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Young children, like adults, understand that human agents can flexibly choose different actions in different contexts, and they evaluate these agents based on such choices. However, little is known about children's tendencies to attribute the capacity to choose to robots, despite increased contact with robotic agents. In this paper, we compare 5‐ to 7‐year‐old children's and adults' attributions of free choice to a robot and to a human child by using a series of tasks measuring agency attribution, action prediction, and choice attribution. In morally neutral scenarios, children ascribed similar levels of free choice to the robot and the human, while adults were more likely to ascribe free choice to the human. For morally relevant scenarios, however, both age groups considered the robot's actions to be more constrained than the human's actions. These findings demonstrate that children and adults hold a nuanced understanding of free choice that is sensitive to both the agent type and constraints within a given scenario. [ABSTRACT FROM AUTHOR]

A central problem in the cognitive sciences is identifying the link between consciousness and neural computation. The key features of consciousness—including the emergence of representative information content and the initiation of volitional action—are correlated with neural activity in the cerebral cortex, but not computational processes in spinal reflex circuits or classical computing architecture. To take a new approach toward considering the problem of consciousness, it may be worth re‐examining some outstanding puzzles in neuroscience, focusing on differences between the cerebral cortex and spinal reflex circuits. First, the mammalian cerebral cortex exhibits exascale computational power, a feature that is not strictly correlated with the number of binary computational units; second, individual computational units engage in noisy coding, allowing random electrical events to gate signaling outcomes; third, this noisy coding results in the synchronous firing of statistically random populations of cells across the neural network, at a range of nested frequencies; fourth, the system grows into a more ordered state over time, as it encodes the predictive value gained through observation; and finally, the cerebral cortex is extraordinarily energy efficient, with very little free energy lost to entropy during the work of information processing. Here, I argue that each of these five key features suggest the mammalian brain engages in probabilistic computation. Indeed, by modeling the physical mechanisms of probabilistic computation, we may find a better way to explain the unique emergent features arising from cortical neural networks. [ABSTRACT FROM AUTHOR]

Past work has found that infants show more interest when an object that has at least two properties of animate beings, such as engaging in self‐generated motion and having fur, is shown to be hollow than when an object with none or one of these properties is revealed to be hollow. When an object is grabbed by a hand and moved to a new place, by 7 months of age, infants explain the motion of the object as due to the hand, and thus do not interpret this object as capable of self‐generated motion. This constant application of force is called an "entraining" event. Other work has found that 6‐month‐old infants are sensitive to the reversals of causal roles in "launching" events (billiard‐ball‐like collisions), but not entraining events. Here, we examine whether 10‐month‐old infants explain the motion of the patient in a launching event as being due to the contact with the launching agent. Experiment 1 replicates past work, showing that infants look longer when a self‐propelled object with animate features (fur or feathers) is shown to be hollow, compared to a similar object undergoing spatiotemporally identical motion entrained by a human agent. Experiment 2 finds that infants look equally at the agent and patient, both covered by fur or feathers, of a launching event when each is revealed to be hollow. Experiment 3 shows that infants look longer when a fur‐covered causal patient is shown to be hollow compared to a plain‐box causal agent, indicating that 10‐month‐old infants do not explain the motion of the causal patient of a launching event as due to the agent, even though they do so for an entraining event. This dissociation suggests the existence of multiple independent causal representations in the first year of life. [ABSTRACT FROM AUTHOR]