Human-Centered AIThe remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity. |
Contents
Are People and Computers in the Same Category? | |
Will Automation AI and Robots Lead to Widespread Unemployment? | |
Summary and Skeptics Corner | |
Rising Above the Levels of Automation 7 Defining Reliable Safe and Trustworthy Systems | |
How to Bridge the Gap from Ethics to Practice | |
TwoDimensional HCAI Framework | |
What Are the Goals of AI Research? | xviii |
Science and Innovation Goals | xxxiv |
Intelligent Agents and Supertools 14 Teammates and Telebots 15 Assured Autonomy and Control Centers 16 Social Robots and Active Appliances | lxvii |
Trustworthy Certification by Independent Oversight | lxx |
Government Interventions and Regulations | cxx |
Summary and Skeptics Corner | cxxxviii |
Assessing Trustworthiness | clx |
Summary and Skeptics Corner PART 4 GOVERNANCE STRUCTURES | i |
Other editions - View all
Common terms and phrases
Accessed June 26 active appliances algorithms applications approach Artificial Intelligence arXiv assessment audit trails autonomous systems bias Boston Dynamics Capability Maturity Model challenge Chapter chatbots citizen science computer automation Conference control centers control panels creative data sets developers devices efforts ethical example explainability Facebook failures give users Google guidelines HCAI framework HCAI systems human control human-centered Human-Computer Interaction human-like IEEE improve independent oversight industry innovation goal Intelligent Systems International life-critical life-critical systems machine learning managers methods monitoring older adults operators organizations performance practices principles problems Proc products and services projects recommender systems reliable responsible safe safety culture science goal self-driving cars sensors Shneiderman social media social robots software engineering stakeholders strategies supertools tasks teammates tele-bots testing training data transparency trustworthy systems understand University user control user experience user experience design user interfaces visual