| 1. |
- Blomsma, Peter, et al.
(författare)
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Backchannel Behavior Influences the Perceived Personality of Human and Artificial Communication Partners
- 2022
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Ingår i: Frontiers in Artificial Intelligence. - : Frontiers Media SA. - 2624-8212. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- Different applications or contexts may require different settings for a conversational AI system, as it is clear that e.g., a child-oriented system would need a different interaction style than a warning system used in emergency situations. The current article focuses on the extent to which a system's usability may benefit from variation in the personality it displays. To this end, we investigate whether variation in personality is signaled by differences in specific audiovisual feedback behavior, with a specific focus on embodied conversational agents. This article reports about two rating experiments in which participants judged the personalities (i) of human beings and (ii) of embodied conversational agents, where we were specifically interested in the role of variability in audiovisual cues. Our results show that personality perceptions of both humans and artificial communication partners are indeed influenced by the type of feedback behavior used. This knowledge could inform developers of conversational AI on how to also include personality in their feedback behavior generation algorithms, which could enhance the perceived personality and in turn generate a stronger sense of presence for the human interlocutor.
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| 2. |
- Kulmizev, Artur, et al.
(författare)
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Schrödinger's tree : On syntax and neural language models
- 2022
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Ingår i: Frontiers in Artificial Intelligence. - : Frontiers Media S.A.. - 2624-8212. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- In the last half-decade, the field of natural language processing (NLP) hasundergone two major transitions: the switch to neural networks as the primarymodeling paradigm and the homogenization of the training regime (pre-train, then fine-tune). Amidst this process, language models have emergedas NLP’s workhorse, displaying increasingly fluent generation capabilities andproving to be an indispensable means of knowledge transfer downstream.Due to the otherwise opaque, black-box nature of such models, researchershave employed aspects of linguistic theory in order to characterize theirbehavior. Questions central to syntax—the study of the hierarchical structureof language—have factored heavily into such work, shedding invaluableinsights about models’ inherent biases and their ability to make human-likegeneralizations. In this paper, we attempt to take stock of this growing body ofliterature. In doing so, we observe a lack of clarity across numerous dimensions,which influences the hypotheses that researchers form, as well as theconclusions they draw from their findings. To remedy this, we urge researchersto make careful considerations when investigating coding properties, selectingrepresentations, and evaluating via downstream tasks. Furthermore, we outlinethe implications of the different types of research questions exhibited in studieson syntax, as well as the inherent pitfalls of aggregate metrics. Ultimately, wehope that our discussion adds nuance to the prospect of studying languagemodels and paves the way for a less monolithic perspective on syntax in thiscontext.
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| 3. |
- Wang, Pei, et al.
(författare)
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A Model of Unified Perception and Cognition
- 2022
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Ingår i: Frontiers in Artificial Intelligence. - : Frontiers Media SA. - 2624-8212. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- This article discusses an approach to add perception functionality to a general-purpose intelligent system, NARS. Differently from other AI approaches toward perception, our design is based on the following major opinions: (1) Perception primarily depends on the perceiver, and subjective experience is only partially and gradually transformed into objective (intersubjective) descriptions of the environment; (2) Perception is basically a process initiated by the perceiver itself to achieve its goals, and passive receiving of signals only plays a supplementary role; (3) Perception is fundamentally unified with cognition, and the difference between them is mostly quantitative, not qualitative. The directly relevant aspects of NARS are described to show the implications of these opinions in system design, and they are compared with the other approaches. Based on the research results of cognitive science, it is argued that the Narsian approach better fits the need of perception in Artificial General Intelligence (AGI).
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| 4. |
- Zdravkova, Katerina, et al.
(författare)
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Cutting-edge communication and learning assistive technologies for disabled children : An artificial intelligence perspective
- 2022
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Ingår i: Frontiers in Artificial Intelligence. - : Frontiers Media S.A.. - 2624-8212. ; 5
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Forskningsöversikt (refereegranskat)abstract
- In this study we provide an in-depth review and analysis of the impact of artificial intelligence (AI) components and solutions that support the development of cutting-edge assistive technologies for children with special needs. Various disabilities are addressed and the most recent assistive technologies that enhance communication and education of disabled children, as well as the AI technologies that have enabled their development, are presented. The paper summarizes with an AI perspective on future assistive technologies and ethical concerns arising from the use of such cutting-edge communication and learning technologies for children with disabilities.
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