1,720,957 research outputs found
Enhancing Environmental Sustainability in AI-Infused objects Ecosystems through User Experience: Expert validation and Insights
Get PDFThe study highlights the need and challenges of assessing the environmental sustainability of AI-infused Objects forming product-service ecosystems through the design lens. Through literature review, it aims to heighten designers' awareness of the environmental impact linked with this technology and facilitating decision-making through impact evaluation. The contribution for designers initiates by outlining three distinct components of AI-Infused Objects analysis, which are physical, digital, and usage. It then proceeds to identify the environmental impacts connected to each component. The study concludes by incorporating insights from field experts interviews aimed to understand how the design perspective can effectively address and overcome the impacts posed by the technology
UX Sustainability in AI-infused Objects: a systematic literature review of available tools for Designers
Get PDFThe rapid integration of AI-infused objects into our daily lives, as part of the growing Internet of Things (IoT) ecosystem, is transforming common appliances into sophisticated and interconnected systems (ITU, 2020). With projections indicating an increase from 5 billion objects in 2020 to over 200 billion by 2030 (CISCO, 2020), these AI-infused objects create expansive networks of data-consuming devices that persist indefinitely (Crawford, 2018). This surge necessitates a deeper understanding of their ongoing environmental impact, particularly during the use phase. Recognizing the potential for user experience Designers to adjust interactions to mitigate the environmental impact during the use phase of AI-infused objects, we conducted a systematic literature review to pinpoint the Design tools that can assist Designers in this effort. Our systematic literature review aims to identify Design tools that evaluate the sustainability of User Experience in IoT products. We analyzed 24 sources dedicated to sustainability from a User Experience perspective, and 22 that assess UX in IoT devices. The findings reveal a strong focus on product-focused evaluation tools, with general emphasis on User Experience and the usage ecosystem of these objects. As AI-infused objects become increasingly prevalent, it is essential for Designers to gain a comprehensive understanding of the environmental impacts and their cause. This awareness could lead Designers to integrate both technological advancements and environmental considerations effectively into their Design process
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
UX sustainability: assessing ai-infused objects : understanding UX Sustainability in AI-infused objects: a first step towards redesign
No full textDOTTORATOQuesta dissertazione presenta un progetto di ricerca dottorale triennale volto a esplorare come l'User Experience (UX) possa contribuire alla sostenibilità dei prodotti AI-infused. L'obiettivo iniziale era indagare come la UX potesse essere utilizzata per progettare o riprogettare prodotti basati su intelligenza artificiale al fine di ridurne l'impatto ambientale. Tuttavia, con l'evolversi della ricerca, è emerso chiaramente che questi prodotti non possono essere compresi appieno isolatamente, senza considerare gli ecosistemi in cui sono inseriti. Gli utenti, infatti, non interagiscono con questi prodotti in modo indipendente, ma li utilizzano all'interno di un più ampio ecosistema di servizi composto da molteplici touchpoint. Ad esempio, i prodotti per la smart home vengono spesso scelti per la loro capacità di essere controllati da remoto, il che implica un'interazione con una serie di sistemi interconnessi.
Come evidenziato da Vitali (2022), gli oggetti AI-infused, come smart speaker e dispositivi wearable, sfruttano l'intelligenza artificiale per migliorare le loro funzionalità, creando ecosistemi complessi attraverso una connettività estesa (Agrò, 2018; Abramovici, 2014; Greengard, 2015). La loro crescente integrazione nella vita quotidiana è ormai innegabile, con previsioni che stimano un aumento dei dispositivi AI-infused da 5 miliardi nel 2020 a oltre 200 miliardi entro il 2030 (CISCO, 2020). Questa diffusione impone una rivalutazione delle pratiche di progettazione e delle considerazioni ambientali, soprattutto in relazione alla presenza sempre più massiccia di questi oggetti e ai potenziali impatti ecologici che generano.
L'obiettivo di questa ricerca di dottorato è supportare i designer nella comprensione dell'impatto ambientale dei prodotti AI-infused all'interno degli ecosistemi di servizi, con un focus specifico sulla fase d'uso. Attraverso l'adozione di un approccio "systems thinking" (Pigosso, 2015), questa ricerca esplora come la UX possa diventare un fattore chiave nell'analisi dell'impatto ambientale di questi prodotti. Ciò implica definire o ridefinire i confini del sistema e raccogliere informazioni dettagliate sugli utenti, sulle modalità di utilizzo e sui fattori contestuali (Kim, 2020). L'indagine si concentra sugli ecosistemi AI-infused in contesti domestici, utilizzando un approccio Research-through-Design per ricavare insight pratici da studi di caso sul campo.
Il principale obiettivo di questo studio è quindi identificare e analizzare i fattori ambientali coinvolti nei prodotti AI-infused durante la fase d'uso, nel contesto del loro ecosistema più ampio. Questa ricerca mira a colmare un'importante lacuna, valutando in modo sistematico le interazioni tra questi prodotti e i loro ecosistemi, nonché gli impatti ambientali che ne derivano. Secondo la definizione di Baumann (2002), l'impatto ambientale comprende qualsiasi cambiamento, positivo o negativo, che un'attività, un prodotto o un servizio genera sull'ambiente. Con l'integrazione sempre più pervasiva dei prodotti AI-infused negli ambienti quotidiani, in particolare nelle abitazioni domestiche (Vailshery, 2022), questa ricerca si focalizza specificamente sui dispositivi utilizzati in tali contesti. Sebbene gli impatti ambientali possano essere classificati in diverse categorie, questa ricerca si concentra in particolare sul consumo energetico, data la natura energivora di questa tecnologia (Pohl et al., 2019).This dissertation outlines a three-year Doctoral research project aimed at exploring how
User Experience (UX) can contribute to the sustainability of AI-infused products. The initial
goal was to investigate how UX could be leveraged to design or redesign AI products to reduce
their environmental impact. However, as the research evolved, it became clear that AI-infused
products cannot be fully understood in isolation from their surrounding ecosystems. Users do
not engage with these products independently; instead, they interact with a broader service
ecosystem composed of multiple touchpoints. For instance, smart home products are often
chosen for their ability to be controlled remotely, which involves interacting with a range of
interconnected systems.
As highlighted by Vitali (2022), AI-infused objects such as smart speakers and wearable
devices use AI to enhance functionality, forming complex ecosystems through extensive con-
nectivity (Agrò, 2018; Abramovici, 2014; Greengard, 2015). Their growing integration into
daily life is undeniable, with forecasts estimating a rise in AI-infused devices from 5 billion in
2020 to over 200 billion by 2030 (CISCO, 2020). This integration calls for a reassessment of
both design practices and environmental considerations, especially in relation to the expand-
ing presence of AI-infused objects and their potential environmental impacts.
The aim of this PhD research is to support designers in understanding the environmen-
tal impact of AI-infused products within service ecosystems, focusing specifically on the use
phase. By adopting a "systems thinking" approach (Pigosso, 2015), this research will explore
how UX can be a key factor in analysing the environmental impact of AI-infused products.
This involves defining or redefining system boundaries and collecting detailed information on
users, usage patterns, and contextual factors (Kim, 2020). The research investigates AI-infused
ecosystems in domestic settings, using a Research-through-Design approach to derive practi-
cal insights from field case studies.
Thus, the primary purpose of this study is to identify and analyse the environmental factors
involved in AI-infused products during their use phase, within their broader ecosystem. This
research aims to fill a crucial gap by systematically assessing the interactions between these
products and their ecosystems, as well as the environmental impacts they generate. As Bau-
mann (2002) defined, environmental impacts are any changes, whether positive or negative,
to the environment resulting from activities, products, or services. With the growing integra-
tion of AI-infused products into everyday environments, especially within domestic settings
(Vailshery, 2022), this PhD specifically examines devices used in these contexts. While there
are various categories of environmental impacts, this research concentrates on energy con-
sumption, given the energy-intensive nature of this technology (Pohl et al., 2019).DIPARTIMENTO DI DESIGN37RAMPINO, LUCIA ROSA ELENARAMPINO, LUCIA ROSA ELEN
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
UX Sustainability: an overview on the sustainability dimension of AI-infused Objects forming product-service ecosystems
Get PDFThis research aims to suggest a new design perspective to analyse the sustainability of an AI-infused object in its entirety. Before we present what AI-infused Objects are and how they form product-service ecosystems, secondly, we analyse the state of the arts of its sustainable dimension. The analysis of AI-infused objects should include: (1) the entire life cycle of the object, its social and economic impact; (2) the impact of the "digital soul" of the object; (3) the ecosystem analysis should also include all indirect impacts of the service, considering how users' behaviour changes when they come in contact with the artificial intelligence ecosystem. The research contributes to the design literature in two ways: (1) by raising awareness in designers on the effective impact of AI-infused Objects forming the product-service ecosystems, (2) by inviting designers to make this awareness concrete through User Experience Sustainability analysis and behavioural change strategies applied to persuasive technology
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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