IT Alternatives to Social Control in Organizations

This paper extends theories of control as an organization design tool and empirically explores the efficacy of delegation technologies in providing the equivalent of social (clan) control for effort-averse agents engaged in low programmable, low outcome measurement task environments

An End-to-End Conversational Style Matching Agent

We present an end-to-end voice-based conversational agent that is able to engage in naturalistic multi-turn dialogue and align with the interlocutor's conversational style. The system uses a series of deep neural network components for speech recognition, dialogue generation, prosodic analysis and speech synthesis to generate language and prosodic expression with qualities that match those of the user. We conducted a user study (N=30) in which participants talked with the agent for 15 to 20 minutes, resulting in over 8 hours of natural interaction data. Users with high consideration conversational styles reported the agent to be more trustworthy when it matched their conversational style. Whereas, users with high involvement conversational styles were indifferent. Finally, we provide design guidelines for multi-turn dialogue interactions using conversational style adaptation

Sentence Context and Meaning Frequency Effects in Children\u27s Processing of Ambiguous Words

Nine‐ and twelve‐year‐old children named target words which were preceded by sentences ending in words having more than one meaning. Sentences biased the ambiguous word toward its dominant (more frequent) or subordinate (less frequent) meaning. Targets were related to the same meaning as that biased by the sentence, the other meaning, or were unrelated. Targets were presented 0, 300, or 700 ms following the sentence. For both ages, dominant sentences facilitated responses only to the contextually appropriate target. However, subordinate sentences led to facilitation of the appropriate meaning only for the younger group. Older children showed greater facilitation for the inappropriate (but more common) meaning. These results indicate that younger children are more sensitive to the sentence context in which an ambiguous word appears, while the processing of the older children is determined more by the relative frequencies of the words meanings

A Computational Model of Trust-, Pupil-, and Motivation Dynamics

Autonomous machines are in the near future likely to increasingly interact with humans, and carry out their functions outside controlled settings. Both of these developments increase the requirements of machines to be trustworthy to humans. In this work, we argue that machines may also benefit from being able to explicitly build or withdraw trust with specific humans. The latter is relevant in situations where the integrity of an autonomous system is compromised, or if humans display untrustworthy behaviour towards the system. Examples of systems that could benefit might be delivery robots, maintenance robots, or autonomous taxis. This work contributes by presenting a biologically plausible model of unconditional trust dynamics, which simulates trust building based on familiarity, but which can be modulated by painful and gentle touch. The model displays interactive behaviour by being able to realistically control pupil dynamics, as well as determine approach and avoidance motivation