Today the average consumer spends 8+ hours a day across all devices interacting with online content almost entirely sponsored by advertisements. At over $550B global market size in 2022, and expected to pass $800B by 2026, digital advertising has already surpassed traditional ads in global spend and continues to grow despite economic headwinds. Digital advertising and in particular computational advertising is perhaps the most visible and ubiquitous application of machine learning and one that interacts directly with consumers. When done right, ads connect us to opportunities to enrich our lives and creep us out when done badly. Recently at the forefront of political battles between governments, large multinational corporations, and consumers, digital advertising remains a dynamic industry and research area. 

Looking at the published literature over the last few years, many researchers might consider computational advertising as a mature field. Yet, the opposite is true. Computational advertising is evolving from simple rule-based ads controlled by monolithic publishers and randomly rotating banner ads to highly personalized content experiences within native, video, and display formats on mobile devices, connected TV, and audio—all utilizing data amassed from petabytes of stored user data collected increasingly through inferred identity providers. Increasing use of sequence models and the rise of Generative AI is spawning new directions such as auto-generation of ad creatives or pay-for-use shopping assistants. Ads are far from done.

The AdKDD workshops held in conjunction with KDD conferences in the past years (2017-2022) continue to generate interest from academia and industry--as one of the top venues specifically for advertising research. We believe this is a unique forum for folks interested in aspects of digital advertising to get together, exchange notes and get a pulse for the state of the art, especially in the industry.