Software tools with autonomous capabilities to generate design outcomes are increasingly used by designers across industries and tasks, and these tools fundamentally revamp traditional design processes. Designers have to focus more on developing and managing the tools and understanding their behavior—and less on understanding the incremental shaping of the design artifact itself.

Autonomous tools acquire these capabilities by using computational methods adopted from artificial intelligence, such as pseudo-random number generation, machine learning, pattern recognition, meta-heuristics, and evolutionary algorithms. Because the tools can run multiple times without placing additional demands on the human designer, they produce increasingly varied and qualitatively different outcomes compared to the use of established automation tools supporting design such as CASE tools or CAD/CAM tools.

Part A: Introduction

• Welcome & review: what has happened since the last workshop?
• Two short presentations

Part B: Surveying the field

• Identification of relevant related/adjacent research fields
• Overview of existent research (across relevant fields)
• Identification of research opportunities (particular industries, technologies, companies, etc.)

Part C: Crafting a research agenda

• Key research questions, e.g., organized by phenomena
• Theoretical lenses
• Where/how to collect data
• What analysis methods to use (perhaps with focus on computational analyses)

Part D: Discussion & Closure