Information Technology

When Sam Altman was ousted as CEO of OpenAI, some hinted that lurid depravities lay behind his downfall. Surely, OpenAI’s board wouldn’t have toppled him if there weren’t some sordid story about to hit the headlines? But the reporting all seems to be saying that it was God, not Sex, that lay behind Altman’s downfall. And Money, that third great driver of human behavior, seems to have driven his attempted return and his new job at Microsoft, which is OpenAI’s biggest investor by far. [click to continue…]

Last September, Abe Newman, Jeremy Wallace and I had a piece in Foreign Affairs’ 100th anniversary issue. I can’t speak for my co-authors’ motivations, but my own reason for writing was vexation that someone on the Internet was wrong. In this case, it was Yuval Harari. His piece has been warping debate since 2018, and I have been grumpy about it for nearly as long. But also in fairness to Harari, he was usefully wrong – I’ve assigned this piece regularly to students, because it wraps up a bunch of common misperceptions in a neatly bundled package, ready to be untied and dissected. [click to continue…]

More AI madness! Couple of months ago there was a weird Daily Beast piece. It’s bad, but in a goofy way, causing me to say at the time ‘not today, Hal!’

But now I’m collecting op-ed-ish short writings about AI for use as models of good and bad and just plain weird writing and thinking, to teach undergrads how hard it is to write and think, so they can do better. And this one stands out as distinctively bad-weird. First the headline is goofy: “ChatGPT May Be Able to Convince You Killing a Person Is OK.” Think about that. But it’s unfair to blame the author, maybe. But read the rest. Go ahead. I’ll wait. What do you think? It’s funny that the author just assumes you should NEVER let yourself be influenced by output from Chat-GPT. Like: if Chat-GPT told you to not jump off a bridge, would you jump off a bridge? There is this failure to allow as we can, like, check claims as to whether they make sense? A bit mysterious how we do this yet we do. And ethics is a super common area in which to do this thing: so it only makes sense that you could get Chat-GPT to generate ethical claims and then people could read them and, if they make sense, you can believe them due to that. Never mind that the thing generating the prospective sensible claims is just a statistics-based mindless shoggoth.

If a shoggoth is talking trolley sense about OK killing, believe it!

Anyway, I thought it was funny. [click to continue…]

Let me try to focus my thoughts from the previous post.

Do is as do does.

Agent-like entities are equivalent to real agents. If GPT-4 can trick people into thinking it’s a trickster, it’s a trickster. If you can mimic a chess master, you’re a chess master. It’s fun to wonder whether there will be anything it’s ‘like’ to be superintelligent AI, ending us, if it does, but that’s by the by.

Is this right? [click to continue…]

To celebrate my new-found determination to do the right thing and blog I’m going to blog.

Specifically, I’m going to blog about something I’m dumb about and don’t understand – because that should be possible, among friends. We’re all friends here on the internet? That’s kind of the point.

This semester I am going to talk to students about all this new-fangled AI – LLM’s. And I don’t understand it. It’s somewhat consoling that everyone who understands it doesn’t understand it either. That is, they may know HOW to work it (which I sure don’t) but they don’t understand WHY what works works. They don’t really grok HOW what works works, or why what works works as well as it does – oddly well and badly by obscure turns. That’s kind of creepy and scifi. [click to continue…]

Yesterday, I dug into the deepest nest of folders on my MacBook Pro to find an article I wrote on a 512K Mac in 1987, for a magazine that no longer exists and isn’t (AFAICT) digitally archived. The file must have made transitions from “hard floppies” to removable 44Mb drives (remember them?) to hard drive to SSD and then, when that filled up, to my iCloud backup.

Today, I read about “digital hoarding“. Count me in!

Whatever the psychological causes, it’s hard to imagine negative real-world consequences from storing files. And it’s easier to search for stuff when you need it than to spend a lot of time filing. I used to sort my email, but now I just delete 90 per cent as it comes in, and archive the rest every couple of years.

In the physical world, I’m the opposite. I’m hopelessly untidy, but I follow Marie Kondo in throwing out anything that no longer sparks joy, and in trying to avoid acquiring stuff I don’t need. Being free of paper has been a huge boon in this respect.

Hello! My name is Kevin Munger, and I’m delighted to have gotten the call up to the blogging big leagues. I’ve been blogging since the beginning of the pandemic at Never Met a Science, a combination of meta-science (get it) and media theory that I intend to continue here.

Crooked Timber has been around for longer than Twitter, and it looks like that which has burnt brightest will burn shortest. 

Twitter’s spectacular conflagration, the wildfire currently burning through some of the dead wood of the digital media ecosystem, both entrances and illuminates. The fantastic release of energy produces pyrrhic phantasms, full of soot and fury…and while the catharsis and camaraderie of the bonfire are not to be taken lightly, we shouldn’t assign any meaning to the random sparks. Breathless attention to what Trump did every day in 2017 was understandable (if ineffective); breathless attention to what Musk does every day in 2022 is embarrassing.

I have been extremely critical of Twitter’s impact on intellectual life, yet I am not pleased to see so many academic colleagues “leaving” Twitter because a Bad Man is now in charge. This isn’t just hipster churlishness; being critical of a bad thing for the wrong reasons can be pernicious. The implication of the current critique is that if the Bad Man were removed, Twitter would be ok.

This wishful thinking has been the opiate of the academic/media/liberal professional class for the past six years, ever since the Great Weirding of 2016. The high water mark of any trend is of course the beginning of its decline, as evidenced by the fumbling of the Obama-Clinton Presidential handoff. This class–my class–has been adrift ever since, disoriented by the reality of contemporary communication technology. Rather than confront the depth of the challenge to the foundations of liberal democracy, we are sold crisis after crisis with the promise that solving this one will bring us back to “normal.”

To be clear: the crises are real. It’s the normalcy that’s fake: “Boomer Ballast” (the central argument of my recent book) has unnaturally preserved the façade of postwar America even as the technosocial reality shifts under our feet. I fear that ours is not an age for “normal science” in the social sciences, where ceteris is sufficiently paribus to engineer marginal gains. 
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There’s been a lot of excitement about Artificial Intelligence (AI) lately, much of focused on long-standing “big questions” like “is AI really intelligent” (short answer, no)

I don’t have an answer to that, so I’ll stick to the easier questions like “will a robot take my job”. I’ve argued before that this isn’t a good way to think about the issue. New technology has been changing the way we work for centuries, and will continue to do so. But for particular jobs being transformed by technological change, it is certainly relevant.

One area that’s moved ahead very rapidly is the generation of human-like text. The cutting edge here is a program called GPT-3, launched in 2020, which can produce impressive looking philosophical discussions. The underlying research has already been commercialised with products like Jasper, which has the much more prosaic (literally!) goal of producing advertising copy, blog posts and so on.

Jasper clearly won’t pass a Turing test if you ask for anything complex, but it is very good for its intended purpose: turning out text that looks as if a human wrote it. This has big implications for a large category of jobs, notably including many that the late David Graeber called “bullsh*t jobs”.

As an example, a fair bit of the content of a typical newspaper consists of press releases that have been lightly edited and perhaps spiced up a bit. With Jasper, the time taken for this task goes from an hour or so to a few minutes. For that matter, the press release itself can be generated from a few prompts in a similarly short time.

As with previous tech advances, that’s not likely to create mass unemployment any time soon. But it will mean that this kind of routine copywriting will be done much faster, by writers who have the skills to give programs like Jasper the right prompts, and then to touch up the final output. And this will extend to lots of admin jobs that have previously been immune from technical change.

Lots of middle management jobs, for example, involve writing memos and reports justifying one corporate decision or another. After you read a few, they all seem the same. AI can distil the essence well enough to mimic the style. After that, it’s just a matter of fitting the verbiage around the desired conclusion.

Over the fold, a few examples.

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Following Elon Musk’s purchase of Twitter, some progressive/left-leaning people have left, or are considering to leave. I haven’t left. So far Twitter has been very useful for me for (1) political activism, especially regarding Higher Education policies in my own country; (2) as a source of information – it’s partly a supplement to newspapers and other traditional media; (3) exchanging information with others, worldwide; (4) some debate and exchange of arguments, which sadly is probably part of the reason the blogosphere has been in decline over the last decade. Hence, there are still reasons not to leave, but obviously I am waiting to see how Twitter under Musk-rule will change.

Nevertheless, it’s high time to start looking seriously into the alternatives; this might make it easier/less costly to leave if we ever judge we have to. I’m at square zero concerning Twitter-alternatives, and surely I’m not the only one. Hence my question: what are your experiences on other social media platforms, and do you have any advice to offer to those considering to move to another place?

I’d like to blog more about my research, but not sure yet how to go about it (e.g., whether to write more about research already completed or about projects currently in the works or both.. feel free to voice your preference). Today, I’m posting a link to a paper that was just published (and is available open access so no paywall to battle): Birds of a Feather Flock Together Online: Digital Inequality in Social Media Repertoires, which I wrote with my friend Ágnes Horvát.

There is some work (not a ton, but a growing literature) on who adopts various social media platforms (e.g., are men vs women more likely to be on Facebook or on Pinterest, are more highly educated people more likely to be on Twitter or on Reddit), but as far as we can tell, no one has looked at the user base of pairs of such services. (I am always very cautious to claim that we are the first to do something as it’s nearly impossible to have a sense of all work out there, but we could not find anything related. Do let me know if we missed something.)

Why should anyone care who adopts a social network site (SNS) and what’s the point of knowing how user bases overlap across such sites? There are several reasons for the former and then by extension, the latter. I started doing such analyses back in the age of MySpace and Facebook finding socioeconomic differences in who adopted which platform even among a group of college students. More recent work (mine and others’) has continued to show differences in SNS adoption by various sociodemographic factors. This matters at the most basic level, because (a) whose voices are heard on these platforms matters to what content millions of people see and share and engage with; and (b) many studies use specific platforms as their sampling frame and so if a specific platform’s users are non-representative of the population (in most cases that is indeed the case) and the research questions pertain to the whole population (or all Internet users at minimum, which is again often the case) then the data will be biased from the get-go.

By knowing which platforms have similar users, when wanting to diversify samples, researchers can focus on including data from SNSs with lower overlaps in their user base without having to sample from too many of them. Also, for campaigns – these could be health-related, political, commercial – that want to reach diverse constituents, it is again helpful to know which sites have similar users versus reach different groups of people. Our paper shows (with graphs that I am hoping are helpful to interpreting the results) how SNS pairs differ by gender, age, education, and Internet skills.

It’s time to share your most helpful tech finds for the year, this time more on the software than the hardware side. My big find was a task management tool that is the mother of all task management tools. It’s called Amazing Marvin and amazing is indeed the word I use when I describe it to friends and colleagues. If there is one downside, it’s that its versatility makes it a bit hard to navigate at first, but the investment is worth it.

Let me take a step back and explain the problem I was trying to solve when I searched for a tool back in the Spring. The search was not necessarily prompted by the pandemic, but launching into a huge data-collection project a week into lockdowns certainly gave a nudge. I had never had a good system for keeping track of tasks, ranging from very specific small to-do items to components of large multi-year projects. I had tried several programs over the years, but none had met my needs, whatever those might have been. (Sometimes you don’t realize what works well until you try to get a program to do what you need and then it hits you that that missing feature is a must-have.) I was using a mix of approaches from putting some things on my Google Calendar to keeping emails unread until I had tended to them, etc. It was a sad patchwork of solutions that, frankly, left me wondering how I wasn’t dropping balls left and right.

Enter Amazing Marvin. [click to continue…]

Reading this tweet by Maciej Ceglowski makes me want to set down a conjecture that I’ve been entertaining for the last couple of years (in part thanks to having read Maciej’s and Kieran’s previous work as well as talking lots to Marion Fourcade).

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Democracy is an information system.

That’s the starting place of our new paper: “Common-Knowledge Attacks on Democracy.” In it, we look at democracy through the lens of information security, trying to understand the current waves of Internet disinformation attacks. Specifically, we wanted to explain why the same disinformation campaigns that act as a stabilizing influence in Russia are destabilizing in the United States. [click to continue…]

Yeah, the zombie version was good. But what if you wrote a version in which they are all zombies? I’m not sure if any actual edits to the original text would be required. Passages like the following are fine. They just need to be understood properly. [click to continue…]