We live in an emerging hyper-connected era where people and appliances are online and interact all the time. These interactions take place via ever increasingly sophisticated ICT systems forming networks of both human and machine participants. Machines are no longer passive participants in such networks, merely mediating communication between humans; they are increasingly taking an active role, enabled by technological advances allowing greater autonomy and ability to perform increasingly complex tasks.
The focus in HUMANE (a typology, method and roadmap for HUman-MAchine NEtworks) is on human-machine networks, which is defined as a collective structure where humans and machines interact to produce synergistic effects. A synergistic effect of a human-machine network is an effect produced by the network which is greater than the sum of the effort produced by its nodes. That is, the interactions between humans and machines have emerging properties, able to achieve outcomes that neither humans nor machines would be able to achieve independently.
The overall objective of HUMANE is to improve public and private services, by uncovering and describing how new configurations of human-machine networks change patterns of interaction, behaviour, trust and sociability, and how public and private services need to fit the specific networks involved.
HUMANE will develop a typology and method for human-machine networks, considering relationships between networked humans and machines such as trust, motivation, reputation, responsibility, privacy and trust. The HUMANE typology and method will help system designers, practicing human-centred design, design new and successful systems by allowing them to explore the behavioural impacts system configurations are likely to have on its users.
IT Innovation has an integral role in this project, providing key expertise on trust, trustworthiness and reliance, building on our experience in projects like OPTET, REVEAL and OPERANDO. This is an essential aspect of the typology development for modelling and understanding the interactions between human and machine actors. We are also applying our expertise on network analysis, social dynamics and psychology concerning human interactions in machine scenarios, drawing on projects such as ROBUST, SERSCIS, SESERV and TRIFoRM.
As a practical application of the HUMANE typology, IT Innovation will develop a generic model and simulation for human-machine networks, in collaboration with ATC, drawing on tools and experience from IRMOS, ROBUST and DAVID. This will be validated on use cases in the project, such as eVACUATE, which focuses on the safe large-scale evacuation of people with the help of a network comprising sensors, a decision support system, operational staff, emergency services and the evacuees themselves.
In the final part of the project, IT Innovation will contribute to the development of a roadmap for future human-machine networks for citizen participation, building on our expertise and engagement with government stakeholders in the SENSE4US project.
HUMANE is part of the open data pilot in the EC's H2020 programme. Therefore, publications are open access and data sets will be made available by the end of the projects.
The first version of the HUMANE typology and method.
Cyberbullying: No Place to Hide. HUMANE Blog, 2017.
GDPR: The Right to be Forgotten. HUMANE Blog, 2016.
Machine Agency and its Implications on Trust. HUMANE Blog, 2016.
Understanding Human-Machine Networks: A Cross-Disciplinary Survey. ACM Computing Surveys, 2017. [arXiv pre-print]
The Interplay between Human and Machine Agency. To appear in the 19th International Conference on Human-Computer Interaction, 2017.
Automation in Human-Machine Networks: How Increasing Machine Agency Affects Human Agency. Under review, International Conference on Man-Machine Interactions.
Machine Agency in Human-Machine Networks; Impacts and Trust Implications. In the 18th International Conference on Human-Computer Interaction, 2016.
Human-Machine Networks: Towards a Typology and Profiling Framework. In Proceedings of the 18th International Conference on Human-Computer Interaction, 2016.
The HUMANE project is funded by the EC H2020 framework programme.
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 645043.