Barone Pamela, Bedia Manuel G, Gomila Antoni
Department of Psychology, University of the Balearic Islands, Palma, Spain.
Human Evolution and Cognition Group (EvoCog), University of the Balearic, IFISC, Associated Unit to CSIC, Palma, Spain.
Front Hum Neurosci. 2020 Mar 24;14:102. doi: 10.3389/fnhum.2020.00102. eCollection 2020.
In the classical Turing test, participants are challenged to tell whether they are interacting with another human being or with a machine. The way the interaction takes place is not direct, but a distant conversation through computer screen messages. Basic forms of interaction are face-to-face and embodied, context-dependent and based on the detection of reciprocal sensorimotor contingencies. Our idea is that interaction detection requires the integration of proprioceptive and interoceptive patterns with sensorimotor patterns, within quite short time lapses, so that they appear as mutually contingent, as reciprocal. In other words, the experience of interaction takes place when sensorimotor patterns are contingent upon one's own movements, and vice versa. I react to your movement, you react to mine. When I notice both components, I come to experience an interaction. Therefore, we designed a "minimal" Turing test to investigate how much information is required to detect these reciprocal sensorimotor contingencies. Using a new version of the perceptual crossing paradigm, we tested whether participants resorted to interaction detection to tell apart human from machine agents in repeated encounters with these agents. In two studies, we presented participants with movements of a human agent, either online or offline, and movements of a computerized oscillatory agent in three different blocks. In each block, either auditory or audiovisual feedback was provided along each trial. Analysis of participants' explicit responses and of the implicit information subsumed in the dynamics of their series will reveal evidence that participants use the reciprocal sensorimotor contingencies within short time windows. For a machine to pass this minimal Turing test, it should be able to generate this sort of reciprocal contingencies.
在经典的图灵测试中，参与者需要判断自己是在与另一个人还是与一台机器进行交互。交互的方式不是直接的，而是通过计算机屏幕消息进行远距离对话。基本的交互形式是面对面的、具身的、依赖上下文的，并且基于对相互的感觉运动偶联的检测。我们的想法是，交互检测需要在相当短的时间内将本体感觉和内感受模式与感觉运动模式整合起来，以便它们呈现为相互偶联、相互对应的。换句话说，当感觉运动模式取决于自身的动作时，交互体验就会发生，反之亦然。我对你的动作做出反应，你对我的动作做出反应。当我注意到这两个组成部分时，我就开始体验到一种交互。因此，我们设计了一个“最小化”图灵测试，以研究检测这些相互的感觉运动偶联需要多少信息。使用感知交叉范式的新版本，我们测试了参与者在与这些智能体的重复接触中是否借助交互检测来区分人类智能体和机器智能体。在两项研究中，我们在三个不同的模块中向参与者展示了人类智能体的动作（在线或离线）以及计算机化振荡智能体的动作。在每个模块的每次试验中，都会提供听觉或视听反馈。对参与者的明确反应以及他们系列动作动态中包含的隐含信息进行分析，将揭示参与者在短时间窗口内使用相互的感觉运动偶联的证据。对于一台机器来说，要通过这个最小化图灵测试，它应该能够产生这种相互偶联。
