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AI beyond Deus ex Machina – Reimagining Intelligence in Future Cities with Urban Experts
Abstract
The current mechanisms that drive the development of AI technologies are widely criticized for being tech-oriented and market-led instead of stemming from societal challenges. In Human-Centered AI discourses, and more broadly in Human-Computer Interaction research, initiatives have been proposed to engage experts from various domains of social science in determining how AI should reach our societies, predominantly through informing the adoption policies. Our contribution, however, seeks a more essential role for social sciences, namely to introduce discursive standpoints around what we need AI to be. With a focus on the domain of urbanism, the specific goal has been to elicit – from interviews with 16 urban experts – the imaginaries of how AI can and should impact future cities. Drawing on the social science literature, we present how the notion of “imaginary” has essentially framed this research and how it could reveal an alternative vision of non-human intelligent actors in future cities.
... We use social imaginaries as a conceptual lens to study the perceptions, understanding, conceptions, and expectations of the practitioners in charge of implementing automation within Amsterdam Airport Schiphol, particularly in the airside context, arguing that automation adoption can be informed by how these practitioners envision its capabilities, limitations, or functionalities and the development pathways that they choose accordingly. This lens has been widely used in prior HCI research [59,74,76,91]. Specifically, we follow the approach of Mlynar et al. [59], where they refer to social imaginaries, as oppossed to sociotechnical imaginaries [40], as "the anonymous, collective, unmotivated force that nevertheless has strong agency to mold the world we live in" (p.3), which they use to study the orientations, symbolic networks, epoch, and world relations of a particular social group (in their case, experts in urbanism) that constitute "support of the orientations and of the distinctions of what matters and what does not to them" (p. ...
... This lens has been widely used in prior HCI research [59,74,76,91]. Specifically, we follow the approach of Mlynar et al. [59], where they refer to social imaginaries, as oppossed to sociotechnical imaginaries [40], as "the anonymous, collective, unmotivated force that nevertheless has strong agency to mold the world we live in" (p.3), which they use to study the orientations, symbolic networks, epoch, and world relations of a particular social group (in their case, experts in urbanism) that constitute "support of the orientations and of the distinctions of what matters and what does not to them" (p. 3). ...
... Imaginaries are collective visions of the future, present, or past [52]. The concept is defined as a "shared network of concepts, images, stories, and myths that make possible common practices and provide a sense of legitimacy" (p.2) [59]. In the CHI and CSCW research communities, we often find imaginaries (e.g., [1,15,23,35,44,52,59,73,74,91]) as a lens to not only surface the assumptions, expectations, anxieties, or social contexts around new technological constructs, but also to map the future position, impact, and functions of those technologies. ...
In organizations, the interest in automation is long-standing. However , adopting automated processes remains challenging, even in environments that appear highly standardized and technically suitable for it. Through a case study in Amsterdam Airport Schiphol, this paper investigates automation as a broader sociotechnical system influenced by a complex network of actors and contextual factors. We study practitioners' collective understandings of automation and subsequent efforts taken to implement it. Using imaginaries as a lens, we report findings from a qualitative interview study with 16 practitioners involved in airside automation projects. Our findings illustrate the organizational dynamics and complexities surrounding automation adoption, as reflected in the captured problem formulations, conceptions of the technology, envisioned human roles in autonomous operations, and perspectives on automation fit in the airside ecosystem. Ultimately, we advocate for contextual automation design, which carefully considers human roles, accounts for existing organizational politics, and avoids techno-solutionist approaches.
... We hypothesize that the inherent differences in the clinical and research practices are in tension with the current role and focus of AI in oncology. So, a meaningful and more adapted development of AI would entail pursuing a human-centric approach, where the incorporation of AI systems in existing -clinical and researchworkflows is not only taken into consideration, but also, is in synergistic agreement with physicians' imaginaries [12,66] of what they want AI to be in oncology. In addition, we argue that HCI's collaborative entanglements with AI research, and its intermediary, yet instrumental, positioning between users and (digital) technology designers, render it a suitable domain to study the aforementioned problem. ...
... This discrepancy is emphasized in the article "Machine Behaviour" by Rahwan et al. [76], who argue that "the scientists who study the behaviours of these [AI agents] are predominantly the same scientists who have created the agents themselves", implying a lack of cross-disciplinary collaboration in AI development. Mlynar et al. [66] further provide grounds for an inclusive, participatory, and rather sociological development of AI, which is different from the "current market-led visions" and is not solely "founded within the [computer and data science] community". ...
... To address this gap, we extend the approach developed by Mlynar et al. [66], which explores expert groups' imaginaries of AI and accounts for their recurrent patterns, as well as conspicuously absent links between the elicited topics. Borrowed from philosophy and the social sciences, l'imaginaire (in French) or the imaginary refers to a "shared network of concepts, images, stories, and myths that make possible common practices and provide a sense of legitimacy" [12, p. 2]. ...
Significant and rapid advancements in cancer research have been attributed to Artificial Intelligence (AI). However, AI's role and impact on the clinical side has been limited. This discrepancy manifests due to the overlooked, yet profound, differences in the clinical and research practices in oncology. Our contribution seeks to scrutinize physicians' engagement with AI by interviewing 7 medical-imaging experts and disentangle its future alignment across the clinical and research workflows, diverging from the existing "one-size-fits-all" paradigm within Human-Centered AI discourses. Our analysis revealed that physicians' trust in AI is less dependent on their general acceptance of AI, but more on their contestable experiences with AI. Contestability, in clinical workflows, underpins the need for personal supervision of AI outcomes and processes, i.e., clinician-in-the-loop. Finally, we discuss tensions in the desired attributes of AI, such as explainability and control, contextualizing them within the divergent intentionality and scope of clinical and research workflows.
... A recent empirical HCI study on AI in future cities [98] highlighted four characteristics of urban intelligence that involve both humans and AI: Contextual, emphasizing the integration of knowledge rooted in human understanding of local contexts; Conscious, advocating for grounding in real-world experiences and interactions over mere quantification and data reliance; Collaborative, highlighting the synergy between tools and information, and between humans and AI; and Controlled, emphasizing the importance of human agency in governing AI interactions. As we shall further see below, these characteristics align with our findings on students' concerns about AI's cooperative role in education. ...
... Such studies remind us to delve deeper into the human values we aim to support, extending far beyond the mere productivity and efficiency that technology could bring. The HCI community has also advocated for solutions that transcend narrow, data-driven approaches (e.g., reflexive AI systems [98]). For instance, the "Whereabouts Clock" [29], which displays family member locations, not only supports family coordination but also contributes to the emotional aspects of family life (though it might also create other problems of its own (e.g., [94])). ...
AI's integration into education promises to equip teachers with data-driven insights and intervene in student learning. Despite the intended advancements, there is a lack of understanding of interactions and emerging dynamics in classrooms where various stakeholders including teachers, students, and AI, collaborate. This paper aims to understand how students perceive the implications of AI in Education in terms of classroom collaborative dynamics, especially AI used to observe students and notify teachers to provide targeted help. Using the story completion method, we analyzed narratives from 65 participants, highlighting three challenges: AI decontextualizing of the educational context; AI-teacher cooperation with bias concerns and power disparities; and AI's impact on student behavior that further challenges AI's effectiveness. We argue that for effective and ethical AI-facilitated cooperative education, future AIEd design must factor in the situated nature of implementation. Designers must consider the broader nuances of the education context, impacts on multiple stakeholders, dynamics involving these stakeholders, and the interplay among potential consequences for AI systems and stakeholders. It is crucial to understand the values in the situated context, the capacity and limitations of both AI and humans for effective cooperation, and any implications to the relevant ecosystem.
... We employed a qualitative approach consisting of semi-structured interviews and a card-sorting task. Semi-structured interviews have been used in previous studies on social media practices [52,71,109] and eliciting future visions across various domains [5,43,84]. To complement the interviews, a card-sorting task was conducted to reveal how activists prioritize their social media needs. This technique, effective both online and offline [19], uncovers key priorities. ...
Social media is central to activists, who use it internally for coordination and externally to reach supporters and the public. To date, the HCI community has not explored activists' perspectives on future social media platforms. In interviews with 14 activists from an environmental and a queer-feminist movement in Germany, we identify activists' needs and feature requests for future social media platforms. The key finding is that on- and offline safety is their main need. Based on this, we make concrete proposals to improve safety measures. Increased control over content presentation and tools to streamline activist workflows are also central to activists. We make concrete design and research recommendations on how social media platforms and the HCI community can contribute to improved safety and content presentation, and how activists themselves can reduce their workload.
... Despite the potential of GAI for bringing playfulness, there is a growing attention to AI systems' risks and harms in public applications, warranting further investigation and consideration [1,27,30,47,50,52,54,88]. GAI may produce socially biased outcomes, be misused, or generate misleading information [9,33,81,82]. ...
Play is pivotal in fostering the emotional, social, and cultural dimensions of urban spaces. While generative AI (GAI) potentially supports playful urban interaction, a balanced and critical approach to the design opportunities and challenges is needed. This work develops iWonder, an image-to-image GAI tool engaging fourteen designers in urban explorations to identify GAI's playful features and create design ideas. Fourteen citizens then evaluated these ideas, providing expectations and critical concerns from a bottom-up perspective. Our findings reveal the dynamic interplay between users, GAI, and urban contexts, highlighting GAI's potential to facilitate playful urban experiences through \textit{generative agency}, \textit{meaningful unpredictability}, \textit{social performativity}, and the associated offensive qualities. We propose design considerations to address citizen concerns and the `tourist metaphor' to deepen our understanding of GAI's impact, offering insights to enhance cities' socio-cultural fabric. Overall, this research contributes to the effort to harness GAI's capabilities for urban enrichment.
... For example, employing philosophical or ethical frameworks could not only guide the rectification of adverse AI aspects but also help to anticipate them by ensuring the inclusion of crucial stakeholder perspectives and values. In addition, socio-technical imaginaries (Mlynar et al. 2022;Verma et al. 2023) emerged as a key component in strategies for designing and integrating AI within socio-technical systems. These shared visions and perspectives significantly shape the deployment and acceptance of AI in various social settings. ...
Large Language Models (LLMs) are expected to significantly impact various socio-technical systems, offering transformative possibilities for improved interaction between humans and technology. However, their integration poses complex challenges due to the intricate interplay between societal structures, human behaviour, and technological innovation. This research explores these multifaceted challenges, emphasising the need for a human-centered approach in integrating LLMs to ensure that technological advancements are aligned with ethical standards and societal needs. Utilizing a structured methodology comprising a workshop, literature analysis, and expert collaborations, the study uses a multi-dimensional human-centered AI framework to guide the responsible integration of LLMs. Key insights include the importance of inclusive data, considering unintended consequences, maintaining privacy, and respecting intellectual property rights. The paper identifies and advocates for principles like human-in-the-loop, continuous longitudinal studies, proactive awareness campaigns, and regular audits to develop LLMs that are ethically sound, adaptable, and effectively integrated into various socio-technical systems, thus addressing user needs and broader societal impacts. The paper also underlines the importance of collaboration among academia, industry, and policymakers to develop LLMs that are ethically aligned, socially beneficial, and adaptable to future societal needs. The findings offer valuable insights into the strategic integration of LLMs, advocating for a broader research perspective beyond industrial motivations to fully understand and leverage LLMs in socio-technical landscapes. ARTICLE HISTORY
... On the one hand, from its outset, the notion of 'artificial intelligence' (AI) has been subject to a powerful conceptual critique of the distinctions and continuities between 'artificial' and 'natural', 'human' and 'machinic', and the centrality of 'mind' and 'intelligence' (e.g., Coulter 1985;Dreyfus 1965). On the other hand, AI has nonetheless become a social object: something that can be talked about (e.g., Mlynář et al. 2022;Petersson et al. 2022), for example seen as a promise or a threat (e.g., Kotásek 2015;Smith 2019), or attributed with societal agency (e.g., Bellon and Velkovska 2023;Collins 2018). These shifting discourses of AI and its social contexts have led to a diffuse range of empirical and methodological approaches to social studies of AI spanning many disciplines (Caluori 2023). ...
Despite its elusiveness as a concept, ‘artificial intelligence’ (AI) is becoming part of everyday life, and a range of empirical and methodological approaches to social studies of AI now span many disciplines. This article reviews the scope of ethnomethodological and conversation analytic (EM/CA) approaches that treat AI as a phenomenon emerging in and through the situated organization of social interaction. Although this approach has been very influential in the field of computational technology since the 1980s, AI has only recently emerged as such a pervasive part of daily life to warrant a sustained empirical focus in EM/CA. Reviewing over 50 peer-reviewed publications, we find that the studies focus on various social and group activities such as task-oriented situations, semi-experimental setups, play, and everyday interactions. They also involve a range of participant categories including children, older participants, and people with disabilities. Most of the reviewed studies apply CA’s conceptual apparatus, its approach to data analysis, and core topics such as turn-taking and repair. We find that across this corpus, studies center on three key themes: openings and closing the interaction, miscommunication, and non-verbal aspects of interaction. In the discussion, we reflect on EM studies that differ from those in our corpus by focusing on praxeological respecifications of AI-related phenomena. Concurrently, we offer a critical reflection on the work of literature reviewing, and explore the tortuous relationship between EM and CA in the area of research on AI.
... However, automation is hard to adopt and make common in daily operations [18,33], despite the ambition of organizations to automate their processes and the implementation efforts carried accordingly. Prior HCI research widely criticized the technologyoriented and market-led development of AI solutions [24,27,30,39], and proposed to take human-centered perspectives to study the integration of automated solutions in real, operational contexts and produce compelling user experiences [20]. For instance, in the healthcare sector, Yang et al. [39,40] investigated clinician work processes to address the implementation of decision-support tools in heart pump implant decisions, Wang et al. [38] inquired data scientists within a multinational technology company about the effect of automated AI in their work practices, or Eißer et al. [15] studied recruiter acceptance of chatbot-based automated communication processes in the context of recruitment in enterprises. ...
Sustained adoption of automation is a problem for organizations, despite the promised benefits of automation and the propensity for organizations to expect it to transform their workplaces. To address this problem, previous work in HCI has mostly considered the perspectives and experiences of users interacting with automation technologies and has not considered the broader organizational context consisting of different stakeholders with varying needs and expectations around automation. Taking Amsterdam Airport Schiphol as a case study, we examine the challenges faced by practitioners responsible for integrating automation projects in its airside ecosystem, in an interview study conducted with 8 participants. Our findings reveal three challenges to the adoption of automation within the organization - the lack of consensus among different stakeholders, the need to adapt the technology to the specific context, and the undefined procedures required to maintain automation after implementation, that should be further addressed by the HCI community.
... Do jisté míry nezávisle se však mezitím UI zároveň etablovala jako sociální objekt, který už je součástí našeho světa: je to něco, o čem lze hovořit (např. Mlynář et al. 2022;Petersson et al. 2022), co můžeme vnímat jako příslib či hrozbu (např. Kotásek 2015; Smith 2019), a čemu lze připisovat společenské působení (např. ...
Příspěvek pojednává o tom, jak může sociologie adekvátně přistoupit k "umělé inteligenci" (UI). Diskutuje některé oborové konceptuální nástroje a naznačuje také inherentní omezení, na něž sociologie může narazit. Jedním z hlavních úskalí je, že UI je běžně (i v sociologii) konceptualizována na základě kognitivistických analogií: mechanickým a digitálním procesům je metaforicky připisována jakási varianta "mysli" a jejích projevů. Jak však ukázala wittgensteinovská filosofie a na ni navazující přístupy, "mysl" a její koreláty lze sociologicky smysluplně uchopit jako pozorovatelné a veřejně přístupné jevy, které jsou zakotveny v sociální interakci. Tento přístup je ilustrován příkladem z interakce s jazykovým modelem ChatGPT a nahrávkou z výzkumného projektu, který zkoumá využití UI v medicínském prostředí. Text směřuje k naznačení základů alternativní konceptualizace UI jako bytostně sociologického problému a sociálního fenoménu produkovaného v reálném čase jednání členů společnosti. Z tohoto hlediska se tak UI neskrývá "uvnitř strojů", ale vyvstává ze specifické uspořádanosti detailů situovaného jednání.
... Several papers touched on AI's privacy ramifications [24,33,47,56,62,63,75,86,89,91]. For example, the privacy ramifications of using human resource management tools in companies can make employees uncomfortable. ...
As Artificial Intelligence (AI) continues to advance rapidly, it becomes increasingly important to consider AI's ethical and societal implications. In this paper, we present a bottom-up mapping of the current state of research in Human-Centered Responsible AI (HCR-AI) by thematically reviewing and analyzing 27 CHI research papers and 19 toolkits from industry and academia. Our results show that the current research in HCR-AI places a heavy emphasis on explainability, fairness, privacy, and security. We also found that there is space to research accountability in AI and build usable tools for non-experts to audit AI. While the CHI community has started to champion the well-being of individuals directly or indirectly impacted by AI, more research and toolkits are still required to address the long-term effects of AI on individuals, societies, and natural resources (human flourishing and sustainability).
AI's integration into education promises to equip teachers with data-driven insights and intervene in student learning. Despite the intended advancements, there is a lack of understanding of interactions and emerging dynamics in classrooms where various stakeholders including teachers, students, and AI, collaborate. This paper aims to understand how students perceive the implications of AI in Education (AIEd) in terms of classroom collaborative dynamics, especially AI used to observe students and notify teachers to provide targeted help. Using the story completion method, we analyzed narratives from 65 participants, highlighting three challenges: AI decontextualizing of the educational context; AI-teacher cooperation with bias concerns and power disparities; AI's impact on student behavior that further challenges AI's effectiveness. We argue that for effective and ethical AI-facilitated cooperative education, future AIEd design must factor in the situated nature of implementation. Designers must consider the broader nuances of the education context, impacts on multiple stakeholders, dynamics involving these stakeholders, and the interplay among potential consequences for AI systems and stakeholders. It is crucial to understand the values in the situated context, the capacity and limitations of both AI and human for effective cooperation, and any implications to the relevant ecosystem.
The rapid advancements in artificial intelligence (AI) have ushered in a new era of innovative applications, while also prompting concerns regarding risks and adverse consequences. In light of the growing interest in comprehending AI's impact on society and its alignment with human values and needs, Human-Centred Artificial Intelligence (HCAI) has emerged as a potential approach to address questions and concerns. In this Systematic Literature Review, we aim to contribute to conceptual clarity around the definition, conceptualisation, and implementation of HCAI. The first part of our review addresses how HCAI is defined in the existing literature, culminating in a novel comprehensive HCAI definition. Subsequently, we delve into the identified constituent elements of HCAI, namely 'purpose', 'values', and 'properties'. Purposes include augmentation, AI autonomy, and automation. Values relate to ethics, safety, and performance. Properties cover oversight, comprehension, and integrity. The third part of the review explores Human-Centred Design processes, methods, and tools and their applicability for HCAI. In conclusion, we discuss the characteristics and critiques of HCAI and provide a research agenda. This literature review contributes to advancing the discourse on HCAI, thus enhancing human welfare and societal well-being. Abbreviations: AI: artificial intelligence; AI-HLEG: high-level expert group on artificial intelligence; GenAI: generative AI; HCAI: human-centred artificial intelligence; HCD: human-centred design; HCI: human-computer interaction; ISO: international organization for standardization; OECD: organisation for economic cooperation and development. ARTICLE HISTORY
Contemporary global challenges such as climate change, resource depletion, ecosystem degradation, and social inequities require comprehensive and integrated approaches to achieve sustainable development. While existing development and sustainability paradigms address specific aspects of sustainability, they often fall short in driving systemic transformation and ensuring long-term resilience. In response to these limitations, the concept of the regenerative economy emerges as a holistic framework that integrates ecological restoration, social equity, and economic vitality. This study conducts a systematic literature review of 84 scholarly articles to synthesize and cluster existing research within the regenerative economy domain. Utilizing a Large Language Model (LLM) for zero-shot classification, the analysis identifies seven primary clusters — Sustainability and Environmental Impact, Climate Change and Energy, Urban and Built Environment, Economic and Industrial Systems, Education and Social Impact, Technological Innovations and Systems, and Policy, Governance, and Standards — further subdivided into 21 subgroups. Each cluster encapsulates key themes and interdisciplinary approaches essential for advancing regenerative economy practices. The findings highlight the interconnectedness of various sustainability dimensions and underscore the necessity of integrated governance, innovative technological solutions, and inclusive policy frameworks. By mapping the current state of regenerative economy research, this study provides a structured overview that facilitates deeper understanding and informs future strategic initiatives aimed at achieving a resilient and prosperous sustainable future.
Keywords: regenerative economy, systematic literature review, large language model, LLM-based cluster analysis, policy implications
L'"intelligence artificielle" telle que nous la concevons aujourd'hui se concentre sur l'apprentissage automatique, par lequel un programme isolé évolue pour prendre des décisions de plus en plus "correctes" en fonction d'un objectif prédéfini. Son mythe se nourrit de l'idéologie du self-made-man, que les plus grand investisseurs du domaine prennent pour un modèle d'intelligence. Malgré le potentiel créatif de l'IA, son imaginaire demeure dans l'orbite de systèmes de pensée établis qu'elle contribue à figer. Pour y échapper, nous avons besoin de perspectives plus larges. Cet essai soutient que l'IA n'est pas une invention récente, mais plutôt la continuation d'une longue tradition de création de systèmes artificiels qui médient notre relation au monde. Son histoire commence avec l'apparition même du langage, et elle se matérialise dans l'écriture et dans le tissu urbain antique. André Ourednik redéfinit l'IA comme l'ensemble des systèmes symboliques et fonctionnels qui méditent notre rapport à l'incontrôlable, à l'innommable, à l'insaisissable, en d'autres mots: à la nature. Reliant les tablettes de lois de la cité d'Ur, les méganombres védiques, les automates du 19e, la cybernétique et les algorithmes génératifs, voici l'histoire de l'autonomie croissante des dispositifs de pensée. Quel sera le rôle futur des humains dans leurs créations? Une intelligence artificielle qui échappe au contrôle humain redevient-elle "nature"? Avec quelles conséquences? L'IA peut-elle nous aider dans nos relations aux êtres vivants et à notre propre subjectivité?
From wearable health tracking to sensor-laden cities, AI-enhanced pervasive sensing platforms promise far-reaching benefits and introduce societal risks. How might designers of these platforms effectively navigate their complex ecology and sociotechnical dy-namics? To explore this question, we interviewed designers who undertook this challenge in the mental health domain. They are hospital chief medical information officers and startup founders together striving to create new sensors/AI platforms and integrate them into the healthcare ecosystem. We found that, while all designers aspired to build comprehensive care platforms, their efforts focused on serving either consumers or physicians, delivering a subset of healthcare interventions, and demonstrating system effectiveness one metric at a time. Consequently, breakdowns in patient journeys are emerging; societal risks loom large. We describe how the data economy, designers' mindsets, and evaluation challenges led to these unintended design approaches. We discuss implications for designing pervasive sensing and AI platforms for social good. CCS CONCEPTS • Human-centered computing → HCI design and evaluation methods; Empirical studies in HCI.
The application of Artifcial Intelligence (AI) across a wide range of domains comes with both high expectations of its benefts and dire predictions of misuse. While AI systems have largely been driven by a technology-centered design approach, the potential societal conse- quences of AI have mobilized both HCI and AI researchers towards researching human-centered artifcial intelligence (HCAI). How- ever, there remains considerable ambiguity about what it means to frame, design and evaluate HCAI. This paper presents a critical review of the large corpus of peer-reviewed literature emerging on HCAI in order to characterize what the community is defning as HCAI. Our review contributes an overview and map of HCAI research based on work that explicitly mentions the terms ‘human- centered artifcial intelligence’ or ‘human-centered machine learn- ing’ or their variations, and suggests future challenges and research directions. The map reveals the breadth of research happening in HCAI, established clusters and the emerging areas of Interaction with AI and Ethical AI. The paper contributes a new defnition of HCAI, and calls for greater collaboration between AI and HCI research, and new HCAI constructs.
Artificial intelligence (AI) is one of the most disruptive technologies of our time. Interest in the use of AI for urban innovation continues to grow. Particularly, the rise of smart cities—urban locations that are enabled by community, technology, and policy to deliver productivity, innovation, livability, wellbeing, sustainability, accessibility, good governance, and good planning—has increased the demand for AI-enabled innovations. There is, nevertheless, no scholarly work that provides a comprehensive review on the topic. This paper generates insights into how AI can contribute to the development of smarter cities. A systematic review of the literature is selected as the methodologic approach. Results are categorized under the main smart city development dimensions, i.e., economy, society, environment, and governance. The findings of the systematic review containing 93 articles disclose that: (a) AI in the context of smart cities is an emerging field of research and practice. (b) The central focus of the literature is on AI technologies, algorithms, and their current and prospective applications. (c) AI applications in the context of smart cities mainly concentrate on business efficiency, data analytics, education, energy, environmental sustainability, health, land use, security, transport, and urban management areas. (d) There is limited scholarly research investigating the risks of wider AI utilization. (e) Upcoming disruptions of AI in cities and societies have not been adequately examined. Current and potential contributions of AI to the development of smarter cities are outlined in this paper to inform scholars of prospective areas for further research.
The rapid advancement of artificial intelligence (AI) is changing our lives in many ways. One application domain is data science. New techniques in automating the creation of AI, known as AutoAI or AutoML, aim to automate the work practices of data scientists. AutoAI systems are capable of autonomously ingesting and pre-processing data, engineering new features, and creating and scoring models based on a target objectives (e.g. accuracy or run-time efficiency). Though not yet widely adopted, we are interested in understanding how AutoAI will impact the practice of data science. We conducted interviews with 20 data scientists who work at a large, multinational technology company and practice data science in various business settings. Our goal is to understand their current work practices and how these practices might change with AutoAI. Reactions were mixed: while informants expressed concerns about the trend of automating their jobs, they also strongly felt it was inevitable. Despite these concerns, they remained optimistic about their future job security due to a view that the future of data science work will be a collaboration between humans and AI systems, in which both automation and human expertise are indispensable.
What makes a city meaningful to its residents? What attracts people to live in a city and to care for it? Today, we might see such questions as concerns for HCI, given the emerging agendas of smart and connected cities, IoT, and ubiquitous computing: city residents' perceptions of and attitudes towards smart city technologies will play a role in technology acceptance. Theories of "placemaking" from humanist geography and urban planning address themselves to such concerns, and they have been taken up in HCI and urban informatics research. This theory offers ideas for developing community attachment, heightening the legibility of the city, and intensifying lived experiences in the city. We add to this body of research with an analysis of several initiatives of City Yeast, a community-based design collective in Taiwan that proposes the metaphor of fermentation as an approach to placemaking. We unpack how this approach shapes their design practice and link its implications to urban informatics research in HCI. We suggest that smart cities can also be pursued by leveraging the knowledge of city residents and helping to facilitate their participation in acts of perceiving, envisioning, and improving their local communities, including but not limited to smart and connected technologies.
Buildings and urban spaces increasingly incorporate artificial intelligence and new forms of interactivity, raising a wide span of research questions about the future of human experiences with, and within, built environments. We call this emerging area Human-Building Interaction (HBI) and introduce it as an interdisciplinary domain of research interfacing Human-Computer Interaction (HCI) with Architecture and Urban Design. HBI seeks to examine the involvement of HCI in studying and steering the evolution of built environments. Therefore, we need to ask foundational questions such as the following: what are the specific attributes of built environments that HCI researchers should take into account when shifting attention and scale from “artefacts” to “environments”? Are architecture and interaction design methods and processes compatible? Concretely, how can a team of interaction designers bring their tools to an architectural project, and collaborate with other stakeholders? Can and will architecture change the theory and practice of HCI? Furthermore, research in HBI should produce knowledge and practical guidelines by experimenting novel design instances that combine architecture and digital interaction. The primary aim of this article is to specify the mission, vision, and scope of research in HBI. As the introductory article to the TOCHI special issue, it also provides a summary of published manuscripts and describes their collective contribution to the development of this field.
Walking is the collaboration and confluence of body, mind, and place. It has been repeatedly acknowledged as the “composing instrument” of the city generating social and urban life, as the most democratic and accessible physical activity, a cultural and aesthetic practice, a vital antidepressant, heart-saver, non-dieting diet, and an antidote to cope with the syndrome of chairs and wheels. Such that the re-discovery of walk may compete with the invention of wheel [1, 2].
Operating from the standpoint that walking is essentially a situated human experience, our aim is to develop a discussion of walking within the context of so-called Smart Cities, hoping that this will initiate a broader multidisciplinary discourse on how to retain and improve the urban walk. Our analytical framework draws on well-established concepts in the broad domain of urban sciences while considering technological enablers in built environments such as pervasive sensing, machine learning, and actuation techniques.
Digital technologies have already become an internal part of our life. They change the way we are looking for information, how we communicate with each other, even how we behave. This transformation applies to many areas, including education. The main objective of this article is to identify prospective impact of artificial technologies to the study process and to predict possible changes in educational landscape. In presented literature review we considered four categories: customized educational content, innovative teaching methods, technology enhanced assessment, communication between student and lecturer. Having reviewed publications on the subject we present here a possible picture of how the Artificial Intelligence (AI) will reshape education landscape.
The Smart City concept is still evolving and can be viewed as a branding exercise by big corporations, which is why the concept is not being used by the United Nations (U.N.). Smart Cities tend to represent the information, communication, and technological (ICT) industry alone without considering the values and cultural and historical profiles that some cities hold as legacies. However, the technology inherent in Smart Cities promises efficiencies and options that could allow cities to be more “inclusive, safe, resilient, and sustainable” as required by the U.N. agenda including cultural heritage. There is a notable lack of Smart City application to cultural and historical urban fabrics. Instead, the modernist new town approach has emerged under this new rubric leading to many problems such as urban decay and unsustainable car dependence. This study therefore presents a review of the literature on the nature, challenges, and opportunities of Smart Cities. A new Smart Cities framework is proposed based on the dimensions of culture, metabolism, and governance. These findings seek to inform policy makers of an alternative viewpoint on the Smart City paradigm, which focuses on urban outcomes rather than technology in isolation.
The need of the hour in present day education environment is adaptivity. Adaptive educational systems aim to customize content and learning paths of students. These aid’s in the minimizing disorientation and cognitive overload problems; thus maximizing learning efficiency. Present learning systems are lacking adaptivity; as they offer same resources for all users irrespective of their individual needs and preferences. Students learn according to their learning styles and determining these is a crucial step in making eLearning or traditional education adaptive. To determine learning styles, learning models have been suggested in literature, but there is no readily available software tool that provides the flexibility to select and implement the most suitable learning model. To fulfil this dire need, a framework of a tool is proposed here, which takes into consideration multiple learning models and artificial intelligence techniques for determining students’ learning styles. The tool would provide the facility to compare learning models, to determine the most suitable one for a particular environment. It is suggested that this tool be deployed in a cloud environment to provide a scalable solution that offers easy and rapid determination of learning styles.
The vision and mission of research under the banner of Ubiquitous Computing has increasingly moved from focusing on the realm of "artifacts" to the realm of "environments". We seek to scrutinize this very transition, and raise questions that relate to the specific attributes of built environments that set them inherently apart from artifacts. How does an interactive environment differ from an interactive artifact, a collection of artifacts, or an integrated suite of artifacts? Consequently, we ask what are the new user experience dimensions that HCI researchers should merge into their considerations, for example, by supplementing us-ability and engagement with occupants' comfort across multiple dimensions, and shifting attention from (often) short lifespan and discretionary to durable and immersive experiences? In this contribution, we bring arguments from the literature of environmental psychology and architecture that highlight the points of divergence between artifacts and architecture, and then translate them into challenges for Human-Computer Interaction, and particularly for the emerging domain of Human-Building Interaction.
We present a structured discussion of the concept of driverless car as a major Ubicomp project, and particularly of its hypothetical integration into the fabric of city. The analytical framework is borrowed from the Transportation and Urban research domains, which provides us with a list of agreed-upon subject matters when accounting for car mobility in urban design. We pose concrete questions about each of these subjects as how self-driven personal vehicles could have a positive or negative impact on them. Out of the six discussed topics, this initial examination showed that driverless car could have a negative impact on five, suggesting smoke detected, and thus the need for broadening such inspections.
Smart urbanism seems to be everywhere you turn. But in practice the agenda is an uncertain one, usually only partially developed, and often more about corporate-led urban development than about urban social justice. Rather than leave smart urbanism to the corporate and political elites, there are opportunities now for critical urban scholarship to not only critique how it is currently constituted, but to give shape to a globally oriented alternative smart urban agenda. An ambition like this means taking the ‘urban’ in ‘smart urban’ much more seriously. It means foregrounding the knowledges, political priorities and needs of those either actively excluded or included in damaging ways in mainstream smart urban discourses. We outline steps towards an alternative smart urbanism. We seek to move beyond the specific to the general and do so by drawing on radically different initiatives across the Global North and South. These initiatives provide tantalizing openings to a more socially just use of digital technology, where urban priorities and justice drive the use—or lack of use—of technology.
There is no question that anthropogenic processes have had planetary effects, in inter/intraaction with other processes and species, for as long as our species can be identified (a few tens of thousand years); and agriculture has been huge (a few thousand years). Of course, from the start the greatest planetary terraformers (and reformers) of all have been and still are bacteria and their kin, also in inter/intra-action of myriad kinds (including with people and their practices, technological and otherwise). 1 The spread of seed-dispersing plants millions of years before human agriculture was a planet-changing development, and so were many other revolutionary evolutionary ecological developmental historical events. People joined the bumptious fray early and dynamically, even before they/we were critters who were later named Homo sapiens. But I think the issues about naming relevant to the Anthropocene, Plantationocene, or Capitalocene have to do with scale, rate/speed, synchronicity, and complexity. The constant question when considering systemic phenomena has to be, when do changes in degree become changes in kind, and what are the effects of bioculturally, biotechnically, biopolitically, historically situated people (not Man) relative to, and combined with, the effects of other species assemblages and other biotic/abiotic forces? No species, not even our own arrogant one pretending to be good individuals in so-called modern Western scripts, acts alone; assemblages of organic species and of abiotic actors make history, the evolutionary kind and the other kinds too. But, is there an inflection point of consequence that changes the name of the “game” of life on earth for everybody and everything? It's more than climate change; it's also extraordinary burdens of toxic chemistry, mining, depletion of lakes and rivers under and above ground, ecosystem simplification, vast genocides of people and other critters, etc, etc, in systemically linked patterns that threaten major system collapse after major system collapse after major system collapse. Recursion can be a drag. Anna Tsing in a recent paper called “Feral Biologies” suggests that the inflection point between the Holocene and the Anthropocene might be the wiping out of most of the refugia from which diverse species assemblages (with or without people) can be reconstituted after major events (like desertification, or clear cutting, or, or, …). 2 This is kin to the World-Ecology
Investment in the release of open data has become increasingly central to the implementation of smart city programs by governments around the world. Though originally arising out of a push towards “open government” and the pursuit of more transparent decision-making by public authorities at multiple scales, open data programs have more recently been adopted by municipal governments to support entrepreneurial goals of enhanced competitive positioning and attracting investment. As urban scholars now subject the smart city project to critical scrutiny for its role in advancing urban entrepreneurialism, this article considers the relevance of the open data agenda as it shapes wider understandings of the smart city. In particular, I address the collection of policy practices, aspirations, stakeholders and entrepreneurs active in framing the opportunities and values of open data for urban governments. Both the momentum of support for open data, along with a recent shift in the rhetorical aspirations of the open data movement away from the values of openness and transparency and towards a more confined focus on value generation, raise important critical questions for urban geographers concerned with the nature of urban governance in an age of big data.
Background: A systematic literature review was conducted on mixed methods area. Objectives: The overall aim was to explore how qualitative information from interviews has been analyzed using quantitative methods. Methods: A contemporary review was undertaken and based on a predefined protocol. The references were identified using inclusion and exclusion criteria and specific key terms in 11 search databases. Results: Evidence was synthesized from 14 references that included the methods used for quantifying qualitative information, analyzing it statistically and the rationale behind this. Gaps in the existing literature and recommendations for future research were identified. Conclusions: This review highlights the need for a new mixed method based on advanced statistical modeling method that will explore complex relationships arising from qualitative information.
Smart city represents one of the most promising, prominent and challenging Internet of Things (IoT) applications [1]. In the last few years, indeed, the smart city concept has played an important role in academic and industry fields, with the development and deployment of various middleware platforms and IoT-based infrastructures. However, this expansion has followed distinct approaches creating, therefore, a fragmented scenario, in which different IoT ecosystems are not able to communicate between them. To fill this gap, there is a need to re-visit the smart city IoT semantic and to offer a global common approach. To this purpose, this paper browses the semantic annotation of the sensors in Cloud, and innovative services can be implemented and considered by bridging Cloud of Things (CoT) and IoT. Things like semantic will be considered to perform the aggregation of heterogeneous resources by defining the CoT paradigm. We survey the smart city vision, providing information on the main requirements and highlighting the benefits of integrating different IoT ecosystems within Cloud under this new CoT vision. This paper also discusses relevant challenges in this research area. Copyright © 2015 John Wiley & Sons, Ltd.
With the advent and popularity of social network, more and more users like to share their experiences, such as ratings, reviews, and blogs. The new factors of social network like interpersonal influence and interest based on circles of friends bring opportunities and challenges for recommender system (RS) to solve the cold start and sparsity problem of datasets. Some of the social factors have been used in RS, but have not been fully considered. In this paper, three social factors, personal interest, interpersonal interest similarity, and interpersonal influence, fuse into a unified personalized recommendation model based on probabilistic matrix factorization. The factor of personal interest can make the RS recommend items to meet users' individualities, especially for experienced users. Moreover, for cold start users, the interpersonal interest similarity and interpersonal influence can enhance the intrinsic link among features in the latent space. We conduct a series of experiments on three rating datasets: Yelp, MovieLens, and Douban Movie. Experimental results show the proposed approach outperforms the existing RS approaches.
On 4 November 2011, the trademark ‘smarter cities’ was officially registered as belonging to IBM. This was an important milestone in a struggle between IT companies over visibility and legitimacy in the smart city market. Drawing on actor-network theory and critical planning theory, the paper analyzes IBM's smarter city campaign and finds it to be storytelling, aimed at making the company an ‘obligatory passage point’ in the implementation of urban technologies. Our argument unfolds in three parts. We first trace the emergence of the term ‘smart city’ in the public sphere. Secondly, we show that IBM's influential story about smart cities is far from novel but rather mobilizes and revisits two long-standing tropes: systems thinking and utopianism. Finally, we conclude, first by addressing two critical questions raised by this discourse: technocratic reductionism and the introduction of new moral imperatives in urban management; and second, by calling for the crafting of alternative smart city stories.
Doing research is, in part, an act of foresight. Even though it is not explicit in many projects, we especially value research that is still relevant five, ten or more years after it is completed. However, published research in the field of interactive computing (and technology research in general) often lacks evidence of systematic thinking about the long-term impacts of current trends. For example, trends on an exponential curve change much more rapidly than intuition predicts. As a result, research may accidentally emphasize near-term thinking. When thinking about the future is approached systematically, we can critically examine multiple potential futures, expand the set of externalities under consideration, and address both negative and positive forecasts of the future. The field of Futures Studies provides methods that can support analysis of long-term trends, support the identification of new research areas and guide design and evaluation. We survey methods for futuristic thinking and discuss their relationship to Human Computer Interaction. Using the sustainability domain an example, we present a case study of a Futures Studies approach - the Delphi Method. We show how Futures Studies can be incorporated into Human Computer Interaction and highlight future work such as rethinking the role of externalities in the validation process.
The concept of Ambient Intelligence (AmI) provides a vision of the Information Society where the emphasis is on greater user-friendliness, more efficient services support, user-empowerment, and support for human interactions. User-centered design involves two fundamental elements: multidisciplinary teamwork; and a set of specialized methods for acquiring user input and converting it into design. The chapter discusses each of the UCD activities from the point of view of Ambient Intelligence, in an attempt to anticipate the main challenges which will need to be addressed, and outline potential directions of investigation. Efforts aimed at user programmability lead to a perspective on Ambient Intelligence as a socio-technical system where intelligence is both human and artificial in an interconnected and collaborative way. The chapter examines the centrality and role of human factors in the emergence and development of AmI environments.
Well-designed technologies that offer high levels of human control and high levels of computer automation can increase human performance, leading to wider adoption. The Human-Centered Artificial Intelligence (HCAI) framework clarifies how to (1) design for high levels of human control and high levels of computer automation so as to increase human performance, (2) understand the situations in which full human control or full computer control are necessary, and (3) avoid the dangers of excessive human control or excessive computer control. The methods of HCAI are more likely to produce designs that are Reliable, Safe & Trustworthy (RST). Achieving these goals will dramatically increase human performance, while supporting human self-efficacy, mastery, creativity, and responsibility.
Cities are increasingly integrating sensing and information and communication technologies to improve municipal services, civic engagement, and quality of life for residents. Although these civic technologies have the potential to affect economic, social, and environmental factors, there has been less focus on residents of lower income communities' involvement in civic technology design. Based on two public forums held in underserved communities, we describe residents' perceptions of civic technologies in their communities and challenges that limit the technologies' viability. We found that residents viewed civic technology as a tool that should strengthen existing community assets by providing an avenue to connect assets and build upon them. We describe how an asset-based approach can move us toward designing civic technology that develops stronger relationships among community-led initiatives, and between the community and local government--- rather than a data-driven approach to civic tech that focuses on transactions between residents and city services.
In recent years, AI systems have become both more powerful and increasingly promising for integration in a variety of application areas. Attention has also been called to the social challenges these systems bring, particularly in how they might fail or even actively disadvantage marginalised social groups, or how their opacity might make them difficult to oversee and challenge. In the context of these and other challenges, the roles of humans working in tandem with these systems will be important, yet the HCI community has been only a quiet voice in these debates to date. This workshop aims to catalyse and crystallise an agenda around HCI's engagement with AI systems. Topics of interest include explainable and explorable AI; documentation and review; integrating artificial and human intelligence; collaborative decision making; AI/ML in HCI Design; diverse human roles and relationships in AI systems; and critical views of AI.
Cities are increasingly turning towards specialized technologies to address issues related to society, ecology, morphology and many others. The emerging concept of Smart Cities highly encourages this prospect by promoting the incorporation of sensors and Big Data through the Internet of Things (IoT). This surge of data brings new possibilities in the design and management of cities just as much as economic prospects. While Big Data processing through Artificial Intelligence (AI) can greatly contribute to the urban fabric, sustainability and liveability dimensions however must not be overlooked in favour of technological ones. This paper reviews the urban potential of AI and proposes a new framework binding AI technology and cities while ensuring the integration of key dimensions of Culture, Metabolism and Governance; which are known to be primordial in the successful integration of Smart Cities for the compliance to the Sustainable Development Goal 11 and the New Urban Agenda. This paper is aimed towards Policy Makers, Data Scientists and Engineers who are looking at enhancing the integration of Artificial Intelligence and Big Data in Smart Cities with an aim to increase the liveability of the urban fabric while boosting economic growth and opportunities.
2001 introduction to in-depth semipstructured qualitative interviewing and to BNIM in paerticular. Unique in its conceptual coherence and its level of practical detail, it cov ers a full spectrum from the identification of topics and research questions, to the interviewing, to the answerin g of research questions, the compring and theorising of cases an d to strategies of writing-up presentations.
Advances in artificial intelligence, sensors and big data management have far-reaching societal impacts. As these systems augment our everyday lives, it becomes increasing-ly important for people to understand them and remain in control. We investigate how HCI researchers can help to develop accountable systems by performing a literature analysis of 289 core papers on explanations and explaina-ble systems, as well as 12,412 citing papers. Using topic modeling, co-occurrence and network analysis, we mapped the research space from diverse domains, such as algorith-mic accountability, interpretable machine learning, context-awareness, cognitive psychology, and software learnability. We reveal fading and burgeoning trends in explainable systems, and identify domains that are closely connected or mostly isolated. The time is ripe for the HCI community to ensure that the powerful new autonomous systems have intelligible interfaces built-in. From our results, we propose several implications and directions for future research to-wards this goal.
Smart cities are a new approach to urban development based on the extensive use of information and communication technologies and on the promotion of environmental sustainability, economic development and innovation. The article is aimed at discussing whether the adoption of a smart city approach entails the transformation of existing institutional structures and administrative practices. To this end, four cases of European smart cities are analysed: Amsterdam, Barcelona, Turin and Vienna. The article describes their models of governance, investigates the level of transformation that occurred in their governmental structures, outlines the main drawbacks and identifies possible connections with the emergent paradigm of the New Public Governance.
A vision of Ambient Intelligence is offered in the report of the Information Society
Technologies Advisory Group of the European Commission (ISTAG, 2003):“The
concept of Ambient Intelligence provides a vision of the Information Society where the
emphasis is on greater user-friendliness, more efficient services support, userempowerment,
and support for human interactions. People are surrounded by
intelligent intuitive interfaces that are embedded in all kinds of objects and an
environment that is capable of recognising and responding to the presence of different
individuals in a seamless, unobtrusive and often invisible way.” (p.1)
Developing information technology to democratize scientific knowledge and support citizen empowerment is a challenging task. In our case, a local community suffered from air pollution caused by industrial activity. The residents lacked the technological fluency to gather and curate diverse scientific data to advocate for regulatory change. We collaborated with the community in developing an air quality monitoring system which integrated heterogeneous data over a large spatial and temporal scale. The system afforded strong scientific evidence by using animated smoke images, air quality data, crowdsourced smell reports, and wind data. In our evaluation, we report patterns of sharing smoke images among stakeholders. Our survey study shows that the scientific knowledge provided by the system encourages agonistic discussions with regulators, empowers the community to support policy making, and rebalances the power relationship between stakeholders.
The pathway to a sustainable society is not clear, and we need to consider different developmental possibilities. This paper describes the results of a research project in the intersection of HCI and Futures Studies as well as in the intersection between "the future information society" and sustainability. We here present parts of the body of materials that were developed in a multi-year research project with the aim of describing and evaluating the sustainability impact of possible future information societies. We also discuss some of the lessons learned and what HCI and design fiction can learn from Futures Studies in general and from this project in particular. The main stakeholders in this project have been city administrators and corporate partners, and the overarching goal has primarily been to influence planning processes at the regional (Stockholm, Sweden) level.
Recent research in urban informatics has presented the city as both a complex technological center and a diverse cultural, social, and political entity. However, there has been little research into the changing role that nature plays in urban space, particularly when it comes to understanding how animals have adapted to life in technological and networked cities. In the wake of urbanization, new kinds of cohabitation, including increased interactions between humans and animals, has resulted in new challenges for those working in urban informatics. We leverage key concepts in the Anthropocene-naturecultures, hybrids, and decentering the human in design-to unpack the entanglements of animal-human-computer interaction in two design cases: The Big Cat Behavioral Tracking Initiative and The Phenology Clock. We contribute to urban informatics and HCI research by reflecting on ways in which design can promote new forms of cohabitation and support a broader conception of the city that sees animals as an essential part of the urban landscape.
Citizen sensing is an approach that develops and uses lightweight technologies with local communities to collect, share and act upon data. In doing so it enables them to become more aware of how they can tackle local issues. We report here on the development and uptake of the 'City- Commons Framework for Citizen Sensing', a conceptual model that builds on Participatory Action Research with the aim of playing an integrating role: outlining the processes and mechanisms for ensuring sensing technologies are co-designed by citizens to address their concerns. At the heart of the framework is the idea of a city commons: a pool of community-managed resources. We discuss how the framework was used by communities in Bristol to measure and monitor the problem of damp housing.
Rob Kitchin talks about how we can bridge the adoption gap between city administrations and developers of smart city technologies. This interview is part of a special issue on smart cities.
The urban built environment is underpinned by an increasingly complex digital infrastructure, which is posing a variety of unpredictable and unprecedented challenges for urban governance. The paper discusses how the new “hard” digital infrastructures such as broadband are accompanied by the need to understand the governance of public sector information; and in turn how this relates to the emergence of smart city strategies. The paper is illustrated using empirical examples drawn from Australian digital infrastructure development, with reference to the international landscape of “smart city” developments. It argues that there is a significant mismatch between the often small scale, bounded capabilities of municipal government, and the operational expertise and scope of technology firms.
The new edition of this landmark volume emphasizes the dynamic, interactional, and reflexive dimensions of the research interview. Contributors highlight the myriad dimensions of complexity that are emerging as researchers increasingly frame the interview as a communicative opportunity as much as a data-gathering format. The book begins with the history and conceptual transformations of the interview, which is followed by chapters that discuss the main components of interview practice. Taken together, the contributions to The SAGE Handbook of Interview Research: The Complexity of the Craft encourage readers simultaneously to learn the frameworks and technologies of interviewing and to reflect on the epistemological foundations of the interview craft.
Learning the City: Translocal Assemblage and Urban Politics critically examines the relationship between knowledge, learning, and urban politics, arguing both for the centrality of learning for political strategies and developing a progressive international urbanism. • Presents a distinct approach to conceptualising the city through the lens of urban learning • Integrates fieldwork conducted in Mumbai's informal settlements with debates on urban policy, political economy, and development • Considers how knowledge and learning are conceived and created in cities • Addresses the way knowledge travels and opportunities for learning about urbanism between North and South.
Collection : la librairie des Humanités
http://www.press.uchicago.edu/ucp/books/book/chicago/D/bo20836025.html
Dreamscapes of Modernity offers the first book-length treatment of sociotechnical imaginaries, a concept originated by Sheila Jasanoff and developed in close collaboration with Sang-Hyun Kim to describe how visions of scientific and technological progress carry with them implicit ideas about public purposes, collective futures, and the common good. The book presents a mix of case studies—including nuclear power in Austria, Chinese rice biotechnology, Korean stem cell research, the Indonesian Internet, US bioethics, global health, and more—to illustrate how the concept of sociotechnical imaginaries can lead to more sophisticated understandings of the national and transnational politics of science and technology. A theoretical introduction sets the stage for the contributors’ wide-ranging analyses, and a conclusion gathers and synthesizes their collective findings. The book marks a major theoretical advance for a concept that has been rapidly taken up across the social sciences and promises to become central to scholarship in science and technology studies.
Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today’s AI engineers. AI is becoming more and more a part of everyone’s life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book’s many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.
HCI can “turn to the wild” but still stay home. Local community life presents a rich context for understanding challenges and possibilities of information technology. We summarize and reflect upon a program of participatory design research in which we facilitated activities and experiences of our neighbors through developing a series of community-oriented programs and information systems through the past two decades. We organize these reflections around five overlapping themes: visibility of community actors, creation of community information infrastructures, the role of place-based identity and activity in community, the effectiveness of participatory relationships, and the research designs and methods appropriate. We frame these reflections around a conceptual model of community, and the suggestion that the local community can be a living laboratory for HCI in the wild.
In the light of the recent growth of artificial intelligence (AI), and of its implications for understanding human behaviour, this paper evaluates the prospects for an association between sociology and artificial intelligence. Current presumptions about the distinction between human behaviour and artificial intelligence are identified through a survey of discussions about AI and `expert systems'. These discussions exhibit a restricted view of sociological competence, a marked rhetoric of progress and a wide variation in assessments of the state of the art. By drawing upon recent themes in the social study of science, these discussions are shown to depend on certain key dichotomies and on an interpretive flexibility associated with the notions of intelligence and expertise. The range of possible associations between sociology and AI reflects the extent to which we are willing to adopt these features of AI discourse. It is suggested that one of the more important options is to view the AI phenomenon as an occasion for reassessing the central axiom of sociology that there is something distinctively `social' about human behaviour.