  The objective of this paper is to explore the opportunities for human
information behaviour research to inform and influence the field of machine
learning and the resulting machine information behaviour. Using the development
of foundation models in machine learning as an example, the paper illustrates
how human information behaviour research can bring to machine learning a more
nuanced view of information and informing, a better understanding of
information need and how that affects the communication among people and
systems, guidance on the nature of context and how to operationalize that in
models and systems, and insights into bias, misinformation, and
marginalization. Despite their clear differences, the fields of information
behaviour and machine learning share many common objectives, paradigms, and key
research questions. The example of foundation models illustrates that human
information behaviour research has much to offer in addressing some of the
challenges emerging in the nascent area of machine information behaviour.
