This post is co-authored with Hunter Priniski (UCLA)
If you want to understand where the conversation about artificial intelligence is heading, it’s good to look at how the experts are feeling.
Hunter Priniski PhD (Substack) (UCLA Postdoc) analyzed a massive dataset from PublicScholarship.org, the largest curated database of public-facing scholarship. This database captures how credentialed experts—computer scientists, ethicists, and sociologists—communicate with the general public through podcasts, videos, and essays.
By running an emotion classifier across 5,233 AI-related entries spanning from April 2016 to March 2026, a striking macro-trend emerges: expert discourse has shifted from an overwhelming sense of surprise to a sustained state of fear. Since expert voices tend to be more accurate than the norm, the fear may very well be justified and signal danger ahead. Check out the interactive graph.
Here is a look at how landmark AI events shaped this emotional trajectory, and how it compares to broader public sentiment.
2016–2018: The Era of Surprise
In the early years of our dataset, “surprise” was the dominant emotion among public intellectuals. This era was defined by astonishing leaps in capability that caught even seasoned researchers off guard:
March 2016: DeepMind’s AlphaGo shocked the world by defeating world champion Lee Sedol, a milestone experts thought was still a decade away.
2017: Google researchers introduced the Transformer architecture in “Attention Is All You Need,” quietly laying the foundation for the modern AI boom.
2018: OpenAI released GPT-1, the first Generative Pre-trained Transformer.
During this period, experts were genuinely astounded by the rapid pace of discovery, asking themselves what these systems meant and where they could possibly go.
2019–2022: Joy, Wonder, and the First Spikes of Unease
While surprise dominated the early days, the middle years of our timeline were highly complex. As we noted in our data fact-check, “joy” actually surged to become a dominant emotion for long stretches between 2019 and late 2022, reflecting genuine excitement about AI’s potential in scientific discovery and creative expression.
However, this period also introduced the first major spikes of fear.
2019: OpenAI partially withheld the release of GPT-2 due to fears of malicious use, and “deepfakes” entered the mainstream consciousness.
2020: The release of GPT-3, DALL-E, and DeepMind’s AlphaFold (which solved the 50-year protein folding problem) showcased that AI could write, create art, and solve biological mysteries.
Late 2022–Present: The ChatGPT Inflection and the Reign of Fear
Everything changed on November 30, 2022, with the release of ChatGPT. As millions of non-technical people experienced conversational AI for the first time, the emotional equilibrium of expert discourse shattered.
Following the release of ChatGPT, fear pulled decisively ahead of all other emotions and remains the dominant sentiment through the present day. This anxiety was sustained by a relentless wave of developments:
2023: The release of GPT-4, an open letter signed by tech leaders calling for a six-month pause on AI training, and advancing negotiations on the EU AI Act.
2024–2025: The rapid proliferation of AI agents and intensifying concerns over deepfakes during global elections.
When experts write fearfully about AI today, it is typically grounded in concrete concerns: labor displacement, the erosion of democratic accountability, and the concentration of corporate power.
How This Compares to Broad Sentiment
This trajectory among public scholars mirrors, and in some cases anticipates, shifts in general public opinion recorded by other researchers:
The Pew Research Center found that the share of Americans who are “more concerned than excited” about AI jumped 15 points in just two years, rising from 37% in 2021 to 52% in August 2023.
A 2026 GDELT study mapping global media discourse found that Western coverage exhibited heavy “regulatory skepticism,” though South and East Asian media remained more positive.
Ouchchy, Coin, and Dubljević (2020) noted that mainstream media coverage of AI ethics is often shallow and lacks input from actual ethicists. This highlights exactly why public-facing scholarship is so vital: it injects much-needed disciplinary depth into the public conversation.
The Takeaway As the novelty of AI has worn off, the gravity of its implications has set in. Because experts process and contextualize information earlier than the general public, their growing apprehension is a leading indicator we should all be paying attention to.
