Machine Learning: Architecture in the age of Artificial Intelligence

Book Description

‘The advent of machine learning-based AI systems demands that our industry does not just share toys, but builds a new sandbox in which to play with them.’ – Phil Bernstein

The profession is changing. A new era is rapidly approaching when computers will not merely be instruments for data creation, manipulation and management, but, empowered by artificial intelligence, they will become agents of design themselves. Architects need a strategy for facing the opportunities and threats of these emergent capabilities or risk being left behind. Architecture’s best-known technologist, Phil Bernstein, provides that strategy. Divided into three key sections – Process, Relationships and Results – Machine Learning lays out an approach for anticipating, understanding and managing a world in which computers often augment, but may well also supplant, knowledge workers like architects. Armed with this insight, practices can take full advantage of the new technologies to future-proof their business. Features chapters on:

  • Professionalism
  • Tools and technologies
  • Laws, policy and risk
  • Delivery, means and methods
  • Creating, consuming and curating data
  • Value propositions and business models.

Table of Contents

Acknowledgments, Introduction, Foreword by Mark Greaves,

1 – PROCESS

1.1 Tools and technologies,

1.2 What is AI?

1.3 Professional Information and Knowledge

1.4 AI and Process Transformation in Design, and Beyond

1.5 Scopes of Service

1.6bDelivery Means and Methods

2 – RELATIONSHIPS

2.1 Economics

2.2 Laws Policy, and Risk

2.3 Professionalism

2.4 Education, Certification, and Training

3 – RESULTS

3.1 Objectives of design

3.2 Creating, Consuming and Curating Data

3.3 Tasks, Automation

3.4 Labour of Design

3.5 Value Propositions and Business Models

Index

Bibliography

Author(s)

Biography

Phil Bernstein is an architect and technologist who is an Associate Dean and Professor, Adjunct at the Yale School of Architecture where he has been a member of the faculty since 1988. Prior to his current full-time role at Yale he was a vice president at Autodesk, where he helped develop and execute the company strategy that resulted in Building Information Modelling. Prior to Autodesk he was a principal at Pelli Clarke Pelli Architects. He is the author of Architecture Design Data: Practice Competency in the Era of Computation, and co-author of Building (In) the Future: Recasting Labor in Architecture and Goat Rodeo: Practicing Built Environments. He writes, lectures, and consults extensively on the implications of technology on architectural practice.

 

Original post: https://www.routledge.com/Machine-Learning-Architecture-in-the-age-of-Artificial-Intelligence/Bernstein/p/book/9781914124013

Leave a Reply

Your email address will not be published. Required fields are marked *