Derailing a high-speed train: Limitations of Agile in the AI development with marginalized communities
Aida Kalender1, Giovanni Sileno2
1SIAS | Socially Intelligent Artificial Systems Group , Informatics Institute, Faculty of Science, University of Amsterdam; 2SIAS | Socially Intelligent Artificial Systems Group , Informatics Institute, Faculty of Science, University of Amsterdam
This paper will examine insights gleaned from the Horizon Europe-funded CommuniCity project to evaluate the scope and effectiveness of recent smart city interventions in the social domain aimed at fostering responsible digital transformation with a focus on marginalized communities.
Our analysis is informed by scholarship in Science and Technology Studies (STS), which emphasizes how historical, social, and cultural factors, along with the interests of actors, shape technologies and influence future societal conditions. This perspective underscores the political significance of technologies in determining social orders, highlighting the importance of understanding the creators, development processes, and contextual factors surrounding technological production (Pinch and Bijker,1984; Jasanoff, 2004; Winner, 1980).
This analysis assesses the impact of the CommuniCity project through the perspective of critics of the "piloting society," as articulated by Ryghaug and Skjølsvold (2021), who identify pilot and demonstration projects as pivotal modes of innovation in contemporary energy and mobility transitions. The authors contend that such projects serve as significant political arenas for shaping future socio-technical orders. Within CommuniCity, the piloting process, as described by key actors involved in developing this procedural framework, is compared to “a high-speed train that, once it takes off, cannot be halted”.
Although this approach in the CommuniCity project is termed Agile piloting, it does not allow for substantive changes to the framework or facilitate the inclusion of various marginalized communities in ways that diverge from a top-down methodology. Moreover, the chosen epistemological framework for piloting with marginalized communities within the CommuniCity project significantly influences how the concept of co-creation—central to the project’s ethical considerations—is articulated and practically implemented. While CommuniCity Agile piloting permits co-creation "for" and "with" marginalized communities, it largely overlooks the broader movement aimed at democratizing digital technologies through lenses of social justice, inclusion and equity, which we refer to as co-creation "by," along with the vision of the types of societies we aspire to create through innovation (Jasanoff, 2018).
This paper further analyzes the ethical, societal, and political implications of this conception of digital innovation and co-creation with marginalized communities, as evidenced in the CommuniCity project, and engages in a discussion regarding the extent to which these approaches promote or hinder democratic participation and the broader application of technologies for social change. The paper additionally proposes ways in which these high-speed top-down innovation frameworks can be decelerated through reflective loops and by incorporating out-of-the-box thinking modules to alleviate the rigidity of the model.
Grasping the impact of artificial intelligence on the tourism industry
Marcel Heerink
Saxion university of applied sciences, Netherlands, The
This paper examines and discusses the multifaceted impact of artificial intelligence (AI) on the tourism industry, focusing on current applications and their effects, showing the evolution from simple expert systems to sophisticated machine learning algorithms reshaping travel experiences.
It identifies several key areas of AI application in tourism. Firstly, in customer service and personalization, AI algorithms analyze user preferences and behaviors to provide personalized recommendations for destinations and accommodations (García-Madurga & Grilló-Méndez, 2023). AI-powered chatbots and virtual assistants offer 24/7 customer support and booking assistance (Ukpabi et al., 2019), while voice-activated AI devices enhance guest experiences in hotels.
Regarding operational efficiency, machine learning algorithms optimize revenue management through dynamic pricing. AI enables precise inventory management and demand forecasting (Samala et al., 2020), while predictive analytics help businesses make informed decisions about resource allocation.
In terms of customer experience enhancement, facial recognition technology streamlines check-in processes and enhances security (Buhalis & Leung, 2018). Augmented Reality combined with AI offers immersive tour experiences, while AI-powered translation services break down language barriers. Additionally, AI enhances safety through facial recognition and biometric authentication.
Recent survey data from YouGov reveals significant adoption trends in the industry. The research shows that 42% of travelers have either used AI in travel planning or express interest, while 28% prefer traditional planning methods. Language translation assistance has emerged as the most popular AI tool, used by 25% of British and 31% of American travelers. Personalized recommendations and AI-powered reviews are also widely used among travelers.
Both opportunities and challenges emerge from this overview. While AI offers unprecedented advances in personalization and efficiency, the industry must address concerns about environmental and social impact, data privacy, maintaining human interaction in hospitality, ensuring accessibility for all travelers regardless of technological preferences and aiming for optimal inclusiveness.
In many aspects the integration of AI is transforming how travel businesses operate and how travelers experience their journeys. Looking ahead, the industry is moving toward more sophisticated, integrated systems that blend physical and digital aspects of travel. Successfull adoption will depend on responsible implementation that balances technological innovation with authentic human experiences. However, future research is needed especially on ethical considerations regarding inclusivity and societal impact.
References
Buhalis, D., & Leung, R. (2018). Smart hospitality—Interconnectivity and interoperability towards an ecosystem. International Journal of Hospitality Management, 71, 41-50.
García-Madurga, M. Á., & Grilló-Méndez, A. J. (2023). Artificial Intelligence in the tourism industry: An overview of reviews. Administrative Sciences, 13(8), 172.
Kong, H., Wang, K., Qiu, X., Cheung, C., & Bu, N. (2023). 30 years of artificial intelligence (AI) research relating to the hospitality and tourism industry. International Journal of Contemporary Hospitality Management, 35(6), 2157-2177.
Samala, N., Katkam, B. S., Bellamkonda, R. S., & Rodriguez, R. V. (2020). Impact of AI and robotics in the tourism sector: A critical insight. Journal of Tourism Futures, 8(1), 73-87.
Ukpabi, D. C., Aslam, B., & Karjaluoto, H. (2019). Chatbot adoption in tourism services: A conceptual exploration. In Robots, Artificial Intelligence, and Service Automation in Travel, Tourism and Hospitality (pp. 105-121). Emerald Publishing Limited.
Battery development beyond justice. A care-based energy ethics
Rafaela Christina Hillerbrand
KIT, Germany
This paper considers the ethics of batteries as an enabler for the transition towards more sustainable energy. We argue that to put energy justice into practice, it is crucial to set focus on the responsibility and agency of engineers designing the energy transition. Building on care ethics, mid-level principles for engineers developing and designing batteries are suggested.
Problem statement: Climate change and limited fossil resources press for a transition towards a more sustainable energy system. Many countries foster a pathway from a fossil-based energy sector to more, or even all renewable energy carriers. In the transition towards more renewable energy, batteries are seen as central enabling technologies for a greener energy future as they provide a very versatile way of storing and supplying electricity. However, batteries may have severe negative impacts on those living today. For example, raw material extraction for batteries (cobalt, lithium, nickel, or other) has tremendous negative social and economic impact on those who mine the batteries and their communities. These societal groups will not directly profit from the energy transition that happens elsewhere in the world. This seeming injustice is further aggravated by laws on recycling in Western countries that will keep the battery metals in a Western material cycle. Over the last decades energy justice emerged as a new crosscutting research agenda to integrate such justice considerations that go beyond intergenerational aspects.
Aim and approach: This paper considers the ethical implications of batteries as enablers of the energy transition considering the full cycle of raw material extraction, production, and recycling. We firstly highlight open ethical questions that a farmwork framework based on energy-justice leaves. Large parts of the energy justice debate approach ethical concerns on a somewhat course-grained level, addressing justice issues mainly on the level of policymaking, laws, regulations, and alike. This “macro” level is important, but our analysis will show that in the case of batteries, energy justice considerations will remain incomplete when the level of the engineers, the “micro” level, is not addressed. The working engineers have to be guided by midlevel principles on how to design and operate the energy systems and its subsystems in a more just way.
Secondly, we turn to care ethics as an ethical approach to augment (not to replace) justice consideration and adumbrate a way of how the responsibility for a just and fair energy transition towards more a sustainable energy system can be put into practice. We suggest that care ethics, though originally proposed as a counter project to theories of justice, may help here to fill in missing pieces in the normative framework.
Our argument seems to hold not only for batteries, but that whenever solutions for a greener energy future are looked for in technological solution (instead of, for example, behavioral change to reduce energy consumptions), then energy justice considerations also have to look at the level of the engineers and supply them with ethical guidance, i.e. a midlevel account based on care ethics.
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