lnu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
On the Social Implications of Collective Adaptive Systems
Fdn Bruno Kessler, Italy.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (ERES)ORCID iD: 0000-0002-2935-6583
Università di Bologna, Italy.
Università di Modena e Reggio Emilia, Italy.
Show others and affiliations
2020 (English)In: IEEE technology & society magazine, ISSN 0278-0097, E-ISSN 1937-416X, Vol. 39, no 3, p. 36-46Article in journal (Refereed) Published
Abstract [en]

Many Collect ive Adaptive Systems (CASs) exist in nature: think of ant colonies, where large collectives of ants operate autonomously but interact with other ants and the environment to provide resilient global behaviors that sustain their colony. Following scientific studies that were aimed at understanding and predicting the evolution of these systems, and fueled by technological advances, research has started to investigate CAS engineering: the methods, tools, and techniques for building CASs. This naturally leads to a vision where collectives of humans and computational elements, situated both in the digital and physical worlds, collaborate to give rise to "intelligent" collective behavior supporting novel kinds of applications and services. Humans can be involved in two ways: both as users and as components of the CAS, in the sense that human behaviors and limitations are often integral to the system description. This has significant social implications that need to be considered by CAS researchers: in this paper, we share a discussion that took place between some experts thinking about CAS engineering, focusing on the social implication of CASs and related open research challenges. We hope that this provides a useful context for future research projects, research grant proposals, and research directions.

Place, publisher, year, edition, pages
IEEE, 2020. Vol. 39, no 3, p. 36-46
Keywords [en]
Adaptive systems, Privacy, Artificial intelligence, Software, Distributed computing, Cyber-physical systems, Robustness
National Category
Human Computer Interaction
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-98382DOI: 10.1109/MTS.2020.3012324ISI: 000572614300001Scopus ID: 2-s2.0-85092181524OAI: oai:DiVA.org:lnu-98382DiVA, id: diva2:1474439
Available from: 2020-10-08 Created: 2020-10-08 Last updated: 2023-05-02Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

D'Angelo, Mirko

Search in DiVA

By author/editor
D'Angelo, Mirko
By organisation
Department of computer science and media technology (CM)
In the same journal
IEEE technology & society magazine
Human Computer Interaction

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 113 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf