The 2006 health care reforms in the Netherlands were aimed at improving the affordability, accessibility, and quality of health care, as well as freedom in health care. However, the reality is that since the reforms (which include the privatisation of health-care insurance), costs have further increased and accessibility has decreased while freedom of choice has declined. The reforms reduced freedom, while increasing costs and reducing accessibility. The aim of this thesis is to investigate whether these issues stem from a deeper (Utilitarian) philosophical foundation of how health care is currently funded and to propose a mode of funding founded on Aristotelian principles that would be in support of freedom without adversely affecting (or even improving) costs, accessibility and quality The analysis of the system of Managed Care (in Chapter 2) and its implementation in The Netherlands (in Chapter 3) suggests that the rising costs of health care may be related at least in part to the utilitarian foundation of this system (with its utility-maximising consumer and its profit-maximising producer who, in an oligopoly like the health-care market, is able to generate super-normal profits), in part to the heavy administrative load associated with Managed Care, and in part due to contracting practices. All of which also restricts freedom of choice. Aristotle's ethics, specifically his extit{Nicomachean Ethics}, underlines the importance of freedom (of deliberation) as the quintessential requirement for eudaimonia. If this were taken as the philosophical foundation for the health care system, then patients and health care providers would be able to make informed choices that align with their personal goals and values. This freedom of deliberation stands in stark contrast with protocolisation, standardisation and homogenisation that Managed Care brings. Such a system creates a 'monoculture' in which it is difficult to find discernible differences in price and quality, making it equally difficult to identify possible trade-offs between the two and implications of such trade-offs. In Chapter 4 I propose a mode of funding Dutch health care that safeguards freedom of deliberation in health care that would be in line with the Dutch socio-economical environment and political system. The proposed Health Care system is a universal health care system with a single-payer that covers all health care expenses; where medical decision/treatments are made autonomously by client and practitioner without meddling/pressure/ruling by other parties who are not practising health care; where the funding of health care is a matter of transparent deliberation between all parties and a part of political discourse. By prioritising freedom of deliberation, the proposed reforms address the limitations of Managed Care's utilitarian philosophy and offers a more human-centred approach to health care. A system that is based on Aristotelian philosophy creates an environment that encourages open and honest communication between all parties involved and is expected to improve all relevant aspects of the Dutch health care system and health itself. The suggested reforms are far reaching and may seem unrealistic. Its proper functioning would indeed require substantial social reform in all spheres of social life (economic, legal-political, and cultural), though they remain entirely in-line with Dutch socio-econo-political reality. In conclusion, this thesis argues that the Netherlands' health care reform should prioritise freedom of deliberation (the fundamental requirement for eudaimonia). As such individuals' well-being and values are prioritised, which is expected to have beneficial effects including reducing costs and improving the overall quality of care without diminishing access to it. Free deliberation and subsequent cooperation are thought to have more potential than competition.

Automated driving systems (ADS) can improve traffic safety, improve accessibility and reduce environmental impact (Shladover, 2016). On the contrary, on May 7th 2016, a fatal accident with a Tesla on autopilot in U.S. Florida was a harsh reminder that the technology is still in its testing phase (Greenemeier, 2016). In complex technical systems like ADS technical failure may occur, which forms a serious threat to human well-being. Moreover, studies have shown that citizens are very concerned about deliberate misuse of ADS (Kyriakidis, Happee, & De Winter, 2015), e.g. people purposely abusing ADS to cause damage or even hurt someone. Therefore, according to many experts, the implementation of ADS does not only entail technical issues but also normative issues. To bridge the gap between technical- and normative issues, responsible innovation can be applied (Santoni de Sio, 2016). Friedman et. al. (2006) propose value-sensitive design to achieve responsible innovation via technical-, empirical- and conceptual research. As following from responsible innovation and value-sensitive design and in particular its focus on empirical research as one of its necessary elements, in this research an effort is made to use empirical research methods to provide more insights in normative issues of automated driving systems (ADS). The focus lies on social acceptance, particularly with respect to traffic safety. Also accessibility, environmental impact and heterogeneity among citizens will be analysed. Social acceptance is defined as “a person's assent to the reality of a situation, recognizing a process or condition (often a negative or uncomfortable situation) without attempting to change it, protest, or exit” (Fish, 2014, page 1). The following questions will be answered in this research: What is the social acceptance of automated driving systems from the perspective of safety, accessibility and environmental impact and what is the corresponding heterogeneity? 1. What percentage of citizens thinks automated driving systems are socially accepted? 2. How is the social acceptance influenced by safety, accessibility and environmental impact? 3. Are traffic fatalities caused by automated vehicles valued differently than current traffic fatalities? 4. Is there heterogeneity in the social acceptance among citizens? A survey is chosen as research method since it is a relatively inexpensive, flexible method to achieve extensive information about characteristics of a population. After an extensive theoretical analysis, seven attributes were identified that possibly influence the social acceptance: level of automation, road exemption, travel time, emissions, human error fatalities, technical failure fatalities and deliberate misuse fatalities. After the experiment was fine-tuned by a pilot study, it was held among a representative sample of 510 Dutch adults during the spring of 2017. The respondents had to state if they were in favour or against ADS for each of the twelve hypothetical futures that were presented to them. In these hypothetical futures, the attributes were systematically varied and described as a change to the current situation. Using a MNL RUM model, the results show that 63% of all citizens prefer ADS over the current system. It is therefore concluded that citizens have a high social acceptance and thus are rather positive towards ADS. Also, citizens prefer a system where human drivers are still in control and can intervene in case necessary. Next, it is concluded that the social acceptance is mostly influenced by fatalities caused by automated vehicles (AVs), while travel time is the least important attribute. However, the differences in influence of the attributes were not substantial. Safety, accessibility and environmental impact are all important for the social acceptance. Nevertheless, technical failure fatalities weigh as much as 4 human error fatalities. For deliberate misuse fatalities this is a factor 5.5. Although these relations coincide with literature, the magnitude is larger than expected. It implies that ADS have to be very safe in order to reach social acceptance. Since AVs are still ‘learning’ how to drive, this might cause problems for current and future experiments. A latent class choice model is estimated to answer the final research question. Results show that large heterogeneity exists among citizens in the social acceptance. Citizens can be segmented into three classes (% of citizens): automated driving enthusiasts (32%), central mass (52%) and risk-averse class (16%). Contradictory to average citizens, automated driving enthusiasts prefer high automation levels. Even so, they still weigh fatalities caused by AVs as much as 3 human error fatalities on average. The central mass shows similar results to the results of the MNL model estimated on the full sample. The risk-averse class has a strong dislike for fatalities caused by AVs. This class weighs technical failure fatalities (deliberate misuse fatalities) as much as 5.5 (10) human error fatalities. In conclusion, primarily two discrepancies are identified that are critical for the implementation of ADS: 1) High social acceptance versus strong dislike for fatalities caused by AVs; 2) Citizens who are enthusiastic about ADS versus citizens who are risk-averse. They lead to the following recommendations: The social acceptance for ADS is high, so it is recommended for policy makers to have a positive and active approach towards ADS. By conducting experiments for professional users, safety risks can be minimalized while a learning curve is ensured. Also technology producers and policy makers should intensify research into cooperate driving. According to experts, ADS and cooperate driving are inseparable (Shladover, 2016), but globally the research into cooperate driving is lacking (Roland Berger, 2017). Since cooperate driving can lead to an increased risk of deliberate misuse, it is deemed critical for the implementation of ADS. Next, policy makers and especially the RDW should review the licensing of AVs. Currently, hardly any restrictions are in place for the licensing of AVs, which can cause dangerous situations on public roads. Finally, information campaigns can help to make citizens aware of the risks and benefits of ADS.

The use of machine learning systems has great potential to better predict probabilities of default for credit underwriting. Despite this advantage, herewith there exists the substantial risk of discrimination. Moreover, machine learning models with the highest prediction-accuracy are often the least explicable (i.e. explainable). Nonetheless, explicability is needed to create accountability of automated credit decisions by machine learning systems. Furthermore, there exists a regulatory need for explicability of machine learning systems in the General Data Protection Regulation (GDPR) and the Consumer Credit Directive (CCD). Besides that, an ethical- and societal need exists for explicability. Within the exploration of literature, it becomes clear that research lacks on how to move from a high-level principle like explicability, towards a prospective assessment of a machine learning use case on this principle, it lacks a multi-disciplinary perspective, and it misses an assessment framework that can guide decision-makers within machine learning use cases, aligned with a multi-organizational development lifecycle. This research aims to design a prospective pragmatic assessment framework that can guide decision-makers, within machine learning applications in European credit underwriting cases from the point of view of explicability. To accomplish this, the Design Science Research Methodology (DSRM), complemented with the Value Sensitive Design (VSD) approach, is utilized. To this end, the Explicability Assessment Framework (EAF) was developed. This framework is adapted to the context- and explanation characteristics of the case, and aligns with the CRISP-DM development lifecycle. It was found in two case studies that the framework helps with the decision-making whether a machine learning system is sufficiently explicable or not. Lastly, a wide range of future research areas is identified that needs attention: empirical validation and expansion of the framework, the relevance for automated explanation creation, the scalability to other context and a large amount of explanations, and the practical perspective regarding adoption in the industry.

The support for the hybrid work setting increased during the pandemic, but there are a lot of challenges to overcome. It is important to study the hybrid work setting. Based on the findings in the existing literature it is found that little research has been done on the effect of the hybrid work setting on individual employee performance. In the current research this is investigated by looking at the relationship between the balance between office and remote work and individual employee performance, as well as the influence of six employee behaviors on this relationship. In addition, the ideal balance between office and remote work in the hybrid work setting is studied. To find an answer to the objectives of the study, the following research question is studied “How is the balance between office and remote work related with individual employee performance in the manufacturing industry?”. The research question is supported by two sub questions (1) “How do employee behaviors affect the relationship between the balance of office and remote work and individual employee performance?” and (2) “What is the ideal balance between office and remote work in the hybrid work setting?”. Answers to the research questions are found by conducting a quantitative self-administered survey. The conceptual model of the survey is based on a literature review. The model consists of an independent variable – remote work percentage, mediating variables – attitudes towards remote work, work engagement, well-being, job satisfaction, communication, and trust relationship, and a dependent variable – individual employee performance. The target population of the study consists of employees, with a hybrid office job, working at companies operating in the manufacturing industry in the Netherlands. The data of the survey is analyzed with SPSS. Sub-question one is answered by looking at the findings. Based on the findings it is clear that the six employee behaviors are based on this study not significantly affecting the relationship between the balance of office and remote work and individual employee performance. For employees working for companies in the manufacturing industry in the Netherlands. Sub-question two is answered by looking at the preferred balance of the employees with regard to office and remote work. Based on the findings, the preferred balance is two days remote work in a four- or five-day work week and one day remote work in a two- or three-day work week. The main research question is answered by looking at the findings. Based on the findings it is clear that the balance between office and remote work is not affecting individual employee performance significantly direct or indirect. One possible reason for the relation not being significant is that there is still a lot unknown about the true effect of the hybrid work setting in comparison with the established work settings in the manufacturing industry. Based on the findings, companies in the manufacturing industry are recommend to start with making new work agreements based on the hybrid work setting. This, because the existing work agreements are based on office work. A good starting point for the agreements could be involving the employees in the decision-making process of the new agreements. By looking not only at their preferred balance of office and remote work, but also taking other insights of the employees with regard to hybrid work into consideration. In addition, the companies should pay attention to the role of communication in the hybrid work setting, because communication is key when employees have to work together remotely with other colleagues.

The increasing use of robots in the workplace presents a valuable opportunity to diversify the workforce by including underrepresented groups such as ethnic minorities and the elder population. However, high unemployment among these social groups shows that the opportunity to boost inclusivity and diversity is not grasped. Seizing this opportunity presents several challenges, especially since diversity can complicate the innovation process. Innovation is a complex multifaceted process influenced by numerous factors, among which formal and informal institutions. Formal institutions are written rules such as laws, standards and obligations, while informal institutions are unwritten rules, such as social and cultural norms, that shape people's perceptions and behaviors. Diversity can be related to social groups holding peculiar norms/beliefs that can conflict with other social norms or regulations. The role of formal and informal institutions in diversity and inclusion initiatives has been largely overlooked in the HRI literature, but existing studies suggest that institutions play a crucial role in enabling/hampering inclusion and diversity through technology. In this research, I make use of qualitative research and the RRI approach to analyze the complex socio-technical system in which robots are implemented and used in the real-world context of the KLM baggage handling facilities at Amsterdam Airport. The aim of this study is to build grounded theory through the analysis of the impact that institutions have on the implementation and utilization of robotic technology in the employment of a workforce that is diverse in terms of age, ethnicity, and race. The research question guiding the research is: “How do formal and informal institutions shape the implementation and use of robots at work aimed at including a diverse workforce?” This research question aims at tackling two different aspects of deploying robots at work: implementation and utilization. The focus on implementation pertains to the analysis of the process by which a diverse workforce is included or not in the deployment of robots in the workplace, and the role that institutions play in shaping this process. The focus on utilization pertains to the analysis of the role that institutions play in shaping the ability and willingness of a diverse workforce to use robots in the workplace. When it comes to the implementation of robots at work, results show that if there are no formal institutions in place to include a diverse workforce in the implementation process, then informal institutions, such as a willingness to use technology, play a prominent role in determining the likelihood that diverse workforce will be included in the process or not. In the Dutch context, factors like age or ethnic diversity do not affect the positive perception of robots at work and willingness to use technology, thus these diverse identities do not influence the participation of the diverse workforce in the implementation of robots at work. When it comes to the utilization of robots, diversity plays both a direct and indirect role. The direct role is related to formal institutions, for instance standard requirements to operate the robot, that may exclude certain ethnic/race groups with different physical characteristics from using the robot. An example of physical characteristics that play a role in the Dutch context are the average height and left-handedness. The indirect effect pertains to the influence of age diversity within the workforce on the formation of informal institutions, such as social norms. Members of the age diverse workforce may hold positions of opinion leadership within the workplace, enabling them to shape the opinions of their colleagues with regard to the use of robots. This, in turn, can influence the utilization of robotic technology by the workforce as a whole. This study has both strong practical and theoretical implications. From a practical standpoint, this study provides valuable insights for organizations seeking to employ a diverse workforce through the use of robotics. The findings highlight the importance of carefully considering both the practical and social implications of this approach, including the need to take into account the physical requirements of a diverse workforce and the potential influence of diversity on the formation of social norms within the workplace. From a research perspective, this study highlights the suitability of the cs{RRI} approach as a conceptual tool for HRI research to assess the socio-technical systems in robotics is used for diversity and inclusivity purposes. Future research could focus on analyzing the interactions between formal and informal institutions and other diverse identities, such as gender, in the context of implementing robots in the workplace. The main limitations of this study pertain to the limited number of participants and the lack of generalizability to SMME. These firms have different organizational structures and limited financial and intellectual resources, thus, when employing a diverse workforce, they may face considerably different challenges when implementing robotic technology in the workplace.

The implementation of social robots in the healthcare industry is becoming substantial as a consequence of the scarcity of healthcare professionals, rising costs of healthcare and an increase in the number of vulnerable populations. Social robots will be deployed, in increasing numbers, in assisting health care professionals during the provision of care to patients. While research in Human-Robot-Interaction (HRI) has investigated mechanisms for making decisions taken by artificial agents more ethical, there is limited work done in investigating adaptations to HRI that promotes ethical behaviour on the human-side. Moral dilemmas can appear when decisions have to be made regarding patientcare. Dealing with them can be challenging for healthcare professionals since the impact of decisions affect multiple parties and involves different considerations and value-trade-offs of the involved people. There are different approaches in which healthcare professionals can be confronted with moral dilemmas. Based on decision making principles, a robot might assist the health care professionals in ethical decision making with an appropriate reflection or confrontation of the dilemma. This thesis investigates how a social robot can confront a professional with a moral dilemma and what the associated effects are. Following the Socio-Cognitive Engineering (SCE) method, two alternative proto-patterns are created for dilemma confrontation by a robot in a resuscitation scenario: Verbal and Multi-modal confrontation. In such a scenario, the robot displays protests of distress and affect in order to help the professionals carry out systematic reflection of the moral dilemmas they experience. In an evaluation, it is tested whether these confrontation patterns are being perceived as intended, comparing the two confrontation patterns with a neutral scenario.

In the past decade, rapid shifting and evolving technological systems that take trust as part of the design objective (call such systems “trust-inviting systems”) have incredibly transformed the way we interact with others. Think of reputation-based platforms mediating interactions between strangers and other digital services provided by institutions, as well as blockchain systems, which work to shape, respectively, our trust relations with individuals, institutions, and technologies. However, the ways these systems use to facilitate trust are not always justifiable and can lead to negative moral and social consequences if certain parts of the systems are shown to be flawed. By reflecting on several present cases of trust-inviting systems that are experiencing great tension of trust, this thesis argues that trust-inviting systems essentially attempt to interpret, translate, and ultimately institutionalize the idea of trustworthiness in given contexts. However, the ways that trust-inviting systems are using to institutionalize the characteristics of trustworthy persons, institutions, and technologies should not be accepted without scrutiny. For each case analysed here, a discrepancy between the intention to improve trust and trustworthiness and the means that are adopted to facilitate them is shown. Such cleavage is argued to be primarily caused by flawed understanding of the trust concepts and the resulting ill-suited design choices, as well as problems emerged from the implementation process. These issues are proposed to be ameliorated by a recalibration of the understanding of the trust concepts, which has the potential for remedying shortcomings of the current design and development of the systems with forward-looking strategies taking into account a wide range of societal needs, values, and technical properties. In a word, it is argued that trust-inviting digital systems should be designed, developed, and deployed in ways that are aligned with the essence of the trust relation in context, in order to achieve proper trust and trustworthy systems. As such, the pitfalls identified in each case are able to be used as perspectives contributing to building affordances that foster warranted trust and foreclosing affordances that would undermine warranted trust. @en

Artificial intelligence is a technology trend that potentially far exceeds the possibilities of all current state technologies, in a sense that these technologies have self-learning abilities. Organizations that manage to adopt and diffuse these technologies may effectively reach a competitive edge over their competitors faster. However, for large organizations such as traditional banks the question arises how to facilitate this transformation to effectively adopt AI technologies. Despite the fact that AI technologies are still in a relatively premature stage of development, traditional banks in the Netherlands are currently exploring its potential. In this exploratory study we interviewed 19 experts in the field of AI and Banking to identify all relevant challenges that arise when traditional banks adopt AI technologies. Additionally, we explored the importance of top management tech-executive roles as a possible solution to address certain challenges. As a result we have found that traditional banks have no common view or approach on how to adopt AI technologies enterprise-wide effectively. Therefore, the appointment of a new Chief AI Officer role may prove to be a valuable solution to address some of these challenges. However, there is still a mixed view on what this roles’ position, responsibilities and other managerial characteristics should be.

These days, autonomous driving has become a popular topic in different fields and showed its unavoidable developing tendency. With the increasing application of autonomous vehicles, a mixed period of autonomous vehicles (AVs) and conventional vehicles (CVs) is inevitable. Therefore, some traffic management was proposed. Exclusive lanes for AVs are a new way to improve the mixed road environment's traffic capacity. However, the effect of exclusive AV lanes was rarely studied. Therefore, the decision-makers could not clearly understand this new policy's impact. Besides, the existing research content did not provide a detailed quantitative analysis of this new policy, which is very important for decision-makers. Thus, this thesis focused on the exclusive AV lanes and proposed the following research question: Under which conditions are exclusive autonomous vehicle lanes societally beneficial?