Do people care who (or what) wrote this?

Generative A.I. as a writing tool has limitations. But what I've discovered over the past week is that my perceptions of those limitations can drastically change when I learn about a new way to use it. Before, I'd been giving ChatGPT fairly vague prompts: "Describe the town of Cottondale Alabama as a news article." Listening to a copy.ai prompt engineer on Freakonomics helped me understand that being more specific in your prompts about the length of the output ("500-1000 words") and the audience ("highly-educated audience") makes all the difference. 

The other key lesson is to think of writing with A.I. as an iterative collaboration: ask the program to generate five options, use your gold ol' fashioned human judgment to select the best one, then ask it to further refine or develop that option. If you find it to be boring, ask it to vary the sentence structure or generate five new metaphors for something and then pick the best one. I sensed that writing with generative A.I. could be more like a collaboration with a co-author than an enhanced version of auto-correct; this helped me to see what, exactly, that collaboration looks like, and how to effectively collaborate with the program. 

As the output got better and better, I wondered, "has anyone done a blind test of readers' ability to discern A.I.-assisted writing from purely human writing?" I'd heard of a few misleading journalistic stunts where writers trick readers into thinking that they're reading human writing when, in fact, they are not. But I'm looking for something more rigorous, something that compares readers' abilities to discern that difference across genres of writing: short news articles, poetry, short stories, long-form journalism, short documentary scripts, etc. It seems likely that readers will prefer the A.I.-assisted version in some cases, but it's important to know what types of cases those will be. 

I also wondered what our reactions - as readers and writers - to all of this. I can think of three metaphors for possible reactions to A.I.-assisted writing:

1) the word processor. It's use changed how writers write. It changed the output. Like most disruptive technologies, it was met with skepticism and hostility. But eventually, it was widely adopted. Young writers who hadn't grown up writing free-hand had an easier time adapting to this new way of writing. The technology became "domesticated" - normal to the point of being invisible, embedded in pre-existing structures of economy and society. 

2) machine generated art. Machines have been generating visual art for decades. Some of that art is indiscernible from human generated visual art. Some of it embodies the kinds of aesthetic characteristics that people value. And yet machine generated art has never risen beyond a small niche. The market for visual art largely rejects it, in part because those who enjoy art care about how it is created. Something about the person who created it and the process by which it was created is part of what they value about art. 

3) performance enhancing drugs. Output from A.I.-assisted writing is superior - in some cases far superior - to unaided human writing, and there is market demand for it - the public sets aside its qualms and embraces good writing regardless of how it came about. This situation is perceived by writers, some industries, and some governments as unfair or possibly dangerous, maybe in terms of what bad actors could do with such a tool or how profoundly disruptive its widespread use would be for economies and society. Therefore, they regulate it, discourage its use through public shaming, or, in some cases, explicitly forbid its use. 

The quality of A.I.-assisted writing's output is only part of what will determine its eventual place in our lives. The general public's reaction to it is another part worth paying attention to. 

An ethical case for using A.I. in creative domains

A few months after first considering the promise and threat of A.I. in creative domains, it's still the threats that are getting the most attention. I tend to hear less about the possibility that by allowing A.I. to be used widely (which helps it grow more sophisticated) we are hastening a machine-led apocalypse and more about what we would lose if we replaced human writers with A.I. It would be an obvious loss for the people who write for a living, but they make the case that it would be a loss for society. Creativity would decline, mediocrity would flourish, and we would lose the ineffable sense of humanity that makes great art. By taking the power to create out of the hands of the many writers and putting it in the hands of the few big tech companies, we would exacerbate inequality and consolidate control over culture. 

There are a few steps in this hypothetical process worth scrutinizing. First, this argument assumed that if A.I. is allowed to be used in a creative field (screenwriting, journalism, education), it will necessarily lead to the replacement of human labor. There's a market logic to this: if you owned a company and you could automate a process at a fraction of the cost of paying someone to do it, you would have to automate it. If you didn't, your competition would automate it, be able to produce an equivalent good or experience at a lower cost, charge consumers less for it, be a better value to shareholders as a publicly traded company, and put you out of business. You could point to examples of such things happening in the past as evidence of this logic (though I have to admit, I found it hard to find examples that used human communication rather than physical labor. I'd assumed chatbots had led to steep declines in customer service labor, but all I could find was editorials about how it will lead to steep declines and competing editorials about how customers find chatbots enraging and still demand human customer service agents). 

But I still have trouble thinking of this particular replacement-of-human-labor trajectory as inevitable. I can't help but think of A.I. as a tool that humans use rather than a replacement for humans, more like a word processor or the internet than a brain. I can't not see a future (and, honestly, a present) in which writers of all kinds use A.I. for parts of the writing process: formatting, idea generation, wordsmithing. Humans prompt the A.I., evaluate its output, edit it, combine it with something they generated, and share an attribution with the A.I. You could call this collaboration or you could call this supervision, depending on how optimistic or pessimistic you are, but the work that it generates is likely better than what A.I. generates on its own and it is generated faster than what humans generate on their own. But humans who prompt, edit, evaluate, and contribute to creating quality work are as necessary as they were before. They can still use that necessity to make their case when bargaining with corporate ownership. 

I also have trouble seeing a marketplace in which all content is generated by A.I. If the A.I. can only generate mediocre content, won't people recognize its mediocrity and prefer human-made creative work? It's hard not to see this particular facet of the argument against A.I. in creative fields as elitist snobbery - "of course the masses will choose the A.I.-generated dreck they're served! We highly-educated members of the creative class must save them by directing them toward 'True Art,' (which we just happened to create and have a financial stake in preserving)."

And that is an ethical argument for A.I. in creative fields that I have yet to hear: the argument that the class of people who are currently paid for being creative are protectionist. If they can just keep us thinking about Big Tech and the obscenely wealthy studio execs, we won't have to think about the vast number of smart, creative, compassionate people who happen to not know how to write well, or to write well in a particular language. I worked hard at becoming a good writer, spending a lot of time and money to acquire this marketable skill. Does that make it morally right to deprive others of the ability to use a writing tool that levels the creative playing field? I assume there are millions of people with the life experience and creativity to be great writers who simply lack the educational experience to craft grammatically correct prose. Who am I to insist they take out loans and wait years before they can make worthy artistic contributions?

I do understand the replacement-of-human-labor argument against A.I. None of the anti-protectionism argument really resolves or even speaks to the market logic argument. I suppose this is what smart regulation does - limit the use of technology in cases where we see clear evidence of social harm but allow it where there are opportunities for social good. As an educator, I want to make sure that students understand how to recognize the characteristics of "good" (i.e., compelling, effective at communicating, lasting the test of time) writing, even if they need a little help getting their subjects and verbs to agree.

It can be hard to see the good of A.I. in creative realms at this stage in the development cycle. It is hard to see the would-be writers and the untold stories, but any ethical approach to the question of A.I. in creative fields must consider them. 

When subreddits go dark

Among the many unforeseen effects of ChatGPT's release, there is a change in policy at Reddit that has caused a significant disruption among its community moderators. Reddit has served as a valuable and, to date, free source of training data for ChatGPT and other large language model (LLM) AI - billions of utterances from hundreds of millions of people about thousands of topics over a 15 year span. These LLM AIs are already worth billions of dollars, more than Reddit was ever worth during its first 15 years. It is therefore understandable that Reddit as a company wants to stop the practice of giving its back catalog of data away for free. They're not the only ones keen to point out that the training data used by LLMs, while ostensibly free to access, were created and facilitated by others who, it could be argued, were indispensable in the creation of now-popular AI programs like ChatGPT.

This isn't the only reason why Reddit would want to turn off the spigot of free access to its vast archives of posts and comments via an API. An ecosystem of third party apps has flourished under this policy, resulting in the loss of untold hours of user attention to ads on Reddit's official app, and thus lost revenue. Many users have become accustomed to accessing Reddit this way, and are understandably upset at having to migrate to the official Reddit app, widely regarded as inferior to the third party apps. 

Then there's the issue of how subreddit moderators use the API to more effectively moderate their communities. They can use the API to quickly assess a user's posting or comment history to see if a disruptive comment or post is part of a larger pattern and thus worth banning the user (this includes spambots and trolls that, unmoderated, could overwhelm a subreddit with useless or disruptive content). They use them to determine when a question asked by a user has already been answered in the past, and to highlight that answer. APIs are also relied upon by some users with disabilities, as a way of access the platform. This post from the moderators of r/AskHistorians has a good summary of other ways in which mods rely on the API. 

Reddit as a company seems interested in addressing the disability accessibility issue, carving out an exception for third party apps specifically designed for users with disabilities. Beyond that, they don't seem particularly interested in walking back their decision to charge for access to the API...yet. 

The conflict between the administrators (paid employees of the company) and moderators (unpaid volunteers who manage Reddit's tens of thousands of active communities) is a familiar one - management vs. labor. As with any such conflict, labor's ability to get what they want assumes that they can't easily be replaced by more willing labor - be it human or automated. Can the company still produce something of value to the consumer without the willing participation of current labor? 

In most cases, replacement labor produces something different than what was produced by the original labor, and in most cases, its (at least initially) regarded as inferior (labor certainly has an interest in highlighting its inferiority). But the question of fungibility of labor, from management's standpoint, in the world of social media is a tricky one. The culture and communities that live on popular social media platforms - the things that makes them valuable - are constantly shifting. As in most cultures and communities in the physical world, users frequently lament these shifts, blaming new entrants to the community or powerful authorities. If they hate the changes enough, they leave. 

So, when moderators of a popular subreddit choose to go on strike, effectively killing that subreddit, what happens to its users? 

One possibility is that they leave the platform. This is, I would think, what the mods are trying to accomplish - driving traffic off the platform, hurting Reddit's bottom line, and getting management some bad press. Another possibility is that the users of that subreddit migrate to other existing subreddits - ones with moderators that didn't strike - and find that these other subreddits are roughly as good at satisfying their need for distraction, information, community, amusement, comfort, etc., resulting in a surge of activity on those subreddits. Yet another possibility is that new subreddits arise to meet the demand created by the absence of striking subreddits. "Splinter" subreddits - subreddits that are created to cater to disgruntled "refugees" from a subreddit that has changed in some disagreeable way - have always been a part of the subreddit ecosystem. Modularity is a defining feature of Reddit, something that sets it apart from the single, amorphous conversation on Twitter and the atomized, fleeting comments on TikTok, YouTube, and Instagram. In this case, it makes it harder for labor to force management to do anything. Unless a critical degree of solidarity among moderators is reached and sustained (a tall order, given the number and diversity of subreddits), its hard to prevent within-platform user migration. 

Reddit's design - a feed or list of posts aggregated from subreddits to which users subscribe - can make it hard to even notice the absence of a striking subreddit. When I went to the site, it took me awhile to realize what was missing; I was still seeing pictures of cute animals, funny things that people said or did, captivating vistas and infuriating news. Of course, the impact is going to vary from user to user. For some users, access to a particular subreddit can be as valuable as access to a close friend, one whose absence would result in a sense of profound loss. It's hard to see how many users are like that - management has an interest in making it seem as though they are a small, vocal minority while labor has an interest in making it seem as though most users are upset by the changes - so upset that they are already in the process of leaving.

It's possible that a large number of currently-popular subreddits die as a result of this disruption, and that a large number of users leave the platform and don't come back. It's easy to point to moribund platforms like Digg or MySpace that never found a replacement community that could sustain the business. But that doesn't take into account the current business climate for these businesses, news organizations, and even video and audio streaming services that seem (with varying degrees of success) to be training consumers to pay - in subscription fees or attention to ads - for what they consume. If the era of free high-quality user-generated-content is over, there may be no substitutable platform for disgruntled users to migrate to. 

It also may underestimate how organic and unpredictable large groups of people are. We get used to versions of these platforms - used to seeing a certain type of post or comment at the top of the feed, the popularity of which reflects the collective sensibilities of a voting constituency of users. That sensibility persists even in the face of high turnover among contributors - it is generated not by a stable group of super-users but by a rotating cast who cater to the preferences of the constituency. Disruptions like the current one can change the voting constituencies and thus change what we see at the top of our feeds. Perhaps mods' lack of free access to APIs will make it effectively impossible to manage subreddits beyond a certain size (say, 1,000 active contributors), leading to a Reddit with no large communities and more moderately sized communities that, when they grow unmanageably large, spawn offshoots - something a bit more like Discord. That version of Reddit might be far more diverse in its interests and sensibilities, and ultimately more successful, than the version we're now accustomed to.

The promise and threat of A.I. in creative domains

Though we've been expecting AI to get good enough at writing to actually perform a decent number and variety of writing tasks "by itself" (it still needs humans to engineer prompts), we hadn't been confronted with that reality until recently, when ChatGPT became more widely used. To test it out, I gave it some of the (relatively simple) prompts I give my undergraduate film history students and saw what it came up with. Then, I asked it to write a pilot episode of a teen drama set in Montana, a grant proposal for a research study on social media use and political polarization, a research paper on the environmental impact of microplastics, a quiz on 1970's media cultural studies, a review of Beck's new album, an amicus brief on microplastics, and a summary of the 1998 NBA Finals in the style of Proust. The results, as many have noted, aren't perfect but are a lot closer to perfect than what we're used to seeing from programs. It's hard to objectively convey the quality of the output and the limitations of the tool; it's best to just try it out yourself. 

I'm sure such tools will improve, but it's hard to say at what rate and to what degree, so I'll try to just stick to evaluating the impact of the current iteration of generative text programs like ChatGPT on two facets of writing: assessment (specifically, educators' ability to assess students' understanding of concepts, thinking, and communication skills) and its applications in various domains (i.e., journalism, creative writing, scientific writing). 

In terms of assessment, the ability of students to avoid actually doing the work of writing for an assignment and to avoid detection has increased significantly. However, the truth of this statement is highly dependent on the assignment. If the assignment just requires students to gather information (particularly older info on an extensively covered topic, person, or event) and synthesize it into a simple, readable essay or article, then ChatGPT seems to be quite good at that. But what about, say, watching a particular video on YouTube and applying something from a particular reading to that video? I would assume that ChatGPT can't easily extract the information that's in the video, so it would have a tough time with this task, and that it's ability to do anything with a particular reading is contingent upon that reading being freely available and accessible online somewhere. If the reading is in a textbook that doesn't appear online (or only appears on a few hard-to-access pirating sites), then this will be harder for ChatGPT to work with than, say, the Magna Carta or any other text that's in the public domain. But in any of these cases, I think that A.I. co-authoring (where ChatGPT does some of the work and the student changes and adds a few things) will be essentially impossible to detect. 

Another approach to ChatGPT's threat to assessment is to simply proctor writing assignments. That's easier to do for short writing assignments but difficult for longer ones, and impractical for online classes. Still, as a professor who has an interest in fairly and accurately assessing his student's writing, I'm leaning toward more in-class writing assignments and fewer outside-of-class writing assignments because of how challenging it will be to tell the difference between A.I.-generated writing and my students' writing outside the classroom. 

But the topic of applications of AI is more interesting to me, and in some sense pre-empts questions about assessment. If AI can accomplish much of what we're trying to train our students to accomplish, what is the point of such training? The rapid adoption of ChatGPT has forced me to reconsider the relationship between writing and thinking. Writing is often the medium through which thought is expressed, though not the only one; spontaneous discussions and conversation are a good alternative. When is writing chiefly a vehicle for thought and when is it more an integral part of the process of thought? Those who defend the sanctity of human writing, I surmise, would say either that writing is very often part of thinking, or that we may not be very good at being able to tell the difference between writing-as-vehicle-for-thought and writing-as-thinking. Therefore, ceding the task of any but the most formulaic types of writing to AI risks sacrificing the ability to think. 

We still want to get better at thinking, and we still want our students to get better at thinking (e.g., critical thinking, creative thinking, logical reasoning, problem solving). Even in a world of prevalent AI, having those abilities will make us better at prompt engineering, better at judging the value of what ChatGPT and similar AI spit out, and better at making refinements to that output. The same would apply for non-linguistic AI: prompting an AI architectural design program and judging/refining the results; prompting an AI coding program and judging/refining the results. In any application I can think of, humans are still part of the process. Whether AI is producing a kind of structural scaffold for ideas, identifying sources of information, or generating new ideas, it has to be set in motion, its output needs to be evaluated, and in its current iteration, its output requires a fair amount of refinement. That process of prompting and refining can be similar to a good conversation or collaborative improvisation ("yes, and..." thinking). 

I sense that there's a widespread antipathy toward applying AI in creative domains. I don't consider myself an AI optimist. I acknowledge how tempting it will be for students, businesses, creators, and governments to use AI in an indiscriminate manner, not bothering to vet or refine its output. I acknowledge that such use could cultivate a kind of passivity and (further) overreliance on technology. More people would get out of the habit of "thinking for themselves." Creativity would be increasingly derivative in the name of efficiency. 

But does this warrant an outright ban on AI? What would such an approach sacrifice?

I feel as though we've been good at articulating the risks of AI (aside from the aforementioned, there's scaling up spam and disinformation, and deceiving job recruiters or potential partners on dating sites). We're less good at articulating its potential upside. I think of that upside chiefly in terms of resource reallocation (which, yes, sounds very cold and business-speaky, but hear me out). 

Let's treat ChatGPT and the like as co-authors. They generate first drafts or templates but don't write the entire text or finished product. Human writers' role in the creative process shifts from crafting sentences and paragraphs to gathering primary original sources and identifying needs in their audiences and communities. What if writers could take the time they would have spent struggling to write formulaic copy and instead spent it cultivating twice as many primary sources as they would have otherwise, or co-writing twice as many stories, or ten times as many stories? Consider all the un-written stories or accounts of events; consider what's missing from historical accounts and news coverage, in part because the people who know how to create thorough and entertaining writing only have so much time. Some people's stories are told, some people and events are remembered, but the vast majority are forgotten. What if we could fill in some of those blanks? We don't have to be indiscriminate in our use of AI to turn data into stories that no one cares to read. Remember, humans and their understanding of what is valued are still part of the process. And what if we could offer those stories in twice as many accessible formats? If editors and readers valued these qualities more than they feared AI's downsides, we could use AI to improve our information environment. 

The genie is out of the bottle. If one country or group of people wants to spend time trying to stuff the genie back into the bottle, that won't stop other countries or groups of people from using it. We needn't be totalizing in how we conceive of the application of AI in creative domains. We have been discriminate in our use of technologies in the past, often making mistakes, attempting to correct those mistakes by introducing limitations or redesigning the technology, fitfully moving along but rarely un-inventing anything. Maybe we should look around and see where the successes and failures are right now. 

Lifelogging: How We Forget

Just read this fascinating article in the Chronicle of Higher Ed about life-logging: recording audio (and eventually, video) every moment of your waking life. You can then search through that data the way you would search through your memory, only it would not decay the way your memory does. Would this be a good thing?

I have kept a personal journal for 11 years now. I've made an effort to record my thoughts and many events from my life, no matter how embarrassing or mundane. Now that I've got 2000 pages worth of data, I can search for a person's name or an emotion (e.g. hate, love, crush) and analyze my life, my behavior, and my consciousness in ways that my decaying memory doesn't allow me to do. So, how is this any different than lifelogging? Isn't it just a matter of degree?

When I have a conversation with someone, even an especially private one, my memory is recording their every word. I than have the option of going back to my computer and recording those words. Those words can then end up on the Internet or who knows where (though I'm obviously very careful to guard them and not put them on the net). But we've had this option of recording private events...forever, right?

So then it is a matter of degree. But that doesn't make it any less significant in the ways in which it could potentially disrupt social life. In fact, this article finally convinced me of the worth of privacy in this age of surveillance. I was a longtime holdout only b/c the crux of most privacy advocates' arguments seemed to be invoking Orwell and leaving it at that. Indeed, its an extremely hard argument to make b/c 1) the march of surveillence technology feels inexorable and 2) its hard to point to many widespread instances of abuse or make the chilling effect on behavior visible.

But that's why this lifelogging experiment that the people in the article engaged in was worth doing. By pushing it to an extreme, by making it personal rather than political, I could finally see the ways in which it would radically alter social behavior. We totally underestimate the role of forgetting and deception in our self-images and the images of others. We are designed to underestimate these things. Perhaps we each need to record our lives (or read about someone else who has done this, in my case) to understand how much we forget and how much we distort our memories.

This brought me back to a thought I had after my hard drive crashed a few weeks ago. I was watching 2001 on TMC, and considering the words of HAL, thinking about whether or not the fear of a sentient machine was still a fear of ours, 40 years after this film was made. The big mistake HAL's programmers made (and indeed a fault of most programmers) was to think that they could design an infallible computer. No matter what, a computer, like a human, can screw up. The reason why computers are inhuman (and perhaps why they strike fear in our hearts) is because they fail in different ways than us. But if we recognized this, and tried to design them to fail in ways more like the ways in which we fail (to design them to "forget" things gradually, to act erratically in certain situations, instead of aspiring to perfection), then computers and robots wouldn't be anything worth fearing. We should get to know the design of our minds, and then design computers in a similar but slightly less flawed fashion.

Really, what makes computers unlike humans is the ways in which they decay. In one of my classes, I'd claimed that digital technology did not decay. It either worked or it did not. I was proven wrong the next week when we brought in several gaming consoles, including my old (roughly 18 year old) Nintendo Entertainment System. One of my students played Mega Man 3 (I think it was 3, but I may be misremembering) and the game gradually became more "buggy," the screen increasingly clogged with glitchy graphics until finally, inevitably, it froze. So I realized that digital technology gradually decays, but it decays in a different way than our minds. And it is vulnerable in ways that we are not.

That is what defines us, or at least sets us apart from computers: the ways in which our minds and memories decay or become damaged. The ways we forget. Perhaps we shouldn't be working on computers that recall everything, but on computers that "forget" data in the same ways we do. I suppose that's the promise of meta-data: to get computers to recognize importance and meaning in the ways that our minds do.

As applied to my personal journal, I'd need some way to teach the computer that some information (my happiest memories) is more important than others (whether it was Mega Man 3 or 4 that student was playing).


http://chronicle.com/free/v53/i23/23a03001.htm