One of the great things about modern HTML is that it tries to standardise stuff that developers are already doing. If there are a myriad ways of, for example, loading video onto a page - then browsers and other interested parties should work out how to make a standard <video> element.

An interesting new proposal has been brought forth by Microsoft. There are a dozen ways to show a preview of an <img> element before the src= attribute has loaded. So why not standardise on previewsrc=? There's an excellent explainer on Patrick Brosset's blog.

I instinctively like the idea - if only to simplify source code and reduce JS usage. But I do have some concerns which I've shared with the team.

What's The User Need?

This is the thing I always bang on about when I'm discussing standards. Additions to HTML should primarily benefit end users, not developers.

Do end users want this? Is there a bunch of research that shows normal people are confused that they don't see a preview image? Do they recoil in fear and distress while waiting for a full resolution picture to appear?

When people see a blurry or blocky image, do they understand that they need to wait for the full thing - or do they assume their computer is broken?

Microsoft has a bazillion dollars - it can afford to spend a few thousand on interviewing some real users and mapping out what they're likely to want from this.

What's The Developer Need

I begrudgingly admit that developers need love too.

What are the pain points of the current implementations? Is it hard to dynamically generate multiple images? Is the syntax hard to use? Do blurs slow down the page?

Again, MS needs to pony up some cash to talk to developers. At the very least run a survey of all existing websites in the BING! database and see what they use.

Alt Text

When an image doesn't load, or loads slowly, a user will normally be shown some alt text - like this:

Is that more or less useful than this?

Accessibility isn't just for people with visual impairments! This is an issue I've raised with them.

Naming Things Is Hard

I've written before about the usability of HTML elements. Some of the newer ones like <picture> have very poorly named attributes in my opinion.

One alternative for previewsrc is poster. That would match with the poster attribute on the <video> element. They both show a preview image before the main content is loaded.

Given their functionality is identical, I think it makes sense for them to have the same name. You wouldn't expect to see <video horizontal="1920" vertical="1080"> would you? No. That's why they use the same width and height attributes as images.

Closing Remarks

There are several interesting objections and discussions on the GitHub repo. I'm delighted that this is being talked about in the open, rather than just being presented as a fait accompli (remember the toast proposal?).

As I said, I genuinely think that there's a useful idea in here. But after writing all of this, I think it would be better and simpler for developers to use progressive images rather than overload HTML with a new attribute.

If website owners can't be bothered to save progressive images, I don't see why they'd bother to create a separate preview image.

Keeping preview images in sync with their full images is also likely to be a problem.

If you think I'm wrong, read the explainer and then chat with Microsoft.

Hey, you know it's like super obvious if you're using AI to write your scripts for TikTok and YouTube, right? [...] It's not just the general AI-isms of "it's not X, it's Y", or the rule of three, or the really weird broken staccato-like way of writing where you just say a lot of things with all these punctuation marks. and it sounds really deep, but it's not.

It's the lack of anything. It's the lack of a definitive sort of spear of your voice. It's the fact I can tell you don't have opinions about the thing that you're talking about.

— @therealcornpop, on TikTok

Tags: tiktok, ai, ai-misuse

OpenAI has an army of contractors who read real ChatGPT users’ prompts and other data to help improve the chatbot’s responses. The idea is that the contractors provide an, obviously, human touch to OpenAI’s models. Well, not all of the contractors are doing that. 404 Media has found multiple contractors hired to improve OpenAI’s models have been fired for using AI to train the AI. That’s not great for the models themselves, but there is also obviously a great irony in AI training companies working for OpenAI firing people for using AI when OpenAI’s whole thing is to make people use AI at work.

Some AI models already exhibit signs of “model collapse,” which is where AI models further trained on AI-generated text can become worse and worse. In this case, some of the people hired to partially stop that happening are themselves using AI-generated responses to train OpenAI’s models.

One contractor said they see people using AI “all the time and people are let go for it all the time, it’s pretty much the one thing that will get you kicked off ASAP.” The person said, “in a group of thousands there are tons that have been caught.” 

Last week, 404 Media revealed Project Lily, in which OpenAI has hundreds of contractors reading real ChatGPT users’ prompts and conversations which can include personal information. Those contractors then rate and critique the responses ChatGPT generated, including making sure that the responses are not too sycophantic or anthropomorphize ChatGPT. That reporting was based on internal documents and conversations with a person who works on the prompts. 

404 Media has now obtained other internal documents and spoken to three contractors doing work for OpenAI across various projects. Those projects can include more than ten thousand contractors, according to one of the internal documents.

One of those documents says contractors must not use AI themselves for their work. 

“Do not use AI detection tools, or AI yourself,” one document describing the work of contractors who are hired to review the work of other contractors, including catching them for using AI, says. “Do not use GPTZero or any other AI detection tool. They are not reliable. Reviewers may not use AI either, including Grammarly and AI translation, to review, write feedback, or write comments.”

The document continues, “Do not tell evaluators why you suspect AI. It is easier for them to hide if they know what you look for. Judge the overall pattern, not one clue.”

All three of the contractors said reviewers are told not to use AI in their work. Two of the sources said people have been fired or offboarded for using AI. 404 Media granted the contractors anonymity as they weren’t permitted to speak to the press.

The contractors who review other contractors’ work are told to be on the look out for tell-tale signs of AI use. That can include repetitive words, AI-style punctuation — which might include over zealous use of the em dash — and contractors finishing their work very quickly.

In related Slack channels where people ask each other for advice, a lot of people will post an example with the question, ‘Is this AI?,’ one contractor said.

“Usually the answer is yes,” the person said.

One contractor said they used AI while helping to train OpenAI’s models and shared what they presented as their termination letter. It said their employer had identified issues with the “authenticity” of their work. 

“I’m not a bad person or worker. I just needed a little boost and turned to AI to help me which eventually led to my downfall,” the contractor told 404 Media. “I felt no joy in the work or that I was contributing to society in any way.”

Two of the contractors 404 Media spoke to worked for Mercor, an AI-training company that hires the contractors who in turn review ChatGPT-related material. A Mercor spokesperson told 404 Media in a statement: “Our experts are hired for their expertise and judgement, which is essential to the ongoing advancement of AI. Our contracts strictly prohibit the use of LLMs to complete projects and we enforce that. We invest heavily in our tools and systems to detect misuse and ensure our experts comply with project rules and contract terms. When we confirm an expert has used AI to complete a task, we immediately remove them from the project.”

404 Media spoke to a fourth contractor who has worked on training models for various AI companies. They said they sometimes purposefully chose the worst responses because they wanted to actively sabotage the models’ training. 

“I did feel guilty about doing this kind of work at the start,” they said. “I either pay zero attention to the results and choose randomly or purposely choose the [worst] output. I’m not sure  how much of a difference it actually makes since there are hundreds of other people also rating prompt results, but it does feel like I’m getting paid to make AI worse.”

OpenAI declined to comment on its contractors being fired for using AI.

I was trained in giving the DIBELS assessments a few weeks ago along with the other new teachers. The training was run by a consultant from my district’s curriculum company. These assessments mostly involve listening to students read and coding the results to see if their reading is at benchmark. We talked about each assessment, practiced, and poked through the website. One is a comprehension assessment, called MAZE, that wasn’t included in the training. The trainer told us the assessment is online, so we assign it to students, students log in, take it, and that’s it.

I asked if there was a paper and pencil option. The trainer seemed taken aback. Well, there is...but why would you want to do that? I realize I have this reputation now as an anti-technology guy but I’m new and I didn’t want this to be my hill to die on so I let it go and we moved on.

Fast forward: we give the assessments. Afterward I was meeting with the other 5th grade teachers, and we had all observed the same thing: a lot of students guessing on the online MAZE assessment, not taking it very seriously. It wasn’t everyone, but it was enough to be concerning. We agreed that we would give the paper version a shot for our next round of testing.

This is a common story in many schools right now. The details vary, but there are two main parts:

• The assumption that we need to give students lots of tests, and that many of those tests should be digital. Digital is assumed to be necessary and rarely questioned.

• At the same time, many teachers are observing students guessing and giving up more quickly than before, trying to get the test over with as fast as possible.

Mode Effects

Here’s an interesting fact that I think should be more widely known. Lots of tests have gone online in the last few years. During that process, folks who write these tests did lots of experimenting to understand what that transition meant. One of the things they learned is what they call a “mode effect,” which is a fancy way of saying that kids do worse on digital tests.

Imagine the exact same test. One on paper, one digital. On average, students will do slightly worse on the digital version. So test makers correct for this: cut scores are a bit lower on the digital version to compensate. That’s kindof wild to me.

What I’m observing is that students’ relationship with technology is changing. More and more of our students grew up with phones or tablets close at hand much of the time. More and more of our students have been taking these tests for years.

The students who guess aren’t a random sample across the class. They are most likely to be students who are lower-achieving, who find the content hard to begin with. And sure, some of those students will guess on paper as well. But there’s something about screens that reduces the friction to guessing, that brings in the habits students develop playing video games or fiddling with apps, swiping on to the next thing.

The Testing Era

We are in the testing era of education in the United States. Students take state tests at the end of the year in most grades, and then they take more tests to figure out if they’re on track for the state test, and then there are more tests to progress monitor in between those tests. All these tests aren’t neutral. Students are building habits, and for more and more students all the tests seem silly so they build a habit of guessing their way through.

I’ve spent some time digging through the materials and I’m honestly pretty impressed with what the major testing organizations are doing. Here’s TIMSS accounting for mode effects, and PISA comparing student effort between countries — no surprise, student effort has decreased over time. Everyone wants to run lots of regressions to see if digital test results are valid.

Meanwhile, I’m watching students taking test after test, treating tests like a video game to get through as fast as possible. I mentioned student guessing on MAZE but not on the NWEA MAP assessment. MAP has a “rapid guessing” detector: if a student is answering questions too quickly, the test pauses. I check in with the student, remind them to take their time, and restart their test. Students figure this out. And what they learn is not that they should try their best. They learn that they need to guess slowly. Guess. Pause. Stare into space for a minute. Guess again. Repeat.

I don’t think switching to paper and pencil will magically solve all of education’s problems. Teaching will still be hard. Low-performing students won’t magically skyrocket because they took a test on paper. Some students will still guess. Others have built a habit of guessing on computers and they’ll just keep guessing on paper. It will be a bit more work for teachers, though we should get rid of some of these tests while we’re at it to help with workload. My concern is less about the validity of the data. Data is valuable, but teachers today are flooded with data and we will be fine with a bit less. My concern is what we’re training students for. Students should come to school to learn. Students should not come to school to practice gaming tests they don’t care about.

Here’s what I’m imagining: fewer tests, with each test linked to clear outcomes and next steps for teachers based on the data. Tests that we do give are largely given with paper and pencil to improve effort and accuracy. Less pressure on districts to buy and maintain fleets of technology. I have a cart of Chromebooks on the side of my room. They mostly sit there, unused. Which feels like a bit of a waste. But when testing week comes around, it’s tough to imagine making do without a cart for every classroom. I don’t blame my district for investing in all this technology. But seriously, it’s 2026. AI is solving million-dollar math problems. We can figure out efficient ways to assess students with paper and pencil.

After two devoted gray fox parents and their six kits moved into our backyard, we became obsessed with watching them grow, play, learn, and finally, move on