Recommender systems have become indispensable tools in the hotel hospitality industry, enabling personalized and tailored experiences for guests. Recent advancements in large language models (LLMs), such as ChatGPT, and persuasive technologies, have opened new avenues for enhancing the effectiveness of those systems. This paper explores the potential of integrating ChatGPT and persuasive technologies for automating and improving hotel hospitality recommender systems. First, we delve into the capabilities of ChatGPT, which can understand and generate human-like text, enabling more accurate and context-aware recommendations. We discuss the integration of ChatGPT into recommender systems, highlighting the ability to analyze user preferences, extract valuable insights from online reviews, and generate personalized recommendations based on guest profiles. Second, we investigate the role of persuasive technology in influencing user behavior and enhancing the persuasive impact of hotel recommendations. By incorporating persuasive techniques, such as social proof, scarcity and personalization, recommender systems can effectively influence user decision-making and encourage desired actions, such as booking a specific hotel or upgrading their room. To investigate the efficacy of ChatGPT and persuasive technologies, we present a pilot experi-ment with a case study involving a hotel recommender system. We aim to study the impact of integrating ChatGPT and persua-sive techniques on user engagement, satisfaction, and conversion rates. The preliminary results demonstrate the potential of these technologies in enhancing the overall guest experience and business performance. Overall, this paper contributes to the field of hotel hospitality by exploring the synergistic relationship between LLMs and persuasive technology in recommender systems, ultimately influencing guest satisfaction and hotel revenue.

SAN FRANCISCO--Toby Ghassemieh is an inquisitive 12-year-old boy with a pet gecko named Coco and the makings of an ant colony in a bedroom cupboard. He built a forge in his backyard with plaster of Paris to melt aluminum into ingots. He wants to be a physicist when he grows up. All that is on hold, though. What he cares about most is the videogame Fortnite. Same for his buddies Matthew Seiden, Max Howe, Jaren Erville and Reed Leidlein, who all live in or near the city's Richmond neighborhood. These seventh-grade pals used to spend their after-school hours together, either at somebody's house or nearby Rochambeau Park. Now, they spend most of their free time apart, sequestered in their respective homes playing Fortnite and chatting through headsets instead of in person.

The headquarters of Boundless Mind looks as if it were created by a set designer to satisfy a cultural cliché. The tech startup is run out of a one-car garage a few blocks from California's Venice Beach. On the morning I visited, in March, it was populated by a dozen screens–phones, tablets, monitors–and half as many 20-something engineers, all of whom were male and bearded, and one of whom wore a cowboy hat. Someone had written in blue marker across the top of a whiteboard in all caps: You're building amazing sh-t. But that, more or less, is where the Silicon Valley stereotypes end. Ramsay Brown, 29, and T. Dalton Combs, 32, the co-founders of Boundless Mind, are hardly the college dropouts of tech lore; they're trained neuroscientists. And unlike most tech entrepreneurs, they are not trying to build the next big thing that will go viral.

A key acceptability criterion for artificial agents will be the possible moral implications of their actions. In particular, intelligent persuasive systems (systems designed to influence humans via communication) constitute a highly sensitive topic because of their intrinsically social nature. Still, ethical studies in this area are rare and tend to focus on the output of the required action; instead, this work focuses on the acceptability of persuasive acts themselves.Building systems able to persuade while being ethically acceptable requires that they be capable of intervening flexibly and of taking decisions about which specific persuasive strategy to use. We show how, exploiting a behavioral approach, based on human assessment of moral dilemmas, we obtain results that will lead to more ethically appropriate systems. Experiments we have conducted address the type of persuader, the strategies adopted and the circumstances. Dimensions surfaced that can characterize the interpersonal differences concerning moral acceptability of machine performed persuasion, usable for strategy adaptation. We also show that the prevailing preconceived negative attitude toward persuasion by a machine is not predictive of actual moral acceptability judgement when subjects are confronted with specific cases.

Personalized technologies aim to enhance user experience by taking into account users' interests, preferences, and other relevant information. Persuasive technologies aim to modify user attitudes, intentions, or behavior through computer-human dialogue and social influence. While both personalized and persuasive technologies influence user interaction and behavior, we posit that this influence could be significantly increased if the two are combined to create personalized and persuasive systems. For example, the persuasive power of a one-size-fits-all persuasive intervention could be enhanced by considering the user being influenced and their susceptibility to the persuasion being offered. Likewise, personalized technologies could cash in on increased successes, in terms of user satisfaction, revenue, and user experience, if their services used persuasive techniques.

The lab of Atul Butte builds and applies computational tools that convert more than 300 billion points of molecular, clinical, and epidemiological data-measured by researchers and clinicians over the past decade-into new diagnostics, therapeutics, and novel insights into disease. Dr. Butte, a bioinformatician and pediatric endocrinologist, will highlight his team's recent work on clinical evaluations of patients presenting with personal genomes, enabled by the largest curated database of human disease-associated SNP's. With so many genomes now sequenced from individuals from a variety of ethnic backgrounds, and analyzed in a clinical context, Dr. Butte will present how ethnicity alters the background distribution of disease SNP's. Finally, Dr. Butte will also present his team's recent work on environment-wide association studies (EWAS) and how they enable studies of gene-environment interactions.