In this book, Helen Pluckrose and James Lindsay document the evolution of postmodern thought from its origins in French postmodernism to its current applications in activist academic fields such as postcolonial theory, queer theory, critical race theory, and intersectionality. They argue that the unchecked proliferation of these ideas, which often assert that knowledge is a social construct, science and reason are tools of oppression, and language is dangerous, presents a significant threat to liberal democracy and modernity. The authors warn that these beliefs, while intended to address social injustices, often do more harm than good, particularly to the marginalized communities they aim to support.
In 'Politics and the English Language', George Orwell argues that vague and imprecise language can obscure truth and manipulate public opinion. He critiques the 'ugly and inaccurate' written English of his time, particularly in political contexts, where language is used to 'make lies sound truthful and murder respectable'. Orwell emphasizes the importance of clear and concrete language, suggesting that poor writing fosters poor political thinking and is a danger to society. He provides examples of bad writing and offers guidelines for effective writing, including six rules to avoid the misuse of language. Orwell believes that language and thought are interdependent and that improving language can help improve political life[1][3][5].
Today we have professor Pedro Domingos and we are going to talk about activism in machine learning, cancel culture, AI ethics and kernels. In Pedro's book the master algorithm, he segmented the AI community into 5 distinct tribes with 5 unique identities (and before you ask, no the irony of an anti-identitarian doing do was not lost on us!). Pedro recently published an article in Quillette called Beating Back Cancel Culture: A Case Study from the Field of Artificial Intelligence. Domingos has railed against political activism in the machine learning community and cancel culture. Recently Pedro was involved in a controversy where he asserted the NeurIPS broader impact statements are an ideological filter mechanism.
Important Disclaimer: All views expressed are personal opinions.
00:00:00 Caveating
00:04:08 Main intro
00:07:44 Cancelling culture is a culture and intellectual weakness
00:12:26 Is cancel culture a post-modern religion?
00:24:46 Should we have gateways and gatekeepers?
00:29:30 Does everything require broader impact statements?
00:33:55 We are stifling diversity (of thought) not promoting it.
00:39:09 What is fair and how to do fair?
00:45:11 Models can introduce biases by compressing away minority data
00:48:36 Accurate but unequal soap dispensers
00:53:55 Agendas are not even self-consistent
00:56:42 Is vs Ought: all variables should be used for Is
01:00:38 Fighting back cancellation with cancellation?
01:10:01 Intent and degree matter in right vs wrong.
01:11:08 Limiting principles matter
01:15:10 Gradient descent and kernels
01:20:16 Training Journey matter more than Destination
01:24:36 Can training paths teach us about symmetry?
01:28:37 What is the most promising path to AGI?
01:31:29 Intelligence will lose its mystery
Machine Learning Street Talk (MLST) 
