Abstract
Generative AI, particularly large language models, is expected to bring about substantial change at the level of users, organizations, and society. While users over the last decade or so have become familiar with conversational interactions with computers though use of chatbots, the availability of large language models – and the benefits of text and image generation through large language models or text-to-image services – have opened a wide range of new use cases. Individual users have already taken up generative AI, particularly for productivity purposes. Organizations regard generative AI as holding high potential benefit but also to entail important challenges, e.g., in terms of security and privacy, as well as new forms of competition. At the level of society, generative AI has been the focus of substantial public debate. While there is increasing agreement on the need for regulation and means to control the development of generative AI, this may be more efficient if it seeks to guide its development rather than curb it. Through human-oriented technology research, we can help guide the impact of generative AI to the benefit of users, organizations, and society. In this talk, I will discuss the knowledge base for such a human-oriented approach and point out important future research needs.
