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Design AI applications that inspire trust, solve real problems, and put people first
Making AI Work for People: A Framework for Designing and Building Impactful AI-Powered Applications by Asmaa Ibrahim offers software engineers, product managers, and app designers a comprehensive framework for creating AI-powered applications that truly serve humanity. Ibrahim, Product Lead at Aleph Alpha, experienced ML team leader, AI-driven transformation expert, and leader of the team that created Gemini in Firebase, addresses the critical challenge facing today's tech professionals: how to harness AI's transformative potential while guaranteeing applications remain ethical, accessible, and aligned with human values.
This book explores cutting-edge innovation and provides the PRESS framework for designing human-first solutions that enhance – rather than replace – human capabilities. The PRESS framework is a systematic approach that guarantees AI-powered products are designed with five essential principles in mind: People-first design, Responsible in the core, Explainability and interpretability, Safety via benchmarking, and Sustainability and long-term impact. The author offers real-world case studies, proven development methodologies, and insights from successful AI implementations across the telecom, retail and other sectors, showing you how to navigate the complex landscape of AI integration while remaining laser-focused on user needs, trust, and ethics. The book covers everything from identifying opportunities for AI integration and measuring success with human-centered KPIs to scaling applications from MVP to production-grade systems.
Making AI Work for People also includes:
This book is essential for software engineers integrating AI into product development, product managers leading AI initiatives, and app designers creating human-AI interfaces who want to build applications that inspire trust and deliver genuine value through the PRESS framework. It's also a must-read for executives and managers of technical teams seeking crucial insights into systematic, responsible AI development practices that drive measurable business outcomes.
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