Artificial general intelligence is a field of research aiming to distil the principles of intelligence that operate independently of a specific problem domain and utilise these principles in order to synthesise systems capable of performing any intellectual task a human being is capable of and beyond. While “narrow” artificial intelligence which focuses on solving specific problems such as speech recognition, text comprehension, visual pattern recognition and robotic motion has shown impressive breakthroughs lately, understanding general intelligence remains elusive. We propose a paradigm shift from intelligence perceived as a competence of individual agents defined in relation to an a priori given problem domain or a goal, to intelligence perceived as a formative process of self-organisation. We call this process open-ended intelligence. Starting with a brief introduction of the current conceptual approach, we expose a number of serious limitations that are traced back to the ontological roots of the concept of intelligence. Open-ended intelligence is then developed as an abstraction of the process of human cognitive development, so its application can be extended to general agents and systems. We introduce and discuss three facets of the idea: the philosophical concept of individuation, sense-making and the individuation of general cognitive agents. We further show how open-ended intelligence can be framed in terms of a distributed, self-organising network of interacting elements and how such process is scalable. The framework highlights an important relation between coordination and intelligence and a new understanding of values.

The human cognitive system is a remarkable exemplar of a general intelligent system whose competence is not confined to a specific problem domain. Evidently, general cognitive competences are a product of a prolonged and complex process of cognitive development. Therefore, the process of cognitive development is a primary key to understanding the emergence of intelligent behavior. This paper develops the theoretical foundations for a model that generalizes the process of cognitive development. The model aims to provide a realistic scheme for the synthesis of scalable cognitive systems with an open-ended range of capabilities. Major concepts and theories of human cognitive development are introduced and briefly explored focusing on the enactive approach to cognition and the concept of sense-making. The initial scheme of human cognitive development is then generalized by introducing the philosophy of individuation and the abstract mechanism of transduction. The theory of individuation provides the ground for the necessary paradigmatic shift from cognitive systems as given products to cognitive development as a formative process of self-organization. Next, the conceptual model is specified as a scalable scheme of networks of agents. The mechanisms of individuation are formulated in context independent information theoretical terms. Finally, the paper discusses two concrete aspects of the generative model -- mechanisms of transduction and value modulating systems. These are topics of further research towards a computationally realizable model.

Transport sector is in the process of being rapidly and fundamentally reshaped by autonomous and collaborative driving technologies. This reshaping promises huge economic and social benefits as well as challenges in terms of developing and deploying secure and safe transportations systems, their smooth integration to social fabric. We have employed Policy Scan and Technology Strategy Design methodology in order to identify concrete societal expectations and problems and map them with mitigating technological availabilities in the domain of autonomous driving and smart mobility. Event Data Recorder for Autonomous Driving (EDR/AD) is an envisioned subsystem of a vehicular Controller Area Network which ensures the confidentiality, integrity and availability of data related to operation of a vehicle in order to permit recovery of exact situation following the occurrence of an event or on demand. The exact technical and regulatory requirements for the device are still in the development internationally, but it is clear that it will be included into vehicle type-approval requirements at UNECE level. We present an analysis of the context of the usage of the EDR/AD in collaborative intelligent transport systems, related security, data provenance and privacy, other regulatory and technical issues considering many interest groups and stakeholders involved. We present a concrete proposal for developing a EDR/AD proof of the concept prototype with clear market deployment potential and urge security researchers, vehicle manufacturers, and component suppliers to form a collaboration towards implementing important technology for making future autonomous vehicles more socially acceptable and legally compliant. Furthermore, EDR/AD technology, apart from its immediate use in autonomous driving and smart mobility domain has a potential to be extended to general autonomous robot and AI applications.

Increasingly accelerating technology advancement affects and disrupts almost all aspects of human society and civilization at large as we know it. Actually, this has been true since the technology started at the dawn of human society, yet the mere speed and magnitude of modern technology development brings about the situation where societies and economies have to adapt to the changing technological landscape as much as technologies have to integrate into the social fabric. The way to to achieve such integration in a changing and unpredictable world is to support the close interaction between the world of societal expectations and the world of technology. Policy Scan and Technology Strategy design methodology presented in this paper was developed precisely for the purpose of addressing specific types of 'ill-defined' problems in terms of observing, analyzing and integrating technology developments and availabilities with policy requirements, social governance and societal expectations. The methodology consists of conceptual tools and methods for developing concrete actions and products for guiding technology adoption for social change. It is geared towards increasingly complex and uncertain situations where existing analysis and problem solving methods often fail due to many non-linearities inherent in the social and technology worlds and, especially, at their area of their inter intersection. The development of the methodology followed the grounded theory construction process which requires a close relation to a specific context of an application domain, determined by actual interaction between the worlds of societal problems and technology. The chosen application domain of this research is the intersection of smart mobility problematics and opportunities, the rising autonomous driving technology, data privacy, provenance and security challenges, policies and legislation.

The current social reality is characterized by all-encompassing change, which disrupts existing social structures at all levels. Yet the prevailing view of society is based on the ontological primacy of stable hierarchical structures, which is no longer adequate. We propose a conceptual framework for thinking about a dynamically changing social system: the Living Cognitive Society. Importantly, we show how it follows from a much broader philosophical framework, guided by the theory of individuation, which emphasizes the importance of relationships and interactive processes in the evolution of a system. The framework addresses society as a living cognitive system -- an ecology of interacting social subsystems -- each of which is also a living cognitive system. We argue that this approach can help us to conceive sustainable social systems that will thrive in the circumstances of accelerating change. The Living Cognitive Society is explained in terms of its fluid structure, dynamics and the mechanisms at work. We then discuss the disruptive effects of Information and Communication Technologies on the mechanisms at work. We conclude by delineating a major topic for future research -- distributed social governance -- which focuses on processes of coordination rather than on stable structures within global society.

Artificial General Intelligence is a field of research aiming to distill the principles of intelligence that operate independently of a specific problem domain or a predefined context and utilize these principles in order to synthesize systems capable of performing any intellectual task a human being is capable of and eventually go beyond that. While "narrow" artificial intelligence which focuses on solving specific problems such as speech recognition, text comprehension, visual pattern recognition, robotic motion, etc. has shown quite a few impressive breakthroughs lately, understanding general intelligence remains elusive. In the paper we offer a novel theoretical approach to understanding general intelligence. We start with a brief introduction of the current conceptual approach. Our critique exposes a number of serious limitations that are traced back to the ontological roots of the concept of intelligence. We then propose a paradigm shift from intelligence perceived as a competence of individual agents defined in relation to an a priori given problem domain or a goal, to intelligence perceived as a formative process of self-organization by which intelligent agents are individuated. We call this process open-ended intelligence. Open-ended intelligence is developed as an abstraction of the process of cognitive development so its application can be extended to general agents and systems. We introduce and discuss three facets of the idea: the philosophical concept of individuation, sense-making and the individuation of general cognitive agents. We further show how open-ended intelligence can be framed in terms of a distributed, self-organizing network of interacting elements and how such process is scalable. The framework highlights an important relation between coordination and intelligence and a new understanding of values. We conclude with a number of questions for future research.