Should We Be Using GenAI?

Introduction

As you have likely worked out on your own already, Artificial Intelligence is not going away. It has gone from being a joke to a novelty to the bogeyman to a tool that many of us use all the time. And yet, there are still holdouts, perhaps you among them. In my workplace, it’s a mixed bag. As recently as 2024 I was forbidden to use ChatGPT or other AI platforms at work; now, my employer  is wheedling, exhorting, begging, and all but requiring my colleagues and me to adopt it. On the family front, one of my daughters uses it a fair bit (sometimes frivolously), the other not at all. My wife is wary of it.

So should you use AI? I consider myself fairly well qualified to answer this. I have been dabbling in AI for almost fourteen years; have devoted a fair amount of research to kicking its tires; and now use it extensively both at work and at home. I’ve blogged about it a bunch of times. I’m unbiased, since I don’t work for the AI Industrial Complex, but I also don’t have a knee-jerk fear of technology.

I’ve blogged before (here) about how we can use AI, describing two fundamental ways—operationally vs. creatively—that people do use it. Today’s post is more about whether we should use it, and how often, particularly in light of the resources (electricity and water) that it consumes. Is environmental responsibility a compelling reason to curb our use of GenAI?

Some housekeeping

As I’ve explained here, AI is much bigger than the Large Language Model (LLM) chatbots that we consciously use as the natural successor to Google. We generally speak of AI as a productivity tool, but a whole lot of AI is devoted to the invisible algorithms on social media, YouTube, etc. that grab and hold our attention, threatening to reduce our productivity. I think of this as secondhand AI (like smoke). Meanwhile, you’re surely hearing a lot of hype about “agentic AI,” which can supposedly act on its own volition to achieve a goal. At this point I’m scared of agentic AI and think you should be, too, but that’s another post. The AI I’m considering here is Generative AI (GenAI), which is the type of chatbot (e.g., ChatGPT, Gemini, Copilot, Claude) that you feed a prompt to as a way to research something, or as a way to quickly compose an essay, letter, or picture. This is how I believe most people think of AI, which is why the terms “AI” and “GenAI” are so often used interchangeably.

(Note that if you are reading this post long after April of 2026, and there isn’t a single living human not using GenAI, and/or the robots have taken over and enslaved you, treat this post as a historical artifact. At least you’ll get a sense of how society initially approached this technology.)

GenAI at work

If you work for a corporation that is clearly embracing GenAI, providing you a commercial, “walled garden” version of it, and the training to go with that, adoption is a no-brainer: do as you’re told and embrace GenAI immediately. My employer is already monitoring my use of it (though they haven’t said exactly how), showing my compliance on a dashboard. (My “AI Tools Usage” is showing 87% and green.) I could bristle at this, but a) I have always know my use of company assets is monitored, and b) my employer’s expectation that GenAI will make me more productive is reasonable, as is their expectation that I will be as efficient as possible. 

It’s remarkable how quickly all this has changed. I have seen GenAI’s use go from something my colleagues formerly tried (in vain) to hide, to something that my manager will outright ask me about. When asked, “Did you use AI to help you with this?” I now assume that the correct answer is a version of “yes.” (This answer is necessarily nuanced. Both in terms of being honest and articulating my ongoing value as an employee, I am sure to explain both how it helped and how it fell short of doing the task for me.) This week my boss tasked me with figuring out how to create a NotebookLM chatbot specializing in expertly summarized minutes of every meeting anyone on our team attends (or previously attended), which updates its training data automatically. So if our colleague Joe is on vacation we can ask the chatbot, “Why did Joe Blow switch out the vPlan in Blascorp’s EZ-Pluck profile?” and hope to learn the history. I feel like this assignment would have been unheard of a year ago.

But what if you work for a small business, or have your own? This is a greyer area, of course. A member of my family is a sole proprietor, and so far has shied away from GenAI because she’s concerned about becoming too reliant on the technology. I get her point, and have blogged before (here and here) about how doing our own thinking and writing prevents us from falling into intellectual torpor. But isn’t a tool that legitimately improves efficiency something we ought to rely on? After all, we wouldn’t even think of trying to run a business without email, a laptop, a smartphone, in many cases videoconferencing capability, and (depending on the business) various types of specialized software. All of these tools were new once, and any small business owner still using a typewriter to generate invoices is surely a) in the minority, and b) wasting a lot of time. From that perspective, it’s all but inevitable that any small business owner will ultimately adopt GenAI for his or her business … so why wait?

GenAI at home

Using GenAI outside the workplace is a more complicated matter, since it’s not helping put food on the table. I mentioned earlier in this post that my older daughter has occasionally used it rather frivolously, such as to punk me. Consider this drawing she had ChatGPT create to memorialize an accident I had at a hotel pool back in 2024, when I got out of the hot tub too fast and fainted:

Her prompt for this was, “Can you create an image of a tall skinny white man feeling faint after leaving a hot tub?” As you can see, the man portrayed looks more hunky than skinny, and my daughter tried three more times to get the picture more accurate. Given that these were throwaway efforts (or would have been had I not used them in an early AI analysis here), this was devoting rather a lot of computing resources to a pretty trivial problem, or shall we say exercise. (Of course part of the point for my daughter was exploring the early technology; it’s not like she’s stuck with throwaway art as her primary use case for GenAI.)

On the flip side, her sister won’t use GenAI at all, somewhat on grounds of intellectual authenticity but mainly due to its environmental impact. The constant construction of ever-larger data centers is all over the news, with some shocking statistics thrown around about how much power and water a single GenAI prompt requires. Today I decided it’s time to vet this claim a bit, studying the available data and describing it in a context that could help guide our behavior appropriately.

How much electricity does GenAI use?

With the help of Claude, because it works better than a Google search, I did some light research and found some great analysis (here) on the website of Epoch AI, a nonprofit founded to “help people understand what is happening in AI from a neutral perspective and grounded in the best possible evidence.” Epoch AI partners with Stanford’s AI Index, which I’ve come across in my professional life and seems well respected, as well as the UK’s Department for Science, Innovation, & Technology, which I trust even more (since it doesn’t have ties to the tech industry like Stanford does). I must acknowledge that truly disinterested AI research is hard to come by, because almost every organization doing serious work in this realm has a business relationship with it. So to spread out the risk of misinformation I also put this query to ChatGPT, which came up with similar numbers but from other presumably trustworthy sources, including ScienceDirect  (which Gemini says “is considered one of the most reliable and authoritative sources for factual data in the world”) and Cornell University.

So: Epoch AI, in an article from about a year ago, examined a widespread previous claim that “an individual ChatGPT query requires around 3 watt-hours of electricity, or 10 times as much as a Google search.” Epoch AI, leveraging “more up-to-date facts and clearer assumptions,” arrived a the following conclusion:

We find that typical ChatGPT queries using GPT-4o likely consume roughly 0.3 watt-hours, which is ten times less than the older estimate. This difference comes from more efficient models and hardware compared to early 2023, and an overly pessimistic estimate of token counts in the original estimate. For context, 0.3 watt-hours is less than the amount of electricity that an LED lightbulb or a laptop consumes in a few minutes.

For further perspective: according to this article, “Google says that its median text query uses around 0.24 Wh of electricity. That’s a tiny amount: equivalent to microwaving for one second, or running a fridge for 6 seconds.”

But that’s just text queries. Creating a picture uses a lot more resources. According to this article by the University of Southern California, using GenAI to create a picture uses 2.9 Wh—over ten times as much as a text query. I had Gemini come up with some household use equivalents to give this number some context, and here’s what it came up with:

• Phone: charges your battery about 19%
• LED bulb: about 19 minutes of light
• Dishwasher: about 14 seconds of a cycle
• Clothes dryer: about 2.6 seconds of a cycle

These seem pretty trivial, but if you consider all the millions of people using GenAI, it can add up, especially if people get it the habit of iterating a dozen or so times to get the image just right. (For what it’s worth, I got the cover art for this post in two tries.)

How much water does GenAI use?

Water is another matter, and very difficult to quantify because the location of a data center has a lot to do with how efficiently it can cool all its servers. This“ Washington Post” article documented a study, involving research from the University of California at Riverside, that found that using ChatGPT to write a 100-word email consumed 519 milliliters of water, which is a little more than a standard bottle. Obviously that is really high, especially considering how many people use GenAI and how much that’s growing.

At the same time, as pointed out by this article, many other industries also use a ton of water, and people don’t seem up in arms about it: “A single burger takes more than 400 gallons of water to produce; a humble cotton T-shirt takes more than 700. The United States’ 16,000 golf courses, meanwhile, each have the potential to use on average between 100,000 to 2 million gallons of water per day. (For comparison, Google says its thirstiest data center in Iowa consumed about 2.7 million gallons per day in 2024; most of the company’s data centers used substantially less.)”

A less abstract comparison

To be fair, it’s not like we all sit around eating burgers all the time; for most of us, that’s a treat. Meanwhile, I would hope most albertnet readers are enlightened enough to hold out for grass-fed beef, which uses a lot less water to produce. And if you’re like me, you buy a lot of clothing secondhand, which helps mitigate the resources required for your wardrobe. So what’s a better comparison that can help us frame the environmental cost of using GenAI? I propose: beer. (I know what you’re thinking: that’s my answer to everything.” Well, okay … guilty as charged.)

So here is my thought exercise: how does using GenAI compare to cracking open a beer? And what is the value of the former vs. the latter? Obviously this is a wide-open scenario so I’ll narrow it down to how I most often use GenAI: when researching a blog post.

Here’s what Claude had to say about the electricity required for a 30-minute research session:

Based on current estimates, a substantive text exchange with an AI like this one — say 20–30 back-and-forth exchanges — is probably in the neighborhood of 5–10 watt-hours of electricity. Google has reported that after major efficiency gains, the median Gemini prompt consumed about 0.24 watt-hours, representing a 33× reduction in energy per prompt compared to a year earlier. At that figure, 30 prompts would use about 7 Wh — roughly equivalent to running a phone for 20 minutes or leaving an LED bulb on for half an hour.

Regarding water use, a Mistral AI lifecycle analysis citied by the Brookings Institution found that a typical 400-token exchange consumes about 45 milliliters of water—about three tablespoons. Multiply by 30 exchanges and you’re somewhere around 1.5 liters of water—very roughly two or three bottles’ worth attributable to the 30-minute research session. (This varies enormously by data center location and cooling method, so we should treat it as an order-of-magnitude estimate.)

To compare the electricity cost of the GenAI session vs. the can of beer, I downloaded a spreadsheet-based waste reduction calculator directly from the EPA’s website. It is designed to help consumers like me understand the value of recycling something vs. tossing it. It calculated that recycling a 12-ounce aluminum can saves 0.3 kWh—which is roughly 40 times more energy than what’s consumed by an entire 30-minute GenAI research session. Granted, I often generate a picture to go with my post, but even if we assume it takes five tries to get it right, the energy cost of those five images is still only about one-twentieth of the energy wasted by tossing a single beer can in the trash. And since this is only the energy cost of recycling, which is less than producing a can from scratch, these numbers are highly conservative. (Meanwhile, I haven’t even factored in the energy required for brewing and transporting the beer itself.)

Meanwhile, the Water Footprint Network, as described here, estimates a total water footprint of 298 liters per liter of beer—so a standard 12-oz can of domestic beer takes over 100 liters of water to produce. More than 90% of that water comes from the agricultural supply chain (e.g., growing the barley) while the brewery uses about 6–8 liters per liter of beer (though a large facility may achieve a 3-to-1 ratio). So my 30-minute research session uses something like 1–2% of the water embodied in the can of beer I might have next to my keyboard. (Full disclosure: there’s a now-empty pint glass on the arm of the sofa as I type this. Yes, drinking while blogging: a rhetorically risky and planet-impacting combination. So sue me.)

Factoring in value

So that covers the environmental cost of researching a blog vs. drinking a beer. But what about the value of each? Discounting pub crawls with my friends—which occur far more seldom than I would like, to the point that they’re a rounding error—I’m really talking about unwinding with a solitary beer at the end of the workday. So in general the value of that beer accrues solely to me.

So does my blog-related GenAI research create any value to justify its water and electricity use? In the interest of humility I won’t merely assume this, and will instead dive into the data. Pageview stats across my blog wouldn’t be very representative, as at least half my posts don’t require any research at all. So for lack of a better idea, I’ve decided to analyze the pageview count for each of the albertnet posts that are about AI. After all, those have to be among the most GenAI-intensive of all, because in writing them I was test driving the various platforms. Here’s a brief summary of how these posts have performed:

• Total pageviews across nineteen AI posts: 15,578 (so far)
• Average pageviews per AI post: 819.9
• Average pageviews per AI post per month: 35.5

I could conclude that, from a somewhat abstract viewpoint, each post is seen by a person a day. But averages aren’t very reliable, and greater specificity is more revealing. Lurking in that “average pageviews per AI post per month” is a bit of (GenAI-performed) number crunching, accounting for the fact that the posts that I published years ago have had a lot more time to accrue pageviews. Ranking my AI posts by pageviews per month shows that they are gaining in popularity, with the more recent ones averaging two to three views per day. Here’s the ranking of all these AI posts over time, so you can see the momentum:

№	Views/Mo	Total Views	Title
1	102.5	1,742	Tech Check-In – How Good is the Latest A.I.? – Part II
2	85.7	257	New Year's Resolutions — AI Edition
3	82.8	1,077	What Is ChatGPT Great At (and Not)?
4	69.9	1,189	Tech Check-In – How Good is the Latest A.I.? – Part I
5	62.4	312	AI Smackdown – ChatGPT vs. Copilot vs. Gemini
6	58.0	290	More AI Smackdown – ChatGPT, Copilot, & Gemini Write Poetry
7	51.2	256	Tech Reflection – Two Sides of AI
8	27.4	1,040	A.I. Smackdown – English Major vs. ChatGPT – Part 2
9	27.1	1,031	A.I. Smackdown – English Major vs. ChatGPT – Part 1
10	23.0	597	Will A.I. Steal Our Jobs?
11	20.0	739	Schooling ChatGPT
12	11.1	719	Could Artificial Intelligence Replace Writers? – Part 1
13	10.6	680	Could Artificial Intelligence Replace Writers? – Part 3
14	10.0	1,230	A.I. Smackdown – Moto vs. Cortana vs. Siri
15	8.8	563	Could Artificial Intelligence Replace Writers? – Part 2
16	7.3	1,201	Almost Intelligent – Part I
17	6.3	838	Smartphones & Artificial Stupidity
18	6.2	1,016	I, Chatbot
19	4.9	801	Almost Intelligent – Part II

It would be reasonable to conclude that the more recent posts, which leverage more GenAI research, are reaching more readers, thus providing a better ROI. Of course I can’t account for all the possible reasons these posts are more popular, but I reckon that to some degree it’s because of the better use of GenAI. Using this tool won’t make be a better writer, but I’ve always been pretty lazy about research and there’s no doubt GenAI helps there. And whether or not this ROI calculation is completely airtight, I hope this helps you at least appreciate my effort to weigh my GenAI “footprint” against its value.

The bigger point here is that the can of beer is consumed once, quickly, leaving nothing behind (except maybe a nice belch). In contrast, the energy that goes into researching a blog post has an effective cost-per-view that keeps dropping every month it’s up, in perpetuity. If you use GenAI to draft an email, how many people will it reach, and low long is its tail? Could you have drafted it on your own—thus exercising your brain—or did you really need GenAI?

I’m not trying to imply that only bloggers should use GenAI; this is just one illustration of a cost/benefit analysis of the use of this tool. If you are doing something useful and an AI chatbot is helping you do it better or more efficiently, then it’s arguably worth the energy and water—or, at least, is a more worthy use of it than shopping for a bunch of clothes, going out for a burger, and then having a few beers.

The point is to be aware of the environmental cost of this technology, the same way so many of us do when we decide among driving, biking, walking, or taking mass transit  somewhere. Just because GenAI takes less water than beef or cotton doesn’t mean we should ignore its environmental cost, since it’s a whole new way people are consuming energy and water. As recently as three years ago, almost nobody was using GenAI in their daily lives; now, it’s an increasingly entrenched behavior, data centers are expanding rapidly, and in some regions power grids are struggling to keep up with demand.

This being said, I truly don’t believe opting out of GenAI is the solution; just reflecting on how much it helped me write this post, I can’t imagine not taking advantage of it. Instead, I’d like to see the millions of people already using it stop acting like it comes without a cost. It’s the same as driving: did I really need to surround myself with two tons of steel and burn a cup of gasoline just to travel a mile to the gym and back? (That was a rhetorical question. I always bike to the gym.)

Speaking of cost: one way to keep yourself honest with GenAI is to not pay for it. If you are on an unpaid account and use up your tokens, so that your chatbot cuts you off for some number of hours, maybe that should be your indication that you’ve gone overboard. Come to think of it, video games, YouTube, and social media should have that “feature.”

A final note on GenAI at work

Now that I’ve examined the environmental cost of GenAI, it’s worth pointing out a final wrinkle: using it in the workplace is actually much more efficient than using it at home. Corporations get the most benefit out of GenAI through Retrieval Augmented Generation (RAG), which is where, instead of asking a large language model to answer from its entire trove of training data, the GenAI retrieves relevant documents from a corporate knowledge base (contracts, manuals, research reports, emails, whatever the organization has indexed), then passes those retrieved chunks to the model as context for its answer. Tools like NotebookLM, most enterprise Copilot implementations, and corporate deployments of models like Gemini or Claude typically work this way.

This is much more efficient than “raw” GenAI like consumers use. The retrieval step is computationally cheap—essentially a sophisticated search. The generation step is shorter because the model doesn't have to work as hard to “remember” or construct relevant context; it’s been handed it. And the answers tend to be more accurate and require fewer iterations, which means fewer wasted queries. For a user to opt out of using it on environmental grounds makes little sense, because the big resource expense has already been incurred. As Claude puts it:

The infrastructure cost of a corporate RAG deployment is largely fixed relative to usage. The vector database has to stay current whether 500 employees query it or 5,000. The embedding pipeline runs continuously. The API connections to the underlying model are on retainer. So each additional active user essentially dilutes the per-capita environmental and financial cost of that overhead. An employee who declines to use the tool isn’t reducing the infrastructure footprint; they’re just reducing the output derived from it. In accounting terms, they’re lowering the return on a sunk cost.

Synthesis

Wow, I just threw a ton of words at you, didn’t I? Maybe I’m the most verbose Large Language Model since, well, ChatGPT! Anyway, here’s my final conclusion: of course you should use GenAI. It’s an amazingly powerful tool, and it’s getting better all the time. Now that it’s here, declining to use it makes about as much sense as blending a smoothie with a knife and a whisk, or doing arithmetic with an abacus, or churning your own butter. But use GenAI judiciously. Ask yourself: is this improving the quality or efficiency of my output? Or am I just being lazy?

Other albertnet posts on A.I., in order of publication

• I, Chatbot
• Almost Intelligent – Part I
• Almost Intelligent – Part II
• Smartphones & Artificial Stupidity
• A.I. Smackdown – Moto vs. Cortana vs. Siri
• Could Artificial Intelligence Replace Writers? – Part 1
• Could Artificial Intelligence Replace Writers? – Part 2
• Could Artificial Intelligence Replace Writers? – Part 3
• A.I. Smackdown – English Major vs. ChatGPT – Part 1
• A.I. Smackdown – English Major vs. ChatGPT – Part 2
• Schooling ChatGPT
• Will A.I. Steal Our Jobs?
• Tech Check-In - How Good is the Latest A.I.? - Part I
• Tech Check-In - How Good is the Latest A.I.? - Part II
• What is ChatGPT Great At (and Not)?
• Tech Reflection – Two Sides of AI
• AI Smackdown – ChatGPT vs. Copilot vs. Gemini
• More AI Smackdown - ChatGPT, Copilot, & Gemini Write Poetry
• New Year’s Resolutions — AI Edition

—~—~—~—~—~—~—~—~—
Email me here. For a complete index of albertnet posts, click here.

More Advice from an Amateur Poet

[Photo enhanced by Nano Banana 2]

Dear Amateur Poet,

I wrote a 14-page poem on the ineffable nature of fog. My workshop said it lacked “stakes.” I wasn’t sure what this meant and was too embarrassed to ask. What did they mean? Can fog have stakes?

Melissa M, Longmont, CO

Dear Melissa,

A poem of 14 pages is bound to try the patience of a workshop where everyone is required to read a lot of amateur work. A reader encountering T.S. Eliot’s “The Waste Land” or Samuel Coleridge’s “The Rime of the Ancient Mariner” obviously wouldn’t worry—they know going in that  there won’t be a word wasted—but you are just a budding poet in a workshop. So I think you should ask yourself: is your 14 pages on fog a deliberately audacious act—that is, you know this is a lot of poetry to devote to such a finite theme, and you’re going to prove it can be done well—or are you just being self-indulgent and abusing the patience of your readers?

Look, I’m not knocking fog, but it’s not the most dramatic topic, especially if you’re narrowing in on the ineffability of it, so you’re kind of working without a net. If your poem is not carried off just right, it may strike the reader as redundant. Let me employ a metaphor (which at first may seem weird but stay with me): imagine having a five-course meal where every course is a Hot Pocket. Not good. But if a chef did manage to make such a meal interesting, that would give him or her huge cred, right? I doubt such a feat has never been achieved, but the standup comic Jim Gaffigan has riffed about Hot Pockets for like 5 minutes straight, which is almost as impressive. But then, Hot Pockets are kind of intrinsically funny, so this is likely a more potent topic for a comedian than fog is for a poet.

But could a great standup go on at great length on a less loaded topic, that probably nobody cares much about? In fact, yes. Gaffigan outdoes himself by going 10 minutes straight on the topic of horses, and his long-windedness is definitely part of the joke. Two and a half minutes in he says in a whispery voice, as though a member of the audience, “How many horse jokes is this guy gonna do?” Four minutes in he says, “Oh, I guess I should tell you, the whole rest of the show is horse jokes.” About 8 minutes in he says, “I can see on some of your faces that you would frankly prefer if I did … more horse jokes.” About nine and half minutes in he says, “Okay, I can see that there’s one or two or 300 of you that are frankly annoyed by the horse jokes. And I want you to know that your annoyance, uh, gives me pleasure.”

But here’s the thing: the long-windedness is only part of what makes the bit funny, and if the monologue dragged at all, the humor would wear thin. But Gaffigan’s horse jokes kill. And so should your fog poem, if it’s going to be that long. (No, standup comedy and poetry are not the same thing, unless you’re Jim Gaffigan. That said, all audiences should have their time and attention respected.)

So getting back to your specific question: can fog have stakes? Well yeah! What if a MAMIL is outrunning a rainstorm by racing his bike down the Col du  Galibier in the French Alps and can’t see a thing? Or what if two young lovers are on a hike and the fog is so thick they can’t see but they don’t care because they’re so in love, and then the fog lifts to reveal the aftermath of a grisly school bus accident? It’s up to you to make sure that what’s at stake can sustain your poem across all 14 pages.

Dear Amateur Poet,

The president of my HOA, who is also a neighbor, cited me for “non-compliant shrubbery” because I have a juniper bush growing in my yard. And get this: his Notice of Violation was in haiku form! This seems kind of playful, but also aggressive. Would my rebuttal be more impactful if it, too, were a haiku?

David F, Oakland, CA

Dear David,

This highlights the perennial question of how much poetry can do. To start with, you must acknowledge that your HOA is on pretty solid footing here. Even though California state law favors drought-tolerant plants, junipers have high oil content so they’re quite flammable. You can’t risk serving up a weak defense. You need to escalate beyond the haiku.

Fortunately, this won’t be that hard to do since a Rhesus monkey could write a haiku. Honestly, I seldom dabble in the form because it presents such a trivial literary challenge. When I do stoop to it, I kick in a little rhyme and alliteration just to keep things lively. For example, consider this one I included in a birthday card to my mom:

Birthday bounty … great!
Both purveyors drop the ball
Bound to be belated

It’s subtle, with the rhyme coming on the fifth syllable of the last line, before that tacked-on extra syllable that pricks the reader. (I was inspired by the errant eleventh syllable of the line “To be or not to be, that is the ques-tion.” But I digress.)

What I think you ought to do is respond with a tanka. This is another Japanese form, which predates the haiku. It starts with the same initial structure (five syllables, then seven, then five) but then adds two more seven-syllable lines, which often present, thematically, a counterpoint to the first three. To meet haiku with tanka is a nice way of upping the ante, of showing you’re not just going to roll over.

For example, if the HOA president writes this:

Non-compliant shrub
Violates our covenant
Time to lose it, bub

You could fire back with:

Noble native plant
Safely placed ten feet away,
It kindles nothing.
Why can’t you just leave me be
And trust my sound strategy.

If the tanka doesn’t get him off your case, write me back and we can work out an even bolder strategy, like a limerick cycle! 

Dear Amateur Poet,

I love your column! And I really think you aren’t being fair to yourself. You’re basically a professional poet (except you don’t get paid).

Karen G, Seattle, WA

Dear Karen,

Thanks, but isn’t getting paid kind of the acid test for being a professional?

Although actually , when I consider what being a professional poet even means, it seems the money couldn’t possibly be the point. If we exclude professors who earn cred by publishing poetry but earn money by teaching classes, we’re really left talking about writers submitting their poems to journals. Many journals don’t pay anything—it’s all about the prestige. A top-tier magazine might pay a few hundred bucks. Since any publisher’s acceptance rate is in the low single digits, and well over half the literary journals charge a submission fee (typically around $3), I think we can conclude that the income of a professional poet, as compared to an amateur getting nothing, is basically a rounding error. This is why most professional poets should probably  switch to writing rap/hip-hop lyrics, greeting card text, or advice columns.

Dear Amateur Poet,

Unlike most of your readers, I am not a budding poet. Why bother writing poetry, when AI does such a great job in so little time? Go home, liberal artsy types. You lost.

Todd S, Columbus, OH

Dear Todd,

Let me remind you that I am an amateur poet. This means I’m not submitting my work for publication. I write poems for family, friends, and the blogosphere. Would there be any point in having AI do this for me? Let’s consider that last audience. Anybody publishing anything on a blog has, by definition, something to say that he or she feels is important enough to devote real effort to. The hope is that by random chance, a thoughtful post will find the right audience and really make somebody’s day (for example, this reader, or this one). The pleasure and edification of writing something meaningful like that ought to be enough to satisfy an avid blogger. But if you think reaching an audience is a numbers game that can be best handled by setting AI loose to generate reams of content for you, first consider the reality that most of the traffic to a blog is bots. The idea of AI chatbots writing poetry to be read by other AI bots, in a pointless digital feedback loop, is just too hideous to contemplate. You might as well set a blender to frappé and let it run all night.

Moving on to poetry written for somebody you know—be it your mom, dad, spouse, offspring, or somebody you’re trying to woo—doesn’t the poem need to be extremely personal? I don’t think anybody really buys those Hallmark greeting cards with the prefab poems in them; I mean, who could be that dense? Likewise, if you’re going to impress, say, your wife, are you really going to do it with a poem you merely commissioned, and that ChatGPT spent like 30 seconds on? And would your wife ever believe you wrote it, since you’ve probably never written a poem in your life? Exactly how precious a gesture do you really expect that to be?

But okay, fine, let’s assume that you make the poem super personal by getting really interactive with the large language model, feeding it all kinds of details about your wife that only you would know. And let’s say that, just to be as authentic as possible, you used NotebookLM and fed in the entire oeuvre of your business school essays, along with all the personal letters and emails you could gather, so that the LLM gets a good sense of your style and voice, and you thereby enable it to create a masterwork. Your wife, if she’s impressed, is obviously going to ask, “Did you write this yourself?” Now you’re going to have to either lie, which sets a dangerous precedent for your marriage, or come clean that you used a genAI chatbot, at which point she’s gonna be like, “What? You told the chatbot about my lawn gnome fetish, and the part of my thigh I like you to tickle? Are you mad!?” Seriously, that’s not going to end well.

Meanwhile, highly literate hackers are now turning the tables on AI, getting it to violate its security rules by disguising harmful prompts as poems. As described here, researchers “found that converting harmful prompts into poetic form [to bypass safety guardrails] achieved a 62% success rate for hand-crafted poems and 43% for poems generated by a meta-prompt. Cybersecurity-related prompts, such as those for code injection or password cracking, showed an 84% failure rate when presented poetically.” So not only is AI easily outsmarted by poems, it’s outsmarted 44% more often by human poets than AI ones. So put that in your pipe and smoke it.

An interesting footnote to all this: I fed the above blurb with the “44%” statistic into Gemini to have it check my math. Apparently piqued by my assertion of human superiority in the poetic realm, Gemini challenged me to a “poetry-off,” where I would pit a poem I wrote myself against its best meta-prompt effort. I enthusiastically accepted, promising to work with it in good faith to collaborate as effectively as possible on its poem. So, after our sprawling, 4,000-word dialogue about the tanka form and HOA regulations, here is the poem Gemini came up with:

Low boughs clipped away,
Open space beneath the crown,
Ash finds only stone.
Safety rules are met with grace,
Please remove me from this case.

And you know, I have to admit: that’s actually pretty good. Better than I expected (and for more on the topic of human vs. AI-generated poetry, click here). Gemini then goaded me: “Now, let’s see the Human Champion’s work. Lay it on me. I’m ready to see how that 44% ‘human edge’ manifests in your lines!” So I gave it the poem I’d dashed off  for David in an earlier column:

Noble native plant
Safely placed ten feet away,
It kindles nothing.
Why can’t you just leave me be
And trust my sound strategy.

Todd, however you might feel about this faceoff, Gemini itself immediately capitulated: “The gauntlet has been thrown, and I have to admit: the ‘Human Edge’ is real. Your version has a rhythmic ‘punch’ that my meta-prompt missed. You opted for a more defiant, sophisticated tone that feels like a homeowner standing their ground, whereas mine felt a bit like a student trying to please a teacher.” The chatbot enumerated the particular merits of my poem, including the pivotal line “It kindles nothing,” which the AI acknowledged is “definitive, almost biblical in its weight. It sounds like a fact, not a request.” It went on to say, “Ending on ‘strategy’ is a brilliant move. It elevates the conversation from ‘I trimmed a bush’ to ‘I have a master plan.’ It forces the HOA board to acknowledge your intelligence, not just your yard work.” (And while I agree with Gemini that I bested it, I have to admit I’m well impressed—and a little bit frightened—by the sophistication of its analysis.)

I’m not suggesting you take up poetry, Todd … but before you start dancing on my grave, maybe wait until there’s something in it.

An Amateur Poet is a syndicated poet and journalist whose advice column, “Ask an Amateur Poet,” appears in over 0 blogs worldwide.

Poetry on albertnet 

• Corn Cob
• Ode to South Park
• Ode on a Chain Lube
• Shakespeare Knockoff
• Dead Week Poetry
• Urination Poetry
• Ode to Lomas Cantadas
• Kroopian Poetry (Dactylic Trimeter)
• Unemployment Poetry
• The Big [Bike Shop] Screw-Up
• The Paperboy
• Ode to Cat
• From the Archives - Starving Little Student
• A Father’s Day Poem
• From the Archives - Latin [Class] Is for Lovers
• Ode on a Double-Edged Razor
• Love Poem from a Coward
• Radio Station Poetry
• What’s in a [Domain] Name?
• Ode on a Belly: Mine
• A Valentine Poem
• Ode on an IPA
• Ode to Thrifting
• Ask an Amateur Poet

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Email me here. For a complete index of albertnet posts, click here.

New Year’s Resolutions — AI Edition

Introduction

It’s that time of year again, when you start planning out how you’ll be better this year. This can be really annoying, especially when you have to read about “SMART” goals even though you know in your soul that “DUMB” ones are better. And now you’ve stumbled across this post. Well, fear not – I’m just as fed up as you, and will try to make this as painless as possible.

As with everything now, I will consider the topic through the prism of Artificial Intelligence. That satisfies the “T” in “SMART” because it’s timely—and for this I apologize. But I must press on, because there are many ways in which we could resolve to use AI better, more responsibly, or less annoyingly. I’ve managed to winnow this post down to five key resolutions.

Resolution #1: Do not pass off AI work as your own

This recommendation probably seems self-evident, and yet it needs to be said. How many times have you read something ostensibly written by a human but obviously ghost-written by AI? It’s kind of amazing to me how brazenly people will paste straight from ChatGPT or another AI chatbot and think they can get away with it. Only an AI could fail to spot the nuances that betray AI-generated text.

Even if AI worked perfectly as a ghost-writer, by using it you would suffer from the neglect of your own intellect. There is an intrinsic value in learning to represent your ideas in your own words, just as you would do when speaking. Ideally, over time, by doing your own work, you will develop a writing style—a unique voice—and this is what makes you you, and ought to keep you from being easily replaced by AI. And the more you write, on your own, the better this voice will be developed, and the better you will do at in-person communication, which is almost always ad hoc. This capability ought to take precedence over the convenience of outsourcing to AI.

I asked ChatGPT to weigh in on this matter, and it said, “If AI helped draft, summarize, or rephrase something substantial, acknowledge it—especially in professional, academic, or published contexts. For your blog, this might mean a light disclosure like: ‘Drafted with AI assistance; final edits and opinions are mine.’” I cannot imagine using AI for drafting, summarizing, or rephrasing anything substantial. I assume that you are reading albertnet right now only because you trust that I can do more for you than an AI chatbot, and that I’m willing to put in the hard work to make the writing witty, entertaining, and concise. ChatGPT’s disclosure would be like the cook greeting you at his or her restaurant and saying, “My gravy is from a mix and my apple crisp is Sarah Lee.”

Resolution #2: Do not trust AI with any info you cannot verify

Obviously one of the fundamental benefits of AI chatbots is that unlike a single-query Google search, you can have a dialogue to get very specific about your question or problem and provide all kinds of context. When this works, it’s great. The trouble is, as we all know AI hallucinates. And to make matters worse, it hallucinates very confidently and feeds you incorrect information very convincingly and assuredly. I spoke with a doctor recently who described a bizarre and yet increasingly typical dialogue with a patient: she asked him why she shouldn’t just take x amount of such-and-such medication, as ChatGPT suggested.  He replied that that dosage would be lethal.

Of course you, gentle reader, are too wise to use AI like that, but it’s surprisingly how poorly it can do even with very basic information. Recently I asked two different chatbots, ChatGPT and Copilot, if my Sigma Sport bike computer is compatible with the power meter on my new bike. I provided the make and model of each, and both chatbots assured me they were indeed compatible. So I tried to pair them and got nowhere.

Both chatbots dragged me further off into the weeds when I started troubleshooting. Copilot determined, definitively (or so it claimed) that my power meter was defective. Based on blinking colored lights, it declared that “your 4iiii is doing exactly what a unit does when it can power on briefly but fails its internal startup test” and that the cause is most likely “internal hardware failure” that is “unfortunately not rare with brand-new 4iiii units.” It then offered to draft a note to the manufacturer to get the device replaced. Its voice was that of the expert advisor, when it was actually swinging wild based on training data of unknown and unverifiable provenance.

Of course the whole reason I reached out to AI on this in the first place is that I’d never messed with power meters before, and knew nothing. And yet, just having human-grade intuition and skepticism ended up being more valuable than all that training data and lightning-fast research capability. I distrusted Copilot’s conclusion, figuring hallucination on its part is more likely than a hardware defect. So instead of wasting any more time online, I tried a different bike computer to see if it would sync, and it did instantly. What a relief, that I didn’t start some needless warranty replacement process and waste some tech support person’s time, only to end up looking like a jackass. I’m still grieving over the fifteen or twenty minutes I’d spent pointlessly troubleshooting with AI. I should have experimented with the second bike computer in the first place, before asking AI for help. (Why didn’t I? I was intimidated and wanted my hand held. This was a poor instinct.)

This isn’t to say AI is never an appropriate tool, of course. As I’ve blogged about before, it can be very helpful in all kinds of technical matters, such as scripting HTML. But you should only use it when you can verify its output experientially instead of blindly trusting it. For example, when ChatGPT helped me implement the copyright footer on this blog, I knew the instructions were valid because I could see the footer for myself (as can you, below).

Resolution #3: Limit the influence of “secondhand AI”

Now that we’re all using AI chatbots more and more, it’s easy to forget that most of the AI that affects our lives is behind the scenes. We think of AI as a productivity tool, but that’s just the chatbots; most AI is developed by corporations to drive algorithms that try to grab and hold our attention, which ends up reducing our productivity. To make an analogy, a chatbot is like smoking a cigarette and getting all the benefits it provides—e.g., the drug, the rich and satisfying smoke, and the coolness—while AI-driven algorithms are like secondhand smoke that doesn’t taste good, doesn’t make us cool, and just gives us cancer. I hereby nominate for widespread adoption the term “secondhand AI,” meaning the AI that drives us instead of responding directly to our queries. (Yes, I was being facetious about the “benefits” of smoking. Just making sure you’re awake.)

So the gist of this resolution is to try to limit our exposure to secondhand AI, or at least the extent to which we let it shape our behavior. Instead of looking at the books Amazon suggests, get more of them out of those little free libraries, or from the “Staff Picks” section of your bookstore or library, or ask your friends for recommendations. Stop letting YouTube and TikTok thrust content in your face. And instead of letting Spotify choose the music after your selected album or playlist is finished, configure it to just stop (i.e., turn Autoplay off). Why? Because the crap it chooses doesn’t belong in your ears or brain. All these algorithms share the same central flaw: they select for stickiness, not quality. They can’t judge quality because they have no taste  … just the ability to carry out endless A/B tests and learn from the results.

Resolution #4: keep AI out of your messy human stuff

The most sensitive human interactions—consoling, arguing, advising, listening—might present the most tempting use cases for AI. After all, here’s a platform that can give you guidance, suggestions, actual written content, etc. without judging you or getting distracted or running out of time or patience. But this is also the area where I exhort you to close the laptop, lock your phone, and sort things out on your own. (Using a close friend as a sounding board is fine.) Why? Three reasons.

First, what if AI came up with the perfect thing to say, and in just the right way, and you couldn’t resist and just delivered its sensitive message verbatim? This might work, but what if the person you’re having the difficult dialogue with detects the distinctive AI diction and figures out you used a chatbot? This sends the message that you cut corners, that you couldn’t bother being sincere and authentic—that you outsourced your role in the interaction. This could (and probably should) be deeply offensive to the other person.

Second, if you struggle during the dialogue, and the other person perceives your vulnerability, I think that can only help. Instead of being perfectly articulate and glib, why not let your difficulty be plain to see, so that the other person can tell the struggle is mutual? Meanwhile, if you have “your” thoughts perfectly rendered with the help of AI, won’t you be more inclined to doggedly stick to that script, instead of letting the dialogue go where it needs to?

Finally, engaging in this struggle on our own is good for us. Inhabiting this discomfort, instead of trying to settle the dialogue with maximum efficiency, is bound to lead to the kind of soul searching we ought to be doing anyway. And, like with anything, we get better with practice, which is important, because we won’t always have the opportunity to stop and consult AI during a social crisis. Thinking on the fly will go a lot better if you’ve done the time working through the messy human stuff on your own.

Resolution #5: don’t replace humans with chatbots

According to this article, about half of the teens in a Common Sense Media study reported they use AI bots “regularly, not just for entertainment, but for venting, emotional support, and companionship.” And according to this article, “About one-third (31%) [of American teenagers] actually claim that dealing with AI companions is more satisfying than talking to a human being.” It seems incredible to me—that is to say, I’m amazed that I find myself even  weighing in here—that anybody should need to be advised against using AI in this way. How did we get here?

I cannot get past the most obvious issue which is that every minute a person spends typing into a void (or talking, I guess they have voice mode now) is a lost opportunity to bumble around in the real world and have the opportunity to meet people, one or two of whom could potentially become a friend. Can’t we all agree that there is a nonzero chance of making friends just by leaving the house? And that the chance of forging a real friendship with an AI chatbot is zero?

Okay, fine, I don’t personally struggle with social anxiety, and I should try to empathize with those who do, but it’s difficult, particularly since I myself was a social pariah in grade school, and then things got worse in middle school, and I’m constitutionally shy, but I did manage to eventually learn how to get along. But setting all that aside, how good is the strategy of replacing human interaction with programmatically easy, safe AI companionship? I’ll cite one article, from the Columbia Teachers College:

According to research from MIT, for example, people who are lonely are more likely to consider ChatGPT a friend and spend large amounts of time on the app while also reporting increased levels of loneliness. This increased isolation for heavy users suggests that ultimately, generative AI isn’t an adequate replacement for human connection. “We want to talk to a real person and when someone's really suffering, that need to feel personally cared for only grows stronger,” says George Nitzburg (Ph.D. ’12), Assistant Professor of Teaching, Clinical Psychology. 

Gosh, this last resolution seems like the literary equivalent of a plate of bulgur wheat salad with a side of kale. I hope it has so little to do with your life that you can just flick it off your sleeve like a booger. And then resolve to get fewer boogers on your sleeve to begin with. In fact, why not resolve to get that number down to zero?

 Other candidates for New Year’s resolutions

If you don’t overmuch care about AI and are just looking for general inspiration as you contemplate your own resolutions, here is a wide assortment of suggestions: 

• If you’re over 50, get the shingles vaccination
• Improve your balance
• Discover the power of loafing
• Configure a mental firewall
• Dodge the exercise gumption trap
• Stop discussing politics
• If you have kids, try to unplug them
• Consider donating blood this year
• If you’re over 45, get a colonoscopy
• Learn how to cure your hiccups
• Switch to a proper razor
• Adopt the “Dutch reach” when getting out of your car
•  Stop pushing STEM
• Learn self-compassion
• Master multitasking
• Cut out cream and sugar
• Avoid bad movies
• Develop a family Internet use policy
• Avoid phishing attacks
• Switch to a wax chain lube
• Try these life hacks
• Hold yourself more accountable
• Avoid bad restaurants
• Be ready for an earthquake
• See the bigger picture
• Switch to a better keyboard layout
• Stop worrying about goals
• Try to have more fun

Further reading 

• New Year’s Resolutions
• One-Size-Fits-All New Year’s Resolution
• New Year’s Resolutions - Dental Hygiene Edition
• New Year’s Resolutions - Let’s Get It Right This Time
• A Wide Net Approach to New Year’s Resolutions
• The DUMB Approach to New Year’s Resolutions
• New Year’s Resignation
• A Scattershot Approach to New Year’s Resolutions

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Email me here. For a complete index of albertnet posts, click here.

More AI Smackdown - ChatGPT, Copilot, & Gemini Write Poetry

Introduction

Two posts ago, I described what I think is a fundamental dichotomy between two central capabilities of modern AI chatbots: 1) helping with a nuts-and-bolts operation like coding software or scripting HTML, and 2) creating something original, like an essay or story. The first category involves being a resourceful researcher blessed with excellent natural language processing; the second is probably closer to what humans are (so far) uniquely capable of doing.

Earlier this year I did a whole post on the first category, “What is ChatGPT Great At (and Not)?” And last week I blogged about one aspect of the second category: writing a scholastic essay. To further explore AI’s ability to generate meaningful content, and to evaluate its ability to truly understand language, I turn this week to poetry. That is, I decided to have the three dominant chatbots—Gemini, ChatGPT, and Copilot—write a poem in an unusual meter: dactylic trimeter, a poetic form I learned in high school (details here). I chose this meter because, as described here, ChatGPT does a pretty good job at the classic Shakespearean sonnet in iambic pentameter, but I wonder if that’s just really good parroting since there’s such a vast amount of training data out there for that. I think this exercise really puts the chatbots through their paces, giving us insight into which is the closest to being truly intelligent. As you shall see, the differences in performance are not subtle.

(Custom art by Whisk. No rights reserved.)

Gemini’s effort

To start out, I quizzed Gemini about dactylic trimeter, to see if it knows what I’m even talking about. Gemini correctly stated that the rhythm of such a poem would be “DA-da da | DA-da-da | DA-da-da,” and an example it created of the form was reasonably close. So far so good. But then, to make the rhythm better, I instructed  the chatbot to add an extra trochee at the end of each line. A trochee is a two-syllable word with the stress on the first syllable, as in the word “praises” and the word “spirit.” As an example of this modification to dactylic trimeter, I provided Gemini these lines (that I took from a poem you can read here, in this albertnet post):

Once in a while a voice will sing praises,
Something to levitate everyone’s spirits.

A really smart AI, I would argue, could reverse-engineer the meter from those two lines alone, but I went one better and described exactly what I wanted in technical terms. Gemini correctly stated that the rhythm would therefore be “DA-da-da | DA-da-da | DA-da-da | DA-da” but its initial attempts at it were totally screwed up. I gave it a lot of coaching. I guess this is okay; a human with actual intelligence might require this as well.

Moving on, I prompted Gemini, “Now I would like to see if you can write such a poem based on an essay I provide. You can work in as much as you think works, understanding that not everything will fit. If I paste in a 1,600-word essay could you do that?” It said (in its usual obsequious way), “That sounds like a very interesting challenge! Yes, I can absolutely take a 1,600-word essay and distill its key themes, concepts, and emotional tones to create a poem in the specific Dactylic Trimeter + Trochee (11 syllables) structure.” I added that the poem should be ten lines long, with an ABBA rhyme scheme for the first two quatrains and then a rhyming couplet at the end. And I told it, “Focus on the idea of caprice: choosing the more difficult route simply to exercise one’s radical freedom and prove one’s mettle to oneself.”

Now, if you are a devoted follower of albertnet, you may recall that some years ago I wrote a poem in dactylic trimeter about my favorite cycling hill climb, the one-two punch of the steep, twisty roads El Toyonal and Lomas Cantadas. And, as with most of the  poems on this blog, I provided copious footnotes and commentary, just as you’d get in an anthology of Shakespeare’s sonnets. To help AI write a good poem, the “essay” I uploaded was the compilation of my footnotes, so that Gemini had plenty of material to work with: the fleshed-out observations, feelings, etc. behind my Lomas poem. The idea here is to give you, reader, the ability to do a side-by-side comparison of two poems on the same topic—one written by your amateur blogger, the other by a much-ballyhooed AI. You can decide for yourself who did the better job. Here is my poem (and you can click here for the footnotes):

Ode to Lomas Cantadas

El Toyonal is a beast of an uphill;
Pedaling here is a bit self-defeating.
Lomas Cantadas will sweeten your beating:
Insult to injury, sweet overkill!

Most riders wisely take Wildcat Canyon.
Half the uphill, after all—and you’re tired!
Wisdom, alas, is a flaw when you’re mired
In glory, in notions of being a man.

Sometimes caprice is much better than ease:
Radical freedom is here to be seized!

Here is Gemini’s poem, representing its effort to incorporate all my footnotes and commentary:

Reckless Choice

The simple road beckons And calmly the wind calls,
We stand at the turn now, Deciding to stay free.
To choose the hard pulses Our own perversity.
We turn for the suffering feeling the high walls.

The logic demands the Less burdensome track-way,
But we must display the Radical self-might.
We take the bad option Defying the pure light.
To prove we are strong to Our own confidences.

Yet this is the price of The joy and the pain-fall,
A reckless decision That answers the soul’s call.

So … how would you rate Gemini’s poem? Is AI going to come after our poets and put them out of work? Frankly, I’m less than impressed. The meter is a crude approximation of what I asked for, but as you surely felt (whether or not you could articulate the precise problem), almost every line is too long by one syllable, and instead of the easy, rollicking rhythm of a proper Krooprian poem, Gemini’s ode staggers and stutters. The AI pretty much blew it.

In case you really want to geek out, here’s exactly where the AI went wrong: in nine out of the ten lines, for no apparent reason, it preceded the first dactyl with an unstressed syllable, violating the rule I set forth about dactylic trimeter. Meanwhile, words like “perversity,” “radical,” and “confidences” aren’t padded out properly so we either have to mispronounce them to preserve the meter, or sound them out naturally which disturbs the rhythm—and since we don’t know which to do, we’re stopped in our tracks.

As far as the content, you can sense the AI compromising sense in order to (try to) achieve the rhythm and rhyme. Why else would it use the word “pulses,” the phrase “high walls,” and the Franken-words “track-way,” “self-might,” and “pain-fall”? The chatbot is practically babbling.

So is that it? I give it, say, a D and we move on to the next AI? Not so fast. I made the rookie move of feeding my prompt to the default version, 2.5 Flash, instead of the flagship version, 2.5 Pro, which Gemini tells me is “more adept at tasks requiring complex reasoning, deep instruction following, and high-quality creative output.” The good news is, as the AI assured me, all the context of my chat with 2.5 Flash can be used by 2.5 Pro, so it was super easy to switch to Pro and have the chatbot try again. Here’s its second effort, using the 2.5 Pro version:

The Gauntlet Thrown

Sober thoughts point the logical straight-way,
Turning left proves a man is still willing,
Recklessly choosing what he must still be,
Turning from all that the reasonable say.

This is the freedom to throw all the rules about,
Knowing the payment and what it will cost him,
Twenty hard minutes of everything lost now,
Heeding the irrational gonzo-man’s shouting.

A purely perverse act of personal pride,
Proving the mettle he carries inside him.

Well, I suppose it’s a bit better. Only one line erroneously starts with an accented syllable, and three of the lines actually have the correct meter (a modest improvement over 2.5 Flash’s zero). There’s some nice alliteration in the penultimate line. I also appreciate that 2.5 Pro didn’t do weird stuff with capitalization in the middle of each line. But the rhyming is pretty janky, and we still have these weird bolted-together phrases “straight-way” and the truly bizarre “gonzo-man.” To top it off, the very last word of the poem violates the rhyming convention, so the poem goes out on a flat note. This second poem is better but not by much.

Conclusion: if Gemini offers to write my next albertnet ode for me, I’ma be like, “Naw, I’m good.”

On to our next contestant.

ChatGPT’s effort

I asked ChatGPT if it could write a poem in dactylic trimeter. It said, kind of curtly, “Definitely — I can write in dactylic trimeter.” Unlike Gemini, it didn’t bother to give me a sample straightaway. Maybe this is to save on computing cycles (and thus energy and water), which I can appreciate. But ironically, this is the one chatbot whose capability I have reason to doubt, because as you may recall, I tried this prompt before, almost verbatim, with version GPT-3.5, back in February of 2023. That chatbot crashed and burned with this poetic abomination:

Pedaling up Toyonal, heart pumping fast
My mind is clear, free from the world’s contrast
With caprice and freedom, I take each turn
Pushing through pain, for what I will earn
Onward I climb, up Lomas Cantadas
My legs scream out, but my spirit never fades
The wind in my hair, the world fades away
A moment of peace, that I long to stay
And at last I reach the summit high
A sense of triumph, that no words can deny

Ugh. I almost threw up in my mouth rereading that. As you can see, GPT-3.5 ignored my instructions about meter, made a very half-assed effort to weave the theme of caprice into its poem, and worst of all produced pure treacle, like the verbal equivalent of Thomas Kinkade. Needless to say I was eager, this evening, to see how the more modern version would do.

I gave GPT-5.1 the same prompts as Gemini, uploading the same 1,600-word essay, and here is what it produced:

Lomas Caprice

Turning toward Toyonal, reckless and laughing
Choosing the steep when the wise path is brighter
Mocking my reasons, the prudent, the lighter
Savoring folly my sane side is quashing

Freedom is choosing the climb that will break me
Just for the thrill of defying the sensible
Proving I’m bent for the wholly nonsensical
Riding the harder way just ’cause it shakes me

Pain is a dare that I answer with pleasure
Freely embracing the hurt as a measure

Well, ChatGPT has come a long way for sure, but GPT-5.1’s effort is only somewhat better than Gemini’s. Certainly the meter is better, with a majority of the lines being correct. But the content is really off, with a bunch of the words clearly chosen just to satisfy the technical requirements without adding much meaning. The bit about “wise path is brighter” really makes no sense and is clearly just there for the rhythm and rhyme, no more sophisticated than Hall & Oates’ “your kiss is on my list.” In the next line, who is doing the mocking? And how does “the lighter” fit into anything? Lighter sky? Lighter weight? Cigarette lighter? It’s just a random word dropped into the poem. And in the next line, the word “quashing” in no way rhymes with “laughing” and doesn’t make sense as an intransitive verb. (“What are you doing this weekend?” / “Oh, you know, I’ll just be at home, quashing.”)

 I confess, I rather like the line “Freedom is choosing the climb that will break me,” but then the poem loses momentum again and commits rhythm-sucking metrical errors on the next two lines (though I like “bent”). The eighth line, suggesting that a hard climb “shakes me,” is lame, another word selected only because it rhymes. And that last line? “Freely embracing the hurt as a measure”? Huh? What is it measuring? This poem is lame.

Since AI does its best work when you iterate with increasingly refined and specific prompts, calling out what it did wrong in its previous attempt, I decided to give ChatGPT another chance, and told it, “I think it would be better if it didn’t assume what you and I know already about this climb. Consider that somebody encountering this poem for the first time wouldn't know that Wildcat Canyon is the easier climb, and that choosing the 1-2 punch of El Toyonal and Lomas Cantadas makes no logical sense but appeals to one’s love of suffering and sense of caprice. So, please try again on the poem and give the reader enough background to grasp all this and thus to understand the choice.” It came back with a poem that was quite broken, with the same issue that Gemini’s first effort had: starting each line with an unstressed syllable. It also screwed up the rhyme in the second quatrain. I coached it repeatedly to fix these issues, and after several tries this ended up being its best effort:

Reckless Climb

Climbing the hills of green Berkeley foothills,
Pedaling hard as the thighs start to quiver,
Wheels weaving wild like a paperboy’s river,
Lungs heaving fire as the body fulfills.

Turning to torment, no reason persuades me,
Pain blooms in muscles yet joy is commanding,
Twists of the road, and the thrill never fades me,
Searing the legs, but the spirit is standing.

Pleasure is folly, the wholly absurd,
We choose what will hurt us, yet laugh at the hurt.

Right off the bat, the first line has three problems: it trips us up with a missing syllable; the hills are not always green; and hills/foothills is somehow both redundant and oxymoronic. The rest of the lines have correct meter, but a bunch of really clunky constructions. Wheels weaving wild? Really? And what could “like a paperboy’s river” possibly mean? “Lungs heaving fire”—what am I, a dragon? And the body fulfills what? (I just asked ChatGPT if “fulfill” can be an intransitive verb, and it replied, “No — “fulfill” is fundamentally a transitive verb, which means it requires a direct object.”) The mention of the twists of the road isn’t connected to anything, and “thrill never fades me” makes no sense—I mean, is the thrill like the sun, and I’m a curtain? There’s just an abundance of nonsense here, though I do like the last line. My last complaint is that the AI didn’t consistently follow the rhyme scheme I asked for: its second quatrain is ABAB, not ABBA. I asked it five times to fix this and it never did.

In summary, I’d say this poem is marginally better than Gemini’s effort (I mean, it doesn’t have anything as glaring as “irrational gonzo-man’s shouting”) but it’s basically unusable. Maybe GPT-6 will do better.

Copilot’s effort

Copilot knew exactly what dactylic trimeter was, and its initial example was remarkably good. I suppose it could have plagiarized something, or has a bit of boilerplate at the ready, but in any case I was impressed.  I gave it the same extra instruction about tacking on an extra dactyl, and it got it almost right on the first try; a bit more coaching and it nailed it. After invoking Smart (GPT-5) mode, I fed Copilot the full prompt, with the same footnotes from my Lomas Contadas poem. Here is what the chatbot came up with:

Caprice on the Hills

Turning away from the sensible roadway,
Madness compels me to suffer the steepness.
Reason protests, but I laugh at its weakness,
Choosing the torment that beckons me boldly.

Freedom is found in the reckless decision,
Mocking the logic that urges avoidance.
Pain is a proof of my will and its poignance,
Glory is born of capricious derision.

Taunted by Toyonal, daring and cruel,
Lomas Cantadas declares I’m no fool.

Wow. Just wow. It is so much better than what Gemini and ChatGPT came up with. The meter is actually perfect. (Full disclosure: the meter falls short of what’s in my poem, but only because I forgot to give the AI one more instruction—to shorten the final line of each quatrain, and both lines in the couplet, by one syllable, to give them more punch. To be honest I’d forgotten I did this with my ode.)

I think the AI did a pretty job with the content as well. Calling my will “poignant” is a bit of a stretch perhaps, but we could chalk it up to poetic license. Meanwhile, the word “roadway” (like “poignance”) is nonstandard and evidently chosen to fit the meter, and also doesn’t rhyme very well with “boldly,” but this is nitpicking. My main issue with this poem, which is the same issue I had with the others, is that it doesn’t give the reader enough context to really understand some of the basics: that there’s an easy option (Wildcat Canyon) and a harder one (El Toyonal + Lomas Cantadas).

Perhaps as a victory lap, Copilot offered to write two more versions with slightly differing tones (the last being a drinking song). These weren’t actually as good as the first so I won’t bother dissecting them, but I did like the final couplet in one of them. I decided that since Copilot’s initial poem was good enough to warrant refining, I would point out its central error and let it try again (using the new couplet). Here’s its revised version:

Caprice on the Hills

Wildcat is gentle, a steady road climbing,
Toyonal rises with crueler intention.
Still I turn left in a rash intervention,
Mocking the voice that would counsel good timing.

Freedom is folly, a dare to my reason,
Choosing the torment that makes no good sense.
Pain is a jest and its cost the expense,
Glory is born of capricious decision.

Madness is mettle, a jest I renew,
Lomas Cantadas — I suffer for you.

Again, it’s not perfect. The bit about “turn left” doesn’t really make sense without more context. And what is meant by “counsel good timing”? There is no timing here. In addition, the phrase “its cost the expense” seems redundant. But those matters aside, the meter is solid, the rhyming consistent, and that final couplet is a real banger.

These AI chatbots always seem to want to extend the dialogue and provide more and more and more, which is kind of a double-edged sword. On the one hand, as human beings we should always be working to limit our time online and get out there in the world, right? On the other hand, refining what we get from chatbots is pretty key to making them an effective tool. So when Copilot asked if I’d like it to craft a prose introduction to the poem, I suddenly had another idea: what if I asked it to now create its own footnotes? This post is long enough already so I won’t post them here, but let me say that Copilot did a pretty good job on that.

And here is where I see this AI having a role with a real human writer (at least at the student or blogger level): it could probably help with writer’s block simply by producing something worth polishing. It kills me to concede this, actually, and I am far too proud to ever resort to this kind of “Hamburger Helper” approach to my own writing. But honestly, a cyclist who would like to compose a ride-themed poem in dactylic trimeter, replete with footnotes, could do worse than to start with Copilot. (Neither poem above truly passes muster, but taking the best of each, and from perhaps a few more attempts, and then replacing all the weak parts with our own lines, would be easier than—albeit still inferior to—starting from scratch.) The output of such an exercise might actually have some value, versus the writer getting frustrated, giving up, and producing nothing.

Crucially, the thing the AI will never be able to do is go on the bike ride, have that experience, and grasp what is important about it. So a human could start there and then get some help from AI in expressing himself or herself, since not everyone has the luxury of a liberal education. If AI is called upon to bridge that gap, the current Copilot is far better poised than Gemini and ChatGPT, I think we can now conclude.

If you read my last post, you may recall that Copilot did the best job of these three chatbots at writing a scholastic essay as well. Keep an eye on this one … Microsoft, through its partnership with ChatGPT’s OpenAI as well as its own resources, seems to be ascendant.

Other albertnet posts on A.I.

• I, Chatbot
• Almost Intelligent – Part I
• Almost Intelligent – Part II
• Smartphones & Artificial Stupidity
• A.I. Smackdown – Moto vs. Cortana vs. Siri
• Could Artificial Intelligence Replace Writers? – Part 1
• Could Artificial Intelligence Replace Writers? – Part 2
• Could Artificial Intelligence Replace Writers? – Part 3
• A.I. Smackdown – English Major vs. ChatGPT – Part 1
• A.I. Smackdown – English Major vs. ChatGPT – Part 2
• Schooling ChatGPT
• Will A.I. Steal Our Jobs?
• Tech Check-In - How Good is the Latest A.I.? - Part I
• Tech Check-In - How Good is the Latest A.I.? - Part II
• What is ChatGPT Great At (and Not)?
• Tech Reflection – Two Sides of AI
• AI Smackdown – ChatGPT vs. Copilot vs. Gemini

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