ELVIRA: an Explainable Agent for Value and Utility-driven Multiuser Privacy

TY - CHAP

T1 - ELVIRA: an Explainable Agent for Value and Utility-driven Multiuser Privacy

AU - Mosca, Francesca

AU - Such, Jose

PY - 2021

Y1 - 2021

N2 - Online social networks fail to support users to adequately share co-owned content, which leads to privacy violations.Scholars proposed collaborative mechanisms to support users, but they did not satisfy one or more requirements needed according to empirical evidence in this domain, such as explainability, role-agnosticism, adaptability, and being utility- and value-driven.We present ELVIRA, an agent that supports multiuser privacy, whose design meets all these requirements. By considering the sharing preferences and the moral values of users, ELVIRA identifies the optimal sharing policy. Furthermore, ELVIRA justifies the optimality of the solution through explanations based on argumentation. We prove via simulations that ELVIRA provides solutions with the best trade-off between individual utility and value adherence. We also show through a user study that ELVIRA suggests solutions that are more acceptable than existing approaches and that its explanations are also more satisfactory.

AB - Online social networks fail to support users to adequately share co-owned content, which leads to privacy violations.Scholars proposed collaborative mechanisms to support users, but they did not satisfy one or more requirements needed according to empirical evidence in this domain, such as explainability, role-agnosticism, adaptability, and being utility- and value-driven.We present ELVIRA, an agent that supports multiuser privacy, whose design meets all these requirements. By considering the sharing preferences and the moral values of users, ELVIRA identifies the optimal sharing policy. Furthermore, ELVIRA justifies the optimality of the solution through explanations based on argumentation. We prove via simulations that ELVIRA provides solutions with the best trade-off between individual utility and value adherence. We also show through a user study that ELVIRA suggests solutions that are more acceptable than existing approaches and that its explanations are also more satisfactory.

KW - Multiuser Privacy

KW - Practical Reasoning

KW - Human-Agent Interaction

KW - Value-based Agents

KW - Explainable Agents

M3 - Conference paper

BT - International Conference on Autonomous Agents and Multiagent Systems (AAMAS)

ER -