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The project goal is to provide a common set where researchers and practitioners reflect, explore and transfer insights on the dimensions of trust experience when one engages with technology; and develop a user-friendly toolset to support designers to shape positive experiences and awareness of trust.
This tool needs to:
Duration: 8 months (05/2020 – 12/2020)
Team: Sonia Sousa, David Lamas, Ighoyota Ben Ajenaghughrure, Priit Tammets, Pjotr Savitski and Anet Põdra
Partner: Tallinn University
This project advocate for a user-centric approach to quantify the dimensions of the trust experience, when, instead of another human, one engages with a complex system. This service, besides helping designers and stakeholders to assess what aspects of system users consider to be risky also indicates which parts of the system users’ consider being untrustworthy. It combines, as well, context-aware methods to assess to what extent this tool can support the reflection on ethical concerns associated with trustworthiness and indications of interacting perceived risk. Its importance lies in using trust as a key to help minimize the risk associated with data breaches and misuse, as well as to foster transparency, user intervenability, and accountability. Builds upon the assumption that in detriment of the default mainstream attention given to privacy and security, we continue to see individuals as a product that we can manipulate to our preferences — forgetting to design transparent systems that can explicitly communicate trusting behaviors to their users.
This project innovation lies in using user experience (UX) evaluation techniques to overcome the tendency to oversimplify the interpretation of how user experience trust — reminding systems designers that trust is highly dependent on social context and that individual’s reactions to it are social. This service, besides supporting them to fully undertake the complexity between existing distrusted technologies and individual’s interpretations of privacy concerns, strategies, and ethical needs. Also helps avoid the tendency to designing systems that enforce individual’s to trust even when fully aware that privacy and data breaches can occur.
TrustedUX builds upon Sousa and colleagues trust in technology framework (Sousa et al, 2014; Gulati et al., 2019) that aggregates three aspects related to the experience of trust: (1) Risk Perception: the level of fear of risk-taking, uncertainty, and anxiety associated to the activity; (2) Benevolence: the level of reported positiveness and meaningfulness of interaction; and (3) Competence: the skill level that supports initiating, maintaining, and returning the interaction. Adopts, as well, their current trust scales empirically sound model, consisting of 12 items (Gulati et al. 2019) to design an easy to apply the instrument to measure and quantify participants’ self-reported experience of trust. The set of identifying factors of trust addressed in their Human-Computer Trust blog that explains individuals particularly susceptibility to their experience of trust and knowledge. Knowledge acquired from applying the trust psychometric scale in the Master level course in Trust in computing taught since 2017 (at a distance and face to face).
M1: Requirements analysis and specification
M2: Prototype, development and integration
M3: Validation, refinement and test
M4: Templates and guidelines (on the basis of interaction design and rules and procedures on how to use)
M5: Dissemination administrative and logistics support
NGI TRUST project site: www.ngi.eu/ngi-projects/ngi-trust/