Social Machinery and Intelligence

Digital Ecosystems and Technologies (DEST), 2010

Social networks, which until recently were populated exclusively by human actors, are starting to become increasingly populated by artificial agents, which play various roles within them. Thus, they can be viewed as an interesting digital ecosystem, with two qualitatively different kinds of agents: biological as well as artificial. An example of such an artificial agent will be presented, which is in this case physically embodied: Sarah the FaceBot, a conversational mobile robot equipped with a social database and interaction memories. Sarah not only participates within the actual human social network by forming relationships with its physical interaction partners, but is also a member of the FaceBook social networking website, which she automatically queries for information which she uses in her dialogues, and on which she also actively deposits social information. Starting from this example, an extensive discussion of open questions, purposes, and potentialities regarding the introduction of artificial agents within human social networks will take place, exposing multiple avenues towards beneficial application of such agents within the newly arising digital ecosystem of hybrid human-machine social networks.

Proceedings of the AISB Annual Convention , 2017

When Alan Turing proposed the imitation game as a method to investigate the question if machines can think, he described a social system. However, the various disciplines that have pursued this seminal inquiry rarely touch base with sociological concepts. One might be tempted to say that progress has been made on brains, bodies, and on models of minds. I claim that there is something largely missing in this picture, which is the social aspect. To propose an alternative route, I consider Niklas Luhmann's theory of social systems as a suitable foundation for guiding the development of hybrid social systems. A hybrid social system is understood as a social assemblage in which minds and machines mingle: humans, machines, certain things, cyborgs. Some animals are welcome, too.

OSF Preprint, 2025

We must reconsider our relationship with machines as artificial intelligence evolves from task-based support to autonomous or assisted generation. Generation is not creation. Human intelligence–our only known model –is the sole benchmark for evaluating AI. Yet, we lack rigorous comparison standards because we do not fully understand the internal mechanisms of human intelligence. Perhaps it is more appropriate to speak of AI in simplified terms–as something that, under certain conditions, emulates what we commonly perceive as intelligent behavior. But even that remains uncertain. To call a circuit board “intelligent,” in my view, is merely an exercise in measuring how well emulation mimics what we recognize as intelligence, based solely on the only model we know: our own. Let us not forget that we still lack a universally accepted definition of intelligence, let alone a definition of thinking, or even a deeper understanding of the complex nature of consciousness. Let us also remember that over the last 80 years of computing and automation, the dominant discipline for solving problems has not been AI, but engineering. Engineering provides the methodologies, mental models, and validation frameworks we use to design and deploy systems. AI extends this legacy — and at the same time, disrupts it, introducing new epistemic and ethical challenges that cannot be resolved solely through efficiency. This manifesto examines why and how AI must evolve in tandem with human cognition, roles, and ethics. It argues that AI demands more than technical or economic scrutiny—it calls for a philosophical revolution in understanding intelligence, responsibility, and human-machine interaction. At the heart of this transition lies the need to articulate a new intellectual discipline: the Philosophy of the Machines. In a world increasingly divided between the celebration of individual agency amplified by AI tools and the calls for stricter regulatory frameworks to govern “machine autonomy”, the Philosophy of the Machines proposes a third way: a foundational philosophical inquiry into how machines reshape the conditions of thinking, acting, and ethical responsibility itself. This is not a technical manual, nor a speculative vision. It is a conceptual framework designed to reframe the logic of AI adoption, shifting from defining efficiency, value, and oversight to allocating agency in automated systems. The Δ–η–ζ model introduced here is not a turnkey tool but a thinking scaffold — a way to build more realistic, ethical, and human-aligned business cases for AI and GenAI. This manifesto aims to open the debate: • What kind of intelligence are we building? • What kind of humans must we become in response? • And how do we share responsibility with systems we no longer fully control? This manifesto is neither techno-optimistic nor purely regulatory; it is ontological, epistemological, and systemic, offering a new intellectual framework for the Age of Artificial Agents. This manifesto invites reflection on these questions not as an academic exercise, but as a call to reshape the human condition in the age of artificial agents.

Proceedings of the 24th International Conference on World Wide Web

This paper sets out an approach to Social Machines (SMs), their description and analysis, based on a development of social constructionist theoretical principles adapted for Web Science. We argue that currently the search for the primitives of SMs, or appropriate units of analysis to describe them, tends to favour either the technology or sociality. We suggest an approach that favours distributed agency whether it is machinic or human or both. We argue that current thinking (e.g. Actor Network Theory) is unsuited to SMs. Instead we describe an alternative which prioritizes a view of socio-technical activity as forming 'reflexive project structures'. We show that reflexivity in social systems can be further usefully divided into more fundamental elements (Recognition and Responsivity). This process enables us to capture more of the variation in SMs and to distinguish them from non-Web based socio-technical systems. We illustrate the approach by looking at different kinds of SMs showing how they relate to contemporary social theory.

L'Harmattan, 2020

Thanks to the development of the NBIC, man has exterorised his intelligence and developed what has come to be known as Artificial Intelligence (AI). This has contributed in enhancing or ameliorating the living conditions of humanity in one way or the other. Yet, the more man uses the new companions given to him by the High-tech industry, the more he tends to forget his fellow man. His existence is thus more and more mechanised so much so that AI has implications on social life. Examining these implications is the aim of this paper.

Integrative Psychological and Behavioral Science, 2020

Can artificial intelligence (AI) develop the potential to be our partner, and will we be as sensitive to its social signals as we are to those of human beings? I examine both of these questions and how cultural psychology might add such questions to its research agenda. There are three areas in which I believe there is a need for both a better understanding and added perspective. First, I will present some important concepts and ideas from the world of AI that might be beneficial for pursuing research topics focused on AI within the cultural psychology research agenda. Second, there are some very interesting questions that must be answered with respect to central notions in cultural psychology as these are tested through human interactions with AI. Third, I claim that social robots are parasitic to deeply ingrained human social behaviour, in the sense that they exploit and feed upon processes and mechanisms that evolved for purposes that were originally completely alien to human-computer interactions.

Shanlax, 2018

Despite problem-solving ability, the issues bothering artificial intelligence (AI) cause concern to the moral circuits. Questions such as what consequences machines make upon human nature and human nurture as social individuals in the community? What machines have become – servants or masters – in the face of upcoming civilization? AI supporters show optimism contrary to the non-supporters who question the credibility and safety of AI reality. The objective of the paper investigates the changes in the self and the social activities of users due to AI in the network society, Secondly, whether the AI technology modify moral standpoint of the people in the future. In synthesis, the way AI network resolves social problems of the society. The subject demands attention by gleaning the references for inquiry. The method of data collection drawn through the secondary sources by using meta-analysis technique from published journals from national and internal forums. AI represents knowledge, logic, and engineering by connecting pieces of facts to get a problem solved or a riddle answered in the real world as the proposition. The social network provides community and AI provide information to people. How by using AI the problems of the world resolved to protract debate and attention in the growth scenario, astutely.

Current Journal of Applied Science and Technology, 2023

The recent appearance of widely available Artificial Intelligence (AI) applications such as ChatGPT and Bard has fuelled a flurry of popular and academic discussions about the implications of such AI tools for all aspects of contemporary life and culture. After examining some aspects of recent developments, this article goes on to review some salient critiques of the emerging AI debate with the intention of analyzing some of the key themes in the current discourse. The key objective will be to deflate some of the more overblown and alarming perspectives informed by anthropomorphising AI developments. In particular, there is an attempt to steer a middle course between doom-laden pessimism and futuristic optimism. Drawing on a range of philosophical positions, it is concluded that AI applications are best conceptualised as powerful tools which need to be utilised pragmatically and regulated ethically in partnership with humans in the best interests of all of us.

Land Forces Academy Review

Every other aspect of intelligence and every structure of the learning process can be described very precisely in a way that teaches a machine how to simulate it, at which point Artificial Intelligence (AI) was established as a new field of study and research and generated expectations extraordinary. AI is the ability of a machine to imitate human functions such as reasoning, learning, planning and creativity. AI systems are able to adapt their behavior to some extent by analyzing the effects of previous actions and operating autonomously. Some AI technologies have been around for over 50 years, but increased computing power, the availability of enormous amounts of data, and new algorithms have led to major advances in AI in recent years. Artificial intelligence is considered a central element of the digital transformation of society and has become a priority for the EU. Future applications are expected to bring enormous changes, but AI is already present in our daily lives. Like an...

B. Meyer, U. Thomas, & O. Kanoun (Eds.), Hybrid Societies - Humans Interacting with Embodied Technologies (Vol. 1). Springer, Forthcoming, 2024

The central question of our paper is not whether Embodied Digital Technologies (EDTs) are to be understood as social actors by analogy with humans. The question is rather how the contingency of machine behavior is communicatively processed in design and how the mechatronics of machines is transformed into a socially accountable shape. To describe the contingency of machine behavior, we draw on Heinz von Foerster's concept of the non-trivial machine. To discuss the actor status of machines, we use the concept of "social frameworks" developed by Erving Goffman: While "natural frameworks" aim at a technical control of environmental phenomena, social frameworks operate with displays and expectations of behavior in order to provide orientation and to gain influence. Goffman's concept of social frameworks leads to the possibility of identifying different types of non-human, technically developed social actors. Each of these types is-as our comparative study shows-characterized by a different principle of organizing the relationship between man and machine.