When is Lying the Right Choice ? ∗

Restricting the spread of sensitive information is important in domains ranging from commerce to military operations. In this position paper, we propose research aimed at exploring techniques for privacy enforcement when humans are the recipient of — possibly obfuscated — information. Such obfuscation could be considered to be a white lie, and we argue that determining what information to share and whether it should be obfuscated must be done through controlled query evaluation, which depends on each agent’s risk/benefit evaluation. We concentrate on machine-human interactions, and note that appropriate specific natural language interfaces need to be developed to handle obfuscation. We propose a solution for creating controlled query evaluation mechanisms based on robust approaches for data representation under uncertainty, viz. SDL-Lite, and propose using ITA Controlled English for natural language generation so as to handle subjectivity. We present the general architecture for our approach, with a focus on the relationship between formal ontology, controlled query evaluation, and natural language.