Kunstig intelligens

This book constitutes the revised selected papers of the First International Conference, ICCSST 2023, held in Bangalore, India, during May 8¿9, 2023.The 39 full papers included in this volume were carefully reviewed and selected from 200 submissions. They focus on artificial intelligence, blockchain technology, cloud computing, cyber security, data science, e-commerce, computer architecture, image and video processing, pandemic preparedness and digital technology, pattern recognition and classification.

Dieses Buch bietet Ihnen einen praktischen Einstieg in die Welt der Künstlichen Intelligenz (KI) und Data Science. Es hinterfragt aktuelle Hypes und ist ein praxiserprobter Guide mit konkreten Schritten für den sinnvollen Einsatz von einfachen bis komplexeren KI-Anwendungen im Unternehmen - mit Schwerpunkt auf Data Analytics und Web-/App-Tracking.In welchen Einsatzbereichen steckt das meiste Potenzial? Wie bestimmen Sie den KI-Reifegrad Ihres Unternehmens und wie planen Sie Ihre KI-Weiterbildungsoffensive? Welche wirtschaftlichen, ethischen und ökologischen Risiken sollten Sie berücksichtigen? Antworten darauf erhalten Sie in diesem Quick Guide - mit zahlreichen Tipps, Methoden und Vorlagen für den Transfer in Ihr Unternehmen. Ein Buch für alle, die sich die Möglichkeiten von KI-Anwendungen jetzt erschließen und schon bald davon profitieren wollen. Der InhaltGrundlagen und historische EinordnungEinsatzbereiche von KI im Bereich AnalyticsRisiken und Chancen beim Einsatz von KI im UnternehmenKI-Governance in fünf konkreten SchrittenAI & Data Analytics trifft Recht: AI Act und DSGVOKI-Strategie aus Ihrer Geschäftsstrategie ableitenKI-Kompetenz im Unternehmen erhöhen - mit Self-Assessment, Gap-Analyse und KI-Kompetenz-CanvasVom Scheitern lernen: Der Friedhof der KI-ProjekteDie Autor:innenDr. Ramona Greiner, Digital Analytics und Data Ethics Consultant bei FELD M in München. Sie leitet internationale Beratungsprojekte, hält Vorträge und Design-Thinking-Workshops und ist Autorin mehrerer Fach- und Sachbücher.Dr. Matthias Böck, Data Scientist und Technischer Leiter für Projekte aus den Bereichen Advanced Analytics und Maschinelles Lernen bei FELD M. Jonas Rashedi, Chief Data Officer bei der FUNKE Mediengruppe, mehrfacher Fachbuch-Autor. Als Managing Director bei The Data Institute berät er Unternehmen, wie sie durch eine klare Datenstrategie ihren Umsatz erhöhen können.

'Generativ AI: 17 vinkler til forståelse og anvendelse' er en lærerig bog, der åbner døren til en spændende verden af generativ kunstig intelligens. Skrevet af to brødre med passion for AI, tager denne bog dig med på en rejse fra teori til praksis, og fra nysgerrighed til forståelse af generativ AI.Med et særligt fokus på populære sprogmodeller som ChatGPT og tekst-til-billede værktøjer, giver bogen dig indblik i, hvordan generativ AI kan påvirke vores måde at tænke, skabe og interagere med teknologi på. Struktureret i 17 uafhængige 'vinkler', dækker bogen et bredt spektrum af emner - fra grundlæggende principper til diverse anvendelsesmetoder.Ud over at give dig en teoretisk forståelse, baseret på den nyeste forskning på området, får du også en praktisk håndbog, der kan tage din brug af AI til et højere niveau. Uanset om du er nybegynder eller erfaren bruger, giver bogen dig værktøjerne og viden til selv at udforske og anvende generativ AI, hvor end du ønsker.Du kan læse mere om bogen på hjemmesiden:https://momentum-ai.dk/bog/

The recent surge of interest in AI systems has raised concerns in moral quarters about their ethical use and whether they can demonstrate fair decision taking processes. Issues of unfairness and discrimination are pervasive when decisions are being made by humans, and are potentially amplified when decisions are made using machines with little transparency, accountability, and fairness. In this monograph, the authors introduce a framework for causal fairness analysis to understand, model, and possibly solve issues of fairness in AI decision-making settings. The authors link the quantification of the disparities present in the observed data with the underlying, often unobserved, collection of causal mechanisms that generate the disparity in the first place, a challenge they call the Fundamental Problem of Causal Fairness Analysis (FPCFA). In order to solve the FPCFA, they study the mapping variations and empirical measures of fairness to structural mechanisms and different units of the population, culminating in the Fairness Map.This monograph presents the first systematic attempt to organize and explain the relationship between various criteria in fairness and studies which causal assumptions are needed for performing causal fairness analysis. The resulting Fairness Cookbook allows anyone to assess the existence of disparate impact and disparate treatment. It is a timely and important introduction to developing future AI systems incorporating inherent fairness and as such will be of wide interest not only to AI system designers, but all who are interested in the wider impact AI will have on society.

The scientific theme of the book is ¿Sustainability for the digital manufacturing erä which is focused on how the technological enablers of digital systems drive the sustainability for products, processes, manufacturing, and logistics systems in the industry of the future. The book¿s chapters describe sustainability drivers specific to the technological advances that motivate, encourage, and engage the economic, social, and environmental aspects within intelligent manufacturing and logistics systems. The novelty of this approach consists in extending the economic sustainability of digital manufacturing with the ethical perspective at human social scale. The general scope of the book is to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods, and solutions for the digital transformation of manufacturing through service orientation in holonic and agent-based control with distributed intelligence. The book¿s readership is comprised of researchers and engineers working in the value chain of products and processes, who develop digital control solutions in the ¿Industry of the Future¿ vision. The book is also addressed to master¿s and Ph.D. students enrolled in Engineering Sciences programs.

This book provides an in-depth discussion of the theoretical and practical issues of criminal imputation for negligence crime involving artificial intelligence. Accordingly, this study combines the imputation challenges brought about by AI with traditional criminal imputation theory and analyses imputation for negligence crime involving AI from three aspects: the basic principles, structure, and results of imputation for negligence crime involving AI. The traditional theory of imputation is discussed in detail. The readership is a group of people interested in this topic, including, in particular, interested laymen, undergraduate students and postgraduate researchers. The highlights of this book are it identifies the imputation challenges bought about by AI, reveals the theoretical and practical gap in the criminal imputation of negligent crimes involving AI, and provides an in-depth and creative ideas of criminal imputation for the negligent crimes involving AI.

T¿his three-volume set constitues selected papers presented at the 18th International Conference on Computer Science and Education, ICCSE 2023, held in Sepang, Malaysia, in December 2023. The 106 full papers and 36 short papers presented were thoroughly reviewed and selected from the 305 submissions. They focus on a wide range of computer science topics, especially AI, data science, and engineering, and technology-based education, by addressing frontier technical and business issues essential to the applications of data science in both higher education and advancing e-Society.