Über uns

À propos de nous

Nachhaltigkeit

Durabilité

Open Access

Karriere

Carrière

Datenschutz

Protection des données

Impressum

Mentions légales

Zahlung und Lieferung

Paiement et livraison

LEXIA

LEXIA Arbeitsrecht

Was ist LEXIA?

C'est quoi LEXIA ?

LEXIA Familienrecht

Zeitschriften

Revues

recht

Pflegerecht

ZBJV

forumpoenale

ZStrR

Anwaltsrevue

Revue de l'avocat

RSAS

FamPra.ch

ASYL

Life Science Recht

BlAR

Sachbuch

Livres spécialisés

LOKI

Semaphor

Fokusthemen

Focus

Thema

Recht studieren

Arbeitsrecht

Droit du travail

Studium

Études

Familienrecht

Droit de la famille

Sozialversicherungsrecht

Droit des assurances sociales

Strafrecht

Droit pénal

Publikationen

Publications

Literatur

Onlinemodule LEXIA

Modules en ligne LEXIA

Bücher

Livres

Buchreihen

Collections

Datenbanken

recht.ch

Studienliteratur

Littérature pour les études

Services

Dienstleistungen für

Corporate Books

Publishing Lösungen

Aktuelles

Geschäftskunden

Professionnels

Corporate Publishing

Content solutions

Buchhandlungen

Librairies

Veranstaltungen

Événements

Presse

Dozierende

Enseignants

Studierende

Étudiants

Inserierende

Annonceurs

Newsletter

Blog

Autorinnen/Autoren

Auteurs

Unsere Schreibenden

Hilfe

Unsere Autorinnen und Autoren

Liste

Autorenlounge

Espace des auteurs

Bei uns publizieren

Publier chez nous

Autorenstimmen

Témoignages

Verlag

Éditions

Themen

Mehr wissen

Mitarbeitende

Collaborateurs

Geschichte

Histoire

Vision und Mission

Vision et mission

Unser Magazin

Notre magazine

Unternehmenskultur

Culture d'entreprise

Partner

Partenaires

Kontakt

Contact

Shop

Schweizer Recht

Ausländisches Recht

Über unseren Shop

Neuerscheinungen

Nouveautés

Unsere Funktionen

Nos fonctions

Vorankündigungen

À paraître

Nach Rechtsgebiet

Par domaine juridique

Kommentare

Commentaires

Gesamtkatalog

Catalogue complet

Kataria A: Explainable AI for Healthcare

Explainable AI for Healthcare

Real-life Applications and Use- Cases for Practitioners

2. Understanding the Framework of Explainable AI in Healthcare 3. The Role of Transparency and Interpretability in Healthcare AI 4. Ethical Considerations in Implementing Explainable AI in Healthcare 5. Advancing Healthcare with Explainable AI: Enhancing Patient Monitoring and Outcomes 6. Navigating Interpretability in AI: Balancing Performance, Standards, and Practical Guidance 7. Applications of Explainable AI in Diagnosis and Treatment 8. Challenges and Solutions in Deploying Explainable AI in Smart Healthcare Systems 9. Case Studies: Real-world Examples of Explainable AI in Healthcare 10. Future Directions and Innovations in Explainable AI for HealthcareAppendix -A

The MIT Press Essential Knowledge series

How tech companies, journalists, and policymakers can prevent AI decision-making from going wrong. Our lives are increasingly governed by automated systems influencing everything from medical care to policing to employment opportunities, but researchers and investigative journalists have proven that AI systems regularly get things wrong. Auditing AI is a first-of-its-kind exploration of why and how to audit artificial intelligence systems. It offers a simple roadmap for using AI audits to make product and policy changes that benefit companies and the public alike. The book aims to convince readers that AI systems should be subject to robust audits to protect all of us from the dangers of these systems. Readers will come away with an understanding of what an AI audit is, why AI audits are important, key components of an audit that follows best practices, how to interpret an audit, and the available choices to act on an audit’s results. The book is organized around canonical examples: from AI-powered drones mistakenly targeting civilians in conflict areas to false arrests triggered by facial recognition systems that misidentified people with dark skin tones to HR hiring software that prefers men. It explains these definitive cases of AI decision-making gone wrong and then highlights specific audits that have led to concrete changes in government policy and corporate practice. The Marquand House Collective: Marc Aidinoff, Lena Armstrong, Esha Bhandari, Ellery Roberts Biddle, Motahhare Eslami, Karrie Karahalios, Nate Matias, Danaé Metaxa, Alondra Nelson, Christian Sandvig, and Kristen Vaccaro.

Auditing AI

This book is a comprehensive guide that immerses you into the world of building and deploying AI-powered solutions. You are introduced to the core architecture of LLMs and equipped with essential Best Data Practices (BDPs) for utilizing Generative AI responsibly, ensuring ethical and efficient AI deployment.The book starts with the foundational aspects of Generative AI application development. You will learn the nuances of data handling in Generative AI apps, from working with embeddings to managing unstructured and structured data, and handling Personally Identifiable Information (PII) data. The exploration extends to understanding the differences between deterministic and LLM-based data synthesis and integrating Generative AI apps with enterprise data, providing you with practical insights into leveraging data effectively for intelligent applications. A chapter on prompt engineering explains the importance of prompts in AI interactions, covering a spectrum of techniques and pitfalls while offering exercises to enhance prompt engineering skills. As you progress through the book, you take a journey from conceptualization to production and deployment of Generative AI applications. You discover the essentials of Generative AI application development, gain insights into the pathway from ideation to production, and explore the intricacies of LLM selection and fine-tuning.The book equips you with the knowledge and tools necessary to navigate the complex terrain of AI development and deployment, making it an indispensable resource for AI enthusiasts, developers, and business leaders alike.What You Will Learn<ul><li>Know the core architecture of LLMs and how these models have revolutionized AI applications</li><li>Handle various data types, including unstructured, structured, and personally identifiable information (PII) data in Generative AI applications</li><li>Understand prompt engineering and its importance in AI interactions and applications</li><li>Understand modular design of Generative AI apps, essential backend and frontend components, and the unique principles guiding Generative AI app design</li></ul>&nbsp;&nbsp;

This book is a comprehensive guide that immerses you into the world of building and deploying AI-powered solutions. You are introduced to the core architecture of LLMs and equipped with essential Best Data Practices (BDPs) for utilizing Generative AI responsibly, ensuring ethical and efficient AI deployment.The book starts with the foundational aspects of Gehatnerative AI application development. You will learn the nuances of data handling in Generative AI apps, from working with embeddings to managing unstructured and structured data, and handling Personally Identifiable Information (PII) data. The exploration extends to understanding the differences between deterministic and LLM-based data synthesis and integrating Generative AI apps with enterprise data, providing you with practical insights into leveraging data effectively for intelligent applications. A chapter on prompt engineering explains the importance of prompts in AI interactions, covering a spectrum of techniques and pitfalls while offering exercises to enhance prompt engineering skills. As you progress through the book, you take a journey from conceptualization to production and deployment of Generative AI applications. You discover the essentials of Generative AI application development, gain insights into the pathway from ideation to production, and explore the intricacies of LLM selection and fine-tuning.The book equips you with the knowledge and tools necessary to navigate the complex terrain of AI development and deployment, making it an indispensable resource for AI enthusiasts, developers, and business leaders alike.&nbsp;What You Will Learn<ul><li>Know the core architecture of LLMs and how these models have revolutionized AI applications</li><li>Handle various data types, including unstructured, structured, and personally identifiable information (PII) data in Generative AI applications</li><li>Understand prompt engineering and its importance in AI interactions and applications</li><li>Understand modular design of Generative AI apps, essential backend and frontend components, and the unique principles guiding Generative AI app design</li></ul>&nbsp;Who This Book Is ForFrom AI enthusiasts exploring the field to software developers seeking practical insights, and business leaders looking to harness the power of AI for organizational growth and innovation&nbsp;&nbsp;

Building and Deploying Ethical AI-Powered Solutions

Practical Generative AI: From Concept to Deployment

Cybersecurity Implications in Blockchain Architecture

The Intersection of CFIUS, Team Telecom, AI Controls, and Other Regulations

Navigating Technology and National Security

Combining Human Thinking and Creativity with Technology to Inspire Audiences

Authentic Marketing

Creativity in the Age of AI

What Art Is Now

Depending on who you ask, artificial intelligence is our salvation or our doom; an overhyped, bigoted artist or the ticket to immortality and utopian abundance; just another tech fad or the last invention we need ever make. The AI discourse is confusing, messy, and frustrating. But the technology — and our response to it — will shape the future, whether or not we’re part of the conversation.
Obsolete is&nbsp;for those who are interested in learning more about AI, but unsure of where to start and who to believe. They may feel intimidated by the technical jargon, put off by dry and abstract prose, or skeptical of the loudest voices on the issue (like Elon Musk and Sam Altman). Obsolete will introduce readers to the basics of AI, the idea that it could lead to human extinction, the roiling three-sided debate surrounding extinction fears, and the people and companies trying to build artificial general intelligence (AGI) — that which can outwit humans across the board. The book will grapple with the core arguments animating the AI debates, which are, by turns, uncritically parroted and unduly dismissed. It will also cut through industry hype while seriously entertaining the implications of AGI.
The risk that AGI could result in our extinction is being recognized by a significant and growing number of leading AI researchers, industrialists, and policymakers, along with the wider public. Existential risk from AI has been explored in other books, but Obsolete will be the first to center its analysis on how both capitalist and great power competition make AI more dangerous.
Obsolete will also tackle questions like: Can machines actually outsmart humanity? If so, when could that happen? If AGI is possible, is it inevitable? Why are people trying to build a technology they claim could end the world? Is the idea of AI-driven extinction the product of a big tech conspiracy aiming to hype the technology and control its regulation? Why has the left mostly ignored or dismissed existential risk from AI? Why do some powerful techies welcome human extinction? How could AI enable stable authoritarian regimes? How could killer robots reshape war and the balance of power? What do China and the US want from AI? And why has it become the front line of their brewing Cold War? And finally: What can and should the left do about it?

Power, Profit, And The Race For Machine Superintelligence

Obsolete

Deep Learning in Computer Vision

'It is quite a feat to pull off a densely informative book about a horrible subject that also manages to be charismatic and funny . . . Highly readable' - The Guardian Polls show that over fifty per cent of us don't believe racism exists. In a world made for White people, The Science of Racism uses clear scientific research to expose what we know about racism, exactly how we know it, and what we can do about it. *British police are nine times more likely to use their tasers on Black people. *An item being advertised on eBay will sell for approximately twenty per cent less if a dark-skinned hand is shown in the photos. *Black Caribbean applicants have to apply for around fifty per cent more jobs in order to receive a positive response. Professor Keon West cuts through the divisive anecdotes and rhetoric with decades' worth of clear, factual, rigorous science - the data that reveals truths about racism that we need to know. And, somehow, entertains and amuses along the way. 'Illuminating, surprising, unnerving, moving' - Sathnam Sanghera 'Short circuits the brain' - The Independent 'A book that shouldn't have to exist . . . but I'm glad it does' - Adam Rutherford

Everything you need to know but probably don't - yet

The Science of Racism

Embedded System and GUI Development using MATLAB for Engineering Applications

A Path to Sustainable Development Goals

AI and ML Techniques in IoT-based Communication

Studies in National Governance and Emerging Technologies

This book examines the relationship between artificial intelligence and power in government. The growth of AI has drastically altered the political landscape, and the shifting power relationships between actors involved in deploying AI have the potential to radically impact the ways in which this technology is understood, adopted and implemented in government. &nbsp;
Drawing together scholars from public policy, public management, information technology and law, this volume throws light on the implications that AI poses for existing power relationships between actors involved in the deployment and use of AI in government, and for existing power relationships between the state and citizens. It addresses these issues through three disciplinary perspectives – legal and regulatory studies, public policy and governance, and public management and innovation – in order to fully assess the interplay between AI and power in different governmental settings across the world. Chapters examine a range of themes pertinent to AI and governance, including the exercise of power, liability issues, ethical policymaking, surveillance, and the use of AI tools in public organizations. A concluding chapter maps out future directions for the study of AI and power in government.
Interdisciplinary in nature, the book will appeal to all those interested in public policy, governance, public management, law, and technology studies.
&nbsp;
Sorin Dan is Assistant Professor of Public Management at the School of Management&nbsp;of the University of Vaasa, Finland.
Niina Mäntylä is Professor of Public Law at the School of Management of the University of Vaasa, Finland.
Jane E. Fountain is Distinguished University Professor and Director of the School of Public Policy at the University of Massachusetts, Amherst, USA.

Artificial Intelligence and Power in Government

Explainable AI for Healthcare

Weitere Titel zum Thema