09:30 - 17:00,
Tuesday 21 March, 2017
Increasingly, activities in work and social life are conducted within human-machine networks, where collaboration involves many different human and non-human actors: governments, organisations, and individuals on the human side and machines which include smart devices, sensors, communication devices, and computing infrastructure. Examples of humans and machines working together range from editors and bots collaborating to make Wikipedia better reflect the knowledge of the world, systems built to help emergency units and individuals in crowds respond better to crisis situations, or networked medical devices that facilitate patient care and monitoring including self-monitoring. As networked devices have become ubiquitous, the applications that connect people to these devices have also proliferated, and the resulting networks of humans and machines are a defining characteristic of our time.
The goals of these humane-machine networks can be aimed at policy making, commercial innovation, education, improved quality of life, information exchange, or resource organisation. As networks become more complex and include more connections between humans and machines, so the characteristics of those networks become important in determining the effectiveness and successful evolution of the collaborations which they support.
In the HUMANE project, we are developing a typology of human-machine networks focused on characteristics of relationships between networked humans and machines such as trust, motivation, reputation, responsibility, privacy and security.
The HUMANE workshop will engage participants in learning more about the state of the art of human-machine networks, discussing the social and technical challenges that face designers who are building these networks, and learning how to apply the HUMANE methodology which has been developed to assist in creating typologies of human-machine networks that can inform system design.
HUMANE is 2-year European Commission project funded under Horizon 2020 to research these topics and suggest roadmaps for future developments of human-machine networks.