This essay introduces this special issue on virtue ethics in relation to military AI. It describes the current situation of military AI ethics as following that of AI ethics in general, caught between consequentialism and deontology. Virtue ethics serves as an alternative that can address some of the weaknesses of these dominant forms of ethics. The essay describes how the articles in the issue exemplify the value of virtue-related approaches for these questions, before ending with thoughts for further research.

Entrepreneurial activities are becoming more and more prevalence in our social life. One of the important questions in entrepreneurship is how to find good quality entrepreneurial opportunities. Previous researches suggested that characteristics of entrepreneurs such as their prior experiences, social capitals, and professional skills may influence the consequence of entrepreneurial opportunities finding. This research will introduce a more dynamic perspective to explain the influencing factor of the entrepreneurial opportunities finding. During the decision making process, some behaviors of team members such (...) as joint decision making and constructive controversy may help decision makers understand key issues more comprehensive and decrease the risk come from uncertainties. Besides, this research also takes the differention of industries’ environmental dynamism into consideration. Thus, we can observe the internal and external effect at the same time. (shrink)

The aim of this exploratory paper is to review an under-appreciated parallel between group agency and artificial intelligence. As both phenomena involve non-human goal-directed agents that can make a difference to the social world, they raise some similar moral and regulatory challenges, which require us to rethink some of our anthropocentric moral assumptions. Are humans always responsible for those entities’ actions, or could the entities bear responsibility themselves? Could the entities engage in normative reasoning? Could they even have (...) rights and a moral status? I will tentatively defend the (increasingly widely held) view that, under certain conditions, artificial intelligent systems, like corporate entities, might qualify as responsible moral agents and as holders of limited rights and legal personhood. I will further suggest that regulators should permit the use of autonomous artificial systems in high-stakes settings only if they are engineered to function as moral (not just intentional) agents and/or there is some liability-transfer arrangement in place. I will finally raise the possibility that if artificial systems ever became phenomenally conscious, there might be a case for extending a stronger moral status to them, but argue that, as of now, this remains very hypothetical. (shrink)

In a very short time, it is likely that we will identify many of the genetic variants underlying individual differences in intelligence. We should be prepared for the possibility that these variants are not distributed identically among all geographic populations, and that this explains some of the phenotypic differences in measured intelligence among groups. However, some philosophers and scientists believe that we should refrain from conducting research that might demonstrate the (partly) genetic origin of group differences in (...) IQ. Many scholars view academic interest in this topic as inherently morally suspect or even racist. The majority of philosophers and social scientists take it for granted that all population differences in intelligence are due to environmental factors. The present paper argues that the widespread practice of ignoring or rejecting research on intelligence differences can have unintended negative consequences. Social policies predicated on environmentalist theories of group differences may fail to achieve their aims. Large swaths of academic work in both the humanities and social sciences assume the truth of environmentalism and are vulnerable to being undermined. We have failed to work through the moral implications of group differences to prepare for the possibility that they will be shown to exist. (shrink)

Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is about (...) fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market. As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions. (shrink)

The emergence of collective intelligence has been studied in much greater detail in small groups than in larger ones. Nevertheless, in groups of several hundreds or thousands of members, it is well-known that the social environment exerts a considerable influence on individual behavior. A few recent papers have dealt with some aspects of large group situations, but have not provided an in-depth analysis of the role of interactions among the members of a group in the creation of (...) ideas, as well as the group’s overall performance. In this study, we report an experiment where a large set of individuals, i.e., 789 high-school students, cooperated online in real time to solve two different examinations on a specifically designed platform (Thinkhub). Our goal of this paper 6 to describe the specific mechanisms of idea creation we were able to observe and to measure the group’s performance as a whole. When we deal with communication networks featuring a large number of interacting entities, it seems natural to model the set as a complex system by resorting to the tools of statistical mechanics. Our experiment shows how an interaction in small groups that increase in size over several phases, leading to a final phase where the students are confronted with the most popular answers of the previous phases, is capable of producing high-quality answers to all examination questions, whereby the last phase plays a crucial role. Our experiment likewise shows that a group’s performance in such a task progresses in a linear manner in parallel with the size of the group. Finally, we show that the controlled interaction and dynamics foreseen in the system can reduce the spread of “fake news” within the group. (shrink)

This article investigates National Defense Education Act and National Defense Education Act-related calls in the late 1950s for the training of guidance counselors, an emergent profession that was to play an instrumental role in both the measuring and placement of students in schools by “intelligence” or academic “ability”. In analyzing this mid-century push for more guidance counseling in schools, this article will first explore a foundational argument for the fairness of intelligence testing made by Educational Testing Service psychometrician (...) William Turnbull in 1951, and then later taken up and employed by other National Defense Education Act-era advocates of testing and grouping. Secondly, this analysis will proceed to National Defense Education Act expert testimony, examining here assertions of the necessity of guidance counseling in schools, and an emergent and shared vision articulating the role guidance counseling was supposed to play in school life. A pattern or structure to this vision emerges here. According to its advocates, guidance counseling would not only inform the self-understanding of the measured individual, but it would also work to condition the ideology of individual intelligence across numerous layers of social life around the student: through peer group, through teachers and school administrators, and finally through home, family, and the wider community. (shrink)

In this paper, we approach the idea of group cognition from the perspective of the “extended mind” thesis, as a special case of the more general claim that systems larger than the individual human, but containing that human, are capable of cognition (Clark, 2008; Clark & Chalmers, 1998). Instead of deliberating about “the mark of the cognitive” (Adams & Aizawa, 2008), our discussion of group cognition is tied to particular cognitive capacities. We review recent studies of group (...) problem-solving and group memory which reveal that specific cognitive capacities that are commonly ascribed to individuals are also aptly ascribed at the level of groups. These case studies show how dense interactions among people within a group lead to both similarity-inducing and differentiating dynamics that affect the group's ability to solve problems. This supports our claim that groups have organization-dependent cognitive capacities that go beyond the simple aggregation of the cognitive capacities of individuals. Group cognition is thus an emergent phenomenon in the sense of Wimsatt (1986). We further argue that anybody who rejects our strategy for showing that cognitive properties can be instantiated at multiple levels in the organizational hierarchy on a priori grounds is a “demergentist,” and thus incurs the burden of proof for explaining why cognitive properties are “stuck” at a certain level of organizational structure. Finally, we show that our analysis of group cognition escapes the “coupling-constitution” charge that has been leveled against the extended mind thesis (Adams & Aizawa, 2008). (shrink)

The evolution of Intelligent Tutoring System (ITS) is the result of the amount of research in the field of education and artificial intelligence in recent years. English is the third most common languages in the world and also is the internationally dominant in the telecommunications, science and trade, aviation, entertainment, radio and diplomatic language as most of the areas of work now taught in English. Therefore, the demand for learning English has increased. In this paper, we describe the design (...) of an Intelligent Tutoring System for teaching English language grammar to help students learn English grammar easily and smoothly. The system provides all topics of English grammar and generates a series of questions automatically for each topic for the students to solve. The system adapts with all the individual differences of students and begins gradually with students from easier to harder level. The intelligent tutoring system was given to a group of students of all age groups to try it and to see the impact of the system on students. The results showed a good satisfaction of the students toward the system. (shrink)

Increasing concerns have been raised regarding artificial intelligence (AI) bias, and in response, efforts have been made to pursue AI fairness. In this paper, we argue that the idea of structural injustice serves as a helpful framework for clarifying the ethical concerns surrounding AI bias—including the nature of its moral problem and the responsibility for addressing it—and reconceptualizing the approach to pursuing AI fairness. Using AI in healthcare as a case study, we argue that AI bias is a form (...) of structural injustice that exists when AI systems interact with other social factors to exacerbate existing social inequalities, making some groups of people more vulnerable to undeserved burdens while conferring unearned benefits to others. The goal of AI fairness, understood this way, is about pursuing a more just social structure with the development and usage of AI systems when appropriate. We further argue that all participating agents in the unjust social structure associated with AI bias bear a shared responsibility to join collective action with the goal of reforming the social structure, and we provide a list of practical recommendations for agents in various social positions to contribute to this collective action. (shrink)

This research investigates the efficacy of business ethics intervention, tests a theoretical model that the love of money is directly or indirectly related to propensity to engage in unethical behavior (PUB), and treats college major (business vs. psychology) and gender (male vs. female) as moderators in multi-group analyses. Results suggested that business students who received business ethics intervention significantly changed their conceptions of unethical behavior and reduced their propensity to engage in theft; while psychology students without intervention had no (...) such changes. Therefore, ethics training had some impacts on business students' learning and education (intelligence). For our theoretical model, results of the whole sample (N = 298) revealed that Machiavellianism (measured at Time 1) was a mediator of the relationship between the love of money (measured at Time 1) and unethical behavior (measured at Time 2) (the Love of Money → Machiavellianism → Unethical Behavior). Further, this mediating effect existed for business students (n = 198) but not for psychology students (n = 100), for male students (n = 165) but not for female students (n = 133), and for male business students (n = 128) but not for female business students (n = 70). Moreover, when examined alone, the direct effect (the Love of Money → Unethical Behavior) existed for business students but not for psychology students. We concluded that a short business ethics intervention may have no impact on the issue of virtue (wisdom). (shrink)

In the development of governmental policy for artificial intelligence that is informed by ethics, one avenue currently pursued is that of drawing on “AI Ethics Principles”. However, these AI Ethics Principles often fail to be actioned in governmental policy. This paper proposes a novel framework for the development of ‘Actionable Principles for AI’. The approach acknowledges the relevance of AI Ethics Principles and homes in on methodological elements to increase their practical implementability in policy processes. As a case study, (...) elements are extracted from the development process of the Ethics Guidelines for Trustworthy AI of the European Commission’s “High Level Expert Group on AI”. Subsequently, these elements are expanded on and evaluated in light of their ability to contribute to a prototype framework for the development of 'Actionable Principles for AI'. The paper proposes the following three propositions for the formation of such a prototype framework: preliminary landscape assessments; multi-stakeholder participation and cross-sectoral feedback; and, mechanisms to support implementation and operationalizability. (shrink)

Although personal and group recommendation systems have been quickly developed recently, challenges and limitations still exist. In particular, users constantly explore new items and change their preferences throughout time, which causes difficulties in building accurate user profiles and providing precise recommendation outcomes. In this context, this study addresses the time awareness of the user preferences and proposes a hybrid recommendation approach for both individual and group recommendations to better meet the user preference changes and thus improve the recommendation (...) performance. The experimental results show that the proposed approach outperforms several baseline algorithms in terms of precision, recall, novelty, and diversity, in both personal and group recommendations. Moreover, it is clear that the recommendation performance can be largely improved by capturing the user preference changes in the study. These findings are beneficial for increasing the understanding of the user dynamic preference changes in building more precise user profiles and expanding the knowledge of developing more effective and efficient recommendation systems. (shrink)

Talk of group minds has arisen in a number of distinct traditions, such as in sociological thinking about the “madness of crowds” in the 19th-century, and more recently in making sense of the collective intelligence of social insects, such as bees and ants. Here we provide an analytic framework for understanding a range of contemporary appeals to group minds and cognate notions, such as collective agency, shared intentionality, socially distributed cognition, transactive memory systems, and group-level cognitive (...) adaptations. (shrink)

Harms and risks to groups and third-parties can be significant in the context of research, particularly in data-centric studies involving genomic, artificial intelligence, and/or machine learning technologies. This article explores whether and how United States federal regulations should be adapted to better align with current ethical thinking and protect group interests. Three aspects of the Common Rule deserve attention and reconsideration with respect to group interests: institutional review board (IRB) assessment of the risks/benefits of research; disclosure requirements (...) in the informed consent process; and criteria for waivers of informed consent. In accordance with respect for persons and communities, investigators and IRBs should systematically consider potential group harm when designing and reviewing protocols, respectively. Research participants should be informed about any potential group harm in the consent process. We call for additional public discussion, empirical research, and normative analysis on these issues to determine the right regulatory and policy path forward. (shrink)

PurposeThis paper aims to demonstrate the relevance of worldviews of the global south to debates of artificial intelligence, enhancing the human rights debate on artificial intelligence (AI) and critically reviewing the paper of UNESCO Commission on the Ethics of Scientific Knowledge and Technology (COMEST) that preceded the drafting of the UNESCO guidelines on AI. Different value systems may lead to different choices in programming and application of AI. Programming languages may acerbate existing biases as a people’s worldview is (...) captured in its language. What are the implications for AI when seen from a collective ontology? Ubuntu (I am a person through other persons) starts from collective morals rather than individual ethics.Design/methodology/approachLiterature overview on the African philosophy of Ubuntu as applied to artificial intelligence. Application of it to the United Nations Educational, Scientific and Cultural Organisation (UNESCO) debates on establishing guidelines to the ethics of artificial intelligence.FindingsMetaphysically, Ubuntu and its conception of social personhood (attained during one’s life) largely rejects transhumanism. When confronted with economic choices, Ubuntu favors sharing above competition and thus an anticapitalist logic of equitable distribution of AI benefits, humaneness and nonexploitation. When confronted with issues of privacy, Ubuntu emphasizes transparency to group members, rather than individual privacy, yet it calls for stronger (group privacy) protection. In democratic terms, it promotes consensus decision-making over representative democracy. Certain applications of AI may be more controversial in Africa than in other parts of the world, like care for the elderly, that deserve the utmost respect and attention, and which builds moral personhood. At the same time, AI may be helpful, as care from the home and community is encouraged from an Ubuntu perspective. The report on AI and ethics of the UNESCO World COMEST formulated principles as input, which are analyzed from the African ontological point of view. COMEST departs from “universal” concepts of individual human rights, sustainability and good governance which are not necessarily fully compatible with relatedness, including future and past generations. Next to rules based approaches, which may hamper diversity, bottom-up approaches are needed with intercultural deep learning algorithms.Research limitations/implicationsThere is very few existing literature on AI and Ubuntu. Therefore, this paper is of an explorative nature.Practical implicationsThe ethics of Ubuntu offers unique vantage points in looking at the organization of society and economics today, which are also relevant for development of AI, especially in its tenet of relatedness rather than individuality (and practical use of AI for individuals), taking responsibility for society as a whole (such as analyzing the benefit of AI for all strata of society), and embodying true inclusiveness. Whether looking at top-down guidelines for the development and implementation of AI or the bottom-up ethical learning process of AI (deep learning), ethics of the Global South can have an important role to play to combat global individualist tendencies and inequity, likely reinforced by AI. This warrants far more research.Social implicationsApplications of AI in Africa are not contextualized, do not address the most pressing needs of the African continent, lead to cybersecurity issues and also do not incorporate African ethics. UNESCO’s work in this regard is important but expert inputs are largely centered around Western “universal” principles and Organisation for Economic Cooperation and Development and EU precedence. African ethics have, so far, a small role to play in global ethics and philosophy and therefore risk to be overlooked in the discussion on AI and ethics. This is why the consultation process of UNESCO on ethics of AI was of paramount importance. However, it does not automatically lead to consultation of African philosophers or sages, as many are educated in Western (ized) education systems. See further details under practical implications.Originality/valueThis is a new area of research in which little work has been done so far. This paper offers the opportunity to widen the debate on AI and ethics beyond the conventional discourse, involving multiple worldviews, of which Ubuntu is just one. (shrink)

This paper discusses two opposing views about the relation between artificial intelligence (AI) and human intelligence: on the one hand, a worry that heavy reliance on AI technologies might make people less intelligent and, on the other, a hope that AI technologies might serve as a form of cognitive enhancement. The worry relates to the notion that if we hand over too many intelligence-requiring tasks to AI technologies, we might end up with fewer opportunities to train our (...) own intelligence. Concerning AI as a potential form of cognitive enhancement, the paper explores two possibilities: (1) AI as extending—and thereby enhancing—people’s minds, and (2) AI as enabling people to behave in artificially intelligent ways. That is, using AI technologies might enable people to behave as if they have been cognitively enhanced. The paper considers such enhancements both on the level of individuals and on the level of groups. (shrink)

When animals share decisions with others, they pool personal information, offset individual errors and, thereby, increase decision accuracy. This is termed ‘swarm intelligence.’ But what if those decisions involve conflicts of interest between individual decision-makers? Should animals share decisions with individuals whose goals are different from, and partially in conflict with, their own? A group decision model developed by Larissa Conradt and colleagues finds that, contrary to intuition, conflicting goals often increase both decision accuracy and the individual gains (...) derived from shared decisions. Thus, conflicts of interest, far from hampering effective decision making, can actually improve decision outcomes for all stakeholders, as long as they also have some goals in common. By contrast, conflict-free decisions shared by animals which all have the same goals are often surprisingly poor. (shrink)

Emotional intelligence, a set of skills which are considered as necessary in the context of interaction with other people, was defined by a number of authors, including Goleman, Gardner and Mayer & Salovey. A number of studies investigated the impact of emotional intelligence on learning, teaching and education. The focus of this article is to explore the definition of emotional intelligence and the impact that emotional intelligence and affective factors have in the context of foreign language (...) learning and teaching. The article also focuses on research conducted with a group of 23 students and their self assessment of emotional intelligence as well as their perceptions of the ways emotional intelligence has an impact on foreign language learning. The article attempts to provide recommendations of implementing activities and teaching practices in the context of foreign language learning and teaching aiming to foster emotional intelligence development. (shrink)

We describe a novel Internet-based method for building consensus and clarifying con icts in large stakeholder groups facing complex issues, and we use the method to survey and map the scienti c and organizational perspectives of the arti cial life community during the Seventh International Conference on Arti cial Life (summer 2000). The issues addressed in this survey included arti cial life’s main successes, main failures, main open scienti c questions, and main strategies for the future, as well as the (...) bene ts and pitfalls of creating a professional society for arti cial life. By illuminating the arti cial life community’s collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups. (shrink)

Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation of (...) the ITS was done by a group of students and teachers. The results were acceptable. (shrink)

In this paper we show how a student can learn the basics of the system databases using (W3school CSS) which was built as intelligent tutoring educational system by using the authoring tool called (ITSB). The learning material contains CSS and HTML. We divided the material in a group of lessons for novice learner which combines relational system and lessons in the process of learning. The student can learn using example of CSS, and types of CSS color. Furthermore, the intelligent (...) tutoring system supports not only lessons; but exercises of different difficult levels for each lesson. When a student finish successfully the first difficulty level in a lesson, the student is allowed to move to the next difficulty level of the exercises of the lesson. (shrink)

In Study 1, we test a theoretical model involving temptation, monetary intelligence (MI), a mediator, and unethical intentions and investigate the direct and indirect paths simultaneously based on multiple-wave panel data collected in open classrooms from 492 American and 256 Chinese students. For the whole sample, temptation is related to low unethical intentions indirectly. Multi-group analyses reveal that temptation predicts unethical intentions both indirectly and directly for male American students only; but not for female American students. For Chinese (...) students, both paths are non-significant. Love of money contributes significantly to MI for all students. In Study 2, using money as a temptation and giving them opportunities to cheat on a matrix task, most Chinese students (78.4 %) do not cheat in open classrooms; supporting survey and structural equation modeling (SEM) results in Study 1. However, students in private cubicles cheat significantly more (53.4 %) than those in open classrooms (21.6 %). Finally, students’ love of money attitude predicts cheating. Factor rich predicts the cheating amount, whereas factor motivator predicts the cheating percentage. Our results shed new light on the impact of temptation and love of money as dispositional traits, money as a temptation, and environmental context (public vs. private) on unethical intentions and cheating behaviors. (shrink)

Recently, Intelligent Tutoring Systems (ITS) got much attention from researchers even though ITS educational technology began in the late 1960s and ITS is just embryonic from laboratories into the field. In this paper we outline an intelligent tutoring system for teaching basics of the databases system called (MDB). The MDB was built as education system by using the authoring tool (ITSB). MDB contains learning materials as a group of lessons for beginner level which include relational database system and lessons (...) in the process to install and set up a database. MDB system has exams for each level of the Lessons. An evaluation was done to see the effectiveness the MDB among learners and instructors. The outcome of the evaluation was promising. (shrink)

This paper argues that the Value Sensitive Design (VSD) methodology provides a principled approach to embedding common values in to AI systems both early and throughout the design process. To do so, it draws on an important case study: the evidence and final report of the UK Select Committee on Artificial Intelligence. This empirical investigation shows that the different and often disparate stakeholder groups that are implicated in AI design and use share some common values that can be used (...) to further strengthen design coordination efforts. VSD is shown to be both able to distill these common values as well as provide a framework for stakeholder coordination. (shrink)

Tennis players have more physical training content, and the training items are complex. For athletes, training programs that adapt to their individual characteristics should be formulated according to their physical characteristics. The current development of big data has brought about changes in thinking, management, and business models. The combination of complex systems and big data can also make breakthroughs in the sports field. Based on this, this article proposes a tennis player training schedule intelligent formulation system based on complex system (...) big data. First of all, this article adopts the literature data method, comparative analysis method, experimental analysis method, etc., in-depth study of the concepts of big data, complex system, and the physical structure characteristics of tennis sports. This paper designs an intelligent system for making tennis players’ training schedule, which collects, transforms, and integrates tennis training data through the characteristics of big data. Then, the dynamic time regulation of tennis is performed through a complex system, and finally, the experimental system is analyzed. This article mainly analyzes the comparison of physical indicators between the experimental group and the control group before and after the experiment, the evaluation indicators of sports events, the strength training effects of tennis events, and the analysis of shoulder joint tests. There is no significant difference between the experimental group and the control group in the items before the experiment, P > 0.05, which suggests that the physical fitness of the two groups of athletes is similar; in the posttest data, the experimental group and the control group have significant differences, P < 0.05, indicating an effect from the experiment. In particular, in fan running, forward and backward strokes, and the serve, the scores of the experimental group were higher than those of the control group, indicating that the use of the formulated training system demonstrated significant results. (shrink)

The study of collective intelligence has focused in the last years on crowdsourcing and artificial swarm intelligence. Currently, large online communities have demonstrated their effectiveness but even if the contributions in this domain are significant, it remains essential to question the functioning of collective intelligence in small groups, especially since the gain in popularity of brainstorming strategies, focus groups and co-working practices. In this context, we conducted a qualitative systematic review using Prospero, PRISMA protocol and bias assessment (...) to identify the factors currently recognised as impacting on the emergence of collective intelligence in small groups. These factors were then organised according to the different levels of abstraction observed in research about collective intelligence. From this work, collective intelligence appears as the crystallization of emerging properties that manifest themselves in interactions and whose possibility of existing is intrinsically linked to meta-cognition and meta-communication processes. (shrink)

Artificial intelligence is becoming part of our everyday experience and is expected to be ever more integrated into ordinary life for many years to come. Thus, it is important for those in product development, research, and public policy to understand how the public’s perception of AI is shaped. In this study, we conducted focus groups and an online survey to determine the knowledge of AI held by the American public, and to judge whether entertainment media is a major influence (...) on how Americans perceive AI. What we found is that the American public’s knowledge of AI is patchy: some have a good understanding of what is and what is not AI, but many do not. When it came to understanding what AI can do, most respondents believe that AI could “replace human jobs” but few thought that it could “feel emotion.” Most respondents were optimistic about the future and impact of AI, though about one third were not sure. Most respondents also did not think they could develop an emotional bond with or be comfortable being provided care by an AI. Regarding the influence of entertainment media on perceptions of AI, we found a significant relationship between people’s beliefs about AI in entertainment media and their beliefs about AI in reality. Those who believe AI is realistically depicted in entertainment media were more likely to see AIs as potential emotional partners or apocalyptic robots than to imagine AIs taking over jobs or operating as surveillance tools. (shrink)

The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This paper discusses several topics that relate more naturally to groups of papers than a single paper published in the journal: ontologies, reasoning about evidence, the various contributions of Douglas Walton, and the practical application of the techniques of AI and Law.

The first issue of _Artificial Intelligence and Law_ journal was published in 1992. This special issue marks the 30th anniversary of the journal by reviewing the progress of the field through thirty commentaries on landmark papers and groups of papers from that journal.

Group size is a function of relative neocortical volume in nonhuman primates. Extrapolation from this regression equation yields a predicted group size for modern humans very similar to that of certain hunter-gatherer and traditional horticulturalist societies. Groups of similar size are also found in other large-scale forms of contemporary and historical society. Among primates, the cohesion of groups is maintained by social grooming; the time devoted to social grooming is linearly related to group size among the Old (...) World monkeys and apes. To maintain the stability of the large groups characteristic of humans by grooming alone would place intolerable demands on time budgets. It is suggested that (1) the evolution of large groups in the human lineage depended on the development of a more efficient method for time-sharing the processes of social bonding and that (2) language uniquely fulfills this requirement. Data on the size of conversational and other small interacting groups of humans are in line with the predictions for the relative efficiency of conversation compared to grooming as a bonding process. Analysis of a sample of human conversations shows that about 60% of time is spent gossiping about relationships and personal experiences. It is suggested that language evolved to allow individuals to learn about the behavioural characteristics of other group members more rapidly than is possible by direct observation alone. (shrink)

Monetary Intelligence theory asserts that individuals apply their money attitude to frame critical concerns in the context and strategically select certain options to achieve financial goals and ultimate happiness. This study explores the bright side of Monetary Intelligence and behavioral economics, frames money attitude in the context of pay and life satisfaction, and controls money at the macro-level and micro-level. We theorize: Managers with low love of money motive but high stewardship behavior will have high subjective well-being: pay (...) satisfaction and quality of life. Data collected from 6586 managers in 32 cultures across six continents support our theory. Interestingly, GDP per capita is related to life satisfaction, but not to pay satisfaction. Individual income is related to both life and pay satisfaction. Neither GDP nor income is related to Happiness. Our theoretical model across three GDP groups offers new discoveries: In high GDP entities, “high income” not only reduces aspirations—“Rich, Motivator, and Power,” but also promotes stewardship behavior—“Budget, Give/Donate, and Contribute” and appreciation of “Achievement.” After controlling income, we demonstrate the bright side of Monetary Intelligence: Low love of money motive but high stewardship behavior define Monetary Intelligence. “Good apples enjoy good quality of life in good barrels.” This notion adds another explanation to managers’ low magnitude of dishonesty in entities with high Corruption Perceptions Index. In low GDP entities, high income is related to poor Budgeting skills and escalated Happiness. These managers experience equal satisfaction with pay and life. We add a new vocabulary to the conversation of monetary intelligence, income, GDP, happiness, subjective well-being, good and bad apples and barrels, corruption, and behavioral ethics. (shrink)

Organizations such as the EU High-Level Expert Group on AI and the IEEE have recently formulated ethical principles and (moral) values that should be adhered to in the design and deployment of artificial intelligence (AI). These include respect for autonomy, non-maleficence, fairness, transparency, explainability, and accountability. But how can we ensure and verify that an AI system actually respects these values? To help answer this question, I propose an account for determining when an AI system can be said (...) to embody certain values. This account understands embodied values as the result of design activities intended to embed those values in such systems. AI systems are here understood as a special kind of sociotechnical system that, like traditional sociotechnical systems, are composed of technical artifacts, human agents, and institutions but—in addition—contain artificial agents and certain technical norms that regulate interactions between artificial agents and other elements of the system. The specific challenges and opportunities of embedding values in AI systems are discussed, and some lessons for better embedding values in AI systems are drawn. (shrink)

Cognitive science has been traditionally organized around the individual as the basic unit of cognition. Despite developments in areas such as communication, human–machine interaction, group behavior, and community organization, the individual-centric approach heavily dominates both cognitive research and its application. A promising direction for cognitive science is the study of augmented intelligence, or the way social and technological systems interact with and extend individual cognition. The cognitive science of augmented intelligence holds promise in helping society tackle major (...) real-world challenges that can only be discovered and solved by teams made of individuals and machines with complementary skills who can productively collaborate with each other. (shrink)

Artificial Intelligence technology presents a multitude of ethical concerns, many of which are being actively considered by organizations ranging from small groups in civil society to large corporations and governments. However, it also presents ethical concerns which are not being actively considered. This paper presents a broad overview of twelve topics in ethics in AI, including function, transparency, evil use, good use, bias, unemployment, socio-economic inequality, moral automation and human de-skilling, robot consciousness and rights, dependency, social-psychological effects, and spiritual (...) effects. Each of these topics will be given a brief discussion, though each deserves much deeper consideration. (shrink)

Benjamin Franklin famously wrote that “the good [that] men do separately is small compared with what they may do collectively” (Isaacson 2004). The ability to join with others in groups to accomplish goals collectively that would hopelessly overwhelm the time, energy, and resources of individuals is indeed one of the greatest assets of our species. In the history of humankind, groups have been among the greatest workers, builders, producers, protectors, entertainers, explorers, discoverers, planners, problem-solvers, and decision-makers. During the late 19th (...) and early 20th century, many social scientists employed the notorious “group mind” idiom to express the sensible idea that groups can function as the seats of cognition, intelligence, and agency in their own right (Allport 1968; Wilson 2004). In their quest to stress (rightly) that group phenomena are something “over and above” the sum of individual contributions, a fondness for vitalist metaphors led them to believe (wrongly) that genuine group cognition must be the result of tapping into individualistically inaccessible, “holistic” forces. Today, inspired in part by historically unparalleled forms of mass collaboration enabled by the internet, it has once again become popular to speak of collective intelligence, group agency, or even the emergence of a “global brain” (cf. the wiki-edited MIT Handbook of Collective Intelligence). -/- In this chapter, I review some contemporary developments of the idea of group cognition, defined broadly as the collaborative performance of cognitive tasks such as remembering, problem-solving, decision-making, or verbal creativity for the purpose of producing a group-level outcome. My discussion serves a two-fold purpose. First, by discussing how the idea of group cognition can be operationalized, I seek to show that we can retain some central theoretical insights of the “group mind” thesis without succumbing to its eccentric metaphysical overtones. Second, by providing a useful array of generalizable taxonomic resources, I hope to foster greater degrees of mutual awareness among insufficiently integrated areas of research on group performance. (shrink)

Sequential transformative design of research :224–235, 2015; Groleau et al. in J Mental Health 16:731–741, 2007; Robson and McCartan in Real world research: a resource for users of social research methods in applied settings, Wiley, Chichester, 2016) allows testing a group of theoretical assumptions about the connections of artificial intelligence with culture and education. In the course of research, semiotics ensures the description of self-organizing systems of cultural signs and symbols in terms of artificial intelligence as a (...) special set of algorithms. This approach helps to consider the arguments proposed by Searle :417–457, 1980) against ‘strong’ artificial intelligence. Searle :417–457, 1980) believes that artificial or machine intelligence cannot fully emulate the processes of the human mind. Machine intelligence shows own inevitable weakness. This is non-autonomous tool for computations and data operating. In fact, this tool cannot provide insight into real cognitive conditions. After Lotman and Uspensky, authors expand the meaning of artificial intelligence. The authors identify a cultural type of ‘strong’ artificial intelligence or ‘self-increase of Logos’ in terms by Lotman and Uspensky. The interpretation of human intelligence as imitation of machine intelligence makes possible such immersion of artificial intelligence in culture. The authors reveal a case of self-organizing autonomous generation, encoding, decoding, reception, storage, and transmission of social information in the field of physical training. From the empirical studies it is clear that the organization of collective activities without external control ensures the development of positive emotions and social orientations. Interest in autonomous behavior provides the formation of educational and cognitive motives. As a special set of algorithms, these motives are the most promising and favorable for personal development. (shrink)

Harms and risks to groups and third-parties can be significant in the context of research, particularly in data-centric studies involving genomic, artificial intelligence, and/or machine learning technologies. This article explores whether and how United States federal regulations should be adapted to better align with current ethical thinking and protect group interests. Three aspects of the Common Rule deserve attention and reconsideration with respect to group interests: institutional review board (IRB) assessment of the risks/benefits of research; disclosure requirements (...) in the informed consent process; and criteria for waivers of informed consent. In accordance with respect for persons and communities, investigators and IRBs should systematically consider potential group harm when designing and reviewing protocols, respectively. Research participants should be informed about any potential group harm in the consent process. We call for additional public discussion, empirical research, and normative analysis on these issues to determine the right regulatory and policy path forward. (shrink)