Erich Prem

The aim of this paper is to challenge and push back against the view that making and maintaining artefacts should be regarded an action where a maker’s intentions are imposed on matter. It addresses software maintenance and how to best conceptualize it to clarify aspects such as software’s formal nature, how it is conceived and produced, and its relation to users and their expectations. The paper diverges from a tradition in the philosophy of artefacts focused on maker’s intentions to clarify the ontological nature of artefacts and their maintenance. It starts from a conceptual analysis of software maintenance and identifies important differences of software to other artefacts including inherent faultiness and functional change. In discussing the ontology of software, the paper proposes a shift from maker’s intentions to functional and organisational criteria and on development processes involving interactions of users and designers to anticipate users’ future needs.

In the past, media portrayed IT entrepreneurs as economic leaders and role models. Recently, however, controversies over the power of large tech firms, questionable business ethics and surveillance capitalism have tarnished this image. These concerns have sparked a new wave of creators, entrepreneurs and activists addressing the ethical challenges of the IT world. This chapter examines individuals who use IT for social good or to challenge the negative impacts of digitization. It explores their motivations through life-history examples. The article concludes by discussing entrepreneurial IT virtues within virtue ethics and argues that systematic analyses of virtuous IT exemplars can help promote ethical practices in IT entrepreneurship.

Recent advances in Artificial Intelligence are nothing short of a revolution in computing technologies. They have become triggers of significant innovation opportunities that many entrepreneurs seek to explore and exploit for commercial success. At the same time, Artificial Intelligence poses enormous challenges regarding the ethical design of these innovations, both at the level of the individual and regarding their impact on society. In this chapter, we review the resulting calls for ethical AI and the challenges they pose for the entrepreneur. We take a closer look at AI principles that have been proposed to address the problem of ethical AI systems. While laudable, principles suffer from a lack of operational practicability. Instead, it is proposed to learn from the examples of other high-risk industry such as pharmaceutics, aeronautics, or medicine that successfully established practices of managing significant and residual risks. This should lead to developing a systematic and contextualised debate about ethical AI systems in prototypical situations adopting lessons from other fields.

At more than 50 years of age, Artificial Intelligence cannot be called a new technology. However, recent advances in AI have made the field widely available and applicable to the extent that it has become a major driver for technology-based innovations. This article investigates the characteristics underlying AI technology that are most relevant for innovation management. It addresses challenges and potential showstoppers such as data requirements, explainability and ethical questions. These questions require a strategic approach to managing AI innovation, i.e. a long-term perspective and a careful consideration of the epistemic flow of information from the problem domain to the application. We propose an epistemic framework for the AI innovation process that helps in understanding and improving key dynamic capabilities for strategic AI innovation management.

This open access textbook introduces and defines digital humanism from a diverse range of disciplines. Following the 2019 Vienna Manifesto, the book calls for a digital humanism that describes, analyzes, and, most importantly, influences the complex interplay of technology and humankind, for a better society and life, fully respecting universal human rights. The book is organized in three parts: Part I “Background” provides the multidisciplinary background needed to understand digital humanism in its philosophical, cultural, technological, historical, social, and economic dimensions. The goal is to present the necessary knowledge upon which an effective interdisciplinary discourse on digital humanism can be founded. Part II “Digital Humanism – a System’s View” focuses on an in-depth presentation and discussion of the main digital humanism concerns arising in current digital systems. The goal of this part is to make readers aware and sensitive to these issues, including e.g. the control and autonomy of AI systems, privacy and security, and the role of governance. Part III “Critical and Societal Issues of Digital Systems” delves into critical societal issues raised by advances of digital technologies. While the public debate in the past has often focused on them separately, especially when they became visible through sensational events the aim here is to shed light on the entire landscape and show their interconnected relationships. This includes issues such as AI and ethics, fairness and bias, privacy and surveillance, platform power and democracy. This textbook is intended for students, teachers, and policy makers interested in digital humanism. It is designed for stand-alone and for complementary courses in computer science, or curricula in science, engineering, humanities and social sciences. Each chapter includes questions for students and an annotated reading list to dive deeper into the associated chapter material. The book aims to provide readers with as wide an exposure as possible to digital advances and their consequences for humanity. It includes constructive ideas and approaches that seek to ensure that our collective digital future is determined through human agency.

In reaction to concerns about a broad range of potential ethical issues, dozens of proposals for addressing ethical aspects of artificial intelligence (AI) have been published. However, many of them are too abstract for being easily translated into concrete designs for AI systems. The various proposed ethical frameworks can be considered an instance of principlism that is similar to that found in medical ethics. Given their general nature, principles do not say how they should be applied in a particular context. Hence, a broad range of approaches, methods, and tools have been proposed for addressing ethical concerns of AI systems. This paper presents a systematic analysis of more than 100 frameworks, process models, and proposed remedies and tools for helping to make the necessary shift from principles to implementation, expanding on the work of Morley and colleagues. This analysis confirms a strong focus of proposed approaches on only a few ethical issues such as explicability, fairness, privacy, and accountability. These issues are often addressed with proposals for software and algorithms. Other, more general ethical issues are mainly addressed with conceptual frameworks, guidelines, or process models. This paper develops a structured list and definitions of approaches, presents a refined segmentation of the AI development process, and suggests areas that will require more attention from researchers and developers.

This chapter provides an overview of existing proposals to address ethical issues of AI systems with a focus on ethical frameworks. A large number of such frameworks have been proposed with the aim to ensure the development of AI systems aligned with human values and morals. The frameworks list key ethical values that an AI system should follow. For the most part, they can be regarded as instances of philosophical principlism. This paper provides an overview of such frameworks and their general form and intended way of working. It lists some of the main principles that are proposed in the frameworks and critically assesses the practicality of the various approaches. It also describes current trends, tools, and approaches to ensure the ethicality of AI systems.

This chapter provides an overview of the challenges involved in algorithmic content moderation. Content moderation is the organized practice of screening user-generated content (UGC) on Internet sites, social media, and other online outlets to determine the appropriateness of the content for a given site, locality, or jurisdiction. The most common technical approaches consist in using classifier systems that assign predefined category labels to individual posts. We briefly introduce pre- and post-moderation and provide real-world examples of algorithmic moderation systems used by an Austrian daily newspaper. We point to significant challenges of moderation such as the ambiguities of natural language and the implications for freedom of expression. We conclude with issues that algorithmic content moderation raises for societal power relations and democratic control.

Digital humanism emerges from serious concerns about the way in which digitisation develops, its impact on society and on humans. While its motivation is clear and broadly accepted, it is still an emerging field that does not yet have a universally accepted definition. Also, it is not always clear how to differentiate digital humanism from other similar endeavours. In this article, we critically investigate the notion of digital humanism and present its main principles as shared by its key proponents. These principles include the quest for human dignity and the ideal of a better society based on core values of the Enlightenment. The paper concludes that digital humanism is to be treated as a technical endeavour to shape digital technologies and use them for digital innovation, a political endeavour investigating power shifts triggered by digital technology, and, at the same time, as a philosophical endeavour including the quest to delineate its scope and to draw boundaries for the digital. Methodologically, digital humanism is an interdisciplinary effort to debate a broad range of digitisation shortfalls in their totality, from privacy infringements to power shifts, from human alienation to disownment. While it overlaps with a range of established fields and other movements, digital humanism reflects a new academic, engineering, and societal awareness of the challenges of digital technologies.

This paper discusses epistemological consequences of embodied AI for Artificial Life models. The importance of robotic systems for ALife lies in the fact that they are not purely formal models and thus have to address issues of semantic adaptation and epistemic autonomy, which means the system's own ability to decide upon the validity of measurements. Epistemic autonomy in artificial systems is a difficult problem that poses foundational questions. The proposal is to concentrate on biological transformations of epistemological questions that have lead to the development of modern ethology. Such an approach has proven to be useful in the design of control systems for behavior-based robots. It leads to a better understanding of modern ontological conceptions as well as a reacknowledgement of finality in the description and design of autonomous systems.