Artificial Intelligence in Performance-Driven Design

Introduction

Narjes Abbasabadi¹ and Mehdi Ashayeri²

¹ Department of Architecture, School of Architecture, College of Built Environments, University of Washington, Seattle, WA, USA

² School of Architecture, College of Arts and Media, Southern Illinois University Carbondale, Carbondale, IL, USA

Artificial intelligence (AI) has emerged as a ubiquitous force in today’s world, asserting its influence across an expansive spectrum of human endeavors. AI, as defined by Margaret A. Boden in AI: Its Nature and Future, “seeks to make computers do the sorts of things that minds can do” (Boden 2016). At its core, AI endeavors to engineer computational entities capable of performing tasks traditionally associated with human cognition and to facilitate a synthetic replication of human abilities such as communication, learning, perception, problem‐solving, and reasoning. In pursuit of this, the discipline is methodically segmented into distinct yet interconnected subfields, for example: machine learning (ML), which learns from data to enable informed decision‐making; natural language processing (NLP), which deciphers and constructs human language; computer vision (CV), which interprets visual data; and robotics, which imparts autonomy to machines for task execution. These diverse subfields underpin AI's quest to forge machines that operate with a semblance of human intelligence, enhancing human capacities and spearheading a revolution in technological innovation.

The history of AI unfolds ...