automation, algorithms, and us

In March 2023 I wrote — understanding the hype and hope — of AI and I highlighted several insights from various experts.

The Good

“With an LLM even a problem with only one user, will be doable, enter your ask, and code gets written, problem gets solved. Runtime ends, app dies. Done. Single use apps are born.” —Linus Ekenstam

US Copyright Office — “ … it is well-established that copyright can protect only material that is the product of human creativity.”

«And in ChatGPT + Wolfram we’re now able to leverage the whole stack: from the pure “statistical neural net” of ChatGPT, through the “computationally anchored” natural language understanding of Wolfram|Alpha, to the whole computational language and computational knowledge of Wolfram Language.» —Stephen Wolfram

“Allen & Overy (A&O), the leading international law firm, has broken new ground by integrating Harvey, the innovative artificial intelligence platform built on a version of Open AI’s latest models enhanced for legal work, into its global practice.”—David Wakeling

The Bad

“Generative AI from large language models is missing core pieces still and had knock-on effects that are really problematic with its lack of understanding facts (or multitudes of facts and truths), but more problematic is it blunts human learning and cognition.” —Thomas Vander Wal

“With the rise of the digital age, this [global, collective] social network is increasingly coupled to algorithms that create unprecedented feedback effects.” —Joseph B. Bak-Coleman et. al.

ChatBots can, “spread misinformation, whether inventing new stories that were never written or telling people about books that don’t exist.” —James Vincent

“… the awesome capabilities of this software could certainly be of use to an authoritarian regime, or a phishing operation, or a spammer, or any number of other dodgy individuals.” —Loz Blain

“The model will confidently state things as if they were facts that are entirely made up.” —Sam Altman

The Ugly

20 jobs that AI will never replace, compared with 20 jobs AI will replace, show ‘Human Resources’ on both lists —Chris Pirillo asking ChatGPT

“So what happens when we automate our most impactful and superior cognitive capacity—thinking—and we don’t think for ourselves?” —Tomas Chamorro-Premuzic

“You can use AI to make fake news faster, cheaper, and on greater scales. That combination is where we might see our extinction.” —Jaron Lanier

Has much changed since then? Recently the New York Times filed a suit against OpenAI and Microsoft for using its stories to train chatbots. Before that, OpenAI fired its CEO and then re-hired him — not exactly a ‘business as usual’ approach. But generative predictive text and image generators are spreading far and wide with some good uses and many charlatans. For positive uses of AI in education and training, follow Donald Clark’s blog —What is Plan B? Not Plan A!

I have played a bit with Sanctum.ai for Mac, but really have not done much with it and still lack a compelling desire to use it. One thing that keeps me from using these generators based on large language models is that they make mistakes or make things up. So if I used one to write an article or prepare a presentation, I would have to spend a fair bit of time checking everything for veracity and accuracy. At this point, I would rather do my own research.

As we enter 2024 I will keep looking at these technologies, the business models around them, and their impacts on society. I will look back next year and review what has changed. Perhaps I will have more information to make a new tetrad based on the McLuhans’ Laws of Media. As I wrote in 2005 — learning the laws of media — like it or not, technology is changing the learning landscape. We cannot adopt one technology and ignore another, or we risk becoming irrelevant. Learning professionals have to understand the technologies that drive our media. The best way to understand these technologies is to use them and watch how others use them.