Emotion, embodied cognition, and Artificial Intelligence

2021 ◽  
Author(s):  
Marina Korsakova-Kreyn
Keyword(s):  
Artificial Intelligence ◽  
Embodied Cognition

The Role of Theories of Embodied Cognition in Research and Modeling of Emotions

2019 ◽  
Vol 62 (5) ◽  
pp. 124-138
Author(s):  
Alexandra V. Shiller
Keyword(s):  
Artificial Intelligence ◽  
Embodied Cognition ◽  
Mirror Neurons ◽  
Empirical Studies ◽  
Unknown Quantity ◽  
Emotional Processes ◽  
Strong Artificial Intelligence ◽  
European Philosophy ◽  
Postmodern Philosophy

The article analyzes the role of theories of embodied cognition for the development of emotion research. The role and position of emotions changed as philosophy developed. In classical and modern European philosophy, the idea of the “primacy of reason” prevailed over emotions and physicality, emotions and affective life were described as low-ranking phenomena regarding cognitive processes or were completely eliminated as an unknown quantity. In postmodern philosophy, attention focuses on physicality and sensuality, which are rated higher than rational principle, mind and intelligence. Within the framework of this approach, there is a recently emerged theory of embodied cognition, which allows to take a fresh look at the place of emotions in the architecture of mental processes – thinking, perception, memory, imagination, speech. The article describes and analyzes a number of empirical studies showing the impossibility of excluding emotional processes and the significance of their research for understanding the architecture of embodied cognition. However, the features of the architecture of embodied cognition remain unclear, and some of the discoveries of recent years (mirror neurons or neurons of simulation) rather raise new questions and require further research. The rigorously described and clear architecture of the embodied cognition can grow the theoretical basis that will allow to advance the studies of learning processes, language understanding, psychotherapy techniques, social attitudes and stereotypes, highlight the riddle of consciousness and create new theories of consciousness or even create an anthropomorphic artificial intelligence that is close to “strong artificial intelligence.”

Embodying algorithms, enactive artificial intelligence and the extended cognition: You can see as much as you know about algorithm

2021 ◽  
pp. 016555152098549
Author(s):  
Donghee Shin
Keyword(s):  
Artificial Intelligence ◽  
Embodied Cognition ◽  
Cognitive Processes ◽  
Process Model ◽  
Extended Cognition ◽  
Dual Process ◽  
Personalized Recommendation ◽  
Normative Values ◽  
And Performance ◽  
Concise Guide

The recent proliferation of artificial intelligence (AI) gives rise to questions on how users interact with AI services and how algorithms embody the values of users. Despite the surging popularity of AI, how users evaluate algorithms, how people perceive algorithmic decisions, and how they relate to algorithmic functions remain largely unexplored. Invoking the idea of embodied cognition, we characterize core constructs of algorithms that drive the value of embodiment and conceptualizes these factors in reference to trust by examining how they influence the user experience of personalized recommendation algorithms. The findings elucidate the embodied cognitive processes involved in reasoning algorithmic characteristics – fairness, accountability, transparency, and explainability – with regard to their fundamental linkages with trust and ensuing behaviors. Users use a dual-process model, whereby a sense of trust built on a combination of normative values and performance-related qualities of algorithms. Embodied algorithmic characteristics are significantly linked to trust and performance expectancy. Heuristic and systematic processes through embodied cognition provide a concise guide to its conceptualization of AI experiences and interaction. The identified user cognitive processes provide information on a user’s cognitive functioning and patterns of behavior as well as a basis for subsequent metacognitive processes.

scholarly journals Nonconscious Cognitive Suffering: Considering Suffering Risks of Embodied Artificial Intelligence

Philosophies ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 24
Author(s):  
Steven Umbrello ◽  
Stefan Lorenz Sorgner
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Embodied Cognition ◽  
Information Integration ◽  
Physical State ◽  
Conscious State ◽  
Human Cognition ◽  
Machine Consciousness

Strong arguments have been formulated that the computational limits of disembodied artificial intelligence (AI) will, sooner or later, be a problem that needs to be addressed. Similarly, convincing cases for how embodied forms of AI can exceed these limits makes for worthwhile research avenues. This paper discusses how embodied cognition brings with it other forms of information integration and decision-making consequences that typically involve discussions of machine cognition and similarly, machine consciousness. N. Katherine Hayles’s novel conception of nonconscious cognition in her analysis of the human cognition-consciousness connection is discussed in relation to how nonconscious cognition can be envisioned and exacerbated in embodied AI. Similarly, this paper offers a way of understanding the concept of suffering in a way that is different than the conventional sense of attributing it to either a purely physical state or a conscious state, instead of grounding at least a type of suffering in this form of cognition.

Pointing the way

1997 ◽  
Vol 20 (4) ◽  
pp. 758-763
Author(s):  
Dana H. Ballard ◽  
Mary M. Hayhoe ◽  
Polly K. Pook ◽  
Rajesh P. N. Rao
Keyword(s):  
Artificial Intelligence ◽  
Eye Movements ◽  
Embodied Cognition ◽  
Visual Processing ◽  
Human Intelligence ◽  
The Core ◽  
Satisfactory Account ◽  
The Way

The majority of commentators agree that the time to focus on embodiment has arrived and that the disembodied approach that was taken from the birth of artificial intelligence is unlikely to provide a satisfactory account of the special features of human intelligence. In our Response, we begin by addressing the general comments and criticisms directed at the emerging enterprise of deictic and embodied cognition. In subsequent sections we examine the topics that constitute the core of the commentaries: embodiment mechanisms, dorsal and ventral visual processing, eye movements, and learning.

Modeling self and others

2018 ◽  
Author(s):  
Josh Bongard
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Social Cognition ◽  
Embodied Cognition ◽  
Learning Methods ◽  
Future Directions ◽  
Inverse Models ◽  
The Brain ◽  
Scientific Hypotheses

Embodied cognition is the view that intelligence arises out of the interaction between an agent’s body and its environment. Taking such a view generates novel scientific hypotheses about biological intelligence and opportunities for advancing artificial intelligence. In this chapter we review one such set of hypotheses regarding how a robot may generate models of self, and others, and then exploit those models to recover from damage or exhibit the rudiments of social cognition. This modeling of self and others draws mainly on three concepts from neuroscience and AI: forward and inverse models in the brain, the neuronal replicator hypothesis, and the brain as a hierarchical prediction machine. The chapter concludes with future directions, including the integration of deep learning methods with embodied cognition.

Artificial Intelligence

2009 ◽  
Author(s):  
David L. Poole ◽  
Alan K. Mackworth
Keyword(s):  
Artificial Intelligence
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