Professor Arvind Narayanan from Princeton University has released the annotated slides from his presentation at the International Conference on Machine Learning (ICML 2026). This document provides a high-level overview of the concept of "AI as Normal Technology," a topic gaining significant attention in the global research community.
Detailed Developments
Narayanan's presentation at ICML 2026, co-authored with Sayash Kapoor, aims to normalize the perception of artificial intelligence. Instead of viewing AI as a supernatural force or an uncontrollable revolutionary technology, the authors urge the academic community and the public to treat AI similarly to other traditional software technologies. The first part of the talk summarizes the core ideas that these two researchers developed in their previous publications.
Technical & Technology Analysis
This approach requires engineers and developers to apply rigorous testing, risk assessment, and quality management standards of classical software engineering to machine learning systems. According to the shared document, mythologizing the capabilities of large language models (LLMs) often leads to overlooking fundamental system errors, security vulnerabilities, and bias in training data. Bringing AI back to its proper place as a normal technology makes it easier to apply standardized technical governance frameworks.
Expert Opinions & Remarks
Meta's Chief AI Scientist, Yann LeCun, reshared the post, implicitly signaling agreement with this less-hyped perspective on AI. Many industry experts also note that viewing AI through a realistic lens will help deflate the expectation bubble and direct investment capital toward practical applications with measurable efficiency rather than speculative projects.
Impact & Future
This document could alter how policymakers and tech enterprises in Vietnam and globally approach the technology. When AI is positioned as a normal technology, regulatory frameworks concerning data safety, product liability, and copyright will be built upon existing legal frameworks rather than creating complex and unnecessary legal exceptions.