Many have suggested that AI-based interventions could enhance learning by personalization, improving teacher effectiveness, or by optimizing educational processes. However, they could also have unintended or unexpected side-effects, such as undermining learning by enabling procrastination, or reducing social interaction by individualizing learning processes. Responsible scientific experiments are required to map both the potential benefits and the side-effects. Current procedures used to screen experiments by research ethics committees do not take the specific risks and dilemmas that AI poses into account. Previous studies identified sixteen conditions that can be used to judge whether trials with experimental technology are responsible. These conditions, however, were not yet translated into practical procedures, nor do they distinguish between the different types of AI applications and risk categories. This paper explores how those conditions could be further specified into procedures that could help facilitate and organize responsible experiments with AI, while differentiating for the different types of AI applications based on their level of automation. The four procedures that we propose are (1) A process of gradual testing (2) Risk- and side-effect detection (3) Explainability and severity, and (4) Democratic oversight. These procedures can be used by researchers and ethics committees to enable responsible experiment with AI interventions in educational settings. Implementation and compliance will require collaboration between researchers, industry, policy makers, and educational institutions.

Many guidelines outline ethical principles for designing and deploying emerging digital technologies, like AI, in public services, but there is a gap between such principles and practices. We evaluate whether an educational intervention can enable public sector professionals to close this gap and implement responsible innovation. The educational intervention was based on Design for Values, a responsible innovation approach to integrate values into the design process. We employ a systems perspective to evaluate the effects of the intervention. While the educational intervention helps foster techno-moral virtues and enhance accountability, its success depends on the broader organizational context. Future research should explore the long-term embedding of Design for Values in various settings, using comparative and longitudinal methods to understand better the factors that influence its effectiveness.

Conceptual engineering is an approach or method for assessing, improving, adapting and disposing concepts. While recent case studies have shown the possibility and success of conceptual engineering, I argue that not all concepts are equally open to conceptual engineering. It is therefore useful to distinguish between generic and specific concepts. While the latter can be the object of conceptual design, I argue that designing generic concepts is problematic for practical and normative reasons. Nevertheless, attempts can be made to change generic concepts through interventions in larger conceptual repertoires. Contrary to specific concepts, generic concepts do not have a well-delineated function that can provide a normative reference for conceptual engineering. Moreover, they are well entrenched in larger conceptual schemes or repertoires, so that they cannot be engineered in isolation. Generic concepts also raise more and larger challenges in terms of implementation and authority than specific concepts. I discuss the consequences of the distinction between generic and specific concepts for conceptual engineering, the ethics of socially disruptive technology and conceptual ethics.

While there is a considerable literature on acceptable risk, which considers questions like under what condition is it acceptable to impose risks on others, this literature has neglected the issue of moral uncertainty. Moral uncertainty is uncertainty about what moral theory is right. I explore whether, and if so how, moral uncertainty is relevant for (moral) decisions about acceptable risk. To do so, I first consider whether a popular decision procedure to deal with moral uncertainty, Maximizing Expected Choiceworthiness (MEC) is an appropriate procedure for accounting for moral uncertainty in decisions about acceptable risk. I conclude it is not, due to reasons of intertheoretic incomparability and lack of justifiability of the resulting decisions. I then consider several alternatives–such as ignoring moral uncertainty, following the decision-maker’s favorite moral theory and decision rules that avoid intertheoretical tradeoffs–that also turn out to be wanting. Next, I argue that the problems of MEC and alternative decision procedures go back to fundamental assumptions about how to deal with moral uncertainty. If these assumptions are lifted, the road is open to a more deliberative and coherentist approach to decision-making about acceptable risk under moral uncertainty that avoids the discussed problems.

Our democratic systems have been challenged by the proliferation of artificial intelligence (AI) and its pervasive usage in our society. For instance, by analyzing individuals’ social media data, AI algorithms may develop detailed user profiles that capture individuals’ specific interests and susceptibilities. These profiles are leveraged to derive personalized propaganda, with the aim of influencing individuals toward specific political opinions. To address this challenge, the value of privacy can serve as a bridge, as having a sense of privacy can create space for people to reflect on their own political stance prior to making critical decisions, such as voting for an election. In this paper, we explore a novel approach by harnessing the potential of AI to enhance the privacy of social-media data. By leveraging adversarial machine learning, i.e., “AI versus AI,” we aim to fool AI-generated user profiles to help users hold a stake in resisting political profiling and preserve the deliberative nature of their political choices. More specifically, our approach probes the conceptual possibility of infusing people’s social media data with minor alterations that can disturb user profiling, thereby reducing the efficacy of the personalized influences generated by political actors. Our study delineates the boundary of ethical and practical implications associated with this ‘AI versus AI’ approach, highlighting the factors for the AI and ethics community to consider in facilitating deliberative decision-making toward democratic elections.

The present study utilizes a value sensitive design (VSD) inspired approach to contribute to the design and implementation of CO₂ electrolysis (CO₂E) within the framework of carbon capture and utilization (CCU) technologies, which convert CO₂ into valuable products. The focus of this study is on a low technology readiness level (TRL) technology, yet likely relevant to reach climate neutrality by 2050. We examine the perspectives of stakeholders along the supply chain and proactively identify relevant sustainability-related values and potential conflicts among them. Thus the current work highlights the importance of considering a broad range of stakeholders and their values in the early stages of technological design. The research approach is consisting of various steps inspired by value sensitive design (VSD): identifying relevant values and norms associated with CO2 electrolysis through literature analysis, conducting qualitative interviews with relevant stakeholders to triangulate the results. Subsequently, a value-based alignment network analysis was employed to examine shared values that are central for the design of the technology. The findings indicate that sustainability-related values such as concern for nature, climate change mitigation, the use of renewable energy, critical raw materials, cost, and return on investment, albeit with potential differences in interpretation, are increasingly becoming central considerations in the decision-making processes of individuals, businesses, and governments alike. Based on these findings, specific aspects of technology design, namely scale, location, integration, and synthesized product, that can impact a wide range of identified values, are discussed.

This report outlines the findings of an investigation conducted by the Responsible Sensing Lab, philosophy of technology experts from the ESDiT consortium (Ethics of Socially Disruptive Technologies) and representatives from the Smart Mobility Program of the city of Amsterdam. The investigation employs a research through design approach, merging prototyping activities, empirical studies, and philosophical reflection. It aims to explore the Driving for Values concept, focusing on car drivers’ experience of the value of autonomy and its relation to the notions of acceptability and acceptance. The Driving for Values system is framed as a voluntary navigation aid providing car drivers with so called “social routes”, which supports the municipality in fostering a variety of public values such as livability and air quality, by managing the use of the public space. Autonomy is here conceptualized as involving two main components: i) the ability to freely choose among different options and ii) the availability of meaningful options, i.e options that enable the agent to decide and act on the basis of their own reasoned values and commitments. Acceptance is conceptualized as the willingness to use the app. Acceptability refers to the system’s adherence to moral norms and principles. The goal of this investigation is to design and evaluate a variety of potential features of the Driving for Values system considering their impact on car drivers’ experience of autonomy and the effects on acceptance and acceptability of the system. Seven studies with a total of approximately 65 participants (including citizens of Amsterdam, designers and researchers) were conducted. In these studies, participants engaged with different versions of the Driving for Values system and compared their features. The insights from these studies together with insights gathered from monthly workshops with experts from academia and municipality representatives are the basis of the recommendations presented below. These recommendations are intended to support the municipality of Amsterdam in further researching and designing the Driving for Values and similar systems.

This paper is the introduction to a topical collection on “Changing Values and Energy Systems” that consists of six contributions that examine instances of value change regarding the design, use and operation of energy systems. This introduction discusses the need to consider values in the energy transition. It examines conceptions of value and value change and how values can be addressed in the design of energy systems. Value change in the context of energy and energy systems is a topic that has recently gained traction. Current, and past, energy transitions often focus on a limited range of values, such as sustainability, while leaving other salient values, such as energy democracy, or energy justice, out of the picture. Furthermore, these values become entrenched in the design of these systems: it is hard for stakeholders to address new concerns and values in the use and operation of these systems, leading to further costly transitions and systems’ overhaul. To remedy this issue, value change in the context of energy systems needs to be better understood. We also need to think about further requirements for the governance, institutional and engineering design of energy systems to accommodate future value change. Openness, transparency, adaptiveness, flexibility and modularity emerge as new requirements within the current energy transition that need further exploration and scrutiny.

Design for Values is an approach that aims at integrating moral values pro-actively in the design of new technology. While this approach originates from outside the field of Technology Assessment (TA), it may now be seen as part of it. This handbook contribution first discusses the emergence, history and some of the theoretical backgrounds of Design for Values. It then describes in more detail how a typical Design for Values process would look like paying attention to: 1) stakeholder analysis and value identification; 2) conceptualizing and specifying values, 3) identifying and dealing with value conflicts, 4) prototyping and testing to validate whether the design indeed embodies the relevant values and 5) ongoing-monitoring for unexpected side-effects and value change, possibly leading to adaptations in the design. Attention is also paid to methods for, and applications of Design for Values, and some of the main limitations and criticism of the approach.

In recent decades, distinct national approaches to engineering ethics have evolved, each tailored to its unique contextual factors. These contextual disparities make it unfeasible to transfer one country's engineering ethics approach directly into another. This calls for a compelling need to enhance our comprehension of engineering ethics within specific national contexts. This paper introduces a novel conceptual framework for national engineering ethics (NEE), inspired by Elinor Ostrom's Institutional Analysis and Development (IAD) framework. The NEE framework categorises engineering ethics activities into three core pillars: research, education, and professional behaviour. This framework facilitates a comprehensive analysis of these activities across three levels—operational, organisational, and governmental. The proposed framework offers a valuable resource for scholars seeking a deeper understanding of engineering ethics within specific national boundaries, enabling structured reporting and analysis. It serves as a critical step towards achieving mutual understanding, allowing for cross-national comparisons and the exchange of best practices. Additionally, it provides a structured platform for policymakers and developers to devise strategies for implementing engineering ethics at the national level.

This editorial paper for the special section on “Modelling Values in Socio/Technical/Ecological Systems” introduces interdisciplinary perspectives on values and reflects on growing appeals for modelling values. In public and academic discourses, values typically relate to matters of importance (e.g., beliefs, priorities) and principles about what is considered to be good (e.g., moral values) and are often seen as shaping individual and collective behaviour. As shown by eight contributions to this special section, it is relevant for social simulation modelling to dive deeper into embedding values in models in order to explore behavioural change on different levels and across contexts. Our goal with this special section is to stimulate interest in developing various approaches that study and operationalise values in agent-based models to investigate the complex problems raised in social, socio-technical and socio-ecological systems. We conclude with a call for future research to be explicit in their modelling assumptions, thus fostering a vigorous foundation for scientific discourse.

Digitalization and datafication of financial systems result in more efficiency, but might also result in the exclusions of certain groups. Governments are looking for ways to increase inclusions and leave no one behind. For this, they must govern an organizational ecosystem of public and private parties. We derive value-based requirements through a systematic research methodology and iteratively refine design principles for achieving inclusivity goals. This refinement process is enriched by interviews with field experts, leading to the formulation of key Design principles: the essential role of inclusive metrics, leveraging alternative data sources, ensuring transparency in loan processes and the ability for decision contestation, providing tailored credit solutions, and maintaining long-term system sustainability. The government's role is to ensure a level playing field where all parties have equal access to the data. Following the principles ensures that exclusion and discrimination become visible and can be avoided. This study underscores the necessity for system-level transformations, inclusion-by-design, and advocacy for a new system design complemented by regulatory updates, new data integration, inclusive AI, and organizational collaborative shifts. These principles can also be used in different data-driven governance situations.

Value and moral change have increasingly become topics of interest in the philosophical literature. Several theoretical accounts have been proposed. These are usually based on certain theoretical and conceptual assumptions. Their strengths and weaknesses are often difficult to determine and compare because they are based on limited empirical evidence. We propose agent-based modeling to build simulation models that can theoretically help us explore accounts of value change. We can investigate whether a simulation model based on a specific account of value change can reproduce relevant phenomena. To illustrate this approach, we build a model based on the pragmatist account of value change proposed by Van De Poel and Kudina (2022). We show that this model can reproduce four relevant phenomena, namely 1) the inevitability and stability of values, 2) societies differ in openness and resistance to change, 3) moral revolutions, and 4) lock-in. This makes this account promising, although more research is needed to see how well it can explain other relevant phenomena and compare its strengths and weaknesses to other accounts. On a more methodological level, our contribution suggests that simulation models might be useful to theoretically explore accounts of value change and make further progress in this area.

This white paper aims to provide an introduction to the topic of Design for Justice for a wide audience. It demonstrates ongoing research on this topic by the TU Delft community and contributes to the exchange of relevant knowledge and expertise, as one of the outcomes of the activities organised for the Delft Design for Values Institute’s annual theme ‘Design for Justice’. This document includes recommendations on how to foster Design for Justice, which are not just relevant for designers, engineers, and academic researchers, but also for educators and policy makers.

The idea that technologies influence society—both positively and negatively—is not new. This is mainly the terrain of the philosophy and the ethics of technology research. Similarly, design research aims to help create new technologies in line with individual, social, and societal needs and values. Against this backdrop, it seems essential to expose relations between design and philosophy of technology research, particularly from a methodological perspective. The main goal of this paper is to suggest a preliminary overview of methods and approaches that can inspire and inform interdisciplinary collaboration and, with that, systematic engagement with ethics in design processes. Through interdisciplinary exchange, we propose a preliminary typology of ethics-informed methods and approaches based on two main dimensions, namely theory-grounded approaches to theoretically-flexible techniques and assessment to accompaniment. This mapping intends to help navigate the ethical qualities of selected methods from both disciplines, and it aims to create a platform for fruitful interdisciplinary conversations.

Technologies have all kinds of impacts on the environment, on human behavior, on our society and on what we believe and value. But some technologies are not just impactful, they are also socially disruptive: they challenge existing institutions, social practices, beliefs and conceptual categories. Here we are particularly interested in technologies that disrupt existing concepts, for example because they lead to profound uncertainty about how to classify matters. Is a humanoid robot - which looks and even acts like a human - to be classified as a person or is it just an inert machine? Conceptual disruption occurs when the meaning of concepts is challenged, and such challenges may potentially lead to a revision of concepts. We illustrate how technologies can be conceptually disruptive through a range of examples, and we argue for an intercultural outlook in studying these socially disruptive technologies and conceptual disruption. Such an outlook is needed to avoid a Western bias in labeling technologies socially or conceptually disruptive, as this outlook takes inspiration from a broad range of philosophical traditions.

Technologies shape who we are, how we organize our societies and how we relate to nature. For example, social media challenges democracy; artificial intelligence raises the question of what is unique to humans; and the possibility to create artificial wombs may affect notions of motherhood and birth. Some have suggested that we address global warming by engineering the climate, but how does this impact our responsibility to future generations and our relation to nature? This book shows how technologies can be socially and conceptually disruptive and investigates how to come to terms with this disruptive potential. Four technologies are studied: social media, social robots, climate engineering and artificial wombs. The authors highlight the disruptive potential of these technologies, and the new questions this raises. The book also discusses responses to conceptual disruption, like conceptual engineering, the deliberate revision of concepts.

Hybrid potato breeding is an emerging technology that can have a strong impact on the potato sector by replacing seed potatoes with true seeds. The Netherlands is a world leader in certified seed potatoes and a number of Dutch companies play a pivotal role in the development of this technology. This implies a certain responsibility for the consequences and conditions of its implementation and we therefore explored how Dutch potato breeding companies see their role and responsibility especially in low- and middle-income countries in the context of the United Nations Sustainable Development Goals (SDGs). From interviews, it appears that most potato breeding companies emphasise the promising role of hybrid potato breeding in achieving SDGs. They also stress that their core business is at the heart of corporate social responsibility as it contributes to the SDGs. We also observed that for the introduction of new varieties they often rely on trickle-down mechanisms, where local farmers are rather passive recipients, rather than being actively involved in strategic choices of innovation. It may explain why the concept of responsible research and innovation (RRI), which emphasises the active involvement of society and affected stakeholders, is relatively unknown in the sector. The main approach in the sector may be labelled as a ‘solution strategy’ where dominant actors rely on their expertise to solve problems. However, the attainment of SDGs should rather be considered as a wicked problem, characterised by complexity, uncertainty and multiple actor’s perspectives. A ‘negotiation strategy’, which is more inclusive and stresses the need of negotiation between different perspectives and interests, may fit better. From the perspective of RRI it is argued that insights from participatory breeding and farmer variety selection traditions and the concept of benefit sharing may be considered as promising negotiation strategies that can contribute to potato breeding practices for the attainment of SDGs.