It's pretty funny to me that this is used as a hit-piece against AI generated content. Here's an open-secret for everyone: web-based sports content companies have been automatically generating content articles for at least a decade; way before LLMs became popular.
It is and was mostly done for search ranking. The more seemingly applicable content, the better your SEO.
This situation has probably happened several times before AI but has gone unnoticed or noticed to little fanfare. It's more indicative of ESPN not having its finger to the pulse and ensuring that one of the copywriters manually updated this particular article. It's not too surprising to me. They've always been known to favour quantity over quality.
source: I worked as a developer on the tech side of a company with this kind of content
the depression shouldn't arise from the generation, but from the consumption, for it is the latter that ultimately drives the former; that, in turn, can generate a reflection on what I myself consume.
I don't think people do actually consume it. In my experience this content was purely for SEO or maybe just a headline that people read quickly to keep up-to-date. The actual article content is rarely seen by a human.
Yes, but not for these articles. Here's a example situation where having good SEO with filler content that makes sense: Lebron James retires.
If you are faster and have the best SEO at that point in time then that means everyone trying to read about Lebron James retiring is going to search it in Google and is going to read your article first, and you're getting the ad revenue. It's a 90/10 situation. The "top" website in the rankings is going to get 90% of the clicks.
You can only be the "top" if your SEO to that point is also the "best". And to have that you need to have all this generated content.
But sports reporting has pretty much always been this way.
Unless anything extraordinary happens, every post game interview features the same questions with the same answers and every article about the game looks the same with only the names of the participating players and their stats changing.
Well, previously you needed an intern working maybe an hour (of they actually wrote good content, obviously more), that intern needs food, air conditioning / heating, so I'm not sure which consumes less energy. Now you have it in a minute and for a predictable low fee.
There are basically two types of content when it comes to these sports recap articles. I'm also excluding opinions/editorials because those are completely different.
1. low profile, not-so-popular content. eg. A Canadian Football League preseason game between the Toronto Argonauts and BC Lions
This was still generated using a template. No human intervention except maybe double-checking it before publishing it. This was before AI, too.
Often it was there for SEO or just updating people via a headline
2. High profile content, eg. Jeremy Lin puts up 38 pts in a game
This is often one of:
- pre-written, especially if we expected to happen that day
- withheld from publishing if there was auto-generated content but something crazy happened that game and then quickly re-written and released. Usually this would still at least be pre-written before the game ended and details that needed to wait for the game to end were filled in seconds before/after the game ended.
There's just as much labour put into it now as before. AI is now generating the low profile template instead of the madlibs we did before. The value add is that it's probably a better read, so you actually get user engagement, and better SEO than before.
And this same issue highlighted in the OP article would also happen without AI.
> This was still generated using a template. No human intervention except maybe double-checking it before publishing it. This was before AI, too.
Odd question but is that why the banal reporting on so many websites is such utter shit? Like in all dimensions, it gets facts wrong, it's usually rife with spelling and grammatical errors... when I spend too much time online I start feeling like the sole person on the planet who gives a shit about writing correctly.
Low quality news sites usually have a target that they need to reach in the form of X articles per day. When you're in that position, at best you can spend a couple of hours on any individual story before you have to turn your attention to the next one.
Good news take time and journalists often don't have that luxury.
Probably money in, money out. I think the content you're looking at _is_ underpaid interns. As another comment mention, sports data is actually very structured these days and its easy to automatically generate articles with it. Actual news, probably not so much.
The efficiency gains are undeniable, and AI can scale in ways that were unimaginable before. Less grunt work, more room for innovation—hopefully, we can reinvest that time and energy wisely.
> ensuring that one of the copywriters manually updated this particular article.
Clearly it was never "there" yet though previously, and obviously still isn't when this article is what's generated. You can tell that a lot of sports articles are essentially "fill in the blank", which is why they get the AP stories up right away, and then have their actual beat reporters come out with something later that night, or early next morning.
Beat reporters will also write during the game, and if I’m remembering correctly, will work on differing versions of the ultimate winner at the same time.
Absolutely correct! In the old days it was mostly video replay and witty banter describing what you were watching, which was fun to watch. Now it's become something I couldn't care less about, which is less video and someone telling me what I should think about what I just watched.
I'm OK with didactic commentators if the person talking to me is an expert and giving me new information.
Broadcast media outlets fail at that. I don't know much about sports but even I can tell that people on TV are speaking in vague generalities so they can never be proven wrong. I get told that the team that lost "didn't want to win" as if people getting paid millions a year to win at sports aren't motivated.
When people are afraid of being proven wrong above all else, they avoid making any substantive claims. If someone isn't afraid of that, they'll make more interesting predictions I can't get elsewhere, and eventually it'll be a more enjoyable product because I can make fun of that person for being wrong.
I can't help but wonder if gambling isn't part of the reason for all the opinions these commentators are having. You're right, expert info is important.
If I was into online sports betting, I would want all the info I could get. Since I'm not, what I want is video replay of what I missed, that's where ESPN lost me.
What web have you been browsing in the past 5+ years? It's not only sports "content". Any kind of content is drowned into low quality SEO pages. Auto generated or not, it's as useless. LLMs just generate it cheaper.
What a weird and rude way to call this out. The parent wasn’t talking about non-sports content and never suggested that sports writing was the only type of content plagued by SEO spam.
to me it doesn't appear particularly against or in favour of. Seemingly, LLMs don't avoid completely some of the mistakes that were already being made. Just as with any technology, the questions should be: by how much the two errors differ? Does the cost justify this margin?
Maybe hit-piece was a strong word; but I do think it's saying this happened _because_ of AI when to me it's been an issue for a long time. ESPN was always pretty egregious when it came to penny-pinching on content and ignoring less popular sports. Ask ice hockey fans how they feel about ESPN.
Not by people in the know, no. But I'd say 80% of "normal" people reading sports websites probably had no idea until now, and the only difference is that (gen)AI is suddenly a "feature" to be boasted about to customers to make shareholders happy. And suddenly all of these normal people are starting to have opinions on it.
Much like when food ingredients are slowly made worse over time, consumers can't necessarily put their finger on how and why somethinng is worse, but they tend to notice that it's worse.
I think people have noticed if not explicitly. They end up going toward platforms that have real humans on them (social media, message boards, substack) and not really understanding it's because they read a bunch of algorithmically generated noise on "traditional" published websites and moved on.
I don't think people did notice. Our view counts for sports articles were always very low, except the very high profile articles. And those ones would always be done by a copywriter and properly edited.
You're missing the entire point. LLMs are super overhyped and this is the 9000th example of how garbage LLM generated "content" is. It doesn't matter that garbage was being generated before. If LLMs were only being sold as "it might be better than the spam generator you're using today" we wouldn't have the current bubble where people are losing their jobs because C-suite clowns believe the hype.
This match was broadcast by ESPN on both ESPN2 and ESPN+. In that case, they are presumably paying two knowledgeable commentators to talk about the match before, during, and after it happens, adding context and describing the important events. Are they not providing a transcript of that to the writerbot? That seems like real low-hanging fruit, especially since the commentary is already live captioned.
I got nerd-snipped by this. I transcribed the match using the whisper-small.en and then asked ChatGPT to create a summary using a neutral prompt:
Here is a transcript of a soccer match. In the style of an experienced professional sports reporter, please write a 200 word article about the match.
Its summary starts, "In her final professional match, Alex Morgan delivered a performance filled with emotion and resilience, though her San Diego Wave fell short in a 3-1 loss to North Carolina Courage. The game at Snapdragon Stadium in San Diego was more than just a contest; it was a tribute to one of soccer’s most iconic figures."
OpenAI transcription & LLM is likely more costly than what they're willing to splurge on this. Care to link soccer.txt, so I can try with Llama 3 / 3.1?
One thing to try is only using the post-match commentary, which starts after the line containing 'final whistle.' When I did this, the result was more factually accurate, while still focusing on Morgan.
You should just need a better prompt. I think everyone would benefit from using a standardized prompt which asks the model to think through its work between `<thought>` tags before writing its response, and also reflecting on the response between `<reflection>` tags, and then outputting the final response afterwards
Sports have so much structured data, and such a high bar for describing it accurately (especially for a brand like ESPN), that there are significant risks to the hallucinations that might develop from a multi-hour transcript being fed into an LLM, especially with commentators excited about potential goals and other events that don't end up happening.
On the other hand, the rather simple task of "here's a set of goals, their times, who made them, who assisted... turn that into prose" could even be done without LLMs with a deterministic algorithm, and may very well have been in this case. Some of the grammar issues in the OP feel very pre-LLM in nature, like a combination of substitution rules gone awry.
Now, could you create a system that repeatedly interrogates the statements made by a first pass of an LLM on summarizing a long transcript, and comparing those results against structured data you know for accuracy? Would this lead to richer content and accessible error rates relative to the simpler approach? Would this be the type of thing that the best machine learning engineers in the world could probably prototype over a hackathon? The answer is very possibly yes to all three of these. But it's far from low-hanging fruit for any sizable, risk-averse organization. It's very difficult to fight against "the thing we have is imperfect, but at least it never gets the facts wrong."
It's a company that see itself as "media / journalism", and having consulted for a few of those I've always been amazed that their tech teams is most often isolated from the content team with very low access to said media. It's very different from what you would expect in tech (access to everything), or just common sense in general.
Note that I have no knowledge whatsoever of how ESPN work, I'm inferring from what I've seen elsewhere.
If "this is the last game for Alex Morgan" wasn't included as any part of the input/prompt, how on earth could the AI summary have come up with this for inclusion in the game recap?
If some teenage intern was given a table with the goals scored (player and minute mark), they would have written a similar article... but that's definitely not a good excuse for news orgs and sports sites to just use generative AI for everything, so I can see why people are annoyed with ESPN.
> If "this is the last game for Alex Morgan" wasn't included as any part of the input/prompt, how on earth could the AI summary have come up with this for inclusion in the game recap?
It couldn't, which is the problem. One of the big selling points of generative AI is to cut people out of the process of writing. If someone actually has to watch the game and describe what happened in the prompt, what's the point of the technology at all?
This is what an application of generative AI looks like: using low-quality input to generate something that looks like an article. This is our glorious future, brought to you by OpenAI.
I'm sure the fact that this would be Morgan's last game was somewhere out there on the Internet, and certainly should have been part of the training data, in which case I would guess that a more nuanced prompt to the AI could have elicited a more robust output.
LLM's general knowledge is trained on data that's months old (or longer). Alex Morgan only announced her retirement a few days ago, so in order for the AI to know about it, someone would need to pick out recent, relevant articles about her and feed it to the generator.
And even then, it's unclear that the AI would be smart enough to identify "retirement" as something that should be called out in the new article without specific prompting.
I don't think the critique is "how stupid of the AI" but rather "this is one example of how AI content falls short" even when it is supposedly reviewed by a human as ESPN claims
Indeed. This doesn't really have anything to do with the limitations of AI inherently, but more about using it better.
It seems like it highlights a clear avenue for improvment: rather than just feeding the events of a game to the LLM and asking it to summarize them, it seems important for the prompt to include summaries of e.g. the last 10 news stories involving participants in the game (players, coaches, etc.) and maybe the 10 top all-time news stories as well.
Then the prompt can be asked to summarize the game (not the other information), but to draw from the other information where it might make the article better.
Seems like exactly the kind of things LLM's can do, right?
It was well-known to people who cared about this (i.e., anyone who would read this recap) that this was Alex Morgan's last game. If ESPN can't capture this and incorporate it into their piece, given their wide reach in sports media, why should a publisher use the ESPN recap service instead of random Y Combinator startup?
Really, they need to set up some kind of RAG system to include this kind of information in the prompt. You could definitely make this semi-automated, but it requires putting more effort in to the system.
> ESPN made a point to note that “each AI-generated recap will be reviewed by a human editor to ensure quality and accuracy.” It’s unclear if the human editor failed to notice Morgan’s absence or also decided it was not worth mentioning.
I don't believe they'll have a human editor ensure quality and accuracy. The whole point of having AI write your stories is to minimize the number of people they have to pay, so paying a trained professional to thoroughly review every story is probably off the table. They may compromise on the thoroughness of the reviews, or the expertise of the editor, or they may just not have a human in the loop for every story, but what they will not do is pay a professional editor to do their job the right way, this I can guarantee.
> but what they will not do is pay a professional editor to do their job the right way, this I can guarantee
I don't think that holds up. They can save a lot of money by using generated articles, but they lose customer (advertiser) confidence if the content isn't accurate. One editor per ten replaced writers is still a significant cost savings.
A few iterations from now we might see editors getting replaced too, but I don't think we're there yet.
The time required to write a good article—by write I mean compose sentences and type them—is a fraction of the time it takes to research it. Because the AI can't do actual reporting or journalism (interviewing people, emailing sources, tracking down documents and ingesting them, checking facts, etc.) then you either push all that work on to the editor, or you consign your publication to only writing stories that require no original reporting. If you push it all on to the editor, the economics no longer pencil out, because the editor is doing the work of 10 authors plus one editor. If you stop doing original reporting, you have a bad product.
Today, with the field of journalism in freefall, we actually have the worst of both worlds: not enough editors, not enough time to report, not enough original reporting being done, and too many AI or computationally generated articles. But, I don't see how getting rid of the humans and doubling down on the AI actually solves that problem in the medium and long terms.
ESPN removed the humans from reporting, and the AI removed the humans from the report.
In their announcement of the service, ESPN made a point to note that “each AI-generated recap will be reviewed by a human editor to ensure quality and accuracy.” It’s unclear if the human editor failed to notice Morgan’s absence or also decided it was not worth mentioning.
"Blame the intern" has been the great scapegoat for the last hundred years.
That was my read, too - basically, "We have a teenager in India that quickly scans through a thousand AI-generated articles per day, looking for offensive language or anything that could get us sued, but that's it."
I hate the AI match recaps of WTT (World Table Tennis) matches.
The AI highlights cut off during a point, skip entire points or even sets. Not to mention they don't account for important events that happen between points, they might cut off exciting commentary/celebrations that happened after a point, and even the handshake at the end of the match.
How are these AI recaps generated? Are they fed a video file of the entire game and it spits out a summary, or maybe a score tally with timestamps for goals (written by a human) which the AI then pads with language and makes into a story?
Back when I worked on it, before AI, you have all the information from a game in an API and you just fill in the template with it.
Now, I imagine they take that raw API call and just use a prompt like, "write a summary article for a game using this data" and it spits it out. And I assume the prompt is more thought out than that (or not? It is ESPN after all).
I don't ever remember "retiring_players" being part of an API response, though, ;P
edit: Oh and yes, the play by play recap is documented EXTREMELY well. You would be surprised. The more popular sports like Gridiron Football and Basketball would literally have player locations by the second. This data all comes from feeds like SportsRadar.
They probably wouldn't pipe the fine tuned stuff like that in to a prompt, but you still have a decent summary like how many 3-pointers someone had and where they shot them from.
If I was going to build this prototype I'd start with just a semistructured textual play by play recap as the input. Also including roster, injury, amd schedule information with a fairly basic prompt would probably go a long way.
This data exists for most live games at this point via various web services. I'm sure espn has significant resources internally to source that info
I don't think ESPN does anything that takes significant resources. That's all handled by SportsRadar or ... there's another big provider but their name alludes me. They basically firehose you all the game information as structured data and you can use it programmatically however you'd like.
Definitely. I have no experience in live game statistics, but from my sports content experience I bet there's data scientists and applications behind the scenes that specifically pull this data to be read on-air.
Yeah it feels like the ideal way is to feed in a transcript of the announcer audio + some standard stats. That would ensure you catch both the human stories & the factual content.
But I wonder if there are licensing issues with using the audio/transcript to generate your summary. I know that the raw stats are public domain but I wouldn't be surprised if they can't use the transcripts or audio.
The gaps between expectations and reality of “genAI” is too vast at this point to ignore. If a multibillion dollar system breaks down because of “human error”, then maybe its capabilities are way overstated. If it needs carefully crafted queries (“prompt engineering”), 100% error proof data, a megaton of power, and humans still need to re-check the output. What have we gained?
Can we all just admit this AI phase is just a bubble?
I've seen a bunch of these articles now and a lot seem to have these sort of "context explainer" paragraphs that seem like they're there as filler to explain the context of the events.
However, they're almost always so general, or even elementary that anyone who would bother to read the article would already know that stuff would wonder why a sports writer would write it. There's zero need for them for the audience they will attract.
A few even have these hilarious "this report was is not intended to indicate X, but .." type paragraphs at the end.
You can almost imagine the prompts that brought them about.
I do think it would be better to just provide a box score if you have to use AI to write your articles. I do realize that you lose ad views this way so it will never happen. The text is merely to get you to stay on a page long enough to see another ad in the ad ponzi system we have forming the base of our tech pyramid right now.
I've only heard of NWSL and this player, as I'm sure the vast majority of people that come across this story, because of this AI recap. I'm guessing without the AI doing it there wouldn't have been one in the first place due to the marginal magnitude of the event. So, in the end a net positive for the league?
> ESPN did post a separate article on their outlets from writer Jeff Kassouf that is all about Morgan and the emotional night. However, that article is located on the side menu of the AI-generated recap and is easy to miss.
So... there was a human-written article to cover the human interest side of the story and an AI-written technical recap of the game. What's the issue?
And regarding the complaint about the link in the sidebar, it's easy to miss only if you came in directly to the AI-generated article. If you go to the main site, they prominently feature the human-generated content [1].
They literally stopped the game in the 13th minute (her jersey number) and subbed her out. Substituting someone that early in a match is typically because of injury and would have relevance to the overall outcome.
According to the article, ESPN said that human editors would review the AI recaps to ensure accuracy, so it wasn't just the AI recap that decided to leave it out.
Sounds like a selling point of the AI to me, if Morgan really wasn't instrumental to the game (it's common for a forward to just disappear for most of the match).
It's hard to watch anything by ESPN or NBC when you're just interested in the game and all they want to do is feed you everyone's backstory, or they're only interested in big name players.
For instance, the year after the Mavs beat the Heat to win the NBA championship, they face off in the first game of the year. Nevermind that the Mavs are the defending charmpions, the Heat had LeBron James and Dwayne Wade. They showed 8 highlights from the game, all from the Heat. The Mavs won the game.
An impartial AI recap does not have a high bar to get over.
Why do we feel the need to defend software bugs? Would we give the same defense of banking software that forgot to carry over the fractions of a penny?
It's a software bug, and there's plenty of resources available to the AI's owner to try and address it. It doesn't need a human advocating for it being OK.
The most relevant comment in this entire page. It is for the same reason that many people defended crypto-stuff here in HN for a long time: the hope that one can generate money from nothing. The holy grail of software development is the idea that one may sit down on a computer for a certain amount of hours/days and come out at the other end a millionaire. Crypto gave many people that impression; you simply build some kind of meaningless distributed crypto-driven app and money will start pouring in. Now it’s AI: learn how to develop with LLMs, build some kind of buzzword-filled low-hanging fruit and all of a sudden you can sell your startup for a billion dollars. If you point out to people that that’s bs, they think you’re trying to crush their dreams, that you’re the reason why it’s not working that well. “If only people would understand the crypto/AI revolution…”
Why is it a software bug? Just because you want to see those emotional sprinkles, doesn't mean that the person planning how to create the article decided that.
You personally and emotionally decided, without evidence, that this is a bug. No one else is saying that.
Imagine if you asked an AI to describe the discovery of radiation, and the AI deiced for you to talk about the personal life of Marie Curie for 2/3 of the whole text.
If you look into the happenings of the game, you'll find that there was a special ceremony held at 13 minutes for the retiring player. It's like summarizing the discovery of radiation and not mentioning Marie Curie at all. It's not emotional sprinkles (which is a pretty messed up way to refer to human interest articles), it's just omitting a notable deviation from the normal game flow is a bug.
We as a community are not used to calling AI failures bugs, but we probably should - it's the most accurate term we have. As is an non-requested backwards joint, or a fan of fingers, on a photorealistic generated image.
> In defense of the AI - the fact that it was her last match has little relevance to the game itself.
Only if you view the game as a cold emotionless process where the important thing is simply the data coming out, rather than the entirely human construct it is.
Right, and what AI misses is that the narrative of the game itself should be superseded (or at least complemented) by the unique additional subtext. It's not a defense of AI that it was oblivious to the most interesting angle.
Everyone’s missing the point here. You’re all saying this isn’t an AI failure directly because the humans in the loop failed to provide the AI with data. That’s true, but imagine this system automating news articles for CNN or whatever, and it’s supposed to be about some minor meeting of government officials, but tens of thousands of fans are NOT watching this meeting, like they are the soccer game, and then the AI fails to report on the officials deciding to, say, tear down the local library because it’s old and useless.
It doesn’t matter if the humans in the loop are at fault, technically, for the omission, the fact that AI replaced a human who could have been tasked with going to the actual events and writing about them was the reason the events were misreported!
We’re the technologists who are supposed to think hard about how to safely implement technology like this and instead of pointing out flaws and carefully testing things, we’re just cheering on tech we don’t understand how to use or get working properly!
this is precisely what I would expect to hear from the echo chamber of HN where the readers are too focused on the tech than on the users of the tech.
AI has been promoted as the best thing since best thing references were created. Of course people that understand the tech will know it's not really that great, but the people being sold the tech just accept the brochure as gospel and think it is amazing.
Do you think that anyone making the decisions on how many human journalists/editors to employee know how AI works, or that they hear the promise of being able to use even fewer humans and run with it?
Yes, that's part of my point, that the predictable outcome would involve this tech being sold to rubes and to people who do understand its limitations but don't care because they see short term profit in it.
The machines simpley obey their instructions, which was presumably to fluff out some words about who scored points, who defended from those who wished to score points, etc...
Ignoring the halftime events seems like a plausibly sane thing for a sports stats fanatic to have happen, and that's exactly what happened here.
Was this an AI/ML geneerated thing? I would question your definition of AI, unless a serries of IF/ELSE statements satisfies your concept of AI... It's just following the rules it was given.
People are very tired of the "move fast and break things" approach of the last decade and a half. Especially when the technology in question is being used to replace real jobs done by real people (in an already very tough job market). The only people benefiting from implimentations of AI like this are the CEOs and executives, who I wouldn't call "hackers" either.
There is definitely an argument for having a human proofread the article, but for all we know the recap could have been proofread by someone with as much understanding of soccer drama as the AI itself.
These articles were mostly written by low paid writers, that already lack the interest in the field. Most of them lacked nuance of recaps, because of who was writing them.
And who are we to say that some disinterested writer would have produced an article any different? After all generative AI only generates articles using the body of data that it's trained on... which leads me to believe that most articles fail to provide player profiles in their recaps in any case.
Well, we can risk of having a disinterested writer write a boring recap of a game, or we can guarantee that a disinterested LLM will write a boring recap of a game. The only difference is that it's cheaper for the CEOs to call an OpenAI API than pay a writer a salary. If corporations are going to try to justify adopting AI (and the mass layoffs that naturally comes with that), then the AI has to produce work that's not just as bad as the worst human output.
Or... We can have 1 highly paid specialist review recaps and adjust the prompt to the LLM, instead of 100 low paid disinterested writers producing crap articles(like they already do today)
Why should we race to the bottom to just employ people? Why do we need another Buzzfeed?
That's all fine but especially for a news site with millions of visitors (that also generates over 1B in profit a year) I expect Disney to screen ai content with a team of editors to ensure it at least meets a quality standard even if it's basic information.
the problem here is not the use of AI/LLM to generate content, it's the fact that the content missed a big detail that basically any human soccer reporter would've made into a graf.
I know we're supposed to be shaking our fist at these stupid AIs, but why should Morgan be mentioned? Did she score any goals? Did she get much playing time? I didn't watch the game myself, but it's entirely possible she did nothing notable on the field. So is the AI really mistaken?
Here, I'll give you the paragraph from the article which talks about your point, since you must have have missed it:
"You could certainly make the case that everything in the recap is accurate from a factual perspective. However, the fact that it doesn’t include any information about Morgan and how important this night was for her, the NWSL, and U.S. women’s soccer speaks to how these kinds of services can’t replicate human writers who can see an event from a 360-degree perspective."
Most game recaps that I've read are no less dry, than the AI generated one.
The reviews that come after are typically the ones that cover broader impact. Reviews also include third party commentary and more insights from specialists.
The benefit of having a factual recap generated minutes after the game far supersede the value added by a few words from a low paid recap writer hours after the game.
> The benefit of having a factual recap generated minutes after the game far supersede the value added by a few words from a low paid recap writer hours after the game.
I guess thats subjective and depends on what the individual finds interesting/important in sport. However including something potentially unecessary is far easier to do and covers more bases than leaving something potentially necessary out.
Thats your subjective opinion again, and thats fine you are entitled to it.
But there are many different types of people who might disagree with you or prefer something different. You seem to be just stating that what you want is what everyone should think is best.
This is literally what good editorial is. That's what makes best articles in journalism.
No one, including you, is interested in every single detail. And no one, including you, will read a novel for every single game.(and every single soccer game can easily become a novel)
It isn't computers and digits and statistics. It's people and personalities and how they interact. There's a reason sports is called a reflection of "the human drama."
Except for the Olympics, I don't watch or follow any sports. But I know enough to know that sports is about people.
The only people who think it's nothing more than numbers are people with gambling addictions.
This is a really romantic view of sports, and a strong attack against the strawman argument that's been advanced by nobody ("sports is just numbers").
But to answer the OP's original question: no, she didn't do anything worth mentioning in the game per the newly updated ESPN article. Her team was dominated, losing by 3.
"It was the final game in the nearly 14-year career of USWNT star Alex Morgan. The two-time World Cup winner and Olympic gold medalist played 15 minutes, exiting in the first half. Her shot on goal in the 10th minute was saved by Courage goalie Casey Murphy."
So should she have been mentioned in the article? Yes, but not for her performance and not in the context of her play in the match.
The commenter is suggesting that Alex Morgan didn't deserve to be mentioned at all, because of her supposed irrelevance in the single game.
The commenter, intentionally or not, is suggesting that nothing is relevant about any particular game except the statistics of the match and the outcome.
So yes, they were suggesting the game is only about numbers.
Factually speaking, knowing it's a player's last match means they won't be there for the next match. Which means any calculations looking at the potential for that next match can't include here. Factually speaking, know it's her last match is critical. Same thing with injuries, or even attempts on goals that fail. An attempt on a goal that fails doesn't impact the score. But it's something that happened in and around the game.
Specifically to this game: it also literally affected the game (maybe not in points, but it did have an impact), and that it wasn't mentioned means the information provided for the game was inaccurate.
If AI is going to summarize a game, it should do so accurately. It did not do that in this case, and that's not debatable. It was wrong. It did not accurately report the game.
If you simply want to see the raw stats from a game and ignore all of the human elements you're certainly welcome to, but it's bizarre to act like that approach is or should be standard. The human drama and history aspect of sports is a huge part of the draw for most people.
> The match, which was simulcast across various networks and streaming services, included a beautiful moment in which Morgan removed her cleats at midfield and tearfully waved to a Snapdragon Stadium crowd that chanted her name while players surrounded and applauded her.
From the article. Or is the claim that the AI model should expect there's nothing noteworthy about this series of events?
She's a big name in soccer and she's retiring. I don't even watch soccer and I recognize her name. It doesn't matter what her performance was in her final game. It's very common to give great athletes recognition (at the very least mention) at their retirement. Your comment is bewildering (tone-deaf).
Yes. It’s probably one of the most-watched games in NWSL this season. People who don’t even watch NWSL watched this game.
I mean, hell, even if it were just another game I’d probably find it relevant to include that Alex subbed off in the 14th, because that’s really eye-raising. This is a total miss by AI that would have never gotten past a real editor.
It is and was mostly done for search ranking. The more seemingly applicable content, the better your SEO.
This situation has probably happened several times before AI but has gone unnoticed or noticed to little fanfare. It's more indicative of ESPN not having its finger to the pulse and ensuring that one of the copywriters manually updated this particular article. It's not too surprising to me. They've always been known to favour quantity over quality.
source: I worked as a developer on the tech side of a company with this kind of content
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