The proliferation of big data and the algorithms that utilize it have revolutionized the way in which individuals make decisions, interact, and live. This dissertation presents a structured analysis of behavioral ramifications of artificial intelligence (AI) and big data in contemporary society. It offers three distinct but interrelated explorations. The first chapter investigates consumer reactions to digital privacy risks under the General Data Protection Regulation (GDPR), an encompassing regulatory act in the European Union aimed at enhancing consumer privacy controls. This work highlights how consumer behavior varies substantially between high- and low-risk privacy settings. These findings challenge existing notions surrounding privacy control efficacy and suggest a more complex consumer risk assessment process. The second study shifts to an investigation of historical obstacles to consumer adherence to expert advice, specifically betrayal aversion, in financial contexts. Betrayal aversion, a well-studied phenomenon in economics literature, is defined as the strong dislike for the violation of trust norms implicit in a relationship between two parties. Through a complex simulation, it contrasts human and algorithmic financial advisors, revealing a significant decrease in betrayal aversion when human experts are replaced by algorithms. This shift indicates a transformative change in the dynamics of AI-mediated environments. The third chapter addresses nomophobia – the fear of being without one's mobile device – in the workplace, quantifying its stress-related effects and impacts on productivity. This investigation not only provides empirical evidence of nomophobia's real-world implications but also underscores the growing interdependence between technology and mental health. Overall, the dissertation integrates interdisciplinary theoretical frameworks and robust empirical methods to delineate the profound and often nuanced implications of the AI-data nexus on human behavior, underscoring the need for a deeper understanding of our relationship with evolving technological landscapes. / Doctor of Philosophy / The massive amounts of data collected online and the smart technologies that use this data often affect the way we make decisions, interact with others, and go about our daily lives. This dissertation explores that relationship, investigating how artificial intelligence (AI) and big data are changing behavior in today's society. In my first study, I examine how individuals respond to high and low risks of sharing their personal information online, specifically under the General Data Protection Regulation (GDPR), a new regulation meant to protect online privacy in the European Union. Surprisingly, the results show that changes enacted by GDPR, such as default choices that automatically select the more privacy-preserving choice, are more effective in settings in which the risk to one's privacy is low. This implies the process in which people decide when and with whom to share information online is more complex than previously thought. In my second study, I shift focus to examine how people follow advice from experts, especially in financial decision contexts. I look specifically at betrayal aversion, a common trend studied in economics, that highlights individuals' unwillingness to trust someone when they fear they might be betrayed. I examine if betrayal aversion changes when human experts are replaced by algorithms. Interestingly, individuals displayed no betrayal aversion when given a financial investment algorithm, showing that non-human experts may have certain benefits for consumers over their human counterparts. Finally, I study a modern phenomenon called 'nomophobia' – the fear of being without your mobile phone – and how it affects people at work. I find that this fear can significantly increase stress, especially as phone-battery level levels decrease. This leads to a reduction in productivity, highlighting how deeply technology is intertwined with our mental health. Overall, this work utilizes a mix of theories and detailed analyses to show the complex and often subtle ways AI and big data are influencing our actions and thoughts. It emphasizes the importance of understanding our relationship with technology as it continues to evolve rapidly.