Making IBM’s Computer Watson Human

Rachlin, Howard

doi:10.1093/acprof:oso/9780199322350.003.0010

Cited by 8 publications

(9 citation statements)

References 8 publications

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“…However, they all hold that psychologists should be silent on anything not publicly observable, and should deal with only observable relations between stimuli and responses in the data. Versions of Interpretation 1 that advocate ignoring all unobservables, though not necessarily taking the form of classical S-R behaviorism, continue to be influential in some areas of psychology (e.g., Baum, 2011;Rachlin, 2012).…”

Section: Discussionmentioning

confidence: 99%

Methodological behaviorism from the standpoint of a radical behaviorist

Moore

2013

BEHAV ANALYST

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Methodological behaviorism is the name for a prescriptive orientation to psychological science. Its first and original feature is that the terms and concepts deployed in psychological theories and explanations should be based on observable stimuli and behavior. I argue that the interpretation of the phrase "based on" has changed over the years because of the influence of operationism. Its second feature, which developed after the first and is prominent in contemporary psychology, is that research should emphasize formal testing of a theory that involves mediating theoretical entities from an nonbehavioral dimension according to the hypothetico-deductive method. I argue that for contemporary methodological behaviorism, explanations of the behavior of both participants and scientists appeal to the mediating entities as mental causes, if only indirectly. In contrast to methodological behaviorism is the radical behaviorism of B. F. Skinner. Unlike methodological behaviorism, radical behaviorism conceives of verbal behavior in terms of an operant process that involves antecedent circumstances and reinforcing consequences, rather than in terms of a nonbehavioral process that involves reference and symbolism. In addition, radical behaviorism recognizes private behavioral events and subscribes to research and explanatory practices that do not include testing hypotheses about supposed mediating entities from another dimension. I conclude that methodological behaviorism is actually closer to mentalism than to Skinner's radical behaviorism.

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Section: Discussionmentioning

confidence: 99%

Methodological behaviorism from the standpoint of a radical behaviorist

Moore

2013

BEHAV ANALYST

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“…Movement sequences result in need reduction as survival adaptations. He assumes that learning can only occur with reinforcement of the responses that lead to attainment of survival needs, and that the mechanism of this reinforcement is the reduction of a biological drive (Rachlin, 2012;Zuriff, 1985;Johnston, & Pennypacker, 2008).…”

Section: Hullian Neo-behaviorism and Mathematic-deductive Study Of Drivementioning

confidence: 99%

From Behaviorism to New Behaviorism: A Review Study

Ziafar

Namaziandost

2019

loquen

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Neobehaviorism bridges the gap between behaviorism and cognitivism. Like Thorndike, Watson, and Pavlov, the neobehaviorists believe that the study of learning and a focus on rigorously objective observational methods are crucial to a scientific psychology. Unlike their predecessors, however, the neobehaviorists are more self-consciously attempting to formalize the laws of behavior. Neobehaviorism is associated with a number of scholars such as Tolman, Hull, Skinner, Hebb, and Bandura. Neobehaviorists demand formalizing the law of behavior. Neobehaviorism takes into consideration abstraction and hidden variables, it represents a holistic approach to behavior. It can be claimed that all neobehavioristic theories have been proposed in order to put some cognition within the mechanistic nature of traditional behaviorism.

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“…DeepBlue (Campbell et al, 2002), Watson (? Rachlin, 2012;Shader, 2016), and AlphaGo (Silver et al, 2016) are AI systems that have achieved great success in challenging human intelligence in some fields by relying on the powerful processing ability of computers. However, these systems cannot evolve to a higher intelligence level by virtue of their own thought processes yet.…”

Section: Introductionmentioning

confidence: 99%

Hybrid-augmented intelligence: collaboration and cognition

郑

刘

任

et al. 2017

Frontiers Inf Technol Electronic Eng

254

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The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models: one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

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Making IBM’s Computer Watson Human

Cited by 8 publications

References 8 publications

Methodological behaviorism from the standpoint of a radical behaviorist

Methodological behaviorism from the standpoint of a radical behaviorist

From Behaviorism to New Behaviorism: A Review Study

Hybrid-augmented intelligence: collaboration and cognition

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