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H2020

HUMANE Report Summary

Project ID: 645043
Funded under: H2020-EU.2.1.1.

Periodic Reporting for period 1 - HUMANE (HUMANE: a typology, method and roadmap for HUman-MAchine NEtworks)

Reporting period: 2015-04-01 to 2016-03-31

Summary of the context and overall objectives of the project

PROJECT CONTEXT
In the emerging hyper-connected era, people and appliances are online all the time. In HUMANE we focus on how work, private life, civic engagement, creativity and innovation are increasingly conducted in networks comprising of humans and machines. We term such networks “human-machine networks”, where network reflects a higher abstraction level than the technical system or machine.

Ever more activities in work and private life are conducted within human-machine networks. For example, actions to address environmental problems are driven in networks involving government, interest organizations, citizens, smart devices and sensor networks. As another example, journalists interact with sources, the public, and other journalists in networks that also include services for automatic and semi-automatic distribution and validation of source content. Also, to improve innovation capabilities, companies involve their customers in networks for open innovation, typically through online open innovation portals.

In consequence, our society is increasingly influenced by networks. For the individual worker and citizen, the form, experience and outcome of life depend less on the characteristics of the individual, and more on the characteristics of online and offline networks. For European companies, public sector and organizations, productivity, innovativeness and civic participation depend on the characteristics of the networks of which workers and citizens are part. Hence, an advanced understanding of different types of networks and how to benefit from their characteristics, could strengthen European productivity, citizen participation and innovation.

The challenge is that human-machine networks cannot be developed and implemented in the same manner as networks of machine nodes alone. Creating successful solutions for human-machine networks requires awareness concerning the kind of network to be established (e.g. simple networking and information-sharing or complex collaboration), the social characteristics (e.g. non-existent, latent, weak or strong ties), and a conceptual framework to assess the fit of the ICT solutions that constitutes the machine nodes of the network with the intended overall human-machine network.

OVERAL OBJECTIVE
The overall objective of HUMANE is therefore to improve public and private services by uncovering 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.

To this end, HUMANE seeks to develop a HUMANE typology and method, tailored to a human-centred design process and applicable to ICT developers and designers; and a HUMANE roadmap tailored to the need to support future thinking, regulatory activities and policy-making. During the first 12 months of the project, the first version of the HUMANE typology and method has been developed. We start developing the HUMANE roadmap in the second year of the project.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

"LITERATURE REVIEW
To ensure a thorough baseline for the development of the first version of the HUMANE typology and method, a systematic review of literature and evidence related to and relevant for human-machine networks was completed in the first phase of the HUMANE project. The output of this work is the public deliverable "Deliverable of Systematic literature review", which will be made available on the project website http://humane2020.eu/. See also the HUMANE blog-post http://humane2020.eu/2015/11/19/literature-review-article/ for more information and access to a pre-print of the article "Understanding Human-Machine Networks: A Cross-Disciplinary Survey".

HUMANE TYPOLOGY AND METHOD V1
In this version of the typology, our aim was to identify the dimensions needed to characterize human-machine networks so as to enable network classification into types, thereby facilitating access to relevant design knowledge and experience, following a design pattern approach. The typology is based on the literature review, and is structured according to four analytical layers: actors, interactions, networks, and behaviours; each including two dimensions. Each dimension is detailed with reference to relevant literature, and with suggestions concerning relevant challenges and design knowledge.

The typology and framework allow for profiling human-machine networks with the intention to facilitate access to relevant design knowledge and experience (see the figure for an example human-machine network profile).

The output of this work is the public deliverable "Typology and method v1", which will be made available on the project website (http://humane2020.eu). See also this HUMANE blog-post (http://humane2020.eu/2016/02/24/new-paper-typology-of-human-machine-networks) for access to the pre-print article "Human-Machine Networks: Towards a Typology and Profiling Framework".

CASE STUDIES
Six case studies have been conducted and completed to explore different aspects of t human-machine networks and to validate the HUMANE typology and method v1. For information about the case studies, see the HUMANE website (http://humane2020.eu/case-studies). The case studies contribute to the overall objective of HUMANE (uncovering new configurations of human-machine networks) and were designed to validate the usefulness of the HUMANE profiling approach; the completeness and adequacy of the HUMANE dimensions; and provide input concerning social implications of HMNs. The results from the case studies are reported in a confidential deliverable. Publicly available papers based on the case studies are listed on the HUMANE website (http://humane2020.eu/publications)."

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

LITERATURE REVIEW
In the HUMANE literature review, we have provided a systematic review of the literature pertaining to human-machine networks. Extending the previous theoretical concepts of socio-technical systems, actor-network theory, and social machines, we concentrated on the interactions among humans and between humans and machines. We identified eight preliminary types of HMNs: public-resource computing, crowdsourcing, web search engines, crowdsensing, online markets, social media, multiplayer online games and virtual worlds, and mass collaboration. These types reflect prototypical HMN purposes. We systematically selected literature on each of these types and reviewed it with a focus on implications for designing human-machine networks. Moreover, we considered risks associated with human-machine networks and identified emerging design and development trends. The resulting deliverable has later been turned into a manuscript currently in review (http://arxiv.org/abs/1511.05324). In the short term, the literature review has served as basis for the work on the HUMANE typology and method. In the long term, we aim for the review to be included in the basis for future thinking on human-machine networks in general and design for future human-machine networks in particular.

HUMANE TYPOLOGY AND METHOD
On the basis of the literature review, we have developed a first version of the HUMANE typology and method. In this version of the typology, our aim was to identify the dimensions needed so as to enable classification of human-machine networks into types, thereby facilitating access to relevant design knowledge and experience, following a design pattern approach.

The typology is structured according to four analytical layers developed in the HUMANE literature review, each layer including two dimensions. The dimensions are detailed with reference to relevant literature, and with suggestions concerning relevant challenges and design knowledge.

On the basis of the suggested dimensions, an human-machine network profiling framework has been developed. This profiling network and the associated typology dimensions have been applied and validated in six case studies. Taken together the case studies: (1) Validate the usefulness of the first version of the profiling approach; (2) Validate the completeness and adequacy of the suggested human-machine network dimensions; and (3) Provide input concerning social implications.

In the next project iteration the profiling approach will be strengthened with tool and method support, including an interactive web-based tool, to strengthen the communication and uptake of the typology and method.

The work on the typology and method has so far been presented in two scientific conference papers, included in Springer proceedings, to be presented at HCI International, July, 2016; one describing the typology and approach (http://arxiv.org/abs/1602.07199) and one going into detail on the trust implications of increased machine agency in human-machine networks (http://arxiv.org/abs/1602.08237).

The typology and method, through its alignment with the human-centred design process, represents a useful addition to the toolbox of human-centred design practitioners to strengthen design for human-machine networks.

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