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Our World in Data: AI Conference Attendance
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Useful as empirical background data when discussing the pace of AI development; conference attendance is one of several metrics used to contextualize the growth of AI research activity for policy and safety audiences.
Metadata
Importance: 35/100dataset
Summary
This Our World in Data page tracks attendance trends at major AI research conferences over time, providing empirical data on the growth of the AI research community. It serves as a quantitative indicator of the expanding scale and pace of AI development, relevant to understanding the trajectory of AI capabilities research.
Key Points
- •Tracks attendance figures at major AI conferences (e.g., NeurIPS, ICML) as a proxy for field growth
- •Demonstrates rapid expansion of the AI research community over recent decades
- •Provides publicly accessible, visualized data useful for policy and governance discussions
- •Growth in conference attendance correlates with broader trends in AI investment and capabilities progress
- •Data can inform arguments about the acceleration of AI development and associated safety concerns
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Artificial intelligence (AI) systems already greatly impact our lives — they increasingly shape what we see, believe, and do. Based on the steady advances in AI technology and the significant recent [increases](https://ourworldindata.org/ai-investments) in investment, we should expect AI technology to become even more powerful and impactful in the following years and decades.
It is [easy to underestimate](https://ourworldindata.org/technology-long-run) how much the world can change within a lifetime, so it is worth taking seriously what those who work on AI expect for the future. Many AI experts [believe](https://ourworldindata.org/ai-timelines) there is a real chance that human-level artificial intelligence will be developed within the following decades, and some think it will exist much sooner.
How such powerful AI systems are built and used will be very important for the future of our world and our own lives. All technologies have positive and negative consequences, but with AI, the range of these consequences is extraordinarily large: the technology has immense potential for good. Still, it comes with significant downsides and high risks.
A technology with such an enormous impact needs to be of central interest to people across our _entire_ society. However, currently, the question of how this technology will be developed and used is left to a small group of entrepreneurs and engineers.
With our publications on artificial intelligence, we want to help change this status quo and support a broader societal engagement.
On this page, you will find charts of AI-related metrics, articles, and key insights to help you better understand what is happening and where we might be heading. We hope that this work will be helpful for the growing and necessary public conversation on AI.
# Key Charts on Artificial Intelligence
[See all charts on this topic](https://ourworldindata.org/data?topics=Artificial+Intelligence)
- [Annual granted patents related to artificial intelligence, by industry](https://ourworldindata.org/grapher/artificial-intelligence-granted-patents-by-industry)
- [Computation used to train notable artificial intelligence systems, by domain](https://ourworldindata.org/grapher/artificial-intelligence-training-computation)
- [Cumulative number of large-scale AI systems by country since 2019](https://ourworldindata.org/grapher/cumulative-number-of-large-scale-ai-systems-by-c
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