Selling Advice
The Artificial Intelligence Disclosure Penalty: Humans Persistently Devalue AI-Generated Creative Writing
Manav Raj, Justin Berg & Rob Seamans
Journal of Experimental Psychology: General, forthcoming
Abstract:
Although preliminary evidence suggests that humans often react aversely to artificial intelligence (AI)-generated creative works, we have little understanding of how robust or persistent these reactions may be. In a series of 16 preregistered experiments (N = 27,491), we examine how evaluations of creative writing are affected by whether participants believe the content is produced with an AI model. We find consistent evidence of an AI disclosure penalty: Participant evaluations of creative writing decrease when they believe writing samples were written by an AI model -- or with the help of one -- rather than a human author alone, and this effect is mediated by perceived authenticity. The AI disclosure penalty is sticky, persisting across evaluation metrics, contexts, kinds of written content, and multiple interventions derived from prior research aimed at moderating the effect. Our results indicate that AI disclosure penalties about creative writing may be stubbornly difficult to mitigate, at least at this time.
The Liveness Lift: Viewing Live Streams Creates Connection and Enhances Engagement in Amateur Music Performances
Nofar Duani, Alixandra Barasch & Adrian Ward
Journal of Marketing, forthcoming
Abstract:
Recent advances in live-streaming technology have empowered millions of amateur content creators to broadcast live video over the internet, sharing events and experiences with consumers as they happen. Despite the growing popularity of live streams, little research has examined how liveness may affect viewers’ experiences and behaviors. The current research addresses this gap, and uses the context of amateur music performances to investigate how, when, and why viewing live streams (versus equivalent or identical pre-recorded video) can enhance presence, connection, enjoyment, and engagement. We find evidence of a mere liveness effect on consumer experiences: simply knowing that an online video stream is live causes viewers to feel more connected to streamers. This effect is facilitated by an elevated sense of presence, or “being there,” in events that are viewed in real time. Critically, this effect also drives a liveness lift for online streamers; viewers of live (versus pre-recorded) streams enjoy the content more, choose to continue watching longer, and are more willing to follow and subscribe to the streamers’ channels. These findings have clear substantive implications: marketers, platform developers, and content creators can enhance consumer connection, enjoyment, and engagement by going live.
The Effect of Downvotes on Content Creation: Evidence from Social Media
Varad Deolankar, Jessica Fong & S. Sriram
Journal of Marketing Research, forthcoming
Abstract:
This paper studies how receiving negative peer feedback, in the form of downvotes, affects [user-generated content] creation on Reddit. We focus on the following outcomes: (a) propensity to post (incidence), (b) where users post, and (c) the strength of opinion (intensity), measured by the extremity of users’ texts. The latter two outcomes are important given ongoing concerns about how social media platforms may contribute to echo chamber formation and polarization. We find that negative feedback increases users’ subsequent posting activity, relative to no feedback, and we do not find evidence that receiving negative feedback drives users away, alleviating concerns about echo chamber formation. In addition, negative peer feedback moderates extreme sentiments -- when initial views are extreme, users temper the intensity of their subsequent posts. These effects of negative feedback are consistent with users attempting to maintain their reputation.
Less to Process, More to Express: The Impact of AI-Generated Summaries on Review Diversity
Yi Su et al.
University of Florida Working Paper, October 2025
Abstract:
As generative AI becomes increasingly embedded in online marketplaces, understanding its influence on consumer activities becomes critical. In today's online marketplaces, consumers contributing reviews are particularly important, as consumer review systems now serve as a primary channel for sharing and obtaining product information. Effectively managing consumer review systems in the context of expanding generative AI applications requires a clear understanding of how these tools shape review contributions. Yet, despite the widespread adoption of generative AI tools, empirical evidence of their impact on consumer-generated content remains limited. Our study addresses this gap by exploiting Amazon's rollout of AI-generated summaries (AIGS) on product pages as a natural experiment. Contrary to the prevailing narrative that AI might homogenize voices, we find that the introduction of AIGS significantly increases the diversity of consumer reviews. This effect is consistent with the notion that by condensing prior reviews into concise and informative summaries, AIGS reduces the cognitive effort required to process existing information, enabling contributors to focus on offering more distinctive experiences and insights. Moderation analyses reveal that this positive effect on review diversity is particularly pronounced for products with high rating dispersion or limited product descriptions, contexts in which assimilating prior reviews typically demands greater cognitive effort. These findings support the interpretation that AIGS fosters review diversity by alleviating cognitive load in information processing. Our findings advance the theory on generative AI, human-AI interaction, and user-generated content, while offering practical guidance for platform managers: thoughtfully designed AI features can amplify diverse perspectives, enriching the informational value of reviews.
Does Generative AI Crowd Out Human Creators? Evidence from Pixiv
Sueyoul Kim, Ginger Zhe Jin & Eungik Lee
NBER Working Paper, January 2026
Abstract:
Using a comprehensive dataset of posts from a major platform for anime- and manga-style artwork, we study the impact of the launch of a prominent text-to-image generative AI. Focusing on the majority of incumbent creators who do not adopt AI as a primary tool, we show that the AI launch led to a significant decline in post uploads by illustrators, whereas comic artists were less affected, reflecting the need for tight stylistic alignment across sequential images in comics. We present empirical evidence for two underlying mechanisms. First, illustration posts experience a loss of viewer attention, measured by bookmarks, following the AI launch, which can significantly harm creators’ business models. Second, direct competition from AI-generated content plays an important role: illustrators working on intellectual properties (IPs, such as Pokémon) that are more heavily invaded by AI reduce their uploads disproportionately more. We further examine creators’ responses and show that illustrators with greater exposure to AI avoid using tags favored by AI-generated content after the AI launch and broaden the range of IPs they work on, consistent with a risk-hedging response to AI invasion.