Kirsten thommes (25 résultats)

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Hardback. Etat : New. This open access book introduces social aspects relevant to research and developments of explainable AI (XAI). The new surge of XAI responds to the societal challenge that many algorithmic approaches (such as machine learning or autonomous intelligent systems) are rapidly increasing in complexity, making justified use of their recommendations difficult for the users. A large body of approaches now exists with many ideas of how algorithms should be explainable or even be able to explain their output. However, few of them consider the users' perspective, and even less address the social aspects of using XAI. To fill the gap, the book offers a conceptualization of explainability as a social practice, a framework for contextual factors, and an operationalization of users' involvement in creating relevant explanations.For this, scholars across disciplines gathered at the Shonan meeting to account for how explanation generation can be tailored to diverse users and their heterogeneous goals when interacting with XAI. As a result, social interaction is the key to the involvement of the users. Accordingly, we define sXAI (social eXplainable AI) as systems that interact with the users in such a way that an incremental adaptation of explaining to the users is possible, along with the unfolding context of interaction, to yield a relevant explanation at the interface with both active partners-human and AI. To encourage novel interdisciplinary research, we propose to account for the following dimensions.    Patterndness: XAI should account for different contexts that yield different social roles impacting the construction of explanations.    Incrementality: XAI should build on the contribution of the involved partners who adapt to each other.    Multimodality: XAI needs to use different communication modalities (e.g., visual, verbal, and auditory).This book also addresses how to evaluate social XAI systems and what ethical aspects must be considered when employing sXAI. Together, the book pushes forward the building of a community interested in sXAI. To increase the readability across disciplines, each chapter offers a rapid access to its content.…

Etat : New.

Etat : New.

Etat : New.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book introduces social aspects relevant to research and developments of explainable AI (XAI). The new surge of XAI responds to the societal challenge that many algorithmic approaches (such as machine learning or autonomous intelligent systems) are rapidly increasing in complexity, making justified use of their recommendations difficult for the users. A large body of approaches now exists with many ideas of how algorithms should be explainable or even be able to explain their output. However, few of them consider the users' perspective, and even less address the social aspects of using XAI. To fill the gap, the book offers a conceptualization of explainability as a social practice, a framework for contextual factors, and an operationalization of users' involvement in creating relevant explanations.For this, scholars across disciplines gathered at the Shonan meeting to account for how explanation generation can be tailored to diverse users and their heterogeneous goals when interacting with XAI. As a result, social interaction is the key to the involvement of the users. Accordingly, we define sXAI (social eXplainable AI) as systems that interact with the users in such a way that an incremental adaptation of explaining to the users is possible, along with the unfolding context of interaction, to yield a relevant explanation at the interface with both active partners human and AI. To encourage novel interdisciplinary research, we propose to account for the following dimensions: Patterndness: XAI should account for different contexts that yield different social roles impacting the construction of explanations. Incrementality: XAI should build on the contribution of the involved partners who adapt to each other. Multimodality: XAI needs to use different communication modalities (e.g., visual, verbal, and auditory).This book also addresses how to evaluate social XAI systems and what ethical aspects must be considered when employing sXAI. Together, the book pushes forward the building of a community interested in sXAI. To increase the readability across disciplines, each chapter offers a rapid access to its content.…

Hardcover. Etat : Brand New. 400 pages. 9.26x6.11x9.21 inches. In Stock.

Hardback. Etat : New. This open access book introduces social aspects relevant to research and developments of explainable AI (XAI). The new surge of XAI responds to the societal challenge that many algorithmic approaches (such as machine learning or autonomous intelligent systems) are rapidly increasing in complexity, making justified use of their recommendations difficult for the users. A large body of approaches now exists with many ideas of how algorithms should be explainable or even be able to explain their output. However, few of them consider the users' perspective, and even less address the social aspects of using XAI. To fill the gap, the book offers a conceptualization of explainability as a social practice, a framework for contextual factors, and an operationalization of users' involvement in creating relevant explanations.For this, scholars across disciplines gathered at the Shonan meeting to account for how explanation generation can be tailored to diverse users and their heterogeneous goals when interacting with XAI. As a result, social interaction is the key to the involvement of the users. Accordingly, we define sXAI (social eXplainable AI) as systems that interact with the users in such a way that an incremental adaptation of explaining to the users is possible, along with the unfolding context of interaction, to yield a relevant explanation at the interface with both active partners-human and AI. To encourage novel interdisciplinary research, we propose to account for the following dimensions.    Patterndness: XAI should account for different contexts that yield different social roles impacting the construction of explanations.    Incrementality: XAI should build on the contribution of the involved partners who adapt to each other.    Multimodality: XAI needs to use different communication modalities (e.g., visual, verbal, and auditory).This book also addresses how to evaluate social XAI systems and what ethical aspects must be considered when employing sXAI. Together, the book pushes forward the building of a community interested in sXAI. To increase the readability across disciplines, each chapter offers a rapid access to its content.…

Taschenbuch. Etat : Neu. Neuware -Die Kompetenzen der Mitarbeitenden sind gerade in wissensintensivenUnternehmen der wichtigste Wettbewerbsfaktor. Viele Unternehmen stehen aktuellvor der Aufgabe, im Zuge der Digitalisierung Kompetenzen erfassen und entwickeln zu müssen.Diese Kompetenzen sollen Beschäftigte befähigen neue Aufgaben zu übernehmenund in sich ändernden Kontexten zu arbeiten. Die Herausforderung betrifft alleMitarbeiter, aber insbesondere auch die Arbeit in (agilen) Teams. Wir stellenein praxisorientiertes Framework für ein prädiktives Kompetenzmanagementfür agile Teams vor, das den Leser in die Lage versetzt, ein digitalesKompetenzmanagement für Unternehmen aufzubauen. 152 pp. Deutsch.…

Etat : New. 2024th edition NO-PA16APR2015-KAP.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Die Kompetenzen der Mitarbeitenden sind gerade in wissensintensivenUnternehmen der wichtigste Wettbewerbsfaktor. Viele Unternehmen stehen aktuellvor der Aufgabe, im Zuge der Digitalisierung Kompetenzen erfassen und entwickeln zu müssen.Diese Kompetenzen sollen Beschäftigte befähigen neue Aufgaben zu übernehmenund in sich ändernden Kontexten zu arbeiten. Die Herausforderung betrifft alleMitarbeiter, aber insbesondere auch die Arbeit in (agilen) Teams. Wir stellenein praxisorientiertes Framework für ein prädiktives Kompetenzmanagementfür agile Teams vor, das den Leser in die Lage versetzt, ein digitalesKompetenzmanagement für Unternehmen aufzubauen.…

Etat : New. Die Kompetenzen der Mitarbeitenden sind gerade in wissensintensivenUnternehmen der wichtigste Wettbewerbsfaktor. Viele Unternehmen stehen aktuellvor der Aufgabe, im Zuge der Digitalisierung Kompetenzen erfassen und entwickeln zu muessen.Diese Kompetenzen sol.

Taschenbuch. Etat : Neu. Digitales und prädiktives Kompetenzmanagement | Kirsten Thommes (u. a.) | Taschenbuch | xvii | Deutsch | 2024 | Springer | EAN 9783662688373 | Verantwortliche Person für die EU: Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Str. 46, 65189 Wiesbaden, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Etat : Gut. Zustand: Gut | Sprache: Deutsch | Produktart: Bücher | Keine Beschreibung verfügbar.

Softcover. Etat : gut. 2007. Outsourcing von Personalfunktionen In deutscher Sprache. pages.

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book introduces social aspects relevant to research and developments of explainable AI (XAI). The new surge of XAI responds to the societal challenge that many algorithmic approaches (such as machine learning or autonomous intelligent systems) are rapidly increasing in complexity, making justified use of their recommendations difficult for the users. A large body of approaches now exists with many ideas of how algorithms should be explainable or even be able to explain their output. However, few of them consider the users' perspective, and even less address the social aspects of using XAI. To fill the gap, the book offers a conceptualization of explainability as a social practice, a framework for contextual factors, and an operationalization of users' involvement in creating relevant explanations.For this, scholars across disciplines gathered at the Shonan meeting to account for how explanation generation can be tailored to diverse users and their heterogeneous goals when interacting with XAI. As a result, social interaction is the key to the involvement of the users. Accordingly, we define sXAI (social eXplainable AI) as systems that interact with the users in such a way that an incremental adaptation of explaining to the users is possible, along with the unfolding context of interaction, to yield a relevant explanation at the interface with both active partners human and AI. To encourage novel interdisciplinary research, we propose to account for the following dimensions: Patterndness: XAI should account for different contexts that yield different social roles impacting the construction of explanations. Incrementality: XAI should build on the contribution of the involved partners who adapt to each other. Multimodality: XAI needs to use different communication modalities (e.g., visual, verbal, and auditory).This book also addresses how to evaluate social XAI systems and what ethical aspects must be considered when employing sXAI. Together, the book pushes forward the building of a community interested in sXAI. To increase the readability across disciplines, each chapter offers a rapid access to its content. 617 pp. Englisch.…

Hardcover. Etat : Brand New. 400 pages. 9.26x6.11x9.21 inches. In Stock. This item is printed on demand.

Etat : new. Questo è un articolo print on demand.

Hardcover. Etat : new. Hardcover. This open access book introduces social aspects relevant to research and developments of explainable AI (XAI). The new surge of XAI responds to the societal challenge that many algorithmic approaches (such as machine learning or autonomous intelligent systems) are rapidly increasing in complexity, making justified use of their recommendations difficult for the users. A large body of approaches now exists with many ideas of how algorithms should be explainable or even be able to explain their output. However, few of them consider the users' perspective, and even less address the social aspects of using XAI. To fill the gap, the book offers a conceptualization of explainability as a social practice, a framework for contextual factors, and an operationalization of users' involvement in creating relevant explanations.For this, scholars across disciplines gathered at the Shonan meeting to account for how explanation generation can be tailored to diverse users and their heterogeneous goals when interacting with XAI. As a result, social interaction is the key to the involvement of the users. Accordingly, we define sXAI (social eXplainable AI) as systems that interact with the users in such a way that an incremental adaptation of explaining to the users is possible, along with the unfolding context of interaction, to yield a relevant explanation at the interface with both active partnershuman and AI. To encourage novel interdisciplinary research, we propose to account for the following dimensions: Patterndness: XAI should account for different contexts that yield different social roles impacting the construction of explanations. Incrementality: XAI should build on the contribution of the involved partners who adapt to each other. Multimodality: XAI needs to use different communication modalities (e.g., visual, verbal, and auditory).This book also addresses how to evaluate social XAI systems and what ethical aspects must be considered when employing sXAI. Together, the book pushes forward the building of a community interested in sXAI. To increase the readability across disciplines, each chapter offers a rapid access to its content. mso-fareast-theme-font: minor-fareast;">Patterndness: XAI should account for different contexts that yield different social roles impacting the construction of explanations. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This open access book introduces social aspects relevant to research and developments of explainable AI (XAI). The new surge of XAI responds to the societal challenge that many algorithmic approaches (such as machine learning or autonomous intelligent systems) are rapidly increasing in complexity, making justified use of their recommendations difficult for the users. A large body of approaches now exists with many ideas of how algorithms should be explainable or even be able to explain their output. However, few of them consider the users' perspective, and even less address the social aspects of using XAI. To fill the gap, the book offers a conceptualization of explainability as a social practice, a framework for contextual factors, and an operationalization of users' involvement in creating relevant explanations.For this, scholars across disciplines gathered at the Shonan meeting to account for how explanation generation can be tailored to diverse users and their heterogeneous goals when interacting with XAI. As a result, social interaction is the key to the involvement of the users. Accordingly, we define sXAI (social eXplainable AI) as systems that interact with the users in such a way that an incremental adaptation of explaining to the users is possible, along with the unfolding context of interaction, to yield a relevant explanation at the interface with both active partnershuman and AI. To encourage novel interdisciplinary research, we propose to account for the following dimensions: Patterndness: XAI should account for different contexts that yield different social roles impacting the construction of explanations. Incrementality: XAI should build on the contribution of the involved partners who adapt to each other. Multimodality: XAI needs to use different communication modalities (e.g., visual, verbal, and auditory).This book also addresses how to evaluate social XAI systems and what ethical aspects must be considered when employing sXAI. Together, the book pushes forward the building of a community interested in sXAI. To increase the readability across disciplines, each chapter offers a rapid access to its content.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 632 pp. Englisch.…

Buch. Etat : Neu. Social Explainable AI | Communications of NII Shonan Meetings | Katharina Rohlfing (u. a.) | Buch | xv | Englisch | 2026 | Springer | EAN 9789819652891 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. …

Etat : New. Print on Demand.

Etat : New. PRINT ON DEMAND.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Die Kompetenzen der Mitarbeitenden sind gerade in wissensintensivenUnternehmen der wichtigste Wettbewerbsfaktor. Viele Unternehmen stehen aktuellvor der Aufgabe, im Zuge der Digitalisierung Kompetenzen erfassen und entwickeln zu müssen.Diese Kompetenzen sollen Beschäftigte befähigen neue Aufgaben zu übernehmenund in sich ändernden Kontexten zu arbeiten. Die Herausforderung betrifft alleMitarbeiter, aber insbesondere auch die Arbeit in (agilen) Teams. Wir stellenein praxisorientiertes Framework für ein prädiktives Kompetenzmanagementfür agile Teams vor, das den Leser in die Lage versetzt, ein digitalesKompetenzmanagement für Unternehmen aufzubauen.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 152 pp. Deutsch.…