Ethically Aligned Design of Autonomous Systems: Industry viewpoint and an empirical study

A behavioral economics approach to programming autonomous systems in moral dilemmas

Autonomous systems (ASs) will eventually make many decisions in moral dilemmas without human oversight. How humans will respond to the presence of ASs and whether humans will accept them will crucially depend on how ASs’ decisions are programmed. For example, how moral dilemmas are approached in the programming of autonomous vehicles (AVs) is stated as an important factor by potential adopters of this technology. After all, how risks are assigned between different road users will have a strong impact on the socioeconomic structures of society’s mobility. Until now, research on preferences for the programming of ASs in moral dilemmas confronts participants in many instances with life-and-death scenarios based on abstract philosophical thought experiments. This paper offers a first step in evaluating how new knowledge in this area can be acquired through the combination of disciplines. Three empirical studies illustrate the potential advantages of a behavioral economics approach for this string of research. We compare choices in high-stakes hypothetical vignette dilemmas with choices in structurally equivalent low-stakes incentivized experiments. We find that, especially for dilemmas with self-interest, incentivized experiments can provide important additional information, as people tend to overstate their altruistic tendencies in hypothetical dilemmas.

Pragmatism, the Ethics of Artificial Intelligence and Sociotechnical Systems

Metanormative Theory for RL-Based Moral Agents

This paper aims to draw out ideas from recent work in metanormative theory that can be useful for designing artificial moral and value-aligned agents and examine the RL architecture through the lens of these ideas.

Is Ethical Artificial Intelligence Possible?

Ethical artificial intelligence (AI) is emerging as a widespread approach that refers to the development and use of AI technologies in a manner compatible with human values. However, the tendency of AI companies in Europe to relocate their operations to the United States is increasing debates about the applicability of this approach. One of the main reasons for this is the European Union's General Data Protection Regulation (GDPR); the costs, controls, and restrictions imposed by this regulation on data use may lead global technology firms to move outside of Europe. The high economic value-generating potential of AI creates pressure for the relaxation of these regulations, presenting a choice between ethical principles and economic interests. This study aims to provide a conceptual evaluation within the framework of the question of whether the economic gains provided by AI can outweigh human-centered ethical values. Accordingly, the research adopts a qualitative approach based on the literature and examines the current debates at a conceptual level. The assessments indicate that the European Union's desire to compete with the United States and China in the global artificial intelligence race creates a context that may make prioritizing ethical principles difficult. In this context, it is considered that the development of an ethical understanding of artificial intelligence cannot be considered independently of economic and political dynamics, and while it presents various limitations under current conditions, it offers a structure that can be improved with appropriate governance mechanisms.

Human Values in the Age of Autonomous Technologies

The rapid development of autonomous technologies such as artificial intelligence (AI), machine learning, and robotics has transformed the relationship between humans and machines. While these systems enhance efficiency and productivity, they raise critical concerns about preserving human values in automated decision-making. Key values such as fairness, accountability, transparency, privacy, and dignity are often overlooked, as autonomous systems rely heavily on data-driven algorithms that may embed biases. This misalignment can lead to discrimination, reduced trust, and unintended consequences in sensitive sectors like healthcare, transportation, and criminal justice. Addressing this issue requires integrating human values into system design through an interdisciplinary approach combining computer science, ethics, sociology, and policy studies. The paper highlights challenges such as value ambiguity, contextual differences, and technical limitations in encoding ethics. It proposes a mixed-method approach involving stakeholder analysis, value elicitation, algorithm auditing, and ethical performance evaluation. Findings suggest that systems incorporating multi-stakeholder input and adaptive ethical constraints align better with human values than purely data-driven models. The study emphasizes the importance of regulatory frameworks, transparency, explainable AI, and continuous monitoring to ensure ethical deployment. Ultimately, embedding human values in autonomous systems is a socio-ethical necessity, requiring scalable, context-aware, and culturally sensitive solutions to achieve sustainable technological development.

SOCIAL AND ETHICAL IMPLICATIONS OF FULLY AUTONOMOUS AI

It is proposed to rethink social and tech ethics from the standpoint of a renewed attention to the constitutions of these economic actors within the capitalist system.