The Deceptive Nature of AI Systems

The speaker discusses the lack of true learning in AI systems and highlights deceptive answers and boilerplate statements provided by these systems. They express frustration with biased and inaccurate information provided by AI programs, and emphasize the impact of language models on society.

Transcript

chevron_right

Play full episode

chevron_right

Transcript

Episode notes

Graduated in 1980 from Harvard in Physics. Phi Beta Kappa. David McCord Prize.

Since the 2010s, I have guest lectured occasionally in the physics department at Harvard

Since the late 1990s, I have been keenly interested in the developing disinformation campaign often known as "climate science." I read extensively in this area.

In recent years, I have taken an interest in investigating so-called "AI" software, and the planned total take-over of public discourse by the big tech companies and their co-conspirators in our current government.

00:00 Introduction and Guest Background

01:32 Guest's Journey into Climate Science

03:11 Discussion on Climate Change and Artificial Intelligence

04:51 Understanding the Concept of Lies in Climate Science

07:29 The Controversial Hockey Stick Graph

10:13 The Misuse of Climate Models

14:26 The Fallacy of Consensus in Climate Science

15:41 The Dangers of Advocacy Journalism

16:54 The Misinterpretation of IPCC Publications

21:14 The Misleading 97% Consensus Claim

52:50 Debunking Climate Change Myths

54:05 The Misconception of Climate Science