfered with by demographic factors which mean that communication strategies have to be tailored depending on demographic factors. The paper highlights how psychology and AI design can collectively inform climate communication strategies to be evidence-based, persuasive, and inclusive, and offers recommendations to policymakers, educators, and communicators so they can increase awareness, drive informed decision-making, and promote pro-environmental behavior.