The organization of behavior: A neuropsychological theory

After virtue, a study in moral theory

In the past five years, private companies, research institutions and public sector organizations have issued principles and guidelines for ethical artificial intelligence (AI). However, despite an apparent agreement that AI should be ‘ethical’, there is debate about both what constitutes ‘ethical AI’ and which ethical requirements, technical standards and best practices are needed for its realization. To investigate whether a global agreement on these questions is emerging, we mapped and analysed the current corpus of principles and guidelines on ethical AI. Our results reveal a global convergence emerging around five ethical principles (transparency, justice and fairness, non-maleficence, responsibility and privacy), with substantive divergence in relation to how these principles are interpreted, why they are deemed important, what issue, domain or actors they pertain to, and how they should be implemented. Our findings highlight the importance of integrating guideline-development efforts with substantive ethical analysis and adequate implementation strategies.

The global landscape of AI ethics guidelines

In the last five years, private companies, research institutions as well as public sector organisations have issued principles and guidelines for ethical AI, yet there is debate about both what constitutes "ethical AI" and which ethical requirements, technical standards and best practices are needed for its realization. To investigate whether a global agreement on these questions is emerging, we mapped and analyzed the current corpus of principles and guidelines on ethical AI. Our results reveal a global convergence emerging around five ethical principles (transparency, justice and fairness, non-maleficence, responsibility and privacy), with substantive divergence in relation to how these principles are interpreted; why they are deemed important; what issue, domain or actors they pertain to; and how they should be implemented. Our findings highlight the importance of integrating guideline-development efforts with substantive ethical analysis and adequate implementation strategies.

Artificial Intelligence: the global landscape of ethics guidelines.

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.

https://journals.sagepub.com/doi/pdf/10.1177/2053951716679679

The ethics of algorithms: Mapping the debate:

Common mental health disorders are rising globally, creating a strain on public healthcare systems. This has led to a renewed interest in the role that digital technologies may have for improving mental health outcomes. One result of this interest is the development and use of artificial intelligence for assessing, diagnosing, and treating mental health issues, which we refer to as ‘digital psychiatry’. This article focuses on the increasing use of digital psychiatry outside of clinical settings, in the following sectors: education, employment, financial services, social media, and the digital well-being industry. We analyse the ethical risks of deploying digital psychiatry in these sectors, emphasising key problems and opportunities for public health, and offer recommendations for protecting and promoting public health and well-being in information societies.

/pdf/digital-psychiatry-ethical-risks-and-opportunities-for-1eo410h1vb.pdf

Digital psychiatry: ethical risks and opportunities for public health and well-being

Cyber attacks are escalating in frequency, impact, and sophistication. For this reason, it is crucial to identify and define regulations for state behaviour and strategies to deploy countering measures that would avoid escalation and disproportionate use of cyber means, while protecting and fostering the stability of our societies. To this end, strategies to deter cyber attacks and norms regulating state behaviour in cyberspace are both necessary; unfortunately neither is available at the moment. In this chapter, I offer a theory of cyber deterrence and a set of policy recommendations to fill this vacuum.

Norms and Strategies for Stability in Cyberspace

This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by Computer and Information Ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the Level of Abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even the data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations — the interactions among hardware, software, and data — rather than on the variety of digital technologies that enables them. And it emphasises the complexity of the ethical challenges posed by Data Science. Because of such complexity, Data Ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of Data Science and its applications within a consistent, holistic, and inclusive framework. Only as a macroethics Data Ethics will provide the solutions that can maximise the value of Data Science for our societies, for all of us, and for our environments.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2907744_code2644503.pdf?abstractid=2907744&mirid=1

What is Data Ethics

Abstract The article analyses the role of smart contracts in the architecture of the European Union’s Data Act proposal. It identifies five difficulties: lack of flexibility in terms of both content and operation; dependence on oracles which could lead to errors; vulnerability to bugs and changes in architecture; immutability and privacy; and problems of enforcement. It then offers some recommendations about how to address them to improve the Data Act. 

/pdf/how-to-improve-smart-contracts-in-the-european-union-data-16je1c8d.pdf

How to Improve Smart Contracts in the European Union Data Act

https://link.springer.com/content/pdf/10.1007/s44206-023-00052-4.pdf

Mariarosaria Taddeo

Papers

Digital psychiatry: ethical risks and opportunities for public health and well-being

Norms and Strategies for Stability in Cyberspace

What is Data Ethics

How to Improve Smart Contracts in the European Union Data Act

Correction to: How to Improve Smart Contracts in the European Union Data Act