MORAL ORTHOSES: A NEW APPROACH TO HUMAN AND MACHINE ETHICS

Machines are increasingly involved in decisions with ethical implications, which require ethical explanations. Current machine learning algorithms are ethically inscrutable, but not in a way very different from human behavior. This article looks at the role of rationality and reasoning in traditional ethical thought and in artificial intelligence, emphasizing the need for some explainability of actions. It then explores Neil Lawrence's embodiment factor as an insightful way of looking at the differences between human and machine intelligence, connecting it to the theological understanding of embodiment, relationality, and personhood. Finally, it proposes the notion of artificial moral orthoses, which could provide ethical explanations for both artificial and human agents, as a more promising unifying approach to human and machine ethics.     

Shared Moral and Spiritual Development Among Human Persons and Artificially Intelligent Agents

Technical advances in artificial intelligence make somewhat likely the possibility of robotic or software agents exhibiting or extending human-level intelligence within a few decades. Theological investigation can help meet significant research goals in artificial intelligence by orienting the development of agent communication and moral reasoning toward a shared moral and spiritual development of human persons and intelligent agents. In particular, Josiah Royce’s Loyalty-to-Loyalty initiates a moral stance within which humans and intelligent agents can develop constructive ethical frameworks and his semiotic philosophy of community can guide the development and functioning of an agent’s interpretive processes and can model shared spiritual formation.     

The role of cognitive architectures in general artificial intelligence

The term “Cognitive Architectures” indicates both abstract models of cognition, in natural and artificial agents, and the software instantiations of such models which are then employed in the field of Artificial Intelligence (AI). The main role of Cognitive Architectures in AI is that one of enabling the realization of artificial systems able to exhibit intelligent behavior in a general setting through a detailed analogy with the constitutive and developmental functioning and mechanisms underlying human cognition. We provide a brief overview of the status quo and the potential role that Cognitive Architectures may serve in the fields of Computational Cognitive Science and Artificial Intelligence (AI) research.     

Living up to one's commitments: Agency, strategies and trust

In human social interaction, the notions of commitment and trust are strongly interrelated. A formal model for this interrelation will enable artificial agents to benefit from the associated reduction of complexity and improved possibilities for cooperation. We argue that the notion of living up to one's commitments, rather than actual fulfillment, plays the key role in the trust–commitment interrelation, and we propose a formal analysis of that notion in the framework of agents and strategies in branching time. The main technical innovation is a stringency ordering on an agent's strategies that allows one to classify what an agent does as more or less appropriate with respect to a given commitment, leading to a fine-grained assessment of trustworthiness.     

Toward ethical cognitive architectures for the development of artificial moral agents

New technologies based on artificial agents promise to change the next generation of autonomous systems and therefore our interaction with them. Systems based on artificial agents such as self-driving cars and social robots are examples of this technology that is seeking to improve the quality of people’s life. Cognitive architectures aim to create some of the most challenging artificial agents commonly known as bio-inspired cognitive agents. This type of artificial agent seeks to embody human-like intelligence in order to operate and solve problems in the real world as humans do. Moreover, some cognitive architectures such as Soar, LIDA, ACT-R, and iCub try to be fundamental architectures for the Artificial General Intelligence model of human cognition. Therefore, researchers in the machine ethics field face ethical questions related to what mechanisms an artificial agent must have for making moral decisions in order to ensure that their actions are always ethically right. This paper aims to identify some challenges that researchers need to solve in order to create ethical cognitive architectures. These cognitive architectures are characterized by the capacity to endow artificial agents with appropriate mechanisms to exhibit explicit ethical behavior. Additionally, we offer some reasons to develop ethical cognitive architectures. We hope that this study can be useful to guide future research on ethical cognitive architectures.     

Transdisciplinarity,neuro-techno-philosophy,and the future of philosophy

Philosophy and science have always striven to make sense of the world, continuously influencing each other in the process. Their interplay paved the way for neurophilosophy, which harnesses neuroscientific insights to address traditionally philosophical questions. Given the rapid neuroscientific and technological advances in recent years, this paper argues that philosophers who wish to tackle intractable philosophical problems and influence public discourse and policies should engage in neuro-techno-philosophy. This novel type of inquiry describes the transdisciplinary endeavor of philosophers, (neuro)scientists, and others to anticipate the societal implications of the impending transformations of subjects and theorizers. While human enhancement is likely to irreversibly change what it means to be human, disruptive technologies might lead to the emergence of artificial intelligent agents and human-machine hybrids. The paper predicts that neuro-techno-philosophy will be indispensable to understanding and engaging with these game-changing innovations and thus play a pivotal role in the future of philosophy.     

THE ARTIFICIALIZATION OF MIND AND WORLD

The rapid advancement of artificial intelligence (AI) has led to renewed ambitions of developing artificial general intelligence. Alongside this has been a resurgence in the development of virtual and augmented reality (V/AR) technologies, which are viewed as “disruptive” technologies and the computing platforms of the future. V/AR effectively bring the digital world of machines, robots, and artificial agents to our senses while entailing the transposition of human activity and presence into the digital world of artificial agents and machine forms of intelligence. The intersection of humans and machines in this shared space brings humans and machines into ontological continuity as informational entities in a totalizing informational environment, which subsumes both cyber and physical space in an artificially constructed virtual world. The reconstruction of mind (through AI) and world (through V/AR) thus has significant epistemological, ontological, and anthropological implications, which constitute the underlying features in the artificialization of mind and world.     

颜色知觉恒常理论的回顾

本文对早期颜色恒常理论、系数理论、计算理论和 Octant模型作了简要回顾 ,并结合已有的研究成果进行评述。对影响颜色恒常性机制的主要因素进行了探讨。强调了知觉经验、记忆、认知决策等高级意识活动对颜色恒常知觉的作用 ,并尝试性地提出了描述颜色恒常知觉过程的一般参照框架。     

Can a Robot Lie? Exploring the Folk Concept of Lying as Applied to Artificial Agents

The potential capacity for robots to deceive has received considerable attention recently. Many papers explore the technical possibility for a robot to engage in deception for beneficial purposes (e.g., in education or health). In this short experimental paper, I focus on a more paradigmatic case: robot lying (lying being the textbook example of deception) for nonbeneficial purposes as judged from the human point of view. More precisely, I present an empirical experiment that investigates the following three questions: (a) Are ordinary people willing to ascribe deceptive intentions to artificial agents? (b) Are they as willing to judge a robot lie as a lie as they would be when human agents engage in verbal deception? (c) Do people blame a lying artificial agent to the same extent as a lying human agent? The response to all three questions is a resounding yes. This, I argue, implies that robot deception and its normative consequences deserve considerably more attention than they presently receive.     

The role of color in human face detection

Significant advances have been made in understanding human face recognition . However, a fundamental aspect of this process, how faces are located in our visual environment, is poorly understood and little studied. Here we examine the role of color in human face detection. We demonstrate that detection performance declines when color information is removed from faces, regardless of whether the surrounding scene context is rendered in color. Furthermore, faces rendered in unnatural colors are hard to detect, suggesting a role beyond simple segmentation. When faces are presented such that half the surface is colored appropriately, and half unnaturally, performance declines. This suggests that observers are not simply using the presence of skin color "patches" to detect faces. Rather, our data suggest that detection operates via a face template combining diagnostic color and face-shape information. These findings are consistent with color-template approaches used in some computer-based face detection systems.     

Computational approaches to color constancy: adaptive and ontogenetic considerations

Recent computational approaches to color constancy can be realized using a two-stage model of color vision. Adaptation at both the sensor stage and the second or reflectance channel stage is necessary to compute illuminant-invariant reflectance estimates. von Kries adaptation is shown to contribute significantly toward reducing, but not completely eliminating, the need for adaptation at the second stage. Examples of computations from the model using daylight illuminants, simulated natural reflectance functions, and putative human spectral sensitivity functions are shown. The ontogenetic plausibility of these models is also discussed. The role of the second-stage transformation in estimating surface reflectance is compared with the role of opponent color transformations in decorrelating primary receptor outputs.     

What Is the Model of Trust for Multi-agent Systems? Whether or Not E-Trust Applies to Autonomous Agents

A socio-cognitive approach to trust can help us envisage a notion of networked trust for multi-agent systems (MAS) based on different interacting agents. In this framework, the issue is to evaluate whether or not a socio-cognitive analysis of trust can apply to the interactions between human and autonomous agents. Two main arguments support two alternative hypothesis; one suggests that only reliance applies to artificial agents, because predictability of agents’ digital interaction is viewed as an absolute value and human relation is judged to be a necessary requirement for trust. The other suggests that trust may apply to autonomous agents because predictability of agents’ interaction is viewed only as a relative value since the digital normativity that grows out of the communication process between interacting agents in MAS has always deal with some unpredictable outcomes (reduction of uncertainty). Furthermore, human touch is not judged to be a necessary requirement for trust. In this perspective, a diverse notion of trust is elaborated, as trust is no longer conceived only as a relation between interacting agents but, rather, as a relation between cognitive states of control and lack of control (double bind).     

Explaining color term typology with an evolutionary model

An expression-induction model was used to simulate the evolution of basic color terms to test Berlin and Kay's (1969) hypothesis that the typological patterns observed in basic color term systems are produced by a process of cultural evolution under the influence of biases resulting from the special properties of universal focal colors. Ten agents were simulated, each of which could learn color term denotations by generalizing from examples using Bayesian inference, and for which universal focal red, yellow, green, and blue were especially salient, but unevenly spaced in the perceptual color space. Conversations between these agents, in which agents would learn from one another, were simulated over several generations, and the languages emerging at the end of each simulation were investigated. The proportion of color terms of each type correlated closely with the equivalent frequencies found in the World Color Survey, and most of the emergent languages could be placed on one of the evolutionary trajectories proposed by Kay and Maffi (1999). The simulation therefore demonstrates how typological patterns can emerge as a result of learning biases acting over a period of time.     

Representations in dynamical embodied agents: re-analyzing a minimally cognitive model agent

Understanding the role of 'representations' in cognitive science is a fundamental problem facing the emerging framework of embodied, situated, dynamical cognition. To make progress, I follow the approach proposed by an influential representational skeptic, Randall Beer: building artificial agents capable of minimally cognitive behaviors and assessing whether their internal states can be considered to involve representations. Hence, I operationalize the concept of representing as 'standing in,' and I look for representations in embodied agents involved in simple categorization tasks. In a first experiment, no representation can be found, but the relevance of the task is undermined by the fact that agents with no internal states can reach high performance. A simple modification makes the task more "representationally hungry," and in this case, agents' internal states are found to qualify as representations. I conclude by discussing the benefits of reconciling the embodied-dynamical approach with the notion of representation.     

Cue learning by rufous hummingbirds (Selasphorus rufus)

The authors investigated the use by wild-living rufous hummingbirds (Selasphorus rufus) of flower color pattern and flower position for remembering rewarded flowers. Birds were presented with arrays of artificial flowers, a proportion of which was rewarded. Once the locations were learned by the birds, the array was moved 2 m, and flower color pattern and/or rewarded positions were manipulated. The birds' ability to learn which were the rewarded flowers in this 2nd array was much more strongly affected by whether the rewarded flowers occupied the same positions as in the 1st array than by their color patterns.     

From embodied to socially embedded agents – Implications for interaction-aware robots

First, this article proposes a minimal definition of embodiment that can be applied across animals and artefacts. We discuss the potential contributions of this operational definition with respect to assessing and measuring the degree of embodiment in different biological and artificial systems. Second, we outline how this definition can be extended to lead to the particular notion of social embeddedness. Socially embedded agents are structurally coupled with their social environment, in that their sensorimotor activity is grounded in the social environment that the agent is surrounded by. Lastly, based on research in the social sciences on human–human interaction, we discuss perceptual requirements for interaction-aware robotic agents—agents whose identification and interpretation of the (social) environment is facilitated by awareness of the structure of agent–agent interactions (including humans ‘in the loop’). We suggest relevant concepts and heuristics that can contribute to studies of degrees of embodiment of robots that interact with social environments. Manipulating and systematically investigating these heuristics permits variation of the degree of embodiment of such interaction-aware robots.     

Pharmacologic management of sexual dysfunction: benefits and limitations

What is the current knowledge concerning the pharmacologic treatment of human sexual dysfunction? A number of interventions, including oral phophodiesterase inhibitors and intracorporeal agents with vasodilatory effects, are available to treat male erectile disorder. Serotonergic drugs have been shown to be effective in the treatment of rapid ejaculation. Various lines of research suggest that high dosages of androgenic agents may eventually have a role in the treatment of decreased libido in females. There may be a role for phophodiesterase inhibitors in the treatment of a subgroup of women with arousal disorders. Normal sexual function involves successful integration of biological, psychological, and interpersonal influences. Clinical psychiatry with its biopsychosocial model should incorporate the treatment of human sexual dysfunction within its purview.     

Disagreements Over Analogies

This essay presents a dialogical framework for treating philosophical disagreements as persuasion dialogues with analogical argumentation, with the aim of recasting philosophical disputes as disagreements over analogies. This has two benefits: (1) it allows us to temporarily bypass conflicting metaphysical intuitions by focusing on paradigmatic examples, (dis)similarities, and the plausibility of conclusions for or against a given point of view; and (2) it can reveal new avenues of argumentation regarding a given issue. This approach to philosophical disagreements is illustrated by studying the role of argumentation by analogy in disputes over Lockean justifications of intellectual property rights, and disagreements over whether artificial agents should be treated as moral agents. Finally, a nonexhaustive list of possible global and local points of contention over analogical arguments is identified in order to highlight potential avenues of argumentation in disagreements over analogies.     

The Concurrentism of Thomas Aquinas: Divine Causation and Human Freedom

The paper deals with the problem of divine causation in relation to created agents in general and human rational agents in particular. Beyond creation and conservation, Aquinas specifies divine contribution to created agents’ operation as application in the role of the first cause and the operation of the principal cause employing an instrumental cause. It is especially the latter which is open to varying interpretation and which might be potentially threatening to human freedom. There are different readings of what it is for the secondary agent to “act through the power of the principal cause”. Either the divine cause causes only the existence of the effect of the secondary cause, or it also causes the cause to operate in the sense that it determines its outcome. The latter seems to contradict human freedom. Both readings of Aquinas were developed in the latter half of the sixteenth century within scholastic philosophy and theology.