The radio research community has aggressively embraced cognitive radio for dynamic radio spectrum management to enhance spectrum usage, e.g., in ISM bands and as secondary users in unused TV bands, but the needs of the mobile wireless user have not been addressed as thoroughly on the question of high quality of information (QoI) as a function of place, time, and social setting (e.g. commuting, shopping, or in need of medical assistance). This paper considers the evolution of cognitive radio architecture (CRA) in the context of motivating use cases such as public safety and sentient spaces to characterize CRA with an interdisciplinary perspective where machine perception in visual, acoustic, speech, and natural language text domains provide cues to the automatic detection of stereotypical situations, enabling radio nodes to select from among radio bands and modes more intelligently and enabling cognitive wireless networks to deliver higher QoI within social and technical constraints, made more cost effective via embedded and distributed computational intelligence.