Big Data Big Design: Why Designers Should Care about Artificial Intelligence - Softcover

Armstrong, Helen

 
9781616899158: Big Data Big Design: Why Designers Should Care about Artificial Intelligence

Inhaltsangabe

Big Data, Big Design provides designers with the tools they need to harness the potential of machine learning and put it to use for good through thoughtful, human-centered, intentional design.

Enter the world of Machine Learning (ML) and Artificial Intelligence (AI) through a design lens in this thoughtful handbook of practical skills, technical knowledge, interviews, essays, and theory, written specifically for designers. Gain an understanding of the design opportunities and design biases that arise when using predictive algorithms. Learn how to place design principles and cultural context at the heart of AI and ML through real-life case studies and examples. This portable, accessible guide will give beginners and more advanced AI and ML users the confidence to make reasoned, thoughtful decisions when implementing ML design solutions.

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Über die Autorin bzw. den Autor

Helen Armstrong is a professor of graphic design at North Carolina State University in Raleigh, North Carolina. Her previous books include Graphic Design Theory, Digital Design Theory, and Participate.

Keetra Dean Dixon is a designer, former professor at RISD, and winner of a US Presidential Award with a permanent design collection at SFMOMA, based on the East Coast and rural Alaska.

Von der hinteren Coverseite

Big Data Big Design defines and explores what every designer needs to know about artificial intelligence (AI) and machine learning (ML), all the while inspiring designers to harness this technology and establish leadership via thoughtful, human-centered design. It’s not just about the algorithms, it’s about what we do with the data once received. Ellen lupton says, “ Important and accessible!” Readers will explore the principles and cultural context of Ai and ML, as well as gain an understanding of the design opportunities and pitfalls that arise as designers incorporate predictive algorithms into their practice. Designers will walk away from this portable, friendly book inspired by practical and theoretical knowledge that will allow them to make thoughtful decisions as this technology unfolds.

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