The Future of Cybercrime: AI and Emerging Technologies Are Creating a Cybercrime Tsunami

This paper reviews the impact of AI and emerging technologies on the future of cybercrime and the necessary strategies to combat it effectively. Society faces a pressing challenge as cybercrime proliferates through AI and emerging technologies. At the same time, law enforcement and regulators struggle to keep it up. Our primary challenge is raising awareness as cybercrime operates within a distinct criminal ecosystem. We explore the hijacking of emerging technologies by criminals (CrimeTech) and their use in illicit activities, along with the tools and processes (InfoSec) to protect against future cybercrime. We also explore the role of AI and emerging technologies (DeepTech) in supporting law enforcement, regulation, and legal services (LawTech)

Toward a Criminal Law for Cyberspace: Distributed Security

Cybercrime creates unique challenges for the reactive model of crime control that has been predominant for approximately the last century and a half. That model makes certain assumptions about crime, which derive from characteristics of real-world crime. These assumptions do not hold for cybercrime, so the reactive model is not an appropriate means of dealing with online crime. The article explains how modified principles of criminal law can be utilized to implement a new, non-reactive model which can deal effectively with cybercrime. This model of distributed security emphasizes prevention, rather than reaction, which is achieved by holding citizens liable for their failure to prevent cybercrime

Self-Governing Hybrid Societies and Deception

Self-governing hybrid societies are multi-agent systems where humans and machines interact by adapting to each other’s behaviour. Advancements in Artificial Intelligence (AI) have brought an increasing hybridisation of our societies, where one particular type of behaviour has become more and more prevalent, namely deception. Deceptive behaviour as the propagation of disinformation can have negative effects on a society's ability to govern itself. However, self-governing societies have the ability to respond to various phenomena. In this paper we explore how they respond to the phenomenon of deception from an evolutionary perspective considering that agents have limited adaptation skills. Will hybrid societies fail to govern deceptive behaviour and reach a Tragedy of The Digital Commons? Or will they manage to avoid it through cooperation? How resilient are they against large-scale deceptive attacks? We provide a tentative answer to some of these questions through the lens of evolutionary agent-based modelling, based on the scientific literature on deceptive AI and public goods games

Learning and Governance in Inter-Firm Relations

This paper connects theory of learning with theory of governance, in the context of inter-firm relations. It recognizes fundamental criticism of transaction cost economics (TCE), but preserves elements from that theory. The theory of governance used incorporates learning and trust. The paper identifies two kinds of relational risk: hold-up and spillover. For the governance of relations, i.e. the control of relational risk, it develops a box of instruments which includes trust, next to instruments derived and adapted from TCE. These instruments are geared to problems that are specific to learning in interaction between firms. They also include additional roles for go-betweens.transaction cost economics;trust;inter-organizational learning

OWL-POLAR : semantic policies for agent reasoning

The original publication is available at www.springerlink.comPostprin

Meta-Science:Towards a Science of Meaning and Complex Solutions

Science has lost its ethical imperatives as it moved away from a science of ought to a science of is. Subsequently, it might have answers for how we can address global challenges, such as climate change and poverty, but not why we should. This supposedly neutral stance leaves it to politics and religions (in the sense of non-scientific fields of social engagement) to fill in the values. The problem is that through this concession, science implicitly acknowledges that it is not of universal relevance.Objective knowledge, as Karl Popper calls for, might be less easily attainable in the world of ideas and within the confines of scientific idealism. However, if ideas, values and meaning have equal claim to be drivers of change in the sense of causation, aspiring to identify objective knowledge about the world of ideas and of meaning is necessary. If the sciences and disciplines aim to give objectively valid reasons for our actions (and for how to address global challenges), we need to elevate the study of meaning beyond the cultural, disciplinary and ideational delineations. We need to come to a meta understanding of values and meaning equal to objective knowledge about the material world. But differently than in the material world this meta understanding needs to incorporate individual and subjective experiences as cornerstones of objectivity on a meta-level.We need a science of meaning; one that can scientifically answer Kant’s third question of “what may we hope for”

Meta-Science:Towards a Science of Meaning and Complex Solutions

Science has lost its ethical imperatives as it moved away from a science of ought to a science of is. Subsequently, it might have answers for how we can address global challenges, such as climate change and poverty, but not why we should. This supposedly neutral stance leaves it to politics and religions (in the sense of non-scientific fields of social engagement) to fill in the values. The problem is that through this concession, science implicitly acknowledges that it is not of universal relevance.Objective knowledge, as Karl Popper calls for, might be less easily attainable in the world of ideas and within the confines of scientific idealism. However, if ideas, values and meaning have equal claim to be drivers of change in the sense of causation, aspiring to identify objective knowledge about the world of ideas and of meaning is necessary. If the sciences and disciplines aim to give objectively valid reasons for our actions (and for how to address global challenges), we need to elevate the study of meaning beyond the cultural, disciplinary and ideational delineations. We need to come to a meta understanding of values and meaning equal to objective knowledge about the material world. But differently than in the material world this meta understanding needs to incorporate individual and subjective experiences as cornerstones of objectivity on a meta-level.We need a science of meaning; one that can scientifically answer Kant’s third question of “what may we hope for”

Meta-Science:Towards a Science of Meaning and Complex Solutions

Science has lost its ethical imperatives as it moved away from a science of ought to a science of is. Subsequently, it might have answers for how we can address global challenges, such as climate change and poverty, but not why we should. This supposedly neutral stance leaves it to politics and religions (in the sense of non-scientific fields of social engagement) to fill in the values. The problem is that through this concession, science implicitly acknowledges that it is not of universal relevance.Objective knowledge, as Karl Popper calls for, might be less easily attainable in the world of ideas and within the confines of scientific idealism. However, if ideas, values and meaning have equal claim to be drivers of change in the sense of causation, aspiring to identify objective knowledge about the world of ideas and of meaning is necessary. If the sciences and disciplines aim to give objectively valid reasons for our actions (and for how to address global challenges), we need to elevate the study of meaning beyond the cultural, disciplinary and ideational delineations. We need to come to a meta understanding of values and meaning equal to objective knowledge about the material world. But differently than in the material world this meta understanding needs to incorporate individual and subjective experiences as cornerstones of objectivity on a meta-level.We need a science of meaning; one that can scientifically answer Kant’s third question of “what may we hope for”

Meta-Science:Towards a Science of Meaning and Complex Solutions

Science has lost its ethical imperatives as it moved away from a science of ought to a science of is. Subsequently, it might have answers for how we can address global challenges, such as climate change and poverty, but not why we should. This supposedly neutral stance leaves it to politics and religions (in the sense of non-scientific fields of social engagement) to fill in the values. The problem is that through this concession, science implicitly acknowledges that it is not of universal relevance.Objective knowledge, as Karl Popper calls for, might be less easily attainable in the world of ideas and within the confines of scientific idealism. However, if ideas, values and meaning have equal claim to be drivers of change in the sense of causation, aspiring to identify objective knowledge about the world of ideas and of meaning is necessary. If the sciences and disciplines aim to give objectively valid reasons for our actions (and for how to address global challenges), we need to elevate the study of meaning beyond the cultural, disciplinary and ideational delineations. We need to come to a meta understanding of values and meaning equal to objective knowledge about the material world. But differently than in the material world this meta understanding needs to incorporate individual and subjective experiences as cornerstones of objectivity on a meta-level.We need a science of meaning; one that can scientifically answer Kant’s third question of “what may we hope for”