On the way to hybrid intelligence: influence of the human-system interaction rate on the human cognitive performance

Oleksandr Burov, E. Lavrov, S. Lytvynova, Olha P. Pinchuk, K. Horska, Oleksii M. Tkachenko, N. Kovalenko, Y. Chybiriak
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Abstract

IntroductionHybrid job and learning create new opportunities and set new requirements to control a human-machine interaction. It is important to keep in mind that modern and future participants of these activi-ties can include the artificial intellect (AI-actor) as well. One of the critical features of their interaction could be the rate of the information exchange, because an AI-actor can accept and produce tasks in a quite stable rate, in contrast with a human-actor whose performance quality can very in time. As a result, their interaction needs to be adjusted in many cases from viewpoint of complexity and rate. It is supposed that the process of the information task flow should correspond an individual or moderate rate, in the best case. But according to our preliminary data (Burov, 1990, 1996), the moderate rate (even individually adapted) of perceptual and cognitive task flow was accompanied by a higher physiological strain than slow and fast ones. Because the cognitive component of the mental work becomes more and more significant both for a job and for a teaching/learning, it is useful for adaptive systems’ design to clarify if the free (“auto”) and moderate rates have the same and/or similar influence on a human performance quality (reliability and speed) and health consequences. GoalTo carry out the comparison analysis of the speed and reliability of cognitive activity by subjects performing computer tasks at a free and fixed pace, considering the physiological "cost" of such activities. Discussion of ResultsThe methodological basis of our research are models and methods for assessment a human ability to cognitive work using the computer system for psychophysiological research developed by authors. The survey included cognitive test task performance, blood pressure and heart rate before and after the test performance, as well as electropuncture diagnostics (EPD) after Nakatani (including 3 stress-points) for each subject. 47 subjects participated in experiments, 4 times per month (three times performing tests in the fix pace, one time in the free pace, each test session in a week). The duration of each test session was 3 continuous hours. Variation of the cognitive test task performance (accuracy and reliability) over the research period were studied and compared with changes of psychological and physiological indices, namely heart rate, blood pressure, vegetative stress index after Bayevsky as well as stress indices after Nakatani. It has been revealed strong increase of the stress by physiological and EPD indices and deterioration in activity (task performance time, reliability) in test sessions with fixed pace. Individual and inter-dividual variations are considered.Significance of the Proposed PresentationThe results can be applied to optimize a human and digital system interaction accounting a hu-man cognitive and psychophysiological limitations in interaction pace. The optimization goal can be to adjust their interaction pace to achieve maximal general performance in short- and long-term per-spective.
在通往混合智能的道路上:人机交互率对人类认知能力的影响
工作和学习的混合为控制人机交互创造了新的机会,并提出了新的要求。重要的是要记住,这些活动的现代和未来参与者也可能包括人工智能(AI-actor)。他们互动的一个关键特征可能是信息交换的速度,因为人工智能演员可以以相当稳定的速度接受和产生任务,而人类演员的表演质量可以非常及时。因此,在许多情况下,它们的交互需要从复杂性和速率的角度进行调整。假设在最好的情况下,信息任务流的处理应该对应一个单独的或中等的速率。但根据我们的初步数据(Burov, 1999,1996),与慢速和快速任务流相比,中等速度(甚至是单独适应)的感知和认知任务流伴随着更高的生理压力。由于心理工作的认知成分对工作和教学/学习都变得越来越重要,因此对于自适应系统的设计来说,澄清自由(“自动”)和适度的速度是否对人类的表现质量(可靠性和速度)和健康后果具有相同和/或相似的影响是有用的。目的在考虑计算机任务的生理“成本”的情况下,对自由和固定速度的计算机任务的认知活动速度和可靠性进行比较分析。本研究的方法学基础是利用作者开发的心理生理研究计算机系统评估人类认知工作能力的模型和方法。调查内容包括每位受试者的认知测试任务表现、测试前后的血压和心率,以及中谷后的电穿刺诊断(EPD)(包括3个应激点)。47名受试者参加实验,每月4次(固定配速测试3次,自由配速测试1次,每次测试周期为一周)。每次测试持续时间为连续3小时。研究了认知测试任务表现(准确性和可靠性)在研究期间的变化,并与心率、血压、巴耶夫斯基实验后的植物应激指数和中谷实验后的应激指数等心理生理指标的变化进行了比较。生理和EPD指标显示,在固定节奏的测试中,压力明显增加,活动(任务执行时间、可靠性)恶化。考虑了个体和个体间的差异。研究结果可用于优化人与数字系统的交互,考虑到人在交互速度上的认知和心理生理限制。优化目标可以是调整它们的交互速度,以在短期和长期的角度上获得最大的总体性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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