This paper endeavors to appraise scholarly works from the 1940s to the contemporary era, examining the scientific quest to transpose human cognition and consciousness into a digital surrogate, while contemplating the potential ramifications should humanity attain such an abstract level of intellect. The discourse commences with an explication of theories concerning consciousness, progressing to the Turing Test apparatus, and intersecting with Damasio’s research on the human cerebrum, particularly in relation to consciousness, thereby establishing congruence between the Turing Test and Damasio’s (...) notions of consciousness. Subsequently, the narrative traverses the evolutionary chronology of transmuting human cognition into machine sapience, and delves into the fervent endeavors to metamorphose human minds into synthetic counterparts. Additionally, theoretical perspectives from the domains of philosophy, psychology, and neuroscience provide insight into the constraints intrinsic to AI implementations, contentious hypotheses, the perils concealed within artificial networks, and the ethical considerations necessitated by AI frameworks. Furthermore, contemplation of prospective repercussions facilitates the refinement of strategic approaches to safeguard our future Augmented Age Realities within AI, circumventing the prospect of inhabiting an intimidating technopolis where a mere 30% monopolize the intellect and ingenuity of the remaining 70% of human minds. (shrink)

The recent proliferation of AI scandals led private and public organisations to implement new ethics guidelines, introduce AI ethics boards, and list ethical principles. Nevertheless, some of these efforts remained a façade not backed by any substantive action. Such behaviour made the public question the legitimacy of the AI industry and prompted scholars to accuse the sector of ethicswashing, machinewashing, and ethics trivialisation—criticisms that spilt over to institutional AI ethics boards. To counter this widespread issue, contributions in the literature have (...) proposed fixes that do not consider its systemic character and are based on a top-down, expert-centric governance. To fill this gap, we propose to make use of qualified informed lotteries: a two-step model that transposes the documented benefits of the ancient practice of sortition into the selection of AI ethics boards’ members and combines them with the advantages of a stakeholder-driven, participative, and deliberative bottom-up process typical of Citizens’ Assemblies. The model permits increasing the public’s legitimacy and participation in the decision-making process and its deliverables, curbing the industry’s over-influence and lobbying, and diminishing the instrumentalisation of ethics boards. We suggest that this sortition-based approach may provide a sound base for both public and private organisations in smart societies for constructing a decentralised, bottom-up, participative digital democracy. (shrink)

In this 60th anniversary of Business & Society essay, we seek to make three main contributions at the intersection of governance and artificial intelligence. First, we aim to illuminate some of the deeper social, legal, organizational, and democratic challenges of rising AI adoption and resulting algorithmic power by reviewing AI research through a governance lens. Second, we propose an AI governance framework that aims to better assess AI challenges as well as how different governance modalities can support AI. At the (...) heart of our framework lies the governance forces that apply to institutions, organizations, and individuals, who ultimately provide, regulate, and use AI decision-making. We discuss how businesses may harness AI’s economic power through governance solutions without creating or amplifying societal biases and inequalities. Third, as part of our section on future research, we identify a set of governance trade-offs in AI adoption, suggest future research avenues to conceptually strengthen research on the governance of AI, and lay out key policy recommendations. (shrink)

The ethics of artificial intelligence is a widely discussed topic. There are numerous initiatives that aim to develop the principles and guidance to ensure that the development, deployment and use of AI are ethically acceptable. What is generally unclear is how organisations that make use of AI understand and address these ethical issues in practice. While there is an abundance of conceptual work on AI ethics, empirical insights are rare and often anecdotal. This paper fills the gap in our current (...) understanding of how organisations deal with AI ethics by presenting empirical findings collected using a set of ten case studies and providing an account of the cross-case analysis. The paper reviews the discussion of ethical issues of AI as well as mitigation strategies that have been proposed in the literature. Using this background, the cross-case analysis categorises the organisational responses that were observed in practice. The discussion shows that organisations are highly aware of the AI ethics debate and keen to engage with ethical issues proactively. However, they make use of only a relatively small subsection of the mitigation strategies proposed in the literature. These insights are of importance to organisations deploying or using AI, to the academic AI ethics debate, but maybe most valuable to policymakers involved in the current debate about suitable policy developments to address the ethical issues raised by AI. (shrink)

Applications of artificial intelligence (AI) bear great transformative potential in the economic, technological and social sectors, impacting especially future work environments. Ethical regulation of AI requires a relational understanding of the technology by relevant stakeholder groups such as researchers, developers, politicians, civil servants, affected workers or other users applying AI in their work processes. The purpose of this paper is to support relational AI discourse for an improved ethical framing and regulation of the technology. The argumentation emphasizes a widespread reembodied (...) understanding of AI technology as critical requirement for capable ethical and regulatory frameworks. A sociotechnical perspective encourages the material interpretation of AI as reembodied adaptation of biological intelligence. Reviewing Cartesian dualism as motivating the disembodiment of human intelligence for its transfer to machines, the argumentation develops an integrated embodiment concept of AI in its mechanistic, naturalistic, combined AI and neuroethical, and relational contexts. This concept is discussed in relation to basic phenomenological and postphenomenological assumptions, and is applied to the example of AI-based neurotechnology potentially disrupting future work processes. Strengthening a human-centered approach, the presented concept for a reembodied understanding of AI technology enables better integrated ethical and regulatory debates, and improves social discourse and human agency in developing and regulating AI technology. (shrink)

The popularization of intelligent machines such as service robot and industrial robot will make human–machine interaction, an essential work mode. This requires employees to adapt to the new work content through learning. However, the research involved human–machine interaction that how influences the employee’s learning is still rarely. This paper was to reveal the relationship between human–machine interaction and employee’s learning from the perspective of job characteristics and competence perception of employees. We sent questionnaire to 500 employees from 100 artificial intelligence (...) companies in China and received 319 valid and complete responses. Then, we adopted a hierarchical regression for the test. Empirical results show that human–machine interaction has a U-shaped curvilinear relationship with employee learning, and employee’s vitality mediates the curvilinear relationship. In addition, job characteristics moderate the U-shaped curvilinear relationship between human–machine interaction and employee’s vitality, especially the results of moderating effects varying with employee’s competence perception. Exploring the mechanism of the effect of human–machine interaction on employee’s learning enriches the socially embedded model. Moreover, it provides managerial implications how to enhance individual adaptability with the introduction of AI into firms. However, our research focuses more on the impact of human–machine interaction on employees at the initial stage of AI development, and the level of machine intelligence in various industries will reach a high degree of autonomy in the future. The future research can explore the impact of human–machine interaction on individual’s behavior at different stages, and the results may vary depending on the technologies mastered by different individuals. The study has theoretical and practical significance to human–machine interaction literature by underscoring the important of individual’s behavior among individuals with different skills. (shrink)

Social development organizations increasingly employ artificial intelligence -enabled tools to help team members collaborate effectively and efficiently. These tools are used in various team management tasks and activities. Based on the unified theory of acceptance and use of technology, this study explores various factors influencing employees’ use of AI-enabled tools. The study extends the model in two ways: a) by evaluating the impact of these tools on the employees’ collaboration and b) by exploring the moderating role of AI aversion. Data (...) were collected through an online survey of employees working with AI-enabled tools. The analysis of the research model was conducted using partial least squares, with a two-step model – measurement and structural models of assessment. The results revealed that the antecedent variables, such as effort expectancy, performance expectancy, social influence, and facilitating conditions, are positively associated with using AI-enabled tools, which have a positive relationship with collaboration. It also concluded a significant effect of AI aversion in the relationship between performance expectancy and use of technology. These findings imply that organizations should focus on building an environment to adopt AI-enabled tools while also addressing employees’ concerns about AI. (shrink)

The popular debates about the future organization of work through artificial intelligence technologies focus on the replacement of human beings by novel technologies. In this essay, we oppose this statement by closely following what has been developed as AI technologies and analyzing how they work, specifically focusing on research that may impact work organizations. We develop this argument by showing that the recent research and developments in AI technologies focus on developing accurate and precise performance models, which in turn shapes (...) organizational patterns of work. We propose that the increased interest in the relationship between human cognition and performance will shortly bring human cognition to the focus on AI systems in workplaces. More specifically, we claim that the cognitive load measurement will shape human performance in manufacturing systems shortly. (shrink)

This study investigates the ethical use of Big Data and Artificial Intelligence (AI) technologies (BD + AI)—using an empirical approach. The paper categorises the current literature and presents a multi-case study of 'on-the-ground' ethical issues that uses qualitative tools to analyse findings from ten targeted case-studies from a range of domains. The analysis coalesces identified singular ethical issues, (from the literature), into clusters to offer a comparison with the proposed classification in the literature. The results show that despite the variety (...) of different social domains, fields, and applications of AI, there is overlap and correlation between the organisations’ ethical concerns. This more detailed understanding of ethics in AI + BD is required to ensure that the multitude of suggested ways of addressing them can be targeted and succeed in mitigating the pertinent ethical issues that are often discussed in the literature. (shrink)

Communication programs seek to cultivate students who become professionals not only with expertise in their chosen field, but also ethical awareness. The current study investigates how exposure to ethics instruction and internship experiences may influence communication students’ ethical perceptions, including ideological orientations on idealism and relativism, as well as awareness of contemporary ethical issues related to social media and artificial intelligence (AI). The effects were also assessed on students’ support for general uses of AI for communication practices and adoption of (...) generative AI, specifically ChatGPT. The survey results based on a student sample in Taiwan show that internship experience is more significant than ethics instruction on swaying ethical perceptions and behavioral inclinations of adopting AI applications. Adding to the limited body of knowledge on the effect of ethics education and internship programs, the findings also offer insights for how communication education can address emerging ethical challenges brought by new technology. (shrink)

This essay discusses sentient robot research through the lens of suffering. First three kinds of suffering are considered: physical, psychological, and existential. Physical pain is shown to b...

The burgeoning of new technologies is increasingly affecting people’s lives. One new technology that is heatedly discussed is artificial intelligence in education. To allow students to understand the impact of emerging technologies on people’s future lives from a young age, some popular science activities are being progressively introduced into elementary school curricula. Popular science activities are informal education programs and practices of universal education. However, two issues need to be discussed in the implementation of these activities. First, because these informal (...) curricula are usually short in duration, the question of whether they only serve to generate motivation or actually enhance learning outcomes requires examination. Second, the role of teacher support in popular science activities and its impact on students’ learning results need to be further investigated. To this end, this study aims to explore the effectiveness of popular AI science activities in informal curricula on students’ AI achievement and the interrelationship between students’ learning outcomes in popular AI science activities with and without teacher support. A 6-h-long AI popular science activity was conducted with 22 fifth- and sixth-grade students in elementary school. This study was conducted using a one-group pretest and posttest design, and the data collection tools included AI achievement pre- and posttests and an artifact scoring rubric. The results showed that with regard to learning outcomes, popular science activities were helpful for cognitive enhancement of AI concepts, but more time was needed for skills to improve. Additionally, this study found that students’ learning performance was different with and without teacher support. Activities with teacher support can enhance students’ learning outcomes, but students become accustomed to relying on their teachers. In contrast, activities without teacher support seem to be more effective in fostering students’ independent computational thinking and problem-solving abilities. (shrink)

Several technological developments, such as self-service technologies and artificial intelligence, are disrupting the retailing industry by changing consumption and purchase habits and the overall retail experience. Although AI represents extraordinary opportunities for businesses, companies must avoid the dangers and risks associated with the adoption of such systems. Integrating perspectives from emerging research on AI, morality of machines, and norm activation, we examine how individuals morally behave toward AI agents and self-service machines. Across three studies, we demonstrate that consumers’ moral concerns (...) and behaviors differ when interacting with technologies versus humans. We show that moral intention is less likely to emerge for AI checkout and self-checkout machines compared with human checkout. In addition, moral intention decreases as people consider the machine less humanlike. We further document that the decline in morality is caused by less guilt displayed toward new technologies. The non-human nature of the interaction evokes a decreased feeling of guilt and ultimately reduces moral behavior. These findings offer insights into how technological developments influence consumer behaviors and provide guidance for businesses and retailers in understanding moral intentions related to the different types of interactions in a shopping environment. (shrink)

Inspired by Koselleck’s approach to conceptual history, this essay presents a semantic analysis of management. Our inquiry into what management is, focuses on lingual and cognitive wholes of meaning and signification. The essay undertakes a periodization of management history, in an attempt to formulate expectations for a dystopian future management by artificial intelligence. Five periods are distinguished. Each period entails a specific characterisation for three questions: what is the activity of managing, what or who is managed, and who manages? Starting (...) from managing-by-hand, successive differentiation of meaning occurs with regard to different elements of the management relationship (object, activity, agent), followed by a rescaling of the whole relationship into an attitude that can be applied anywhere by anyone. The implication is a dissociation between manager and decision-maker. The essay also speculates how plausible this evolution makes non-human managers (i.e. artificial intelligence). Throughout these five periods, hierarchy is an immanent feature of management. For each period, the essay discusses differentiated meaning, corresponding social reality and characterizes its hierarchy and justification. (shrink)

Social information processing theory suggests that the chief executive officer’s entrepreneurial orientation is an organisational signal that influences the members’ innovativeness. Middle management teams are expected to be more innovative as they connect senior managers with frontline managers in the dynamic competitive environment of the digital economy. How CEOs guide MMT innovations through EO becomes critical in the process of capturing opportunities and creating value. However, previous research has failed to adequately identify distinct CEO EO manifestations with organisational contexts configurations (...) that influence MMTs innovation. Thus, based on differences in organisational contexts and MMTs’ cognition, this study thoroughly investigates how the vertical manifestation of CEO EO impacts the innovativeness of MMTs. We used fuzzy-set qualitative comparative analysis on a sample of 117 organisations to determine which configurations of CEO EO vertical penetration within an organisation can stimulate MMT innovativeness. The study discovered four first-level configurations that support stimulating MMT innovativeness respectively when the CEO EO is fully or partially manifested, and without the CEO EO. Moreover, we found the internal reasons for MMTs’ information interpretation heterogeneity, which is critical for realising the coordination and unity of entrepreneurial cognition and behaviours. Finally, these findings’ theoretical and practical implications are discussed. (shrink)