# Winning and losing with Artificial Intelligence: What public discourse about ChatGPT tells us about how societies make sense of technological change

arXiv: https://arxiv.org/abs/2507.06876 · HTML: https://mlsanity.com/paper/2507.06876/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 49 references that are in the map.
- First posted on arXiv 9 Jul 2025.

## Builds on (most cited first, 9 of 9)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [Hierarchical Text-Conditional Image Generation with CLIP Latents](https://mlsanity.com/paper/2204.06125/) (2022)
- [ChatGPT: A Meta-Analysis after 2.5 Months](https://mlsanity.com/paper/2302.13795/) (2023)
- ["I think this is the most disruptive technology": Exploring Sentiments of ChatGPT Early Adopters using Twitter Data](https://mlsanity.com/paper/2212.05856/) (2022)
- [Public Perception of Generative AI on Twitter: An Empirical Study Based on Occupation and Usage](https://mlsanity.com/paper/2305.09537/) (2023)
- [Public Attitudes Toward ChatGPT on Twitter: Sentiments, Topics, and Occupations](https://mlsanity.com/paper/2306.12951/) (2023)
- [Linguistic Landscape of Generative AI Perception: A Global Twitter Analysis Across 14 Languages](https://mlsanity.com/paper/2405.20037/) (2024)
- [Artificial Intelligence in Election Campaigns: Perceptions, Penalties, and Implications](https://mlsanity.com/paper/2408.12613/) (2024)

## Built on by (most cited first, 1 of 1)

- [Expectation, Backlash, Recovery, and Excitement: How Model Releases Shape Reddit Perceptions of Conversational AI Systems](https://mlsanity.com/paper/2608.24654/) (2026)

## Abstract (arXiv)

Public product launches in Artificial Intelligence can serve as focusing events for collective attention, surfacing how societies react to technological change. Social media provide a window into the sensemaking around these events, surfacing hopes and fears and showing who chooses to engage in the discourse and when. We demonstrate that public sensemaking about AI is shaped by economic interests and cultural values of those involved. We analyze 3.8 million tweets posted by 1.6 million users across 117 countries in response to the public launch of ChatGPT in 2022. Our analysis shows how economic self-interest, proxied by occupational skill types in writing, programming, and mathematics, and national cultural orientations, as measured by Hofstede's individualism, uncertainty avoidance, and power distance dimensions, shape who speaks, when they speak, and their stance towards ChatGPT. Roles requiring more technical skills, such as programming and mathematics, tend to engage earlier and express more positive stances, whereas writing-centric occupations join later with greater skepticism. At the cultural level, individualism predicts both earlier engagement and a more negative stance, and uncertainty avoidance reduces the prevalence of positive stances but does not delay when users first engage with ChatGPT. Aggregate sentiment trends mask the dynamics observed in our study. The shift toward a more critical stance towards ChatGPT over time stems primarily from the entry of more skeptical voices rather than a change of heart among early adopters. Our findings underscore the importance of both the occupational background and cultural context in understanding public reactions to AI.