Regulating Hypersuasion

The landscape of consumer business interactions is undergoing a profound transformation propelled by the emergence of generative artificial intelligence (GenAI). Ever since the launch of ChatGPT, the field of GenAI has witnessed a remarkable surge in popularity, with large language models (LLMs) leading the field. From a technical standpoint, various characteristics differentiate these AI models from conventional ones. GenAI systems, such as LLMs, are known for their extensive capabilities and independence in identifying patterns within vast datasets. These LLMs possess the unique ability to process a wide range of inputs from different domains, so that they can generate content seamlessly. Many LLMs are also multimodal, meaning they can handle and produce various types of data formats simultaneously. For instance, GPT can process text, image, and audio inputs concurrently to generate texts, images, and even videos. However, despite their impressive performance in diverse tasks, advanced LLMs raise concerns among scholars regarding the legality and accuracy of the texts they generate. This chapter explores the intricate relationship between and GenAI. Prominent tools like Bing Chat, ChatGPT, Google’s Gemini (formerly known as Bard), OpenAI’s DALLE, and Snapchat’s AI chatbot are widely recognized, and they dominate the generative AI landscape. However, numerous smaller, unbranded GenAI tools are embedded within major platforms, often going unrecognized by consumers as AI-driven technology. In particular, the focus of this chapter is the phenomenon of algorithmic consumers, whose interactions with digital tools, including GenAI, have become increasingly dynamic, engaging, and personalized. Indeed, the rise of algorithmic consumers marks a pivotal shift in consumer behaviour, which is now characterized by heightened levels of interactivity and customization