Technical, Socio-Economic, and Ethical Aspects of AI
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Item AI Psychometrics: Evaluating the Psychological Reasoning of Large Language Models with Psychometric Validities(2025-01-07) Li, Yibai; Lin, Xiaolin; Sha, Zhenghui; Jin, Zhiye; Lee, EmilyThe immense number of parameters and deep neural networks make large language models (LLMs) rival the complexity of human brains, which also makes them opaque "black box" systems that are challenging to evaluate and interpret. AI Psychometrics is an emerging field that aims to tackle these challenges by applying psychometric methodologies to evaluate and interpret the psychological traits and processes of artificial intelligence (AI) systems. This paper investigates the application of AI Psychometrics to evaluate the psychological reasoning and overall psychometric validity of four prominent LLMs: GPT-3.5, GPT-4, LLaMA-2, and LLaMA-3. Using the Technology Acceptance Model (TAM), we examined convergent, discriminant, predictive, and external validity across these models. Our findings reveal that the responses from all these models generally met all validity criteria. Moreover, higher-performing models like GPT-4 and LLaMA-3 consistently demonstrated superior psychometric validity compared to their predecessors, GPT-3.5 and LLaMA-2. These results help to establish the validity of applying AI Psychometrics to evaluate and interpret large language models.Item Illuminating Ethical Dilemmas in AI-Driven Regulation of Healthcare Marketing on Social Media(2025-01-07) Abby Sen, Abraham; Joy, Jeen; Jennex, MurrayThis paper explores the issues, ethical considerations and challenges social media platforms must navigate when using AI (Artificial Intelligence) as a filter for online healthcare advertisements. We examine the emergence of healthcare misinformation on social media platforms, which pose significant public health risks. We discuss the severe consequences of healthcare misinformation, including undermined public trust in the healthcare system, strained healthcare resources, and compromised individual health. Drawing on theoretical and applied ethical frameworks, the paper discusses the nuances of each ethical framework and the moral responsibilities of social media companies in regulating misinformation.Item Rethinking AI and Big Data in Marketing Strategy: Emphasizing Ethics through a Sensemaking Perspective(2025-01-07) Wang, Emma Junhong; Berthon, Pierre; Su, YiranThe exponential growth of big data, driven by AI and machine learning technologies, underscores the need for an ethical and sustainable approach to data utilization. Using problematization methodology, we consider the assumptions underpinning Big Data and AI, and reconsider them from a sensemaking perspective. Big data represents an enactment rather than an objective reality, and organizations play an active role in its adoption and use. Strategizing is driven by plausibility rather than accuracy, and big data generates a retrospection of the past rather than a prediction of the future. A sensemaking perspective serves as reality check for managers, emphasizing the necessity of long-term sustainability and societal well-being. By cultivating experiments for learning communities and incubating innovation, organizations can effectively leverage big data in marketing, fostering transparent, collaborative, ethical, and sustainable data practices.Item Introduction to the Minitrack on Technical, Socio-Economic, and Ethical Aspects of AI(2025-01-07) Li, Yibai; Sha, Zhenghui; Deng, Xuefei