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Effect of Artificial Intelligence Education on Adults’ Understanding of Automated Decision-Making

Abstract

Artificial Intelligence Education refers to organized learning experiences that equip adults with knowledge and skills for understanding the nature, applications, capabilities, and limitations of artificial intelligence technologies. Automated decision-making refers to the use of computational systems or artificial intelligence technologies to process information and make or support decisions with limited or no direct human involvement at particular stages. Adults’ understanding of automated decision-making is important because AI-supported decisions are increasingly relevant to everyday services, workplaces, education, finance, and digital platforms. However, limited knowledge of how automated decisions are produced may make it difficult for adults to recognize when such systems are being used or appreciate the need for appropriate human oversight. This study therefore seeks to examine the effect of Artificial Intelligence Education on adults’ understanding of automated decision-making. Artificial Intelligence Education can expose adults to concepts such as automated systems, algorithms, data inputs, machine learning, decision rules, AI-generated recommendations, human oversight, and the limitations of automated outputs. Through discussions, demonstrations, case studies, and practical activities, adults can learn how information may be processed by automated systems to generate classifications, recommendations, predictions, or decisions. Such learning can also help participants understand that automated systems depend on their underlying data, design, and programmed or learned processes, and that their outputs may require appropriate human evaluation. Adults’ understanding of automated decision-making involves their ability to explain the concept, recognize situations in which automated systems may influence decisions, identify the role of data and algorithms, and understand the difference between automated outputs and human judgment. It also includes awareness that automated decisions can have important consequences and may require review, interpretation, or human oversight. Artificial Intelligence Education may strengthen this understanding by providing adults with opportunities to examine practical examples and develop clearer knowledge of how AI-supported decision processes operate. The study will adopt a suitable descriptive survey research design. The population will comprise adults participating in selected Adult Education and digital-literacy programmes, from which an appropriate sample will be selected using a suitable sampling procedure. Data will be collected through a structured questionnaire and an appropriate assessment designed to measure participants’ understanding of automated decision-making. The research instruments will be subjected to appropriate validation procedures, while their reliability will be established before administration. Data collected will be analysed using relevant descriptive and inferential statistical techniques to determine the effect of Artificial Intelligence Education on adults’ understanding of automated decision-making. The study is expected to establish that Artificial Intelligence Education has a positive effect on adults’ understanding of automated decision-making. Adults exposed to relevant AI learning are expected to demonstrate improved knowledge of automated systems, algorithms, data inputs, AI-generated recommendations, and the role of human oversight. The study is also expected to indicate that practical exposure to examples of automated decision-making can strengthen adults’ ability to recognize how AI technologies may influence decisions in different areas of everyday life. The findings are expected to have important implications for Adult Education practitioners, digital-literacy educators, technology educators, and programme planners. Adult Education programmes may benefit from incorporating automated decision-making into relevant AI and digital-literacy activities. Demonstrations, case studies, guided discussions, decision-analysis exercises, and practical examples of AI-supported systems could help adults develop a clearer understanding of how automated decisions are produced and interpreted. Such learning can also encourage adults to approach automated outputs with appropriate awareness and critical judgment. The study is expected to contribute to the understanding of how Adult Education can strengthen adults’ knowledge of emerging artificial intelligence applications and their implications for everyday decision-making. It is recommended that Adult Education programmes provide relevant learning opportunities on automated systems, algorithms, data use, AI outputs, human oversight, and critical evaluation of automated decisions. Such programmes should combine conceptual knowledge with practical examples that enable adults to understand automated decision-making in realistic contexts. The study concludes that effective Artificial Intelligence Education can improve adults’ understanding of automated decision-making and promote more informed engagement with AI-supported systems.

Keywords: Artificial Intelligence Education, Adult Education, Adult Learning, Artificial Intelligence, Automated Decision-Making, AI Literacy, Algorithms, Automated Systems, Data Processing, Machine Learning, AI Outputs, Human Oversight, Digital Literacy, Technology Awareness, Decision Processes