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.

2025 in Review - The Quiz

Introduction

As I close out 2025, I want to give my readers a little quiz about the topics I covered on albertnet over the past year. You can consider this quiz open-book (because after all, how could I police this)? 

Now, you might recall that I did a similar quiz four years ago, which might have annoyed you because all the multiple-choice answers were correct—that is, it wasn’t a quiz at all, but a farce. Well, fear not: this time there’s really only one right answer per question. And you don’t have to wait until next week for the answers … they’re right down at the bottom of the post. As a special bonus, I will award a merchandise prize to the first reader who gets a perfect score and reports it to me by clicking here. (Obviously you’re on the honor system here...)

2025 in Review – The Quiz

1. Which of the following is not a New Year’s Resolution that I recommended last January?

a) Get control of your dog – If you are a dog person, it might come as a real surprise to you that what you consider either adorable or at least lovably rambunctious misbehavior is actually a drag for grouches like me. For example, I’m out for a walk and your dog comes bounding over to me and tries to run up my body, his front paws raking my legs and groin, and you call out, “Don’t worry, he’s friendly!” And I’m thinking, fine, you’re probably friendly too, but would you windmill me like this?

b) Take better care of your teeth – If you don’t always brush, and/or seldom floss, then it’s time to face the fact that your teeth and gums are probably disgusting. If your parents spent a fortune on orthodontia, it’s a shame that you’re taking such poor care of their investment. And if you didn’t get orthodontia, your teeth need all the help they can get.

c) Stop wearing a COVID mask alone in your car – In the early days of the COVID lockdown when nobody know what was going on, we did all kinds of silly stuff, like forensic-grade wipe-downs of shopping cart handles, and wearing a mask in the car. But it never made sense to wear a mask when driving alone, did it? Are you worried you’ll give your car COVID?

d) Stop using my hairbrush – This one really only applies to my younger daughter when she’s home from college. So, L—, to be clear, it’s actually okay if you use my hairbrush on the sly such that I don’t even know about it. But when I have to look for it, I get nervous … what if you took it to a slumber party and lost it? As you know, it’s my oldest possession so I’m inordinately fond of it.

 2. Which of the following is not one of my five recommendations on how to improve your LinkedIn profile?

a) Rework your headline section – Here is an example of a good Headline:

>>Growth | Digital | Generative AI | Culture Cultivator | Mentor | Advocate |Outside the Box | Clarity Bringer | AI/ML | Driving Innovation | Flawless Executation| Podcaster | Olympian | Frontends | Evangelist | Stakeholdering | C++ | pDOOH | Rainmaker |Delivering Scalability| Solutionist

I’m not just supplying that as an example of what a tech worker would list; I’m telling you to literally copy and paste the above into your Headline (except “Executation” which was to make sure you’re paying attention).

b) Create an entrepreneurial vibe – Rank-and-file employees, be they wretched “individual contributors” or pathetic “middle managers,” just don’t get any respect. They’re as despised as tourists. But people love entrepreneurs. The trouble is, we can’t all be entrepreneurs, and if we were, we probably wouldn’t bother to fine-tune our LinkedIn profiles … we’d be whispering right into the ears of angel investors. But there’s another way forward: figure out what other type of –preneur you might be. Choose from the following or invent your own:

• Hellapreneur – like an entrepreneur but better
• Contrapreneur – has a startup that bucks current trends; for example, launches a new flip phone to corner the digital detox market
• Epipeneur – this person is launching a startup despite having a severe peanut allergy
• Codependepreneur – spins his wheels on yet another doomed startup because between him and his partner they’ve convinced themselves this thing is viable
• Saagpaneur – wants to open an Indian restaurant

c) Refine your Experience section and make it data-driven – For example, instead of just saying, “Performed software QA testing,” put, “Via disruptive and visionary software QA testing, reduced operating costs by 37%, saving $2.3 million in one year while improving CSAT scores by 24%.” The recruiter reading this, whose BS detectors will be lighting up like crazy, will think, “Oh, good, he’s also a storyteller! We can always use more of those.”

d) Have an AI chatbot help you revise your profile – As we all know, affinity bias is real. That is, if you and the hiring manager both went to UC Berkeley, you’ll have a leg up. Well, this affects your LinkedIn profile too: since it will only be read by bots, it should be co-written by a bot. Any of these AI LLMs will be sure to prune the unimportant stuff, like how you graduated summa cum laude (because who speaks Latin anymore?).

3. When I solicited advice from ChatGPT about how to monetize my blog, which of the following was not useful feedback that it provided?

a) “Your Blogger page view count is inflated” – The chatbot warned me that, although albertnet received 1.2 million page views in the preceding three months, the vast majority were probably from bots, scrapers, SEO crawlers, and AI training bots, so turning on Adsense would not generate any appreciable passive income

b) “Here is a boilerplate privacy policy for your blog” – When I asked it to help me compose my privacy policy (something I’d neglected to do for like 15 years), it provided a response that was mostly unusable, but did have some good points, and if nothing else prevented writer’s block and paved the way for my own policy, which you can read here and which I’ve linked to in my blog’s footer

c) “Here is what you need to achieve GDPR compliance if your blog uses cookies” – It gave me a nice rundown on what the GDPR requirements are, and I felt I could trust it not to hallucinate because this is such widely available information

d) “Here’s some example HTML script to invoke the traffic tracking” – It spoon-fed me actual HTML that I could paste in to my blog to start tracking various metrics

4. Which of these passages is not from my Ode to Thrifting?

a) A pair of Docs for only forty bucks? / I’ll take ‘em ‘cause they’re only barely used

b) Of course there’s all the stuff you’d never buy / Such pseudo-brands as George and Charter Club

c) Upon the racks of thrift, the brands they lie / Forgotten names that once did softly shine

d) But when I think of forking out full price? / No thanks – I’ll opt for thrift and toss the dice

5. The brutal 105-mile mountain bike ride I did on the Canyonlands White Rim Trail taught me that:

a) If you travel to a sufficiently isolated place like Canyonlands, you can be so dwarfed by giant reddish rock formations towering above you that you never need to see the celestial heavens again, if feeling insignificant is your thing

b) Regardless of how much experience we have, middle-aged cyclists have no business trying to keep up with Division 1 collegiate cross-country runners

c) During two-day driving trips, an all-taqueria-all-the-time approach to dining is totally worth it, even if it causes percussive flatulence that disturbs the much-needed pre-ride good night’s sleep

d) Clif and/or Kind bars are actually inferior to peanut butter and jelly sandwiches for long-distance cycling, especially in the heat

6. Which of the following is not a classic O.G. move, according to the albertnet-featured columnist “Ask an O.G.”?

a) Making pour-over coffee instead of using a Mr. Coffee or (shudder) a Keurig

b) Using a traditional double-edged razor instead of the modern plastic type with the blade cartridges

c) Buying your music on vinyl instead of CD or (gasp) Spotify

d) Sticking with standard bike handlebars and levers instead of the narrow, flared-out bars with goofy levers that stick out like chicken wings

7. Which of the following does not represent my take on the usefulness of locknuts for Presta valves?

a) If you have a commuter bike with Presta valves, use the locknuts or not, at your whim

b) If you have a folding bike, use the locknut because this type of bike tends to actually have Dunlop valves

c) If you have a backup “rain bike” that you mainly ride on the indoor trainer, you better be using noise-canceling headphones, in which case you can use locknuts or not, because who cares if they (or your valves) rattle?

d) For your flagship road or mountain bike, run tubeless with locknuts, and if anybody makes fun of you, send them my Presta valve locknut blog post

8. Which of the following strategies is not among my recommendations for when your loved one buys a juicer?

a) Let the juicer-buyer fail – It can be so hard to just stand by and watch a loved one fail, but in the case of a juicer, it’s actually the best thing you can do. If the purchaser perceives a battle of wills between the two of you, his judgment is bound to be further clouded. Just watch and wait, and when that first batch of kale, cucumber, carrot, and beet concoction comes out, accept the proffered glass willingly. Your vain attempt to avoid wincing, grimacing, puckering, or even gagging, and the pleasant smile you try to arrange, will be duly noted. In fact, you will be invoking the juicer-buyer’s empathy.

b) Be alert to collateral damage – If you have children, watch for any warning signs that they are coping poorly. Seeing a juicer in action, and knowing it was purchased intentionally, may cause them to doubt the foundation of reliable, competent parenting they rely so heavily upon.

c) Lead with empathy – Remember, this buyer is already in a highly vulnerable state … if she weren’t, she wouldn’t have bought the juicer in the first place! So instead, as strange and inappropriate as this may feel, thank her for thinking of the family’s health. Remember, if you’re going to eventually pick up the pieces and move on, you need her to feel like you’re on her side.

d) When the time is right, “disappear” the juicer – Out of sight, out of mind. Spare your family the ongoing trauma of repeated attempts to make a palatable vegetable beverage. The juicer-buyer may well assume the juicer is just “hiding” and may even feel secretly relieved not to have to try again.

9. I challenged the three leading AI chatbots to write a poem in dactylic trimeter. The topic I assigned was the reckless behavior of choosing to bike up Lomas Cantadas, a brutal climb, just to celebrate one’s radical freedom. Match each passage below with its author: ChatGPT, Gemini, Copilot, or Dana.

a) Turning to torment, no reason persuades me, / Pain blooms in muscles yet joy is commanding

b) Wisdom, alas, is a flaw when you’re mired / In glory, in notions of being a man

c) This is the freedom to throw all the rules about, / Knowing the payment and what it will cost him

d) Madness is mettle, a jest I renew, / Lomas Cantadas — I suffer for you

10. The term MAMIL—middle-aged man in Lycra—lacks a widely recognized corresponding term for a middle-aged woman in Lycra. Which of the following proposed terms is mine?

a) SOMAT (slightly overweight middle-aged totty)

b) OWL (older woman in Lycra)

c) WILMA (woman in Lycra, middle-aged)

d) MAVIS (middle-aged vixen in spandex)

Answers

Here are the correct answers. 

1. (b) – “Take better care of your teeth” is not one of my suggested Resolutions. Although this is fine advice, I did not propose it in 2025; it’s from my 2018 post about New Year’s Resolutions. [Source: A Scattershot Approach to New Year’s Resolutions ]

2. (d) – “Have an AI chatbot help with your profile” was not one of my suggestions in this post. I don’t actually believe that AI platforms have affinity for one another. (And incidentally, it was a human career counselor who advised me to remove summa cum laude from my LinkedIn profile. I left it in, but translated it to English.) [Source: Five Tips for Improving Your LinkedIn Profile ]

3. (a) – “Your Blogger page view count is inflated.” ChatGPT did not caution me thus. In fact, it was a sucker for raw data and showed a serious lack of skepticism around page view stats. Blithely assuming that page views represented real readers, it calculated that if I were to turn on Adsense, I stood to make about $2,000 a month in passive income from this blog! It did provide a number of caveats, such as how my results might be affected by the geographical location of my readers, the positioning and type of ads, ad targeting, how well ads match my content, user engagement, and so on. But the question of bots vs. human readers didn’t cross its mind until I prompted it very specifically on this. Gemini failed similarly. This kind of “big picture” thinking is a major weakness of AI platforms, I think. [Source: What Is ChatGPT Great At (and Not)? ]

4. (c) – “Upon the racks of thrift, the brands they lie / Forgotten names that once did softly shine.” This was penned by ChatGPT, and shows once again that AI is pretty bad at poetry. Too general, and sacrifices meaning for adherence to the meter. [Source: Ode to Thrifting ]

5. (b) – “Regardless of how much experience we have, middle-aged cyclists have no business trying to keep up with Division 1 collegiate cross-country runners” is not one of my takeaways from this brutal ride. Actually, the young cross-country runners only put the hurt on Peter and me for about the first forty miles. Eventually their rambunctiousness caught up with them, or perhaps it was just the well-earned capacity for endless drudgery that Pete and I have built up over the decades, but we were all equally knackered by the end. [Source: Biking the White Rim Canyonlands Trail With Young Bucks ]

6. (c) – “Buying your music on vinyl instead of CD or (gasp) Spotify” is not something this columnist considers an O.G. move. In fact, he stated, “If a music lover still has the record player he bought as a teenager, and all his original records, plus perhaps a few select purchases to round out his collection, I’d consider that O.G. But when wealthy people buy modern turntables with multi-layer plinths, decoupled motor systems, and carbon fiber tonearms, and painstakingly replace their CD or MP3 collections with pricey records, that’s more of an epicurean thing than O.G. (Not saying it’s bad, mind you. Just not O.G.) [ Source: Ask an O.G. ]

7. (b) – “If you have a folding bike, use the locknut because this type of bike tends to actually have Dunlop valves” is not one of my conclusions from this post. It’s a total red herring here. [Source: Presta Valve Locknuts, aka Valve Rings ]

8. (d) – “When the time is right, ‘disappear’ the juicer” is not one of my recommendations. This would be helping the juicer-buyer to delude herself, instead of facing the fact of her error and learning from it. [Source - When Your Loved One Buys a Juicer ]

9. Here are the authors behind each poem exerpt:

    (a) – “Turning to torment, no reason persuades me, / Pain blooms in muscles yet joy is commanding” – ChatGPT

    (b) – “Wisdom, alas, is a flaw when you’re mired / In glory, in notions of being a man” – Me (from my “Ode to Lomas Cantadas”)

    (c) – “This is the freedom to throw all the rules about, / Knowing the payment and what it will cost him” – Gemini

   (d) – “Madness is mettle, a jest I renew, / Lomas Cantadas — I suffer for you” – Copilot

Once again, AI generally does a fairly poor job of maintaining sense when it’s trying to get the meter right, and Gemini didn’t even get the dactylic trimeter right. The outlier is Copilot which I think did remarkably, perhaps even frighteningly, well. [Source: More AI Smackdown - ChatGPT, Copilot, & Gemini Write Poetry ]

10. (d) – MAVIS (middle-aged vixen in spandex) is the term I suggested. Help me make this a household word! [Source: Ask a MAMIL ]

Scoring

9-10: You are a genius! You probably know this blog better than I do.

6-8: Excellent! You’re either just very good at taking tests, or you actually read my blog pretty faithfully in 2025.

3-5: Solid! It seems you’re actually pretty familiar with albertnet, even if you fell off a bit this past year.

1-2: Good! I’m impressed you made it all the way through the test!

0: Not so bad! Next time perhaps you’ll actually take the test instead of just skimming my post!

<0: You are either magical, a space alien, or an emoticon of a person with a big nose and a goatee.

Did you win?

If you scored a perfect 10, email me here and let me know. If you are the first perfect-scoring reader, I will respond to your email and make shipping arrangements for your special prize!

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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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