#artificial intelligence curriculum

[dyanamic]

Starting 2026, UAE schools will integrate AI education into the national curriculum, preparing students for a tech-driven future. Learn more about this groundbreaking initiative.

[angryonabus]

As a teacher, this is the thing I come back to again and again. I am not doing this job because I am on some god-given quest to find The Best Ever Essay; I am doing this job because I am on a (self-given) quest to turn my students into People Who Can Write A Pretty Decent Essay, or at least People Who Can Write A Better Essay Than They Could Have Written This Time Last Year.

When students use ChatGPT or similar generative garbage, they are thwarting my quest in two ways. As mentioned above, they're not doing the mental work that will allow them to practice the skills I'm trying to teach, and no practice means no improvement. Sure, the final product might look shiny and nice — although because generative AI isn't actually intelligent and can't actually think, it quite often doesn't, but that's a whole other post — but my students haven't engaged in the kind of productive struggle that OP & others have mentioned, meaning that they haven't actually learned anything.

AND ALSO: As a teacher, the point of assigning work is to see how students are engaging with the content, not just to give them a grade but so that I can see where they're need more support or more challenge. If you give me an essay that ChatGPT wrote, I don't know what you can do, which makes it impossible for me to help you in any meaningful way (beyond saying, "kid, stop using ChatGPT").

School is about learning, and learning requires that you use your brain. Stop trying to outsource the process.

Something I don't think we talk enough about in discussions surrounding AI is the loss of perseverance.

I have a friend who works in education and he told me about how he was working with a small group of HS students to develop a new school sports chant. This was a very daunting task for the group, in large part because many had learning disabilities related to reading and writing, so coming up with a catchy, hard-hitting, probably rhyming, poetry-esque piece of collaborative writing felt like something outside of their skill range. But it wasn't! I knew that, he knew that, and he worked damn hard to convince the kids of that too. Even if the end result was terrible (by someone else's standards), we knew they had it in them to complete the piece and feel super proud of their creation.

Fast-forward a few days and he reports back that yes they have a chant now... but it's 99% AI. It was made by Chat-GPT. Once the kids realized they could just ask the bot to do the hard thing for them - and do it "better" than they (supposedly) ever could - that's the only route they were willing to take. It was either use Chat-GPT or don't do it at all. And I was just so devastated to hear this because Jesus Christ, struggling is important. Of course most 14-18 year olds aren't going to see the merit of that, let alone understand why that process (attempting something new and challenging) is more valuable than the end result (a "good" chant), but as adults we all have a responsibility to coach them through that messy process. Except that's become damn near impossible with an Instantly Do The Thing app in everyone's pocket. Yes, AI is fucking awful because of plagiarism and misinformation and the environmental impact, but it's also keeping people - particularly young people - from developing perseverance. It's not just important that you learn to write your own stuff because of intellectual agency, but because writing is hard and it's crucial that you learn how to persevere through doing hard things.

Write a shitty poem. Write an essay where half the textual 'evidence' doesn't track. Write an awkward as fuck email with an equally embarrassing typo. Every time you do you're not just developing that particular skill, you're also learning that you did something badly and the world didn't end. You can get through things! You can get through challenging things! Not everything in life has to be perfect but you know what? You'll only improve at the challenging stuff if you do a whole lot of it badly first. The ability to say, "I didn't think I could do that but I did it anyway. It's not great, but I did it," is SO IMPORTANT for developing confidence across the board, not just in these specific tasks.

Idk I'm just really worried about kids having to grow up in a world where (for a variety of reasons beyond just AI) they're not given the chance to struggle through new and challenging things like we used to.

[compassionmattersmost]

Planting Seeds of Compassion in a Digital Age

A Classroom Kit for Teaching AI + SEL with Heart As artificial intelligence becomes a bigger part of our lives, a new question is blooming in the minds of educators: How can we help children not only use AI—but relate to it with empathy, wisdom, and kindness? This class material offers one answer: a vibrant, age-appropriate toolkit for K–5 learners that blends AI literacy, ethics, and…

[classroomlearning]

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[mkcecollege]

At M.Kumarasamy College of Engineering (MKCE), we emphasize the significance of engineering ethics in shaping responsible engineers. Engineering ethics guide decision-making, foster professionalism, and ensure societal welfare. Our curriculum integrates these principles, teaching students to consider the long-term impacts of their work. Students are trained in truthfulness, transparency, and ethical communication, while also prioritizing public safety and environmental sustainability. We focus on risk management and encourage innovation in sustainable technologies. Our programs also address contemporary challenges like artificial intelligence and cybersecurity, preparing students to tackle these with ethical responsibility. MKCE nurtures future engineers who lead with integrity and contribute to society’s well-being.

To know more : https://mkce.ac.in/blog/engineering-ethics-and-navigating-the-challenges-of-modern-technologies/

[cleveredlearning]

Clevered: Artificial Intelligence Lab for Schools and the Implications of NEP 2020

In the ever-evolving landscape of education, the integration of Artificial Intelligence (AI) has emerged as a transformative force, offering boundless opportunities for learning and innovation. With the advent of the National Education Policy (NEP) 2020, India has taken significant strides towards embracing AI in education, recognizing its potential to equip students with the skills needed for the future. In this context, the establishment of AI Coding Labs in schools stands as a pivotal initiative, poised to shape the next generation of thinkers, problem-solvers, and creators.

Understanding the Significance of AI Coding Labs:

AI Coding Labs serve as dynamic spaces where students are introduced to the fundamentals of AI and coding from an early age. These labs provide hands-on experience, fostering a deep understanding of AI technologies such as machine learning, neural networks, and natural language processing. By engaging in real-world projects and challenges, students develop critical thinking, computational thinking, and problem-solving skills essential for success in the digital age.

NEP 2020 and the Paradigm Shift in Education:

The National Education Policy (NEP) 2020 marks a paradigm shift in the Indian education system, emphasizing holistic development, flexibility, and the integration of technology. With its focus on skill-based learning and experiential education, NEP 2020 aligns seamlessly with the objectives of AI Coding Labs, providing a framework for their implementation across schools nationwide.

Key Objectives of AI Coding Labs:

Promoting Digital Literacy: AI Coding Labs play a crucial role in promoting digital literacy by familiarizing students with AI technologies and programming languages. Through hands-on activities and projects, students develop fluency in coding, enabling them to navigate the digital landscape with confidence.

Fostering Innovation: By encouraging experimentation and exploration, AI Coding Labs foster a culture of innovation among students. Through collaborative projects, students learn to apply AI concepts creatively, developing solutions to real-world problems and contributing to technological advancement.

Building Critical Skills: AI Coding Labs focus on nurturing critical skills such as problem-solving, analytical thinking, and creativity. Through interactive learning experiences, students learn to approach challenges methodically, fostering resilience and adaptability in the face of change.

Preparing for the Future: In a world increasingly shaped by AI and automation, AI Coding Labs prepare students for the jobs of tomorrow. By equipping them with in-demand skills such as coding, data analysis, and AI proficiency, these labs empower students to thrive in the digital economy.

Integrating AI Coding Labs into the Curriculum:

The successful implementation of AI Coding Labs requires a strategic approach that integrates them seamlessly into the existing curriculum. Schools must allocate dedicated resources for the establishment and maintenance of these labs, including trained educators, infrastructure, and software tools. Furthermore, collaboration with industry partners and experts can enrich the learning experience, providing students with insights into real-world applications of AI.

Impact of AI Coding Labs on Students:

The impact of AI Coding Labs extends far beyond the acquisition of technical skills. By nurturing curiosity, creativity, and collaboration, these labs cultivate a growth mindset among students, empowering them to embrace lifelong learning and adaptability. Moreover, by fostering diversity and inclusivity, AI Coding Labs ensure that all students have equal access to opportunities in the field of AI, regardless of their background or socioeconomic status.

Conclusion:

In conclusion, the establishment of Artificial Intelligence Lab for Schools represents a significant step towards realizing the vision of NEP 2020 and preparing students for the challenges and opportunities of the future. By equipping students with the skills, knowledge, and mindset needed to thrive in a digital world, AI Coding Labs empower them to become active contributors to society and drivers of technological innovation. As we embark on this transformative journey, let us embrace the potential of AI in education and pave the way for a brighter, more inclusive future for all.

[pipszhou]

𝐩𝐫𝐨𝐟𝐞𝐬𝐬𝐨𝐫 𝐜𝐚𝐥𝐞𝐛'𝐬 𝐩𝐞𝐭

✧ — synopsis: Top of the class? Not for long. All it took was one lecture, one remote-controlled vibrator, and Professor Caleb’s merciless control to turn you into a shaking, dripping mess. And when he calls you up to the chalkboard, you learn the real curriculum: obedience, humiliation, and being bred full by your favorite professor.

✧ — pairing: caleb x mc

✧ — wc: ~2.5k

✧ — tags: professor caleb, semi-public sex, vibrators, humiliation, degradation, subspace, sexual overstimulation, creampie, breeding, power imbalance, dom/sub, rough sex, size kink, dirty talk, cock warming, spanking, hair-pulling, biting, marking, possessive behavior, multiple orgasms, orgasm control, begging, soft aftercare, classroom sex, pet names

✧ — notes: hello hello again i'm really horny so i wrote this within a day. not beta read, i hope you enjoy my horny endeavors! i just need more power imbalance lmao

You’re in a predicament.

The top student of the entire university—the pride of the campus—yet here you are, sitting at the back of the lecture hall with your thighs pressed tightly together, your nails digging into the edges of your seat. Your brows furrow, delicate lines forming between your temples as you bite down hard on your bottom lip, desperately trying to smother the whimpers threatening to spill out.

Because nestled deep inside you, hidden from the world, is a merciless vibrator—thick, hot, and unforgiving—pounding into your dripping cunt with devastating precision. Each thrust stretches you open wide, the fat head grinding against every desperate, soaked spot inside you. The toy doesn't just vibrate; it fucks into you, grinding in deep, twisting and pulsing like a real cock seeking to wreck you completely. Your walls flutter helplessly around it, clenching and spasming in pathetic pleasure.

As if that wasn’t enough, a suction toy clamps tightly onto your swollen clit, tugging and slurping with obscene, wet noises, like it's trying to suck your soul straight out through your trembling folds. Every pull sends white-hot sparks through your body, every pulse making you jolt and tremble.

All because of him.

Professor Caleb. Your childhood friend. Your Gege. Now the most sought-after artificial intelligence lecturer on campus—the heartthrob every girl wanted. And the man who had no mercy for you.

This was his game. His twisted, cruel judgment: could you endure, maintain your perfect, untouchable image... while the toy he prepared tore you apart from the inside out?

Or would you crack, humiliate yourself by running to the bathroom to finger yourself raw like a desperate little thing?

You refused to lose.

Your pride was too fierce.

Your stubbornness, too stupid.

So you stayed in your seat, trembling, thighs sticky and slick, grinding ever so slightly against the chair in a desperate bid for relief. Hands clamped over your mouth, you prayed no one would hear the faint, wicked buzzing between your legs. You clenched, you gasped, you endured.

Until the voice you dreaded most called out, slicing through your fragile composure like a blade.

"Class number 13," Caleb said smoothly, his voice sending shivers down your spine. "Please come up and solve the problem. What is the predicted value output of this activation layer in the full network?"

Oh gods.

Oh fuck.

Your heart plummeted. Your body spasmed around the merciless toy, gushing helplessly. Your mind—blank, so utterly blank, filled only with the overwhelming feeling of being stuffed full and sucked dry.

You hadn’t heard a single word of the lecture.

But you had a reputation to keep. The golden girl. The untouchable ace.

You forced yourself to rise, your nails digging into the table so hard they threatened to break. You took slow, shaky breaths, fighting to control the feverish pulse hammering through you. Your legs trembled as you stepped out into the aisle, every eye in the room burning into your skin, every step feeling like a mile-long walk of shame.

You reached the front—and there he was. Professor Caleb. Eyes dark with amusement. Smirk hidden behind the respectable façade.

He handed you the chalk. His fingers brushed yours—and in that exact moment, you caught it: the glint of the remote tucked in his palm.

A flick of his thumb.

The vibrator inside you roared to life, surging to its highest setting, brutal and relentless. It slammed into you, the fat shaft pistoning deep, hammering your g-spot, dragging moans up your throat you barely swallowed down. The toy twisted with each brutal thrust, the head grinding against your sweetest spots, almost lovingly cruel in how it refused to let you breathe.

The suction on your clit tightened too, a filthy, slurping rhythm pulling at you in time with each thrust inside—as if the toy was fucking and drinking you at once, milking you dry.

Your knees buckled slightly. You caught yourself against the chalkboard.

You could feel it.

The thick, pulsing length of the toy stuffing you full, stretching your cunt to its limits, buzzing violently against your spasming walls. Your panties were drenched, your thighs glistening. Your dignity, seconds away from shattering.

And yet you had to solve the equation.

In front of the entire class.

Under his watchful, merciless gaze.

The chalk trembled in your hand. He leaned in close, voice a low purr only you could hear. "Go on, top student," Caleb murmured, dark and wicked against your ear.

"Show me how well you can think… while getting fucked dumb.”

Fuck—a moan slipped past your lips before you could catch it. You wanted to curse the existence out of him. You wanted to tear him apart with words, call him the cruelest bastard alive. But all you could do was look at him—eyes burning with dark, venomous vengeance, even as your body betrayed you with heavy, panting breaths and soft, pathetic whimpers.

You tried—you really fucking tried—to walk your mind through every algorithm, every neural network formula you’d memorized so well. You tried to scribble something on the chalkboard, your hand trembling. But it was useless. Your writing was a mess of illegible lines, nonsense formulas no one could make sense of, the chalk crumbling and snapping in your tight, desperate grip.

Then you heard it— the low, rich sound of his chuckle. Amused. Entertained. Savoring your unraveling.

With a lazy flick of his thumb against the remote, he cranked the suction to maximum.

The effect was immediate. Your entire body convulsed, a helpless jolt of pleasure rippling up your spine. The suction on your clit was savage, unrelenting—greedy little pulls that sent wave after wave crashing through your gut, making your vision blur with stars.

Fuck, you were so close. So fucking close.

You slapped a trembling palm against the chalkboard to steady yourself. The chalk clattered to the floor with a hollow thud as your fingers lost their grip. Your knees buckled, barely holding you up as your hips gave a desperate, involuntary twitch.

Inside you, the thick vibrator kept thrusting deep—the textured veins along its shaft dragging against your slick walls with every ruthless stroke, the fat, rounded head grinding mercilessly against your sensitive cervix. It was maddening—perfect—too good. Every thrust knocked the air from your lungs, every pulse made your cunt flutter helplessly, greedy for more.

The suction was obscene, slurping at your clit so loudly you were sure someone, anyone, could hear. Humiliation and raw, brain-melting pleasure tangled inside you, choking you.

Then—his hand.

You felt it. Large, warm, strong fingers gripping your shoulder tightly.

You barely registered him leaning down, his breath hot against the shell of your ear, his voice a low, sinful growl meant for you alone.

"Fuck, baby," Caleb rasped, the words sending a violent shudder through your entire body.

"Why don't you just give up—let go—and I'll fill you up with my babies later, hm? Breed you nice and full right here…"

That was it.

The last straw.

You came—hard. Your body seized violently, every muscle locking tight as the orgasm tore through you, raw and merciless. Slick gushed down your thighs, soaking through your panties, dripping onto the floor. You bit down on your own hand to muffle the loud, broken moan that ripped free from your throat.

You shattered under him, completely undone, just as he wanted.

You heard it—the low, scandalous murmurs rippling across the room. The students whispering, stealing glances at the obscene sight before them. You, gasping for air, your knees buckling under you, while Professor Caleb—the campus heartthrob—stood so close you could taste his cologne, feel the heat of him against your trembling skin.

Then he stood upright, rolling his shoulders lazily like nothing was wrong. Like you weren’t falling apart on the floor.

"Alright, folks. Class dismissed," he said, mock sympathy dripping from his voice. "I'll take care of our top student here. She must be feeling a little... overwhelmed."

He winked—a cruel, knowing thing that made your blood boil.

"Come back next week with the answers to the problem on the board."

Students scurried out, throwing lingering stares your way, none brave enough to question him.

None knowing just how soaked you were—how the vibrator still pounded inside you, thrusting, suctioning, working your overstimulated folds mercilessly. The cum from earlier leaking out, wetting your thighs shamefully.

Once the last student left, Caleb locked the door with a click. He turned, his steps slow and deliberate as he stalked toward you. He grabbed your arm and pulled you up, no patience left in him.

"Stand up, Pip-squeak," he said, his professor mask fully dropped, replaced by something darker, filthier. "I’ll make it fast for you."

You nodded, helpless. Your legs felt like jelly, your cunt still clenching pathetically around the toy buried deep inside. With his steadying hand, you stumbled upright.

He guided you to his seat—the throne at the front of the room—and sat back lazily, spreading his legs in a welcoming posture.

"Strip, baby," he ordered, voice thick with lust. "I wanna see every curve hiding under that tight little shirt and short skirt you wore, thinking you could tease me."

You glared at him, breathing heavy. God, you hated him. You hated how hot he made you. How wet you got just from the sound of his voice.

"Chop chop," he said, tapping his jaw with his fingers smugly. "Or do you want me to rip it off you instead? I won't be gentle, Pips."

You cursed under your breath but obeyed—gripping the hem of your tank top, peeling it over your head slowly, exposing trembling skin. Your skirt pooled down your legs with a soft whisper, leaving you utterly bare, nothing left to hide.

"What now, Caleb?" you asked, your voice small, shivering slightly.

"Good girl," he murmured, unzipping his fancy linen pants with one smooth motion. His thick, heavy cock sprung free—long, veined, angry red at the tip, leaking pre-cum like he couldn't wait to ruin you again.

The same cock that had broken you a hundred times before.

The same cock you dreamed about, drooled over, worshiped like it was your personal god.

"Sit on me," he said. "You know the drill."

You let out a shaky breath, heart pounding in your ears. No matter how much you wanted to slap him for being an asshole—you wanted him more.

You were his cocksleeve, after all. His needy little thing.

You climbed onto his lap, one trembling hand gripping his collarbone for balance. The other reached down between your legs, pulling the soaked, buzzing vibrator out of your stretched hole and tossing it somewhere carelessly.

Lining him up, you sank down. It was like the first time all over again.

His cock was thicker than anything, harder, hotter—stretching your walls until they clamped around him desperately. Every vein of him dragged along your sensitive insides perfectly, the fat head of his cock pushing into your cervix with sinful precision. He filled you up like he was made for you—like he owned every inch of your tight, ruined cunt.

He was your naughty professor.

Your filthy god.

Your damnation and your salvation wrapped in one devastating man.

You started moving—bouncing weakly, trying to ride him the way he liked, but your legs were too shaky, too spent from the relentless overstimulation. You whimpered, grinding pathetically against him, barely able to lift yourself.

"Oh, baby," he cooed mockingly, hands resting heavy on your ass. "Is that all you got? After coming so pretty in front of the whole class?"

He slapped your ass hard enough to make you squeal, then soothed it with a rough grope, making you rock harder against him.

You tried to look away, humiliated, but his dark gaze pinned you in place—all-consuming. Inescapable.

"Shut up, Caleb," you snarled weakly. "Shut the fuck up—I—"

He gripped your hair tight, yanking your head back roughly. A broken cry escaped you, your back arching, pressing your tits flush against his chest.

"You don't get to order me around, baby," he growled, voice pure sin against your ear. He bit down on your neck, hard enough to bruise, suckling dark purple marks into your skin like a man possessed.

"You're mine, Pip-squeak. My perfect little whore."

Your mind spun. Your body shook. You fell deeper into subspace—weightless, aching, desperate for him. He toyed with you, slapping your ass, groping your tits, biting your throat, until you were a trembling mess in his lap.

"Need help, my lovely top student?" he whispered against your ear, voice thick with cruel affection. You nodded frantically, tears clinging to your lashes, your body begging.

He chuckled low and deep—"could’ve said so sooner, Pips."

Then he took control. His hands grabbed your waist, slamming you down onto his cock with brutal, merciless thrusts. Each movement drove him impossibly deep, splitting you open, pounding against your g-spot so viciously that your cries turned into strangled, high-pitched sobs.

You dug your nails into his back, leaving angry red trails down his spine. You wanted to brand him. You wanted him to remember how you fell apart on his cock.

The lecture hall echoed with the wet, filthy slap of skin on skin—your cries, his low groans, the obscene, squelching sound of your cunt sucking him in greedily. "Keep it down, baby," he mocked, voice a rumble in your chest. "Others might hear you begging to be bred."

Fuck him.

Fuck him so much.

But you were too far gone. Your second orgasm built fast, violent, white-hot, ripping through you with every devastating thrust. You couldn’t hold back—your body convulsed, your cunt squeezing him desperately, trying to milk every drop from him.

And he was close too. You could hear it in his ragged breaths, feel it in the way his thrusts became rougher, erratic.

"Baby," he moaned brokenly, forehead pressed against yours, "I’m gonna come—open up, please—"

You did—your walls clamping down, your legs shaking, your mind blank as you came undone together. He spilled inside you with a low, desperate groan—thick, endless spurts of cum flooding your sore, twitching cunt. You could feel every hot, filthy drop filling you, leaking out, dripping down your thighs in thick, sticky trails.

You collapsed against him, shaking, gasping, his cock still buried deep inside your pulsing heat. His arms wrapped around you tight, possessive, like he was afraid you might slip away.

"Mine," he murmured against your hair, voice rough and spent. "Always mine, Pip-squeak."

And you wouldn’t have it any other way.

You stayed there—your body convulsing in little aftershocks, your pussy throbbing around him like it was the end of the world. He held you close, a suffocating, trembling embrace, like he needed to feel you breathing against him just to stay sane.

Even after the humiliation he put you through—after the teasing, the breaking, the claiming—you still loved him just the same. Your Gege. Your professor. Your ruin. Your home.

"Meet me after your classes end," he rasped, his temple resting against your bare shoulder, his cock still buried deep inside you. "Five p.m. sharp. As usual."

You nodded weakly, knowing full well—

You weren’t going to make it home in one piece.

[vague-humanoid]

https://www.nbc4i.com/news/local-news/ohio-state-university/ohio-state-announces-every-student-will-use-ai-in-class/

@that-biracial-geek-girl @quasi-normalcy @startorrent02

Starting this fall, every Ohio State student will be asked to use artificial intelligence.

“Through AI Fluency, Ohio State students will be ‘bilingual’ — fluent in both their major field of study and the application of AI in that area,” Ravi V. Bellamkonda, executive vice president and provost, said.

Ohio State’s AI Fluency Initiative will embed AI education throughout the undergraduate curriculum. The program will prioritize the incoming freshman class, and OSU said from 2029 onward, every Ohio State graduate will be fluent in the application of AI in their field.

[mostlysignssomeportents]

"Open" "AI" isn’t

Tomorrow (19 Aug), I'm appearing at the San Diego Union-Tribune Festival of Books. I'm on a 2:30PM panel called "Return From Retirement," followed by a signing:

https://www.sandiegouniontribune.com/festivalofbooks

The crybabies who freak out about The Communist Manifesto appearing on university curriculum clearly never read it – chapter one is basically a long hymn to capitalism's flexibility and inventiveness, its ability to change form and adapt itself to everything the world throws at it and come out on top:

https://www.marxists.org/archive/marx/works/1848/communist-manifesto/ch01.htm#007

Today, leftists signal this protean capacity of capital with the -washing suffix: greenwashing, genderwashing, queerwashing, wokewashing – all the ways capital cloaks itself in liberatory, progressive values, while still serving as a force for extraction, exploitation, and political corruption.

A smart capitalist is someone who, sensing the outrage at a world run by 150 old white guys in boardrooms, proposes replacing half of them with women, queers, and people of color. This is a superficial maneuver, sure, but it's an incredibly effective one.

In "Open (For Business): Big Tech, Concentrated Power, and the Political Economy of Open AI," a new working paper, Meredith Whittaker, David Gray Widder and Sarah B Myers document a new kind of -washing: openwashing:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4543807

Openwashing is the trick that large "AI" companies use to evade regulation and neutralizing critics, by casting themselves as forces of ethical capitalism, committed to the virtue of openness. No one should be surprised to learn that the products of the "open" wing of an industry whose products are neither "artificial," nor "intelligent," are also not "open." Every word AI huxters say is a lie; including "and," and "the."

So what work does the "open" in "open AI" do? "Open" here is supposed to invoke the "open" in "open source," a movement that emphasizes a software development methodology that promotes code transparency, reusability and extensibility, which are three important virtues.

But "open source" itself is an offshoot of a more foundational movement, the Free Software movement, whose goal is to promote freedom, and whose method is openness. The point of software freedom was technological self-determination, the right of technology users to decide not just what their technology does, but who it does it to and who it does it for:

https://locusmag.com/2022/01/cory-doctorow-science-fiction-is-a-luddite-literature/

The open source split from free software was ostensibly driven by the need to reassure investors and businesspeople so they would join the movement. The "free" in free software is (deliberately) ambiguous, a bit of wordplay that sometimes misleads people into thinking it means "Free as in Beer" when really it means "Free as in Speech" (in Romance languages, these distinctions are captured by translating "free" as "libre" rather than "gratis").

The idea behind open source was to rebrand free software in a less ambiguous – and more instrumental – package that stressed cost-savings and software quality, as well as "ecosystem benefits" from a co-operative form of development that recruited tinkerers, independents, and rivals to contribute to a robust infrastructural commons.

But "open" doesn't merely resolve the linguistic ambiguity of libre vs gratis – it does so by removing the "liberty" from "libre," the "freedom" from "free." "Open" changes the pole-star that movement participants follow as they set their course. Rather than asking "Which course of action makes us more free?" they ask, "Which course of action makes our software better?"

Thus, by dribs and drabs, the freedom leeches out of openness. Today's tech giants have mobilized "open" to create a two-tier system: the largest tech firms enjoy broad freedom themselves – they alone get to decide how their software stack is configured. But for all of us who rely on that (increasingly unavoidable) software stack, all we have is "open": the ability to peer inside that software and see how it works, and perhaps suggest improvements to it:

https://www.youtube.com/watch?v=vBknF2yUZZ8

In the Big Tech internet, it's freedom for them, openness for us. "Openness" – transparency, reusability and extensibility – is valuable, but it shouldn't be mistaken for technological self-determination. As the tech sector becomes ever-more concentrated, the limits of openness become more apparent.

But even by those standards, the openness of "open AI" is thin gruel indeed (that goes triple for the company that calls itself "OpenAI," which is a particularly egregious openwasher).

The paper's authors start by suggesting that the "open" in "open AI" is meant to imply that an "open AI" can be scratch-built by competitors (or even hobbyists), but that this isn't true. Not only is the material that "open AI" companies publish insufficient for reproducing their products, even if those gaps were plugged, the resource burden required to do so is so intense that only the largest companies could do so.

Beyond this, the "open" parts of "open AI" are insufficient for achieving the other claimed benefits of "open AI": they don't promote auditing, or safety, or competition. Indeed, they often cut against these goals.

"Open AI" is a wordgame that exploits the malleability of "open," but also the ambiguity of the term "AI": "a grab bag of approaches, not… a technical term of art, but more … marketing and a signifier of aspirations." Hitching this vague term to "open" creates all kinds of bait-and-switch opportunities.

That's how you get Meta claiming that LLaMa2 is "open source," despite being licensed in a way that is absolutely incompatible with any widely accepted definition of the term:

https://blog.opensource.org/metas-llama-2-license-is-not-open-source/

LLaMa-2 is a particularly egregious openwashing example, but there are plenty of other ways that "open" is misleadingly applied to AI: sometimes it means you can see the source code, sometimes that you can see the training data, and sometimes that you can tune a model, all to different degrees, alone and in combination.

But even the most "open" systems can't be independently replicated, due to raw computing requirements. This isn't the fault of the AI industry – the computational intensity is a fact, not a choice – but when the AI industry claims that "open" will "democratize" AI, they are hiding the ball. People who hear these "democratization" claims (especially policymakers) are thinking about entrepreneurial kids in garages, but unless these kids have access to multi-billion-dollar data centers, they can't be "disruptors" who topple tech giants with cool new ideas. At best, they can hope to pay rent to those giants for access to their compute grids, in order to create products and services at the margin that rely on existing products, rather than displacing them.

The "open" story, with its claims of democratization, is an especially important one in the context of regulation. In Europe, where a variety of AI regulations have been proposed, the AI industry has co-opted the open source movement's hard-won narrative battles about the harms of ill-considered regulation.

For open source (and free software) advocates, many tech regulations aimed at taming large, abusive companies – such as requirements to surveil and control users to extinguish toxic behavior – wreak collateral damage on the free, open, user-centric systems that we see as superior alternatives to Big Tech. This leads to the paradoxical effect of passing regulation to "punish" Big Tech that end up simply shaving an infinitesimal percentage off the giants' profits, while destroying the small co-ops, nonprofits and startups before they can grow to be a viable alternative.

The years-long fight to get regulators to understand this risk has been waged by principled actors working for subsistence nonprofit wages or for free, and now the AI industry is capitalizing on lawmakers' hard-won consideration for collateral damage by claiming to be "open AI" and thus vulnerable to overbroad regulation.

But the "open" projects that lawmakers have been coached to value are precious because they deliver a level playing field, competition, innovation and democratization – all things that "open AI" fails to deliver. The regulations the AI industry is fighting also don't necessarily implicate the speech implications that are core to protecting free software:

https://www.eff.org/deeplinks/2015/04/remembering-case-established-code-speech

Just think about LLaMa-2. You can download it for free, along with the model weights it relies on – but not detailed specs for the data that was used in its training. And the source-code is licensed under a homebrewed license cooked up by Meta's lawyers, a license that only glancingly resembles anything from the Open Source Definition:

https://opensource.org/osd/

Core to Big Tech companies' "open AI" offerings are tools, like Meta's PyTorch and Google's TensorFlow. These tools are indeed "open source," licensed under real OSS terms. But they are designed and maintained by the companies that sponsor them, and optimize for the proprietary back-ends each company offers in its own cloud. When programmers train themselves to develop in these environments, they are gaining expertise in adding value to a monopolist's ecosystem, locking themselves in with their own expertise. This a classic example of software freedom for tech giants and open source for the rest of us.

One way to understand how "open" can produce a lock-in that "free" might prevent is to think of Android: Android is an open platform in the sense that its sourcecode is freely licensed, but the existence of Android doesn't make it any easier to challenge the mobile OS duopoly with a new mobile OS; nor does it make it easier to switch from Android to iOS and vice versa.

Another example: MongoDB, a free/open database tool that was adopted by Amazon, which subsequently forked the codebase and tuning it to work on their proprietary cloud infrastructure.

The value of open tooling as a stickytrap for creating a pool of developers who end up as sharecroppers who are glued to a specific company's closed infrastructure is well-understood and openly acknowledged by "open AI" companies. Zuckerberg boasts about how PyTorch ropes developers into Meta's stack, "when there are opportunities to make integrations with products, [so] it’s much easier to make sure that developers and other folks are compatible with the things that we need in the way that our systems work."

Tooling is a relatively obscure issue, primarily debated by developers. A much broader debate has raged over training data – how it is acquired, labeled, sorted and used. Many of the biggest "open AI" companies are totally opaque when it comes to training data. Google and OpenAI won't even say how many pieces of data went into their models' training – let alone which data they used.

Other "open AI" companies use publicly available datasets like the Pile and CommonCrawl. But you can't replicate their models by shoveling these datasets into an algorithm. Each one has to be groomed – labeled, sorted, de-duplicated, and otherwise filtered. Many "open" models merge these datasets with other, proprietary sets, in varying (and secret) proportions.

Quality filtering and labeling for training data is incredibly expensive and labor-intensive, and involves some of the most exploitative and traumatizing clickwork in the world, as poorly paid workers in the Global South make pennies for reviewing data that includes graphic violence, rape, and gore.

Not only is the product of this "data pipeline" kept a secret by "open" companies, the very nature of the pipeline is likewise cloaked in mystery, in order to obscure the exploitative labor relations it embodies (the joke that "AI" stands for "absent Indians" comes out of the South Asian clickwork industry).

The most common "open" in "open AI" is a model that arrives built and trained, which is "open" in the sense that end-users can "fine-tune" it – usually while running it on the manufacturer's own proprietary cloud hardware, under that company's supervision and surveillance. These tunable models are undocumented blobs, not the rigorously peer-reviewed transparent tools celebrated by the open source movement.

If "open" was a way to transform "free software" from an ethical proposition to an efficient methodology for developing high-quality software; then "open AI" is a way to transform "open source" into a rent-extracting black box.

Some "open AI" has slipped out of the corporate silo. Meta's LLaMa was leaked by early testers, republished on 4chan, and is now in the wild. Some exciting stuff has emerged from this, but despite this work happening outside of Meta's control, it is not without benefits to Meta. As an infamous leaked Google memo explains:

Paradoxically, the one clear winner in all of this is Meta. Because the leaked model was theirs, they have effectively garnered an entire planet's worth of free labor. Since most open source innovation is happening on top of their architecture, there is nothing stopping them from directly incorporating it into their products.

https://www.searchenginejournal.com/leaked-google-memo-admits-defeat-by-open-source-ai/486290/

Thus, "open AI" is best understood as "as free product development" for large, well-capitalized AI companies, conducted by tinkerers who will not be able to escape these giants' proprietary compute silos and opaque training corpuses, and whose work product is guaranteed to be compatible with the giants' own systems.

The instrumental story about the virtues of "open" often invoke auditability: the fact that anyone can look at the source code makes it easier for bugs to be identified. But as open source projects have learned the hard way, the fact that anyone can audit your widely used, high-stakes code doesn't mean that anyone will.

The Heartbleed vulnerability in OpenSSL was a wake-up call for the open source movement – a bug that endangered every secure webserver connection in the world, which had hidden in plain sight for years. The result was an admirable and successful effort to build institutions whose job it is to actually make use of open source transparency to conduct regular, deep, systemic audits.

In other words, "open" is a necessary, but insufficient, precondition for auditing. But when the "open AI" movement touts its "safety" thanks to its "auditability," it fails to describe any steps it is taking to replicate these auditing institutions – how they'll be constituted, funded and directed. The story starts and ends with "transparency" and then makes the unjustifiable leap to "safety," without any intermediate steps about how the one will turn into the other.

It's a Magic Underpants Gnome story, in other words:

Step One: Transparency

Step Two: ??

Step Three: Safety

https://www.youtube.com/watch?v=a5ih_TQWqCA

Meanwhile, OpenAI itself has gone on record as objecting to "burdensome mechanisms like licenses or audits" as an impediment to "innovation" – all the while arguing that these "burdensome mechanisms" should be mandatory for rival offerings that are more advanced than its own. To call this a "transparent ruse" is to do violence to good, hardworking transparent ruses all the world over:

https://openai.com/blog/governance-of-superintelligence

Some "open AI" is much more open than the industry dominating offerings. There's EleutherAI, a donor-supported nonprofit whose model comes with documentation and code, licensed Apache 2.0. There are also some smaller academic offerings: Vicuna (UCSD/CMU/Berkeley); Koala (Berkeley) and Alpaca (Stanford).

These are indeed more open (though Alpaca – which ran on a laptop – had to be withdrawn because it "hallucinated" so profusely). But to the extent that the "open AI" movement invokes (or cares about) these projects, it is in order to brandish them before hostile policymakers and say, "Won't someone please think of the academics?" These are the poster children for proposals like exempting AI from antitrust enforcement, but they're not significant players in the "open AI" industry, nor are they likely to be for so long as the largest companies are running the show:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4493900

I'm kickstarting the audiobook for "The Internet Con: How To Seize the Means of Computation," a Big Tech disassembly manual to disenshittify the web and make a new, good internet to succeed the old, good internet. It's a DRM-free book, which means Audible won't carry it, so this crowdfunder is essential. Back now to get the audio, Verso hardcover and ebook:

http://seizethemeansofcomputation.org

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2023/08/18/openwashing/#you-keep-using-that-word-i-do-not-think-it-means-what-you-think-it-means

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[mangionebabymama]

hiiii i was just curious — as u mentioned you're in college and i'm not very educated about the system anymore — if you had any insight about lu's uni life! (i had to drop out after my first semester years ago for health issues, would love to go back and be in an academic environment again but.. sigh unfortunately it feels like mid 20's is too late to start again, along with the risk of not knowing what degree would be right and it being costly — ahh sorry i'm side tracking) i know he got his bachelors and masters in 4 years with honours (which sounds like a crazy feat in itself) but was also wondering how that fit in with him also being a counsellor (?) ta (?) at stanford! i saw someone say he did it for like a year (don't quote me on that) so was curious how that side of things work, and at what year into his degree he did it! was it part of a program that gave him credits he could transfer back to penn? or was it something that cut into his degree time and was mainly for experience? another thing i saw ppl talking about is the amount of time in which he completed his degree, i typically thought a bachelors is a 3-4 year mark and then masters is another year or 2 on top of that, so how did he complete both so quickly? i could be completely wrong here so sorry for all the questions, and thank u for being such a big sis like safe space!

Hello!

This is the best insight that I can give you from his uni life:

So, first off, yes, he was a counselor and also a TA while in college, and these two roles were two completely different experiences that he had while at UPenn and outside of his time while in school. He was a head counselor for the Stanford Pre-Collegiate Studies, an academic program that middle and high school students can attend to learn advanced coursework in different subjects. As a counselor, he supervised the residential aspect for students attending the program and taught them artificial intelligence during the summer of 2019 while on summer break; he did this during the summer after his junior (3rd) year and before the start of his last (4th) year at UPenn. This had no affiliation with him going to UPenn; he participated in this probably out of his own interest. So no, it was not part of a program that gave him credits. My educated guess on why he did this was to first gain more and broaden his leadership skills, explore more with his computer science background, and add an impressive experience to his resume and educational experience.

Then, between his second and third years of college, he was a teaching assistant for an actual class at UPenn for about a year and a half. Now, I don't know if he actually received credits towards his degree as a TA, but it is very common to earn college credit by assisting with teaching courses, depending on the institution and program you're a part of.

And then about his Bachelor's and Master's degrees—yes, typically, a Bachelor's degree takes about 4 years to complete. On the other hand, a Master's can take about 1-2 years, although it can vary based on different factors like the program requirements, the enrollment type, and how fast the program goes. I don't know what the Computer Science program at UPenn is like, but he probably completed his degrees that quick because of either an accelerated or a dual-degree program, where the curriculum of your field of study allows you to earn both degrees in a shorter time at an accelerated rate. Many universities offer this kind of program for a number of different studies, where you can earn both a Bachelor's and a Master's degree concurrently within 4 years.

A little side note: I'm sorry you dropped out early because of health issues. I know that wasn't the easiest decision to make, but know that you did the right thing by taking care of yourself first and foremost. Please understand that you are never too late to start all over again, and it's okay if you don't necessarily know that you want to study first—at some point, it will come to you when you see what you want to do and what matters the most to you. If this gives you any sign of reassurance, I did not go to college for my first degree until an entire year after graduating high school. I decided to take a gap year. I was severely ill with a virus, and I nearly fought my last year of high school being extremely sick. When I graduated high school, I realized then that I wasn't ready for that next transition—I realized that I needed to take care of myself first before starting that next part of my life. I'm glad I did because I was ready when I finally started college. I know many people who are older than me who have either started school later in life, whether to get their first ever degree or their next one, whether it was because of a job change, family life, or financial reasons. Remember, do what you want to do and what makes you content in your life, and don't think you have to compare yourself to another person—we all have different choices on what we want to achieve in life, which means we may have to go about them differently. That doesn't automatically mean you're on the wrong path! 🤍

[workersworldparty]

https://www.workers.org/2025/05/85608/

In response to a call by the Palestinians to increase resistance, students at the University of Washington (UW) were spurred to make action plans. Students and community members escalated the struggle by occupying a building just opened with a $10 million gift from war contractor Boeing.

The students used many tactics to keep the cops at bay, including blocking police cars and overturning and burning trash dumpsters in front of the building, which kept the cops away for over an hour.

This building, the Interdisciplinary Engineering Building, has as its purpose ���establishing an AI [artificial intelligence] educational institute for developing military technology and securing Boeing in the engineering curriculum, which functions as a pipeline channeling UW engineering students into Boeing internships and contracts,” say direct action activists. (crimethinc.com) The building is just one of many Boeing projects at the UW. Boeing has given the school at least $100 million over the years.

[pscottm]

Ohio State announces every student will use AI in class | NBC4 WCMH-TV

https://www.nbc4i.com/news/local-news/ohio-state-university/ohio-state-announces-every-student-will-use-ai-in-class/

Starting this fall, every Ohio State student will be asked to use artificial intelligence.

“Through AI Fluency, Ohio State students will be ‘bilingual’ — fluent in both their major field of study and the application of AI in that area,” Ravi V. Bellamkonda, executive vice president and provost, said.

Ohio State’s AI Fluency Initiative will embed AI education throughout the undergraduate curriculum. The program will prioritize the incoming freshman class, and OSU said from 2029 onward, every Ohio State graduate will be fluent in the application of AI in their field.

[guysgoneexposed]

Daddy's Always Willing to Help

After graduating college, Taylor was thrilled to be accepted into the very exclusive: Kink Academy. As a legacy, you'd think things would have been easier, but his "Daddy" was a legend at the academy and the expectations for Taylor to impress were very high.

Things had changed a bit since his Daddy had been the big man on campus. Technology is now a huge part of the curriculum and something Taylor was very skilled at and passionate for.

This semester Taylor's special project was working on an app that integrated AI (artificial intelligence) and AR(augmented reality) to create a one of a kind kinky experience he's calling "Deep Fucked". He'd been working hard training the AI with data from the school's digital archives and vault (which had lots of material featuring "Daddy", but that's a story, several stories, for another day) and was ready for the human testing phase. It was designed for at least two users: an operator and a participant. He needed someone he could trust to try it out on.

He knows his Daddy will be proud, but would he be willing to help him test it out? Taylor asks Daddy for help, and without batting an eye, or asking any questions, Daddy agrees to do whatever it takes.

So what does Daddy have to do? To begin with, Taylor just needs to scan Daddys full body. "You need me naked?" Daddy asks. Taylor smiles and laughs a bit: "No, not yet at least, for now... You can stay dressed". Daddy laughed:" I don't understand. I thought this was kinky". Taylor just smiles and winks saying:"You'll see... If it works". Just stand nice and still. Taylor gets a full body scan... front and back... Now to see if it works: "let me try a few of the filters... Let's see if it will take your shirt off. Ah... Wow... It's so realistic... Nice undershirt Daddy". Dad looks at him: "It's working? What's it doing?". "Don't worry, trust me..." Taylor replies as he presses the remove pants button to see his Daddy without pants! Oh the power he has at his finger tips. He has to know, does the fully nude option work? "Now for the real test..." He skips some of the other options and presses the fully nude button. He gasps... Here his Daddy is fully clothed in person, but butt ass naked on his phone's screen. He gasps with awe. "Wow, Daddy... It works! I'm staring at a completely nude image of you". Daddy completely shocked instinctively covers his junk with his hands. "Um , what do you mean?" He says nervously. Why am I feeling so exposed? What do you mean naked? Taylor gives him a stern: "Don't cover that cock Daddy, I've already seen it, recorded it, so show it off. Now spin around and let me see how well it works on that juicy back side of yours". What do you mean you've seen it before? Daddy still doesn't quite understand: "But how? I'm fully clothed!". Just spin around! I've been working with the school archives. I've seen everything you got up to. I know what made you a legend among legends. This app is going to help build my own legend status, with your help! Daddy nervously chuckles as his spins around and puts his hands behind his head as instructed. Surely he didn't see EVERYTHING? Taylor scrolls through several options to see how well they look on his Dad from behind. Including the "women's lingerie" option which makes Taylor giggle a bit, but also reminds him that Daddy looks great in and OUT of everything. Taylor laughs, "You've created a kinky genius... Don't worry, now that I have your scans I'll be able to make some tweaks and make it even better. I'm showing my progress to a few of my professors(most of which were buddies of Daddy's during his time at the school) and my class, well really the entire school tomorrow. If also like to share these images of how realistically naked you look on my socials- I've been crowd sourcing some of the ideas to make this the best app it can be. I think the more eyes on the project... On you... The better! Just wait for some of the updates I have planned". I've only just begun.

[cleveredlearning]

Transforming Education: The Power of Artificial Intelligence Labs and Certified Coding Curricula in Schools

Introduction:

In an era defined by rapid technological advancements, integrating Artificial Intelligence (AI) and Coding Labs into school curricula has become a crucial component of fostering future-ready students. Recognizing the transformative potential of these educational tools, schools are increasingly adopting AI Labs and Certified Coding Curricula to equip students with essential skills for the digital age.

The Need for AI Labs in Schools:

As the world becomes more interconnected and technology-driven, the demand for individuals skilled in AI is escalating. To meet this demand, educational institutions are establishing dedicated AI labs within their premises. These labs serve as innovative spaces where students can explore the intricacies of AI, machine learning, and data science. By engaging with real-world applications, students gain a profound understanding of AI concepts, preparing them for the evolving job market.

The Role of Coding Labs in Schools:

Coding is the language of the future, and understanding it is no longer a niche skill but a fundamental literacy. To address this, schools are incorporating Coding Labs into their curricula, providing students with hands-on experience in programming languages like Python, Java, and JavaScript. These labs foster problem-solving skills, logical thinking, and creativity, laying the foundation for future careers in technology.

Certified Curriculum for Schools:

A critical aspect of implementing AI Coding Labs in schools is the use of certified curricula. These curricula ensure that students receive structured and standardized education in AI and coding, promoting a comprehensive learning experience. Certified programs often align with industry standards, guaranteeing that students are equipped with skills that are not only relevant but also recognized globally.

Components of a Comprehensive AI Lab:

An effective AI lab for schools comprises various components designed to provide a holistic learning experience. These may include state-of-the-art hardware such as high-performance computers, GPUs, and robotics kits. Additionally, software tools and platforms like TensorFlow and PyTorch enable students to engage in practical applications, fostering a deep understanding of AI concepts.

Benefits of AI Labs for Schools:

Hands-on Learning: AI labs offer students the opportunity to engage in hands-on learning, allowing them to experiment with AI algorithms and applications in a controlled environment.

Critical Thinking: Exploring AI concepts encourages critical thinking and problem-solving skills, as students tackle real-world challenges through the application of AI principles.

Interdisciplinary Learning: AI labs facilitate interdisciplinary learning, bridging the gap between technology and other subjects. Students can apply AI in areas such as biology, physics, and economics, expanding their knowledge base.

Career Readiness: Exposure to AI labs prepares students for future careers in technology, giving them a competitive edge in a job market increasingly dominated by AI-driven solutions.

The Significance of Coding Labs in Schools:

Promoting Logical Thinking: Coding labs enhance logical thinking and reasoning skills as students learn to break down complex problems into smaller, manageable tasks.

Fostering Creativity: Coding is a creative process that allows students to express themselves through problem-solving and the development of unique solutions.

Digital Literacy: Coding labs contribute to digital literacy, ensuring that students are proficient in using technology and understand the underlying principles of software development.

Adaptability: Coding skills are transferable across various fields, making students adaptable to the evolving demands of the job market.

Certified Coding Curricula:

Certified coding curricula play a pivotal role in standardizing the learning process. They ensure that students receive a structured education, covering essential programming concepts and languages. Moreover, certified programs often include assessments and examinations, validating the students' proficiency and providing a tangible recognition of their skills.

Conclusion:

The integration of AI and Coding Labs for school, coupled with certified curricula, represents a transformative approach to education. By exposing students to cutting-edge technologies and equipping them with coding skills, schools prepare them for a future where technology is intertwined with every aspect of society. As educational institutions continue to embrace these advancements, they empower students to not only navigate the digital landscape but also contribute meaningfully to the ever-evolving world of technology.

[makers-muse]

Kickstart a STEM Lab in Nagpur Schools with These 5 Easy Steps 

The STEM Lab program in Nagpur schools provides students with the necessary skills to effectively utilize science, technology, engineering, and mathematics. In effect, hands-on learning provisions create an environment conducive to unleashing creativity and building problem-solving abilities. 

STEM lab installations in Nagpur schools are not merely modern approaches in pedagogy; they are paradigm-shifting. These labs will assist students in exploring the latest subjects—from robotics to artificial intelligence—while preparing them for real-world challenges. It begins with choosing the right STEM Lab solution in Nagpur schools that can ensure that the entire setup-from curriculum to equipment-is made around the special needs of each institution. Read full blog here !