Value Sensitive Design and Information Systems

Author(s):  
Batya Friedman ◽  
Peter H. Kahn ◽  
Alan Borning
2015 ◽  
Vol 1 (1) ◽  
pp. 4 ◽  
Author(s):  
Batya Friedman ◽  
David G. Hendry ◽  
Alina Huldtgren ◽  
Catholijn Jonker ◽  
Jeroen Van den Hoven ◽  
...  

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>In the 2010’s it is widely recognized by computer and information scientists, social scientists, designers, and philosophers of technology that the design of information systems is not value neutral [5-8,11]. Rather, such systems are value laden in part because societal values are major factors in shaping systems, and at the same time the design of the technology reinforces, restructures or uproots societal value structures. Of the many theories and methods to design for this phenomenon one continues to gain traction for its systematic and overarching consideration of values in the design process: Value Sensitive Design (VSD) [5-7]. The aim of this multidisciplinary workshop is to bring together scholars and practitioners interested in ways values can be made to bear upon design and to help continue to build a community by sharing experiences, insights, and criticism. </span></p></div></div></div>


Author(s):  
Majid Dadgar ◽  
K. D. Joshi

This chapter advocates the use of a value-sensitive design (VSD) approach toward deriving patient intelligence by illustrating that the insights provided by the healthcare data that captures patients' concerns, needs, and desires—known as values—provide more sustainable care. Authors examine three cases extracted from top information systems (IS) peer-reviewed journals in which medical data is collected and analyzed and in which intelligence is derived through a VSD framework. VSD is a three-part methodology that comprises conceptual, empirical, and technical investigations. This chapter investigates the value sensitivity of the following key activities and tasks that result in intelligence from data: data collection, data analysis, and data reporting.


Author(s):  
Peter Batya Friedman ◽  
H. Kahn ◽  
Alan Borning

1984 ◽  
Vol 1 (1) ◽  
pp. 175-185
Author(s):  
Michael E. D. Koenig

2020 ◽  
Vol 64 (1) ◽  
pp. 6-16 ◽  
Author(s):  
Sarah M. Meeßen ◽  
Meinald T. Thielsch ◽  
Guido Hertel

Abstract. Digitalization, enhanced storage capacities, and the Internet of Things increase the volume of data in modern organizations. To process and make use of these data and to avoid information overload, management information systems (MIS) are introduced that collect, process, and analyze relevant data. However, a precondition for the application of MIS is that users trust them. Extending accounts of trust in automation and trust in technology, we introduce a new model of trust in MIS that addresses the conceptual ambiguities of existing conceptualizations of trust and integrates initial empirical work in this field. In doing so, we differentiate between perceived trustworthiness of an MIS, experienced trust in an MIS, intentions to use an MIS, and actual use of an MIS. Moreover, we consider users’ perceived risks and contextual factors (e. g., autonomy at work) as moderators. The introduced model offers guidelines for future research and initial suggestions to foster trust-based MIS use.


1993 ◽  
Vol 38 (10) ◽  
pp. 1094-1095
Author(s):  
Scott P. Robertson
Keyword(s):  

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