This is, by the way, the dirty secret of the machine learning movement: almost everything produced by ML could have been produced, more cheaply, using a very dumb heuristic you coded up by hand, because mostly the ML is trained by feeding it examples of what humans did while following a very dumb heuristic. There's no magic here. If you use ML to teach a computer how to sort through resumes, it will recommend you interview people with male, white-sounding names, because it turns out that's what your HR department already does. If you ask it what video a person like you wants to see next, it will recommend some political propaganda crap, because 50% of the time 90% of the people do watch that next, because they can't help themselves, and that's a pretty good success rate.

Forget Privacy: You're Terrible at Targeting Anyway

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Since the generative AIs have been trained on the entirety of human work — most of it mediocre — it produces “wisdom of the crowd”-like results. They may hit the mark but only because they are average.

Kevin Kelly • Interview: Kevin Kelly, Editor, Author, and Futurist

all of this remains much less a science than an art, and AIs still work more like people than software.

Ethan Mollick • Co-Intelligence: Living and Working with AI

A machine-learning model, trained by data, “is by definition a tool to predict the future, given that it looks like the past. . . . That’s why it’s fundamentally the wrong tool for a lot of domains, where you’re trying to design interventions and mechanisms to change the world.”

Brian Christian • The Alignment Problem

Meanwhile AI may make better decisions than people and steal our jobs, but computers and algorithms cannot frame. AI is brilliant at answering what it is asked; framers pose questions never before voiced. Computers work only in a world that exists; humans live in ones they imagine through framing.

Kenneth Cukier, Viktor Mayer-Schoenberger, • Framers

And I’ll make the case that many of the algorithmic systems that we have put in place to guide our companies and our economy have been designed to disregard the humans and reward the machines.

Tim O'Reilly • Wtf?

In little more than a decade, machine learning has moved from a highly specialized technique to something that almost anyone with data and computational power can do. That is to be welcomed — yet it remains essential that the industry can navigate both the proliferation of tools and frameworks in the space and the ethical issues that are becoming

Kevin Kelly • Interview: Kevin Kelly, Editor, Author, and Futurist

Ethan Mollick • Co-Intelligence: Living and Working with AI

Brian Christian • The Alignment Problem

Kenneth Cukier, Viktor Mayer-Schoenberger, • Framers

Tim O'Reilly • Wtf?

Thoughtworks • Technology Radar | An opinionated guide to technology frontiers | Thoughtworks