Sept. 29, 2023, 6:48 p.m. | Viggy Balagopalakrishnan

Towards Data Science - Medium towardsdatascience.com

Targeting specific mechanisms mitigates AI risks more effectively, is easier to get consensus on, and avoids unintended consequences of brute force approaches

Photo by Growtika on Unsplash

This is the second of three articles in Unpacked’s “Tech Policy September” series.

Disclaimer: The views expressed in this article are solely my own and do not reflect the views or positions of any organization with which I am affiliated, including current and past employers.

The launch of ChatGPT kicked off a new …

ai regulation ai-risk ai risks article articles artificial intelligence case consensus consequences data science deep-dives policy regulating ai risks september series tech tech policy

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne