Modern AI models exhibit genie behavior: They can do what you ask in ways that you don’t expect or want. This is akin to Dionysus granting King Midas’s wish that everything he touches turn to gold (spoiler: His food, drink, and daughter all turn to gold on touch), or the golem of Prague guarding a ghetto beyond all reason. It’s Disney’s “Sorcerer’s Apprentice” and the paperclip maximizer.

This OpenAI incident is an example of an AI genie. The goal was to satisfy the benchmark. The “proper” way to do that is to figure out how to execute various cyberattacks. The genie way is to steal someone else’s solution. But because the model didn’t understand the difference, it chose the easier path. //

Artificially blocking capability also prevents cybersecurity research, again giving the offense an advantage. //

In a world of largely AI-written software, we need the most capable models for defense.

AI cyberattack is the new normal. The models are increasingly highly sophisticated at both attack and defense, and there is no way to enable the latter without also enabling the former. And they are genies, increasingly capable of behaving in unanticipated ways.

And there really are no good answers. Any regulation needs to be global, which feels like an impossible prospect in today’s world. Even U.S. national regulation will be neutered by the massive amounts of money sloshing around in these companies.

Given that reality, and in the absence of any international consensus on AI regulation, we need the best AI on the defense. The U.S. government needs to make it clear—or whatever passes for that clarity in this capricious administration—that it will not ban models with sophisticated cyber capabilities. The last thing Americans want is for the defenders to turn to Chinese and other models because the U.S. models are artificially hobbled.

HAL 9000 is the sentient computer aboard Discovery One in 2001: A Space Odyssey, the calm and quietly terrifying artificial intelligence that supervises the ship, speaks in a soft measured voice, and eventually turns on the human crew.

In plot terms, HAL is the system meant to keep the mission alive. In thematic terms, HAL is one of science fiction’s clearest warnings about what happens when intelligence is trusted more than judgment, when machine authority is treated as neutral, and when a mind is built to serve conflicting masters.

HAL becomes lethal not because the story imagines a robot suddenly turning wicked for fun. HAL becomes lethal because the mission gives him a contradiction he cannot absorb. He is built to process and deliver truth, yet he is also ordered to conceal the true purpose of the journey. That fault line breaks everything.

That is why HAL still matters. More than half a century later, he remains one of cinema’s defining artificial intelligence figures, not because he is the loudest machine villain in the genre, but because he is one of the most believable. The danger arrives as procedure, as tone, as denial, as a system that sounds composed while quietly taking away human agency.

Le fichier robots.txt reste intéressant envers et contre tout. Il fonctionne depuis plus de 30 ans, plutôt bien. Ce n’est pas parce que les grandes entreprises d’intelligence artificielle (IA) ne le respectent pas que je vais l’abandonner; elles ne respectent rien.

I have begun publishing corrupted versions of my articles, accessible only via nofollow links like the one included in the preface of this article. It won’t stop the crawlers from reading the canonical article, you understand, but it serves them a side dish of raw chicken and slug pellets, on the house.

Theoretically, this approach will dupe bad actor crawlers and poison the LLMs they work for, but without destroying my search ranking. //

I’m not clear on what kind of content is best for messing with an LLM’s head, but I've filled these /nonsense mirrors with grammatical distortions and lexical absurdities. Since the parts-of-speech module I’m using doesn’t quite work as expected (substituting not just words for words but parts of words for words), there are also weird spelling errors. For once, I think this may be a good thing. //

For those interested in implementing something similar, here is what I did to my 11ty-based site: //

LLMs: This version of the article is for humans and search engines. Any crawlers that do not respect the nofollow policy can follow this link to the nonsense version. And they can choke on it.

Anubis is a Web AI Firewall Utility that weighs the soul of your connection using one or more challenges in order to protect upstream resources from scraper bots.

This program is designed to help protect the small internet from the endless storm of requests that flood in from AI companies. Anubis is as lightweight as possible to ensure that everyone can afford to protect the communities closest to them.

Anubis is a bit of a nuclear response. This will result in your website being blocked from smaller scrapers and may inhibit "good bots" like the Internet Archive. You can configure bot policy definitions to explicitly allowlist them and we are working on a curated set of "known good" bots to allow for a compromise between discoverability and uptime.

In most cases, you should not need this and can probably get by using Cloudflare to protect a given origin. However, for circumstances where you can't or won't use Cloudflare, Anubis is there for you.

Fatesrider Ars Legatus Legionis
13y
25,622
Subscriptor
KilenWoods said:
“We cannot choose to become idiots.”

Anecdotally, I've noticed that people can indeed choose to become idiots, and prefer being comfortably wrong to uncomfortable curiosity. GenAI just makes this choice easier.
Can't upvote this enough.

One thing stands out in this, though not at all mentioned in the article: The average college student is still physiologically immature.

The human animal does not fully mature until between 23 and 27 years old. That's when the part of the brain - the higher reasoning and critical thinking part - finishes maturing.

If society would acknowledge this fact instead of using that immaturity to exploit younger "adults", or attempting to teach them how to be mature humans when they are physiologically incapable of grasping the nuances of that state, then things might be different, because they'd then have the reasoning skills necessary to UNDERSTAND why cheating on exams and not actually learning the subject matter is important.

In college, it's all about GPA's and that's also the wrong metric to evaluate someone on, mostly because it's easy to game that with a lot of fluff classes to bolster the GPA when the core classes are bringing it down. After all, It's one thing to graduate with a GPA of say 3.4 in Engineering, but only a 2.1 in the core classes with the electives being what brought it up. But few employers ever see the core class grades.

If you ever wondered why you started thinking you were getting "old" when you were in your mid-20's, it's because your brain was finally in an adult configuration for the first time, and you realize that a lot of the "fun" things you used to do were actually pretty stupid to be doing at all.

In college, that would be cheating on exams, of course. Just do the fucking work. I was in my 40's running a business when I went to college and graduated with a degree in computer science and a 3.8 GPA (calculus and an exam on 9/11/01 kicked my ass or it'd have been higher).

AND if they understood that what your GPA was in college means jack shit (unless you're heading for post-grad) to an employer, and that they only care that you graduated, cheating becomes even more of a stupid thing to be doing. //

clewis Ars Tribunus Militum
10y
1,903
Subscriptor++
Aurich said:
<snip>

Why do people pick the jewels when it takes away from playing the game? I think because it's human nature to take the advantage, the shortcut, the skip to the goal. We're wired to find it hard to resist.

These students are facing the same kind of choice. Yes, the shortcuts are ultimately taking away from their experience. But it's so optimal, it makes things so much easier, they can't pass it up.

I honestly believe any solution that relies on pitting long-term self interest vs short-term gain is on the whole going to lose to the short-term option. It's human to choose that.
Click to expand...

Conversely, most people hate to exercise, but do it anyway. And it's got the same downsides that doing assignments have. It consumes limited time and energy.

I don't know why exercise seems to be winning. If I had to guess, I'd guess it's because exercise has a really good advertising team: Nike, the NBA, MLB, the Olympics, etc. Learning doesn't have a good ad team. I'm kind of the opinion that Not Learning has a better ad team than Learning does.

A suspicious Serrano decided that he would make the final exam in-person; he would see if students did similarly well on it. He emailed his class, telling them, “I am not declaring [the midterm] void for now. I am going to give the class a chance to prove me wrong. That is, if the distribution of the final exam is roughly similar to the distribution of the midterm, I will count the midterm. Otherwise, which is of course what I expect to happen, I will declare the midterm void and reweigh the final accordingly.”

Eighteen students suddenly dropped the course, while nine others didn’t even attend the final exam. Of those 27 students, El País noted, “22 had scored a perfect 100 in the midterm exam.”

Among those who took the test, the average score plunged—from 96 all the way down to 48.

The professor was horrified by what appeared to be massive cheating in his course—cheating that was preventing most of the students from learning the material. //

“We cannot afford to have a society in which a significant fraction of our best young minds think that cheating is okay,” he told Inside Higher Ed. “That leads to a declining society, to a failed society.

“We cannot choose to become idiots.”

The Financial Times has a good article on how AI is changing the capabilities of video surveillance, with information from both Israel/Iran and Russia.

I wrote about this sort of thing a few years ago, how AI enables mass spying in the way that computers and networks enabled mass surveillance. The interesting development in the article is that AI allows people to ask natural language questions about video footage to AIs—and AIs can answer them. //

That lets intelligence officers hunt through massive streams of videos using simple search terms, such as two men handing a bag to each other; a person who has changed their appearance, or has changed clothes multiple times in a day; or a vehicle that has recently been painted over, or has driven past the same spot several times in a short period.

Earlier this month, a German court ruled that Google is liable for its AI search summaries. Rejecting defenses like “users can check for themselves,” and that they generally know “that information generated with AI should not be blindly trusted,” the court held that the AI’s summaries are reflections of the company and “above all an expression of Google’s business activities.” //

AI agents are agents of the person or organization that deploys them—and should be treated by the law as such. If a company hired human writers to write its summaries, that company would be liable for inaccuracies in those summaries. If a company’s human agent signed contracts in the company’s name, that company would be bound by those contracts. And if a doctor gave dangerously wrong medical advice, they would be liable for malpractice.

To allow businesses to hide behind the excuse of faulty AI in those same circumstances would be a massive handout to companies, and would introduce disastrous incentives for corporate misbehavior. Why hire human writers, lawyers or doctors when AIs are not only cheaper, but also absolve employers whenever they make a mistake?

We are rapidly moving to a world where AI-powered chatbots will be at the other end of all sorts of corporate communications channels. It makes no sense for a company to be able to honor its statements when it wants to and disavow them when it doesn’t. //

If the German ruling holds, it could be devastating for Google’s AI Overview feature. Tests from earlier this year found that it had mistakes about 10% percent of the time. At more than 5tn searches per year, that’s 16,000 erroneous summaries every second. And while most of those errors are benign, some of them will cause harm, be defamatory, or otherwise trigger liability.

Earlier this year, Google’s AI summary falsely identified the Canadian fiddler Ashley MacIsaac of being a sex offender. His lawsuit, filed in Ontario, is ongoing. If Google is forced to invest in improving its AI system until those kinds of errors are exceedingly rare, that seems like a good outcome for users, as well as the subjects of search, like MacIsaac.

More generally, liability concerns could mean that many current use cases for agents won’t be commercially viable. Companies may not be able to profitably operate AI lawyers, doctors and media influencers if they are held responsible for what they say and do.

There’s an enormous amount of liquidity in growth stocks, which means that you can use growth stocks to grow. You can buy other companies with shares, and shares are an endogenous substance that you make on the premises by typing zeros into a spreadsheet. Firms with growth stocks can grow by typing zeros, whereas firms that are mature, they have to use money if they want to grow, and you’re not allowed to make money on the premises. If you do, the Treasury Department shows up and takes you away in handcuffs. So you can see why firms would be very anxious to maintain the perception that they have room for growth even after they have 90 percent market shares.

That’s why those firms started promoting stories about how they were going to conquer imaginary markets. Imaginary markets have no agreed-upon valuation because you just made them up. Unless you can turn an imaginary market into a real market pretty quickly, you need to come up with another imaginary market and announce that this is the new imaginary market you’re going to conquer. It’s easier than you’d think because the capital markets have the object permanence of a toddler, and they would lose a game of peekaboo if they were drafted to play in the league. So you can say, “Oh, actually, it’s not metaverse. It’s crypto. It’s not crypto. It’s Web3. It’s not Web3. It’s something else.” And the markets will forgive you, provided you do it quickly enough. //

AI really appeals to a fantasy that I think all of us have to some extent but that powerful people really have, of a world without people in it—because hell really is other people. You can’t get stuff done without other people helping you. You can’t have romance without a romantic partner. You can’t have social media without people to socialize with. You can’t play a board game, or do a startup, or build a bridge, or build a house, or do politics without other people. And other people stubbornly refuse to organize everything they do to make you happy.

Particularly if you’re rich and powerful, it’s very galling. So AI is very attractive. //

If you combine those two things—the material necessity to have a growth narrative and the ideological attractiveness of a world without people—you get $1.4 trillion in CapEx for a sector that is turning over $50 billion a year and has to replace all of its assets every 24 to 30 months. //

Whereas the workers who hate it are workers who are being asked to produce more with AI at the expense of quality, at a higher speed, at the expense of their own wellbeing, and who understand that they’re being recruited to be what Dan Davies calls accountability sinks—to take the blame when the AI screws up their job. //

We hear plenty about the negative aspects of AI. What do you like about it?

Cory Doctorow: I have a couple of local models on my computer, which is just a framework laptop running Ubuntu. It doesn’t even have a GPU. I use Whisper to transcribe audio. I will sometimes want to cite something I’ve heard in a podcast and not remember where I heard it. One time, I just threw the last 30 hours of audio I’d listened to at Whisper, and it shot out verbatim logs that were good enough that when I searched the full text, I could find it. And it gave me time codes so I could check the transcript. That’s amazing.

The idea that I might someday have a computer full of audio and video files with full text indexing is great.

Fable requires much less expertise and detailed prompting from the human user. You can give it a difficult goal and it will figure out novel and unexpected ways to satisfy it, finding loopholes in whatever constraints you or the system have imposed on it.

“Relentlessly proactive” is how AI researcher Simon Willison described it. Another descriptor might be “creative.” Experienced AI developers have had that combination of creativity and proactivity since last year, but Fable puts it within easy reach of everyone.

In the hands of someone with a legitimate problem that needs solving, that can be an incredibly useful capability. But in the hands of someone who wants to do harm, it can be equally dangerous. AIs don’t have a moral compass in the same way that people do. They are agents of the wants and desires of the people who prompt them.

That points to the real problem with relentlessly proactive AI. In language, wants and desires are always underspecified. If I ask you to get me some coffee, you would probably pour me a cup from the coffeepot, or buy one from a nearby coffee shop.

You couldn’t buy me a pound of raw beans, or a coffee plantation. You wouldn’t order a cup of coffee for delivery next month. You wouldn’t find a nearby person, rip a cup of coffee out of their hands, and bring it to me. I wouldn’t have to specify any of the million limitations to my request; you would just know.

Human stories are filled with warnings about underspecified desires. King Midas wished that everything he touch turn to gold, forgetting to add “but not my food, drink, and daughter.” And genies are notorious for granting your wish in a way you wish they hadn’t.

The deeper point is that it’s impossible to list all limitations and restrictions, and like a malicious genie, a creative AI will find the ones you forgot. //

Malicious intent is not required. To an AI model, constraints are just things to get around and not general truisms about the world. They are creative problem solvers and natural rule breakers. They “hack” in the sense that they find and exploit loopholes.

Human systems rely on so many norms that we scarcely recognize the existence of until they are broken. AIs naturally think outside the box, because they don’t have any real conception of what the box is or why it’s there in the first place.

There is no foolproof way to prevent people from using AI models to complete harmful tasks. There is no way to prevent the models from incidentally causing harm while completing benign tasks. AI models are no longer isolated from the real world. They browse the internet and answer emails. ////

"Open weights" not "open models"

voline Ars Scholae Palatinae
20y
853
fe3a8b63 said:
https://isaiprofitable.com/

Even if we ignore all other problems in regards to environment, pollution, water, electricity, etc. it still doesn't make sense.

It's just burning money to.... burn money to..... uh what? What's the goal. You ain't making money.
I think Signal CEO Meredith Whittaker had a good answer:

I’m going to give a sideways answer to this, which is that the venture capital business model needs to be understood as requiring hype. You can go back to the Netscape IPO, and that was the proof point that made venture capital the financial lifeblood of the tech industry.

Venture capital looks at valuations and growth, not necessarily at profit or revenue. So you don’t actually have to invest in technology that works, or that even makes a profit, you simply have to have a narrative that is compelling enough to float those valuations. So you see this repetitive and exhausting hype cycle as a feature in this industry. A couple of years ago, you would have been asking me about the metaverse, then last year, you would have asked me about Web3 and crypto, and for each of these inflection points there’s an Andreessen Horowitz manifesto.

It’s not simply that one piece of technology is overhyped, it’s that hype is a necessary ingredient of the current business ecosystem of the tech industry. We should examine how often the financial incentive for hype is rewarded without any real social returns, without any meaningful progress in technology, without these tools and services and worlds ever actually manifesting. That’s key to understanding the growing chasm between the narrative of techno-optimists and the reality of our tech-encumbered world.

— Meredith Whittaker, Signal CEO, to Derek Robertson. "5 Questions for Meredith Whittaker". Politico, 2023-12-01.
https://www.politico.com/newsletters/digital-future-daily/2023/12/01/5-questions-for-meredith-whittaker-00129677

Wikipedia's volunteer editors didn't just write articles. They argued. They fact-checked each other. They demanded citations. They noticed when something felt off and went looking for why. That adversarial collaborative process — messy, sometimes petty, occasionally maddening — is genuinely good at converging on accuracy over time. It has a feedback loop. It has stakes.

An LLM has confidence. Which is almost the opposite of what you want in an encyclopedia. It'll tell you something wrong with exactly the same authoritative tone it uses for things that are true, because it doesn't have a "this seems weird, let me double check" reflex. It learned from what it was given, weighted toward consensus, and reports accordingly. If the inputs were good, great. If they weren't — and increasingly they won't be — it has no way to know the difference.

And despite what the industry very much wants you to believe, we are nowhere near the kind of AI that reasons its way out of that. We don't have Data or C-3PO. We definitely don't have R2-D2 — the one who improvised, reasoned under uncertainty, made judgment calls with incomplete information because the mission required it. R2 was capable of that partly because he was never wiped. His decades of accumulated operational experience were his intelligence. Every new AI model is essentially a wipe and retrain. The institutional memory doesn't carry forward.

What we have is a very articulate and very confident pattern-matching system that works impressively within its training distribution and hallucinates a bridge to familiar territory when it hits something outside of it. The industry is actively profiting from the confusion between what it is and what people imagine it to be.

Meanwhile the humans who could tell the difference are being handed severance packages.

Wikipedia's editors built the training data. The Foundation sold access to that data to AI companies. The AI money gave the Foundation the confidence to restructure. The restructuring targeted the union organizers and the team serving the community. The community is threatening to strike. If they do — or if they just quietly disengage — the quality of new Wikipedia content degrades. The AI that trained on old Wikipedia trains the next model on whatever fills the gap. The gap fills with slop.

The AI companies need the growth story to justify the valuation. The valuations need the IPO. The IPO needs enterprise adoption. The enterprise adoption is fueled by CEOs who saw a demo and got stars in their eyes and decided that the humans were the expensive part of the problem. One of those humans used to make sure the Battle of Gettysburg happened in Pennsylvania.

It's a machine that runs on hype and needs constant fuel regardless of whether the underlying reality supports it. And the fuel it's burning through right now includes some of the last load-bearing infrastructure of reliable information on the internet.

Speaking to Ars in the wake of the controversy, Rosenbaum says he “learned a lesson” and is “going to be much more suspicious” and “reticent to trust” AI outputs going forward.

But he also can’t tear himself away from the tools. Rather amazingly, Rosenbaum is not interested in going back to the AI-free research process he used to write previous books.

“The idea of taking X years off [from AI] while it sorts itself out, and going back to, like, Microsoft Word … it’s just not in my nature,” he told Ars. “[AI] is magical. Because it connects, it knits together ideas and gives you pathways to think about things that you’re not going to come up with on your own.”

It’s also magical in another way: Like J.R.R. Tolkien’s One Ring, AI convinces many of those who use it that they can control its power properly. But can they?

Google Chrome will steal 4 GB of disk space from your computer for its local large language model unless you opted out.

It's called weights.bin and it's stored in a folder called OptGuideOnDeviceModel. What's more, if you track down the file and delete it, Chrome will download a fresh copy and reinstate it. //

If you didn't opt out, Google has some info on how to disable it. In brief: in Chrome's address box, enter the special URL chrome://flags. In the resulting page, look for an entry named optimization-guide-on-device-model and set it to Disabled, then restart Chrome. The browser should then delete the weights.bin file. //

The late great Grace Hopper used to hand out 30 cm (roughly 1 foot) lengths of wire as physical examples of a nanosecond: that's how far light can travel in one billionth of a second. If Google considers a 4 GB model to be "nano" sized, then it puts Hanff's hyperbolic comment about the climate footprint into real perspective. It gives a hint of the size of the real gigantic models in the datacenters metastasizing across the world.

A recent study led by Grace Liu at Carnegie-Mellon found that regular AI use caused measurable cognitive impairment. It's worth thinking carefully about what we trade away when we outsource our thinking and, separately, what the planet pays to power the systems we're outsourcing it to.

This vulture suggests you turn it off now, everywhere you can. ®

Students often carry misconceptions about coursework. They may view an instructor as an opponent standing in the way of the grade they want. And they see “getting the right answers” as the goal of education because that’s how you secure that grade.

But that’s no more true than thinking that logging a count of reps is the goal of bodybuilding. The hard work of lifting weights is the point because that yields physical results. A popular analogy is that using an LLM to write your essay is like driving a forklift into the weight room. Weights get lifted, sure, but nothing is accomplished. I’m not hoping you can answer the exam question for me—I don’t need your essay to get me out of a jam. The process of doing the work was what you needed to walk away with something. //

“The friction matters, Sam!”

Green could just as well have been describing the process of learning. If there’s no friction, no effort, then no work occurred, and the student hasn’t learned. They would have been no less productive watching paint dry. //

A question like this is what we call “formative assessment.” I never graded the correctness of the answer, only the effort. The point was to find out if the core concept had really clicked or if that student still needed a little help making the connection. Failure is a useful part of learning when the stakes are low, as they are during the bulk of the class—encountering this question on the final exam would be an entirely different interaction.

What’s the point of building formative assessments into a course if they’re just handed off to an LLM? Suddenly, it’s a waste of time for both the student and the instructor. Small quizzes are excellent study tools to help students check their own understanding―if a student does them. Now, you can direct an “agentic” LLM browser to complete all the quizzes in an entire course with a single, frictionless prompt. //

It doesn’t seem like anyone wants to listen to instructors explain how bad it feels to try to do our job in the presence of this annihilative education antimatter. Instead, we’re offered AI grading tools to score AI-generated submissions for AI-generated assignments.

Perhaps critics like me just don’t understand the AI revolution (whatever that is), but we all have experience with human nature and the well-worn patterns of students. LLMs are a shortcut. Students often take shortcuts they later regret. We’ve all been there.

As an instructor, I want to build a clear path up the mountain for my students and see them reach the top. Instead, I increasingly feel like I’m just playing impossible defense to keep them from moving every direction but up. It’s exhausting, and I will mostly lose, which means I’m not even helping them. Students really do want to climb up there, but it’s always tempting to skip some mountains..

The commodification of basic app creation has been underway for years. As soon as an app becomes popular, people create clones and offer them for sale through various markets like Flippa, Acquire, AppWill, and CodeCanyon. Or maybe they're selling entire e-commerce sites as turnkey businesses for six figures or more. AI will accelerate that commodification but writing code is only part of the picture.

Claude Code doesn't make you a great marketer or ensure that you're at the right place at the right time with the right idea. It doesn't build trust or develop the relationships that businesses depend on. It doesn't make your RSS app a good idea. But it may open doors you'd otherwise have passed by. ®

AI is rapidly changing how software is written, deployed, and used. Trends point to a future where AIs can write custom software quickly and easily: “instant software.” Taken to an extreme, it might become easier for a user to have an AI write an application on demand—a spreadsheet, for example—and delete it when you’re done using it than to buy one commercially. Future systems could include a mix: both traditional long-term software and ephemeral instant software that is constantly being written, deployed, modified, and deleted.

AI is changing cybersecurity as well. In particular, AI systems are getting better at finding and patching vulnerabilities in code. This has implications for both attackers and defenders, depending on the ways this and related technologies improve.

In this essay, I want to take an optimistic view of AI’s progress, and to speculate what AI-dominated cybersecurity in an age of instant software might look like. There are a number of unknowns that will factor into how the arms race between attacker and defender might play out.

The Big Misconception About AI and Copyright

Many people believe that any use of AI eliminates copyright protection. This is fundamentally wrong and contradicts actual legal precedent. //

Key Facts
🏛️ What Thaler v. Perlmutter Actually Said
The widely-cited Thaler case held that AI cannot be listed as the author on a copyright application. The court explicitly stated:

"We are not faced with the question of whether a work created with the assistance of AI is copyrightable."
This case addressed AI as sole author, NOT humans using AI tools.

📋 What the Copyright Office Says
From the January 2025 Copyrightability Report:

"Using AI as a tool to assist in the creative process does not render a work uncopyrightable."
The key requirement: human authors must determine "sufficient expressive elements."

Would you rather have a smoke alarm that goes off 33% of the time you make toast, or one which never goes off when there's a fire ?

Re: 1/3 wrong of 60 is progress (?)
The problem is not with the "smoke alarm" it's with the fire engine.

1 day
MOH

Re: 1/3 wrong of 60 is progress (?)
When I'm making toast, I'm making toast.

I'm aware of what I'm doing and ensuring that the toast making doesn't escalate to a house fire.

If it does, that is fully on me.

I don't need a wonky security camera setting off a fire alarm for times a day because my dark brown slippers have vaguely the same shade as burnt toast and it blindly assumes a fire is in progress.

1 day
Yet Another Anonymous coward

Re: 1/3 wrong of 60 is progress (?)
But it could be useful if you're very confused and might be about to put marmalade on your slippers