ThAT Thursdays: Fellowship Seminars
✦ ThAT Thursdays: Fellowship Seminars with Mayank Agrawal
We are pleased to announce an upcoming session of the Thinking About Thinking Fellowship Seminar Series, bringing together researchers and entrepreneurs working at the frontier of intelligence across AI, neuroscience, mathematics, and cognitive science.
𝑺𝒆𝒎𝒊𝒏𝒂𝒓 𝒕𝒊𝒕𝒍𝒆: Proof of Human: The Invisible Turing Test for the Internet
𝑫𝒂𝒕𝒆: June 25th
𝑻𝒊𝒎𝒆: 6pm GMT
𝑳𝒐𝒄𝒂𝒕𝒊𝒐𝒏: Fellowship Seminar Room
𝑰𝒏𝒕𝒆𝒓𝒗𝒊𝒆𝒘𝒆𝒅 𝒃𝒚: Anastasia Ilina
𝑺𝒖𝒑𝒑𝒐𝒓𝒕𝒆𝒅 𝒃𝒚: XTX Markets | Cooley LLP
This Fellowship Seminar is exclusively available to members of the Thinking About Thinking Fellowship.
For this session, Mayank Agrawal will introduce the Process Turing Test, a new framework for distinguishing humans from AI that moves beyond linguistic output to analyse behavioural dynamics.
As large language models increasingly pass traditional text-based Turing Tests, the challenge becomes understanding the underlying architecture of intelligence itself. Drawing on process tracing data from canonical cognitive tasks, Mayank will demonstrate how behavioural embeddings can capture computational signatures unique to human cognition.
The discussion will explore how patterns of perception, control, and decision-making can provide robust proof-of-personhood, creating systems that are resistant to adversarial attacks while offering deeper insight into the fundamental differences between human and machine intelligence.
Bridging cognitive science, machine learning, psychology, and internet infrastructure, this work opens new perspectives on identity, verification, and the future relationship between humans and intelligent systems.
This research is joint work with Milena Rmus (Roundtable), Mathew Hardy (Roundtable), and Tom Griffiths (Princeton University).
𝑨𝒃𝒐𝒖𝒕 𝒕𝒉𝒆 𝒔𝒑𝒆𝒂𝒌𝒆𝒓:
Mayank Agrawal is CEO of Roundtable Technologies, where he leads the development of Proof of Human technology that analyses behavioural patterns to create invisible, continuous human verification.
He holds a PhD in Psychology and Neuroscience from Princeton University, where his research focused on human cognition, decision-making, and computational models of intelligence. His work has been published in leading journals including Science and PNAS, and has been featured by The Guardian.
Combining insights from cognitive science, behavioural analysis, and machine learning, Mayank's work seeks to establish "humanness" as a foundational building block of internet infrastructure.
He is based in San Francisco and writes on minds, machines, and markets.
Bring your most insightful questions and join the discussion.