AI - Reflections & Perspectives

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* "AI is comparable in scale to the Industrial Revolution or electricity, or even the wheel". - Geoffrey Hinton, Godfather of Deep Learning

* "The hottest new programming language is English" - Andrej Karpathy

* "Treat AI assistants as a slightly-drunk knowledgeable friend" - Richard Seroter

* "No matter how valuable your skills are in the market today, they may or may not be highly valued by the market over the course of your lifetime.

With artificial intelligence (AI) threatening to devalue entire categories of human work, we need to be more purposeful in recognizing a key distinction: the market value of a set of skills is not the same as its human value. 

...the US has become a service economy. 

Many people still don’t recognize caregiving, for example — whether for the very young or very old — as a particularly skilled profession. This is mistaken. Anyone who has ever had a teacher who changed the course of their life simply by listening knows that some people develop skills that are extremely valuable and hard to acquire. How do you listen to someone’s needs even when they’re not clearly articulated? How do you help children develop confidence and joy? How do you help people find calm in a chaotic world?

As we enter an era in which the value of “hard skills” may be diminishing due to automation, the value of “soft skills” — such as empathy and communication — will rise. The future of work may lie not in competing with machines on tasks they do better, but in embracing the human touch that technology can’t replicate.

The market has historically done a terrible job telling us how vital someone’s job is to the functioning of our society. 

The market might determine the price of labor, but it doesn’t define the dignity or value of that labor. 

As the world moves into a future where technology increasingly challenges the definition of skilled work, we must remember that our worth is not determined by a paycheck, an algorithm or a label. It is defined by our shared humanity, our ability to contribute in meaningful ways, and our capacity to care for and connect with each other in a world that is constantly changing."  

- Betsey Stevenson, Professor of Public Policy and Economics at the University of Michigan

* Data is the new oil, but models are the refineries. Who builds the best fine-tuning and deployment tools will own the next decade.  - Greg Isenberg

* "...human imagination is the bottleneck to leveraging LLMs" - S Anand

* “...ask smart to get smart. If you want to get a better answer, you have to know how to ask a better question.” -  Sam Schillace, Microsoft CVP and Deputy CTO

* "Now the Web at large is full of slop generated by large language models, written by no one to communicate nothing...If someone is collecting all the text from your books, articles, Web site, or public posts, it's very likely because they are creating a plagiarism machine that will claim your words as its own...The world where I had a reasonable way to collect reliable word frequencies is not the world we live in now. " - Robyn Speer

* "Tracing the history of AI as a field, but especially the last decade, is a master class in marketing! In fact, the US’s consumer protection and competition regulator, Federal Trade Commission, where I have advised on AI, has warned the public about AI “snake oil” because of deceptive claims about the promise of the tech. We can hopefully res cue it from corporate spin and reveal the reality of a highly concentrated, unaccountable, and notoriously opaque sector. If you take a step back, you also see that these grandiose narratives play a crucial business function of keeping staggering amounts of capital flowing. This is despite nothing resembling a viable business model for the gen AI space and many unsolved accuracy, privacy, and security challenges. 75% of global AI startup funding in 2023 came from the three biggest cloud Big Tech cos — Amazon, Microsoft, Google...if AI is going to be the social and economic infrastructure of the future, then is it acceptable that it be driven by such a narrow set of companies and individuals? We’ve seen problems with the proliferation of plagiarism, misinformation, and deepfakes...we’ve seen other kinds of AI systems like so-called ‘predictive policing’...the question isn’t just “do we want innovation” but who wins/who loses." - Amba Kak, Executive Director of the AI Now Institute

* "Why are we so good at accumulating more information and power, but far less successful at acquiring wisdom?" - Yuval Noah Harari, Nexus: A Brief History of Information Networks from the Stone Age to AI

* "We've been using AI for a long time (to predict things), we just called it algorithms" - Prof Lindsay Jaacks, Professor of Global Health and Nutrition at the University of Edinburgh

W.I.P