The increasing integration of Artificial Intelligence (AI) in various aspects of society, such as medicine, education, and science, has led to the emergence of new AI-related jobs and the need for existing jobs to undergo AI re-skilling. This shift in the job market has seen a rise in demand for skills in machine learning and AI, surpassing the demand for general computer skills. Many companies are restructuring their workforces around AI capabilities, leading to a significant impact on the job market.
Beyond its impact on the job market, AI has also influenced the way people process information. The production of deepfake audiovisual materials has become widespread, leading to a rise in fraud and cyberbullying incidents. The emergence of deepfakes has also introduced a new form of disinformation in political campaigns. Research shows that people struggle to distinguish deepfakes from reality, highlighting the need for AI literacy.
AI literacy, a relatively new concept, is crucial in today’s society. It involves the ability to understand, interact with, and critically evaluate AI systems and outputs. Various aspects of AI literacy have been identified, including technical understanding, societal impact, and ethical considerations. Initiatives to promote AI literacy are emerging globally, with efforts to incorporate AI literacy into education systems at different levels.
A comprehensive review of available AI literacy scales has been conducted, highlighting the need for quality assessment tools to measure AI literacy effectively. The review identified 22 studies validating 16 scales, each with its unique characteristics and target populations. While most scales demonstrated good structural validity and internal consistency, there were variations in content validity, reliability, and other key measurement properties.
Recommendations were made based on the quality assessment of the scales, with suggestions for future research and development in the field of AI literacy assessment. The review emphasized the importance of content validity, structural validity, and internal consistency in assessing AI literacy. Overall, the study provides valuable insights into the current landscape of AI literacy scales and offers guidance for researchers and educators working in this field. By improving the quality of AI literacy assessment tools, we can better understand and promote AI literacy development in society.
