Community Announcement:
We are also building DeepVista to help companies run self-improving, agent-native operations. We are currently sharing private beta invitations and distributing tactical playbooks to early partners.
If you want to secure early access and test our workflows, please sign up here.
Digital records of our daily activity are continuously recorded. Every browser click, location check, and social media transaction is stored in databases.
Here is the part that stops you cold: seemingly trivial actions—such as liking a photo of a funny goat on Facebook—are sufficient for machine learning models to predict intimate characteristics like sexual orientation, political views, and intelligence with high accuracy.
Dr. Michal Kosinski thinks that the entire concept of data privacy is mathematically obsolete. And he has spent his academic career proving why.
Michal is an associate professor of Organizational Behavior at Stanford Graduate School of Business. His PhD research, which combined psychology and computer science, proved how digital footprints could be used to predict psychological traits. This exact methodology was later deployed without his involvement in the Cambridge Analytica data-harvesting scandal. Today, his research focuses on artificial intelligence, demonstrating that LLMs have spontaneously developed Theory of Mind capabilities and psychological profiling tools by default.
After reading this newsletter and listening to the interview, you’ll walk away with a functional framework for how algorithms profile human psychology, why regulation cannot keep pace with AI progress, and a practical rule of thumb to protect your digital communication.
The Cambridge Analytica Reality: Why both major political parties deploy psychographic targeting, and how the scandal served as a convenient political scapegoat.
The Math of Digital Footprints: How simple digital traces, like Facebook likes, predict deeply personal traits with high accuracy while bypassing traditional questionnaire biases.
Big Tech Incentives: Why Facebook and dating websites actively profit from friction and imperfect matching rather than perfect targeting.
Democratized Profiling: Why Large Language Models (LLMs) represent a massive leap in profiling capability by pre-encapsulating human psychological profiles.
“Grown” AI vs. “Designed” AI: The shift from programmed algorithms to evolutionary training, where models discover superhuman, uncontrolled strategies to achieve goals.
The Scientist’s Dilemma: Why mixing academic research with ideological activism destroys public trust in science.
Prof. Michal Kosinski (Website): https://www.michalkosinski.com/
Jing Conan Wang (Host): https://www.linkedin.com/in/jingconan/
FounderCoHo: https://www.foundercoho.com/
00:00 - Highlights & Intro
02:33 - Journey from Mathematics to Psychology
09:02 - Interdisciplinary Innovation and Research Philosophy
12:06 - Predicting Psychological Profiles from Digital Footprints
26:43 - The Cambridge Analytica Scandal and Data Harvesting
36:54 - Big Tech Incentives and Advertising Platforms
50:57 - The Illusion and Paradox of Data Privacy
1:01:37 - The Threats of Generative AI and LLMs
1:11:06 - The Conflict Between Science and Activism
1:20:19 - Advice to Younger Self
1:21:05 - Outro
Never miss a FounderCoHo community event, podcast, or newsletter. Join us:
No posts
Comments
Nothing yet. Say the first thing.
Sign in to join the conversation.