A Proximate Mechanism for Communities of Agents to Commemorate Long Dead Ancestors

Many human cultures engage in the collective commemoration of dead members of their community. Ancestor veneration and other forms of commemoration may help to reduce social distance within groups, thereby encouraging reciprocity and providing a significant survival advantage. Here we present a simulation in which a prototypical form of ancestor commemoration arises spontaneously among computational agents programmed to have a small number of established human capabilities. Specifically, ancestor commemoration arises among agents that: a) form relationships with each other, b) communicate those relationships to each other, and c) undergo cycles of life and death. By demonstrating that ancestor commemoration could have arisen from the interactions of a small number of simpler behavioural patterns, this simulation may provide insight into the workings of human cultural systems, and ideas about how to study ancestor commemoration among humans.Agent Based Models, Ancestor Commemoration, Dominance Relationships, Communication, Cooperation, Memory

Designing Sustainable Food Systems

There is significant interest in designing technologies for the food system, from agricultural modeling tools to apps enabling humans to assess nutritional value of various food choices to drones for pest detection. However, a good food system must be a sustainable one. There is an urgent need for deliberation and thoughtfulness in designing for both technologies that support existing food systems and new modalities that work towards more sustainable food systems. This workshop will bring together HCI researchers, designers, and practitioners with an interest in exploring what constitutes a sustainable food system, as well as defining the role of HCI in this domain. Our key objectives for this workshop will be to identify what opportunities for design and collaboration exist and to lay the foundation for an active foodCHI community

The Time Local Convex Hull method as a tool for assessing responses of fauna to habitat restoration: A case study using the perentie (Varanus giganteus: Reptilia: Varanidae)

Understanding the behavioural responses of animals to habitat change is vital to their conservation in landscapes undergoing restoration. Studies of animal responses to habitat restoration typically assess species presence/absencehowever, such studies may be restricted in their ability to show whether restoration is facilitating the return of self-sustaining and functional fauna populations. We present a case study using VHF/GPS tracking of a young adult perentie (Varanus giganteus), to demonstrate the range of applications of the Time Local Convex Hull method of home-range construction in analysing the behavioural responses of fauna to habitat change and restoration. Presence/absence studies provide single point locations of an animal, and the Minimum Convex Polygon method provides an invariant estimate of habitat use across the whole home range. However, the Time Local Convex Hull method provides a useful method for assessing movement and behavioural responses of fauna to habitat change and restoration, and the specific habitat requirements for the long-term support of populations. The breadth and multidimensionality of data generated indicates strongly that understanding the complex interactions between animals and their environment is fundamental to their conservation in the face of ever-increasing rates of human-induced habitat change and degradation

Late-Binding Scholarship in the Age of AI

Scholarly processes play a pivotal role in discovering, challenging, improving, advancing, synthesizing, codifying, and disseminating knowledge. Since the 17th Century, both the quality and quantity of knowledge that scholarship has produced has increased tremendously, granting academic research a pivotal role in ensuring material and social progress. Artificial Intelligence (AI) is poised to enable a new leap in the creation of scholarly content. New forms of engagement with AI systems, such as collaborations with large language models like GPT-3, offer affordances that will change the nature of both the scholarly process and the artifacts it produces