INFORMS Releases

Current thinking increasingly treats artificial intelligence (AI) as a scalable substitute for human coaching in digital health. New research published in the INFORMS journal Marketing Science challenges that assumption, finding that access to human coaches in addition to an AI coach leads to significantly greater weight loss than AI coaching alone.

It’s the most common dilemma that serialized digital content platforms face. Should they release an entire book or season at once so audiences can binge, or release chapters or episodes over time to encourage audiences to return?

Most medical devices do not hit the market through rigorous safety testing but by being deemed similar enough to something already approved—the “predicate” device through a mechanism known as the FDA’s 510(k) pathway. But similar is not a synonym for safe. While the assumption may be that substantial equivalence is a reasonable stand-in for a safety review, a share of devices cleared with this method still get recalled, and the FDA spends valuable time reviewing devices the same way, regardless of how risky it is on paper.

As companies race to integrate artificial intelligence into the workplace, new research suggests workers benefit most when AI is paired with experience rather than treated as a replacement for it.

The common belief throughout the marketing and advertising world is that generative AI can produce striking visuals, but it struggles to match the performance and brand discipline of skilled human designers. New research published in the INFORMS journal Marketing Science challenges that assumption, finding that a carefully designed AI system can outperform visuals created by humans, and it can outperform designs created by another AI model that was optimized solely on the basis of aesthetics.

The study, “Leveraging Generative AI to Create Visual Content in Digital Advertising,” was authored by Remi Daviet of INSEAD and Yohei Nishimura of the Wisconsin School of Business at the University of Wisconsin–Madison. They used active-learning engine as part of a live campaign to solve the problems of finding high-performing AI images while making sure to keep them on-brand and effective.