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A natural question is why AI in design? Although the design applications written about in the journal vary widely, the common thread is that researchers use AI techniques to implement their ideas. The use of AI techniques for design applications, at least when AI EDAM was started, was partially a reaction against the predominant design methods based on some form of optimization. Knowledge-based techniques, particularly rule-based systems of various sorts, were very popular. One of the draws of these methods, I believe, was their ability to represent knowledge that is hard or awkward to represent in traditional optimization frameworks. This mirrors my experience: at the time, I was working in configuration with components that had a large number compatibility and resource constraints. Although many constraints could be represented in mixed integer linear programming systems, it was not easy to conceptualize, write, and most importantly, maintain the constraints in those systems.
Many ethical questions about our future with intelligent machines rest upon assumptions concerning the origins, development and ideal future of humanity and of the universe, and hence overlap considerably with many religious questions. First, could computers themselves become moral in any sense, and could different components of morality – whatever they are – be instantiated in a computer? Second, could computers enhance the moral functioning of humans? Do computers potentially have a role in narrowing the gap between moral aspiration and how morality is actually lived out? Third, if we develop machines comparable in intelligence to humans, how should we treat them? This question is especially acute for embodied robots and human-like androids. Fourthly, numerous moral issues arise as society changes such that artificial intelligence plays an increasingly significant role in making decisions, with implications for how human beings function socially and as individuals, treat each other and access resources.
This paper examines the evidence for the marginal feminine endings *-ay- and *-āy- in Proto-Semitic, and the feminine endings *-e and *-a in Proto-Berber. Their similar formation (*CV̆CC-ay/āy), semantics (verbal abstracts, underived concrete feminine nouns) and plural morphology (replacement of the feminine suffix by a plural suffix with -w-) suggest that this feminine formation should be reconstructed to a shared ancestor which may be called Proto-Berbero-Semitic.
Generative artificial intelligence has a long history but surged into global prominence with the introduction in 2017 of the transformer architecture for large language models. Based on deep learning with artificial neural networks, transformers revolutionised the field of generative AI for production of natural language outputs. Today’s large language models, and other forms of generative artificial intelligence, now have unprecedented capability and versatility. This emergence of these forms of highly capable generative AI poses many legal issues and questions, including consequences for intellectual property, contracts and licences, liability, data protection, use in specific sectors, potential harms, and of course ethics, policy, and regulation of the technology. To support the discussion of these topics in this Handbook, this chapter gives a relatively non-technical introduction to the technology of modern artificial intelligence and generative AI.
The emergence of digital platforms and the new application economy are transforming healthcare and creating new opportunities and risks for all stakeholders in the medical ecosystem. Many of these developments rely heavily on data and AI algorithms to prevent, diagnose, treat, and monitor diseases and other health conditions. A broad range of medical, ethical and legal knowledge is now required to navigate this highly complex and fast-changing space. This collection brings together scholars from medicine and law, but also ethics, management, philosophy, and computer science, to examine current and future technological, policy and regulatory issues. In particular, the book addresses the challenge of integrating data protection and privacy concerns into the design of emerging healthcare products and services. With a number of comparative case studies, the book offers a high-level, global, and interdisciplinary perspective on the normative and policy dilemmas raised by the proliferation of information technologies in a healthcare context.
There are a variety of informatics-centric tasks for which the goal is to predict something or extract some kind of signal. In this section, we consider artificial intelligence broadly, artificial intelligence applied to law, and the very fruitful fields of machine learning (ML) and natural language processing (NLP).
Governing AI is about getting AI right. Building upon AI scholarship in science and technology studies, technology law, business ethics, and computer science, it documents potential risks and actual harms associated with AI, lists proposed solutions to AI-related problems around the world, and assesses their impact. The book presents a vast range of theoretical debates and empirical evidence to document how and how well technical solutions, business self-regulation, and legal regulation work. It is a call to think inside and outside the box. Technical solutions, business self-regulation, and especially legal regulation can mitigate and even eliminate some of the potential risks and actual harms arising from the development and use of AI. However, the long-term health of the relationship between technology and society depends on whether ordinary people are empowered to participate in making informed decisions to govern the future of technology – AI included.
AI and Image illustrates the importance of critical perspectives in the study of AI and its application to image collections in the art and heritage sector. The authors' approach is that such entanglements of image and AI are neither dystopian or utopian but may amplify, reduce or condense existing societal inequalities depending on how they may be implemented in relation to human expertise and sensibility in terms of diversity and inclusion. The Element further discusses regulations around the use of AI for such cultural datasets as they touch upon legalities, regulations and ethics. In the conclusion they emphasise the importance of the professional expert factor in the entanglements of AI and images and advocate for a continuous and renegotiating professional symbiosis between human and machines. This title is also available as Open Access on Cambridge Core.
After its launch on 30 November 2022 ChatGPT (or Chat Generative Pre-Trained Transformer) quickly became the fastest-growing app in history, gaining one hundred million users in just two months. Developed by the US-based artificial-intelligence firm OpenAI, ChatGPT is a free, text-based AI system designed to interact with the user in a conversational way. Capable of answering complex questions with sophistication and of conversing in a breezy and impressively human style, ChatGPT can also generate outputs in a seemingly endless variety of formats, from professional memos to Bob Dylan lyrics, HTML code to screenplays and five-alarm chilli recipes to five-paragraph essays. Its remarkable capability relative to earlier chatbots gave rise to both astonishment and concern in the tech sector. On 22 March 2023 a group of more than one thousand scientists and entrepreneurs published an open letter calling for a six-month moratorium on further human-competitive AI development – a moratorium that was not observed.
This paper presents the main topics, arguments, and positions in the philosophy of AI at present (excluding ethics). Apart from the basic concepts of intelligence and computation, the main topics of artificial cognition are perception, action, meaning, rational choice, free will, consciousness, and normativity. Through a better understanding of these topics, the philosophy of AI contributes to our understanding of the nature, prospects, and value of AI. Furthermore, these topics can be understood more deeply through the discussion of AI; so we suggest that “AI philosophy” provides a new method for philosophy.
In this chapter, Fruzsina Molnár-Gábor and Johanne Giesecke consider specific aspects of how the application of AI-based systems in medical contexts may be guided under international standards. They sketch the relevant international frameworks for the governance of medical AI. Among the frameworks that exist, the World Medical Association’s activity appears particularly promising as a guide for standardisation processes. The organisation has already unified the application of medical expertise to a certain extent worldwide, and its guidance is anchored in the rules of various legal systems. It might provide the basis for a certain level of conformity of acceptance and implementation of new guidelines within national rules and regulations, such as those on new technology applications within the AI field. In order to develop a draft declaration, the authors then sketch out the potential applications of AI and its effects on the doctor–patient relationship in terms of information, consent, diagnosis, treatment, aftercare, and education. Finally, they spell out an assessment of how further activities of the WMA in this field might affect national rules, using the example of Germany.
It is only recently that the EPO’s Boards of Appeal have had to deal with appeals relating to the surge of AI based inventions. In doing so the Boards of Appeal have adopted a gradualist approach, adapting the extensive EPO case law relating to the patentability of computer programs ‘as such’ and applying it to AI inventions. The most recent change to the Guidelines indicates the EPO’s willingness to adapt to technological developments and to refine its approach to patentability of inventions involving AI, while at the same time taking a firm line against patenting non-technical inventions.
AI is a complex, multifaceted concept and is therefore hard to define because AI can refer to technological artifacts, certain methods or a scientific field that is split into many subfields and that is continuously changing and evolving AI systems can therefore be seen as digital artifacts that require hardware and software components and that contain at least one learning or learned component, i.e., a component that is able to change the system’s behavior based on presented data and the processing of this data.
This chapter turns to the possibility that the AI systems challenging the legal order may also offer at least part of the solution. Here China, which has among the least developed rules to regulate conduct by AI systems, is at the forefront of using that same technology in the courtroom. This is a double-edged sword, however, as its use implies a view of law that is instrumental, with parties to proceedings treated as means rather than ends. That, in turn, raises fundamental questions about the nature of law and authority: at base, whether law is reducible to code that can optimize the human condition, or if it must remain a site of contestation, of politics, and inextricably linked to institutions that are themselves accountable to a public. For many of the questions raised, the rational answer will be sufficient; but for others, what the answer is may be less important than how and why it was reached, and whom an affected population can hold to account for its consequences.
Conceptually, the tradition of escape from Egypt requires a place to go, a happy ending. Numbers 21 and Deuteronomy 2–3 provide this in the east, in a tradition that does not of itself assume combination with a western campaign. The Bible as we now have it provides the book of Joshua, with its crossing of the Jordan River from the east (chapters 3–4), the assault on Jericho (chapter 6), followed by eventual victory at Ai (chapters 7–8), forced compromise with the Gibeonites (chapter 9), and at last a sweeping success against the assembled forces of first the south, then the north (chapters 10–11). The rest of the book is built around detailed territorial definitions for all the tribes, both east and west of the Jordan (chapters 13–19), with special consideration for the Levites (chapter 21). All this is framed by speeches from Joshua himself in chapters 1 and 23, which have long been understood as classic examples of deuteronomistic work, in making this collection part of a larger history.
Although the western conquest led by Joshua depends in its full expression on the old Israelite tradition of exodus from Egypt, the book gives it a limited and finally Judahite perspective. Like the later revisions of the Moses traditions, which integrate the tribal scheme of Genesis into the old tales of departure and invasion, the book of Joshua pictures a conquest by twelve tribes. Perhaps this tribal focus allows Judah to be given a special role; in any case, the establishment of all Israel, far beyond the borders of Judah, is essential. Moreover, the geographical ambitions of the book are considerable, reaching beyond the proven accomplishment of Israel in any period. Joshua mixes an Israelite ideal with an overwhelmingly Judahite realization. For all the narrative located in the territory of Israel, it is extremely difficult to isolate plausibly Israelite material. In the end, the one most convincing text is the account of Joshua's victory at Ai in chapter 8. This alone provides a starting point for understanding the construction of a western conquest from the tradition of Joshua as ancient warrior leader. Joshua 8 belongs to the family of biblical texts that presents Israel as a collective unit, especially for going to war, and as such, the text belongs with the various Moses materials.