A growing awareness of bias in artificial intelligence (AI) systems has recently emerged, leading to an increased number of publications discussing ethics in AI. Nevertheless, the specific issue of gender bias remains under-discussed. How can design contribute to preventing the emergence of gender bias in AI-driven systems? To answer this question, we investigated the current state of AI ethical guidelines within the European Union. The results revealed that most guidelines do not acknowledge gender bias but address discrimination. This raised our concerns, as addressing multiple biases simultaneously might not effectively mitigate any of them due to their often-unconscious nature. Furthermore, our results revealed a lack of quantitative evidence supporting the effectiveness of bias prevention implementation methods and solutions. In conclusion, based on our analysis, we propose four recommendations for designing effective guidelines to tackle gender biases in AI. Moreover, we stress the central role of diversity in embedding the gender perspective from the beginning in any design activity.

This paper analyses a new phenomenon to date poorly researched both in entrepreneurship and Design Thinking literature: Design-Intensive Start-ups (DIS), i.e. start-ups that focus on design as primary source for their development. Two main questions underpin the study: what are the specific features that describe design-intensive start-ups? Which are possible conceptual tools supporting designers in the creation of their own design-based enterprises? A multiple case studies protocol was adopted to investigate the first question. According to our results, DIS diverge from New-Technology Start-ups on several dimensions, and represent an alternative entrepreneurial model, which is not supported by extant literature. Currently, there are no tools helping designers to become entrepreneurs. Therefore, we developed a set of Design Thinking tools addressing the specific traits of DIS in the steps of their creation and evolution. Such tools are intended to support the decision-making process of designers-entrepreneurs in the foundation of their own start-ups.

Human–Machine Interfaces (HMIs) in autonomous driving technology have recently gained significant research interest in public transportation. However, most of the studies are biased towards qualitative methods, while combining quantitative and qualitative approaches has yet to receive commensurate attention in measuring user acceptance of design outcome evaluation. To the best of our knowledge, no standardized test procedure that combines quantitative and qualitative methods has been formed to evaluate and compare the interrelationships between different designs of HMIs and their psychological effects on users. This paper proposes a practical and comprehensive protocol to guide assessments of user acceptance of HMI design solutions. We first defined user acceptance and analyzed the existing evaluation methods. Then, specific ergonomic factors and requirements that the designed output HMI should meet were identified. Based on this, we developed a protocol to evaluate a particular HMI solution from in- and out-of-vehicle perspectives. Our theoretical protocol combines objective and subjective measures to compare users’ behavior when interacting with Autonomous Vehicles (AVs) in a virtual experimental environment, especially in public transportation. Standardized testing procedures provide researchers and interaction designers with a practical framework and offer theoretical support for subsequent studies.

Automated Shuttle buses (ASB) are considered an essential and sustainable direction for the future application of autonomous driving technology in public transportation. As the driver’s role gradually decreases and disappears, the Human–Machine Interface (HMI) for information exchange and communication between users and ASB takes a more prominent role and progressively becomes a hotspot in research. However, the unpredictability and complexity of autonomous driving, an exceptionally fast-growing technology, have hindered its future study. This work first reviewed related literature in three categories: internal, external, and station of the ASB. Secondly, the importance of systemic and speculative design is affirmed by exploring existing HMI designs for ASB. Thirdly, the concepts for ASB resulting from three parallel workshops were analyzed. Finally, online questionnaires and interviews completed the critical reflection and discussion. The results show that the introduction of tools and methods related to systemic and speculative design into the design process of the HMI for ASB may help designers to think critically about the future uncertainty of ASB and to deal with the complexity of the system.

The integration of automated vehicle (AV) technology in public transportation systems offers promising opportunities to improve the flexibility and safety of the traffic environment. However, user acceptance remains a critical challenge in the field of human-machine interaction for the effective deployment of shared autonomous vehicles (SAVs). This study presents a design framework aimed at enhancing user acceptance through human-machine interface (HMI) design tailored to SAVs. The framework is developed in adherence to relevant interaction design principles, following a systematic approach encompassing three key steps: analysis, synthesis, and evaluation. It integrates user acceptance factors into the design process, providing a structured method for designers. The framework was iteratively refined through interviews with three international domain experts; a focus group discussion with 10 researchers and professionals specializing in automotive interaction designers; and a workshop with 30 students and designers. The results demonstrate the framework’s ability to guide the development of user-acceptable HMI solutions. The paper concludes by emphasizing the need for further exploration into how user acceptance factors evolve over time and how real-world testing can validate the framework’s effectiveness in promoting user acceptance and satisfaction.