Challenges as catalysts: how Waymo’s Open Dataset Challenges shape AI development

• DOI: 10.1007/s00146-024-01927-x
• Publication Date: 2024-04-17T13:02:03Z
• Authors: Sam Hind; Fernando N. van d...; Max Kanderske
• Keywords: Incrementalism

Abstract Artificial intelligence (AI) and machine learning (ML) are becoming increasingly significant areas of research for scholars in science technology studies (STS) media studies. In March 2020, Waymo, Google/Alphabet’s autonomous vehicle project, introduced the ‘Open Dataset Virtual Challenge’, an annual competition leveraging their Waymo Open Dataset. This freely accessible dataset comprises annotated data from own vehicles. Yearly, has continued to host iterations this challenge, inviting teams computer scientists tackle evolving vision problems using Google's tools. article analyses these challenges, situating them within context ‘Grand Challenges’ artificial (AI), which aimed foster accountable commercially viable advancements late 1980s. Through two exploratory workshops, we adopted a ‘technographic’ approach examine pivotal role challenges development political economy AI. Serving as organising principle AI innovation ecosystem, challenge connects companies external collaborators, driving specific domains. By exploring six key themes—interface methods, incrementalism, metrics, vernacular, applied domains, competitive advantages—the illustrates shaping development. unpacking dynamic interaction between data, computation, labour, serve catalysts propelling towards self-driving technologies. The study reveals how have historically presently shaped landscape