479 research outputs found

    SHARED PATH Service Design and Artificial Intelligence in Designing Human-Centred Digital Services

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    Digitalization and the growing service economy place challenges on organizations for transforming their service offerings to match the high user expectations. Services increasingly exploit digital technologies which play an important role in the creation of service experiences. One of the examples is artificial intelligence (AI), which may actively perform in customer service, but also provide solutions in the back end of services. While AI actively takes part in the creation of service value, the line between human and machine in the service encounters blurs. This creates new type of service components which need to be designed as part of digital service journeys. This dissertation is constructed around seven scientific publications that explore the merging of AI and service design in creating human-centred digital service solutions. The focus in the publications is on applying service design principles to AI-enabled services, from which an AI assistant is an example. AI assistants interact with users through text and voice interfaces and can be perceived as a gateway to complex digital service ecosystems. AI assistants are rather new as services, and they touch upon areas that, besides the design challenges, are ethically, philosophically and legally demanding. Here, service designers face changes both in the design process and in their role as designers. This study was conducted as a qualitative research with roots in the practice of design research. The main research data consist of five case studies and seven expert interviews analysed through coding, content analysis and visual mapping to answer the following research question: How is AI affecting the practice of service design and the design of digital services? The findings from the publications are concluded under the following four topics: (1) AI changes the design of digital service interactions, (2) AI assistants perform as actors in digital services, (3) AI needs to be human-centred rather than human-like and (4) AI assists and augments the practice of service design. Under these topics, the discussion highlights the ethical considerations and humanization aspect of AI as a part of designing and the design outcomes as AI-enabled services.Digitalisaatio ja kasvava palvelukeskeinen markkinatalous asettavat organisaatioille muutoshaasteitta, jotta palvelutarjonnalla pystyttäisiin vastaamaan käyttäjien korkeisiin odotuksiin. Palvelut hyödyntävät yhä enenevissä määrin digitaalista teknologiaa osana palvelukokemusten tuottamista. Yhtenä esimerkkinä teknologioista on tekoäly, jolla voi jo olla aktiivinen osa asiakaspalvelussa sekä ratkaisujen tuottajana palveluiden taustajärjestelmissä. Kun tekoälyn rooli palveluarvon tuottamisessa kasvaa, raja ihmisen ja koneen välillä voi hämärtyä. Tekoäly luo näin uudenlaisia palveluelementtejä, jotka tulee muotoilla osaksi digitaalisia palvelupolkuja. Väitöstyö pohjautuu seitsemään tieteelliseen julkaisuun, joiden kautta tutkimus tarkastelee tekoälyn ja palvelumuotoilun yhteyttä ihmislähtöisten digipalveluiden muotoilemisessa. Julkaisut keskittyvät palvelumuotoilun näkökulmaan tekoälyavusteisten palveluiden kehittämisessä ja käyttävät esimerkkikontekstina tekoälyassistentteja. Tekoälyassistentti on digitaalisen palvelun muoto, joka on vuorovaikutuksessa asiakkaan kanssa joko tekstin tai puheen kautta. Tekoälyassistentti voi myös toimia keulakuvana laajemmalle palvelutarjonnalle ja palveluekosysteemeille. Tekoälyassistentit ovat palvelumuotona melko uusia ja niiden aihepiirit ovat muotoiluhaasteen lisäksi eettisesti, filosofisesti ja juridisesti haastavia. Tämä luo palvelumuotoilijalle haastavan asetelman niin muotoiluprosessiin kuin omaan työhön muotoilijana. Väitöstutkimus on toteutettu laadullisena tutkimuksena muotoilun tutkimuksen kentällä. Tutkimuksen ensisijainen aineisto koostuu viidestä tapaustutkimuksesta ja seitsemästä asiantuntijahaastattelusta. Aineistoa on analysoitu koodaamisen, sisällönanalyysin sekä visuaalisen analyysin keinoin. Analyysin kautta vastataan tutkimuskysymykseen: Mikä on tekoäly vaikutus palvelumuotoilutoimintaan ja digitaalisten palveluiden muotoilemiseen? Tutkimustulokset esitellään neljän aihepiirin kautta: (1) Tekoäly muuttaa digitaalisten palveluiden vuorovaikutusten muotoilua, (2) tekoälyassistentit ovat aktiivisia toimijoita digitaalisissa palveluissa, (3) tekoälyn on oltava ihmiskeskeistä, ei ihmismäistä, ja (4) tekoäly tukee ja laajentaa palvelumuotoilutoimintaa. Näiden aihepiirien kautta tutkimustulokset nostavat esiin tekoälyn eettiset ja inhimilliset näkökulmat osana tekoälyavusteisia palveluita sekä niitä tuottavaa palvelumuotoilutoimintaa

    On Data-driven systems analyzing, supporting and enhancing users’ interaction and experience

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    Tesis doctoral en inglés y resumen extendido en español[EN] The research areas of Human-Computer Interaction and Software Architectures have been traditionally treated separately, but in the literature, many authors made efforts to merge them to build better software systems. One of the common gaps between software engineering and usability is the lack of strategies to apply usability principles in the initial design of software architectures. Including these principles since the early phases of software design would help to avoid later architectural changes to include user experience requirements. The combination of both fields (software architectures and Human-Computer Interaction) would contribute to building better interactive software that should include the best from both the systems and user-centered designs. In that combination, the software architectures should enclose the fundamental structure and ideas of the system to offer the desired quality based on sound design decisions. Moreover, the information kept within a system is an opportunity to extract knowledge about the system itself, its components, the software included, the users or the interaction occurring inside. The knowledge gained from the information generated in a software environment can be used to improve the system itself, its software, the users’ experience, and the results. So, the combination of the areas of Knowledge Discovery and Human-Computer Interaction offers ideal conditions to address Human-Computer-Interaction-related challenges. The Human-Computer Interaction focuses on human intelligence, the Knowledge Discovery in computational intelligence, and the combination of both can raise the support of human intelligence with machine intelligence to discover new insights in a world crowded of data. This Ph.D. Thesis deals with these kinds of challenges: how approaches like data-driven software architectures (using Knowledge Discovery techniques) can help to improve the users' interaction and experience within an interactive system. Specifically, it deals with how to improve the human-computer interaction processes of different kind of stakeholders to improve different aspects such as the user experience or the easiness to accomplish a specific task. Several research actions and experiments support this investigation. These research actions included performing a systematic literature review and mapping of the literature that was aimed at finding how the software architectures in the literature have been used to support, analyze or enhance the human-computer interaction. Also, the actions included work on four different research scenarios that presented common challenges in the Human-Computer Interaction knowledge area. The case studies that fit into the scenarios selected were chosen based on the Human-Computer Interaction challenges they present, and on the authors’ accessibility to them. The four case studies were: an educational laboratory virtual world, a Massive Open Online Course and the social networks where the students discuss and learn, a system that includes very large web forms, and an environment where programmers develop code in the context of quantum computing. The development of the experiences involved the review of more than 2700 papers (only in the literature review phase), the analysis of the interaction of 6000 users in four different contexts or the analysis of 500,000 quantum computing programs. As outcomes from the experiences, some solutions are presented regarding the minimal software artifacts to include in software architectures, the behavior they should exhibit, the features desired in the extended software architecture, some analytic workflows and approaches to use, or the different kinds of feedback needed to reinforce the users’ interaction and experience. The results achieved led to the conclusion that, despite this is not a standard practice in the literature, the software environments should embrace Knowledge Discovery and data-driven principles to analyze and respond appropriately to the users’ needs and improve or support the interaction. To adopt Knowledge Discovery and data-driven principles, the software environments need to extend their software architectures to cover also the challenges related to Human-Computer Interaction. Finally, to tackle the current challenges related to the users’ interaction and experience and aiming to automate the software response to users’ actions, desires, and behaviors, the interactive systems should also include intelligent behaviors through embracing the Artificial Intelligence procedures and techniques

    On data-driven systems analyzing, supporting and enhancing users’ interaction and experience

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    [EN]The research areas of Human-Computer Interaction and Software Architectures have been traditionally treated separately, but in the literature, many authors made efforts to merge them to build better software systems. One of the common gaps between software engineering and usability is the lack of strategies to apply usability principles in the initial design of software architectures. Including these principles since the early phases of software design would help to avoid later architectural changes to include user experience requirements. The combination of both fields (software architectures and Human-Computer Interaction) would contribute to building better interactive software that should include the best from both the systems and user-centered designs. In that combination, the software architectures should enclose the fundamental structure and ideas of the system to offer the desired quality based on sound design decisions. Moreover, the information kept within a system is an opportunity to extract knowledge about the system itself, its components, the software included, the users or the interaction occurring inside. The knowledge gained from the information generated in a software environment can be used to improve the system itself, its software, the users’ experience, and the results. So, the combination of the areas of Knowledge Discovery and Human-Computer Interaction offers ideal conditions to address Human-Computer-Interaction-related challenges. The Human-Computer Interaction focuses on human intelligence, the Knowledge Discovery in computational intelligence, and the combination of both can raise the support of human intelligence with machine intelligence to discover new insights in a world crowded of data. This Ph.D. Thesis deals with these kinds of challenges: how approaches like data-driven software architectures (using Knowledge Discovery techniques) can help to improve the users' interaction and experience within an interactive system. Specifically, it deals with how to improve the human-computer interaction processes of different kind of stakeholders to improve different aspects such as the user experience or the easiness to accomplish a specific task. Several research actions and experiments support this investigation. These research actions included performing a systematic literature review and mapping of the literature that was aimed at finding how the software architectures in the literature have been used to support, analyze or enhance the human-computer interaction. Also, the actions included work on four different research scenarios that presented common challenges in the Human- Computer Interaction knowledge area. The case studies that fit into the scenarios selected were chosen based on the Human-Computer Interaction challenges they present, and on the authors’ accessibility to them. The four case studies were: an educational laboratory virtual world, a Massive Open Online Course and the social networks where the students discuss and learn, a system that includes very large web forms, and an environment where programmers develop code in the context of quantum computing. The development of the experiences involved the review of more than 2700 papers (only in the literature review phase), the analysis of the interaction of 6000 users in four different contexts or the analysis of 500,000 quantum computing programs. As outcomes from the experiences, some solutions are presented regarding the minimal software artifacts to include in software architectures, the behavior they should exhibit, the features desired in the extended software architecture, some analytic workflows and approaches to use, or the different kinds of feedback needed to reinforce the users’ interaction and experience. The results achieved led to the conclusion that, despite this is not a standard practice in the literature, the software environments should embrace Knowledge Discovery and datadriven principles to analyze and respond appropriately to the users’ needs and improve or support the interaction. To adopt Knowledge Discovery and data-driven principles, the software environments need to extend their software architectures to cover also the challenges related to Human-Computer Interaction. Finally, to tackle the current challenges related to the users’ interaction and experience and aiming to automate the software response to users’ actions, desires, and behaviors, the interactive systems should also include intelligent behaviors through embracing the Artificial Intelligence procedures and techniques

    Evaluating the Smart Steps For Stepfamilies: Embrace the Journey Program, a Hierarchical Examination

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    Over the past decade, relationship education has grown as a means of enhancing couple relations. This study examines the experiences of 2,828 ethnically diverse and low-income adults who participated in the Smart Steps for Stepfamilies: Embrace the Journey program, a 12-hour stepfamily education program. Self-report measures of relationship quality, couple commitment, and relationship instability were gathered prior to and immediately after the Smart Steps intervention as well as six weeks, six months, and one year post-program. Results suggest that stepfamily participants experienced increases in relationship quality; however, these increases reduced to near pre-program levels one year after the programs completion. Results further showed no changes in couple commitment or relationship instability measures nor among differing participant groups including Latinos, European Americans, low-income, moderate- income, married, unmarried, those in a first marriage, second remarriage, and higher order remarriage. Finally a cost-analysis of the program was conducted. Application of these findings and policy implications are discussed
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