Cooperative Crisis Response among Emergency Responders & AI Systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Emergency responders are increasingly functioning as knowledge workers relying on complex information systems, social media, and digital communication for situational awareness, coordination, and appraisal of their distributed efforts in crisis contexts. How should AI systems and HCI approaches effectively support these workers, whether in Emergency Operations Centers or in the field? What are the implications for interpreting, trusting, and engaging with AI systems to facilitate and coordinate relief efforts in crisis? How do we design better tools, methods, and best practices that fuse cooperative distributed knowledge among fieldworkers and autonomous systems in disaster settings? We examine prior work to illustrate the key challenges, conditions, and unexplored opportunities emerging in these distributed workplaces, that increasingly rely on real-time communication, mobile applications, and social media analytics. Designing for current and future scenarios that incorporate machine learning to better augment crisis response, presents many challenges, risks, and opportunities that must be carefully explored.
Original languageEnglish
Title of host publication22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing
PublisherACM
Publication statusPublished - 9 Sep 2019
MoE publication typeA4 Article in a conference publication
EventACM Conference on Computer-Supported Cooperative Work and Social Computing - Austin, United States
Duration: 9 Nov 201913 Nov 2019
Conference number: 22
http://cscw.acm.org/2019/

Conference

ConferenceACM Conference on Computer-Supported Cooperative Work and Social Computing
Abbreviated titleCSCW
CountryUnited States
CityAustin
Period09/11/201913/11/2019
Internet address

Fingerprint Dive into the research topics of 'Cooperative Crisis Response among Emergency Responders & AI Systems'. Together they form a unique fingerprint.

Cite this