65,450 research outputs found
Encouraging Privacy-Aware Smartphone App Installation: Finding out what the Technically-Adept Do
Smartphone apps can harvest very personal details
from the phone with ease. This is a particular privacy concern.
Unthinking installation of untrustworthy apps constitutes risky
behaviour. This could be due to poor awareness or a lack of knowhow:
knowledge of how to go about protecting privacy. It seems
that Smartphone owners proceed with installation, ignoring any
misgivings they might have, and thereby irretrievably sacrifice
their privacy
Shinren : Non-monotonic trust management for distributed systems
The open and dynamic nature of modern distributed systems and pervasive environments presents signiļ¬cant challenges to security management. One solution may be trust management which utilises the notion of trust in order to specify and interpret security policies and make decisions on security-related actions. Most trust management systems assume monotonicity where additional information can only result in the increasing of trust. The monotonic assumption oversimpliļ¬es the real world by not considering negative information, thus it cannot handle many real world scenarios. In this paper we present Shinren, a novel non-monotonic trust management system based on bilattice theory and the anyworld assumption. Shinren takes into account negative information and supports reasoning with incomplete information, uncertainty and inconsistency. Information from multiple sources such as credentials, recommendations, reputation and local knowledge can be used and combined in order to establish trust. Shinren also supports prioritisation which is important in decision making and resolving modality conļ¬icts that are caused by non-monotonicity
Users' trust in information resources in the Web environment: a status report
This study has three aims; to provide an overview of the ways in which trust is either assessed or asserted in relation to the use and provision of resources in the Web environment for research and learning; to assess what solutions might be worth further investigation and whether establishing ways to assert trust in academic information resources could assist the development of information literacy; to help increase understanding of how perceptions of trust influence the behaviour of information users
Complacency and Bias in Human Use of Automation: An Attentional Integration
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG gefƶrderten) Allianz- bzw. Nationallizenz frei zugƤnglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Objective: Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation.
Background: Automation-related complacency and automation bias have typically been considered separately and independently.
Methods: Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved.
Results: Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operatorās attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect.Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams.While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency.
Conclusion: Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics.
Application: The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems
Recommended from our members
Evaluating the resilience and security of boundaryless, evolving socio-technical Systems of Systems
An Exploratory Study of COVID-19 Misinformation on Twitter
During the COVID-19 pandemic, social media has become a home ground for
misinformation. To tackle this infodemic, scientific oversight, as well as a
better understanding by practitioners in crisis management, is needed. We have
conducted an exploratory study into the propagation, authors and content of
misinformation on Twitter around the topic of COVID-19 in order to gain early
insights. We have collected all tweets mentioned in the verdicts of
fact-checked claims related to COVID-19 by over 92 professional fact-checking
organisations between January and mid-July 2020 and share this corpus with the
community. This resulted in 1 500 tweets relating to 1 274 false and 276
partially false claims, respectively. Exploratory analysis of author accounts
revealed that the verified twitter handle(including Organisation/celebrity) are
also involved in either creating (new tweets) or spreading (retweet) the
misinformation. Additionally, we found that false claims propagate faster than
partially false claims. Compare to a background corpus of COVID-19 tweets,
tweets with misinformation are more often concerned with discrediting other
information on social media. Authors use less tentative language and appear to
be more driven by concerns of potential harm to others. Our results enable us
to suggest gaps in the current scientific coverage of the topic as well as
propose actions for authorities and social media users to counter
misinformation.Comment: 20 pages, nine figures, four tables. Submitted for peer review,
revision
- ā¦