#Role of AI in fraud | Explore Tumblr posts and blogs

mostlysignssomeportents · 8 months ago

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Conspiratorialism as a material phenomenon

I'll be in TUCSON, AZ from November 8-10: I'm the GUEST OF HONOR at the TUSCON SCIENCE FICTION CONVENTION.

I think it behooves us to be a little skeptical of stories about AI driving people to believe wrong things and commit ugly actions. Not that I like the AI slop that is filling up our social media, but when we look at the ways that AI is harming us, slop is pretty low on the list.

The real AI harms come from the actual things that AI companies sell AI to do. There's the AI gun-detector gadgets that the credulous Mayor Eric Adams put in NYC subways, which led to 2,749 invasive searches and turned up zero guns:

https://www.cbsnews.com/newyork/news/nycs-subway-weapons-detector-pilot-program-ends/

Any time AI is used to predict crime – predictive policing, bail determinations, Child Protective Services red flags – they magnify the biases already present in these systems, and, even worse, they give this bias the veneer of scientific neutrality. This process is called "empiricism-washing," and you know you're experiencing it when you hear some variation on "it's just math, math can't be racist":

https://pluralistic.net/2020/06/23/cryptocidal-maniacs/#phrenology

When AI is used to replace customer service representatives, it systematically defrauds customers, while providing an "accountability sink" that allows the company to disclaim responsibility for the thefts:

https://pluralistic.net/2024/04/23/maximal-plausibility/#reverse-centaurs

When AI is used to perform high-velocity "decision support" that is supposed to inform a "human in the loop," it quickly overwhelms its human overseer, who takes on the role of "moral crumple zone," pressing the "OK" button as fast as they can. This is bad enough when the sacrificial victim is a human overseeing, say, proctoring software that accuses remote students of cheating on their tests:

https://pluralistic.net/2022/02/16/unauthorized-paper/#cheating-anticheat

But it's potentially lethal when the AI is a transcription engine that doctors have to use to feed notes to a data-hungry electronic health record system that is optimized to commit health insurance fraud by seeking out pretenses to "upcode" a patient's treatment. Those AIs are prone to inventing things the doctor never said, inserting them into the record that the doctor is supposed to review, but remember, the only reason the AI is there at all is that the doctor is being asked to do so much paperwork that they don't have time to treat their patients:

https://apnews.com/article/ai-artificial-intelligence-health-business-90020cdf5fa16c79ca2e5b6c4c9bbb14

My point is that "worrying about AI" is a zero-sum game. When we train our fire on the stuff that isn't important to the AI stock swindlers' business-plans (like creating AI slop), we should remember that the AI companies could halt all of that activity and not lose a dime in revenue. By contrast, when we focus on AI applications that do the most direct harm – policing, health, security, customer service – we also focus on the AI applications that make the most money and drive the most investment.

AI hasn't attracted hundreds of billions in investment capital because investors love AI slop. All the money pouring into the system – from investors, from customers, from easily gulled big-city mayors – is chasing things that AI is objectively very bad at and those things also cause much more harm than AI slop. If you want to be a good AI critic, you should devote the majority of your focus to these applications. Sure, they're not as visually arresting, but discrediting them is financially arresting, and that's what really matters.

All that said: AI slop is real, there is a lot of it, and just because it doesn't warrant priority over the stuff AI companies actually sell, it still has cultural significance and is worth considering.

AI slop has turned Facebook into an anaerobic lagoon of botshit, just the laziest, grossest engagement bait, much of it the product of rise-and-grind spammers who avidly consume get rich quick "courses" and then churn out a torrent of "shrimp Jesus" and fake chainsaw sculptures:

https://www.404media.co/email/1cdf7620-2e2f-4450-9cd9-e041f4f0c27f/

For poor engagement farmers in the global south chasing the fractional pennies that Facebook shells out for successful clickbait, the actual content of the slop is beside the point. These spammers aren't necessarily tuned into the psyche of the wealthy-world Facebook users who represent Meta's top monetization subjects. They're just trying everything and doubling down on anything that moves the needle, A/B splitting their way into weird, hyper-optimized, grotesque crap:

https://www.404media.co/facebook-is-being-overrun-with-stolen-ai-generated-images-that-people-think-are-real/

In other words, Facebook's AI spammers are laying out a banquet of arbitrary possibilities, like the letters on a Ouija board, and the Facebook users' clicks and engagement are a collective ideomotor response, moving the algorithm's planchette to the options that tug hardest at our collective delights (or, more often, disgusts).

So, rather than thinking of AI spammers as creating the ideological and aesthetic trends that drive millions of confused Facebook users into condemning, praising, and arguing about surreal botshit, it's more true to say that spammers are discovering these trends within their subjects' collective yearnings and terrors, and then refining them by exploring endlessly ramified variations in search of unsuspected niches.

(If you know anything about AI, this may remind you of something: a Generative Adversarial Network, in which one bot creates variations on a theme, and another bot ranks how closely the variations approach some ideal. In this case, the spammers are the generators and the Facebook users they evince reactions from are the discriminators)

https://en.wikipedia.org/wiki/Generative_adversarial_network

I got to thinking about this today while reading User Mag, Taylor Lorenz's superb newsletter, and her reporting on a new AI slop trend, "My neighbor’s ridiculous reason for egging my car":

https://www.usermag.co/p/my-neighbors-ridiculous-reason-for

The "egging my car" slop consists of endless variations on a story in which the poster (generally a figure of sympathy, canonically a single mother of newborn twins) complains that her awful neighbor threw dozens of eggs at her car to punish her for parking in a way that blocked his elaborate Hallowe'en display. The text is accompanied by an AI-generated image showing a modest family car that has been absolutely plastered with broken eggs, dozens upon dozens of them.

According to Lorenz, variations on this slop are topping very large Facebook discussion forums totalling millions of users, like "Movie Character…,USA Story, Volleyball Women, Top Trends, Love Style, and God Bless." These posts link to SEO sites laden with programmatic advertising.

The funnel goes:

i. Create outrage and hence broad reach;

ii, A small percentage of those who see the post will click through to the SEO site;

iii. A small fraction of those users will click a low-quality ad;

iv. The ad will pay homeopathic sub-pennies to the spammer.

The revenue per user on this kind of scam is next to nothing, so it only works if it can get very broad reach, which is why the spam is so designed for engagement maximization. The more discussion a post generates, the more users Facebook recommends it to.

These are very effective engagement bait. Almost all AI slop gets some free engagement in the form of arguments between users who don't know they're commenting an AI scam and people hectoring them for falling for the scam. This is like the free square in the middle of a bingo card.

Beyond that, there's multivalent outrage: some users are furious about food wastage; others about the poor, victimized "mother" (some users are furious about both). Not only do users get to voice their fury at both of these imaginary sins, they can also argue with one another about whether, say, food wastage even matters when compared to the petty-minded aggression of the "perpetrator." These discussions also offer lots of opportunity for violent fantasies about the bad guy getting a comeuppance, offers to travel to the imaginary AI-generated suburb to dole out a beating, etc. All in all, the spammers behind this tedious fiction have really figured out how to rope in all kinds of users' attention.

Of course, the spammers don't get much from this. There isn't such a thing as an "attention economy." You can't use attention as a unit of account, a medium of exchange or a store of value. Attention – like everything else that you can't build an economy upon, such as cryptocurrency – must be converted to money before it has economic significance. Hence that tooth-achingly trite high-tech neologism, "monetization."

The monetization of attention is very poor, but AI is heavily subsidized or even free (for now), so the largest venture capital and private equity funds in the world are spending billions in public pension money and rich peoples' savings into CO2 plumes, GPUs, and botshit so that a bunch of hustle-culture weirdos in the Pacific Rim can make a few dollars by tricking people into clicking through engagement bait slop – twice.

The slop isn't the point of this, but the slop does have the useful function of making the collective ideomotor response visible and thus providing a peek into our hopes and fears. What does the "egging my car" slop say about the things that we're thinking about?

Lorenz cites Jamie Cohen, a media scholar at CUNY Queens, who points out that subtext of this slop is "fear and distrust in people about their neighbors." Cohen predicts that "the next trend, is going to be stranger and more violent.”

This feels right to me. The corollary of mistrusting your neighbors, of course, is trusting only yourself and your family. Or, as Margaret Thatcher liked to say, "There is no such thing as society. There are individual men and women and there are families."

We are living in the tail end of a 40 year experiment in structuring our world as though "there is no such thing as society." We've gutted our welfare net, shut down or privatized public services, all but abolished solidaristic institutions like unions.

This isn't mere aesthetics: an atomized society is far more hospitable to extreme wealth inequality than one in which we are all in it together. When your power comes from being a "wise consumer" who "votes with your wallet," then all you can do about the climate emergency is buy a different kind of car – you can't build the public transit system that will make cars obsolete.

When you "vote with your wallet" all you can do about animal cruelty and habitat loss is eat less meat. When you "vote with your wallet" all you can do about high drug prices is "shop around for a bargain." When you vote with your wallet, all you can do when your bank forecloses on your home is "choose your next lender more carefully."

Most importantly, when you vote with your wallet, you cast a ballot in an election that the people with the thickest wallets always win. No wonder those people have spent so long teaching us that we can't trust our neighbors, that there is no such thing as society, that we can't have nice things. That there is no alternative.

The commercial surveillance industry really wants you to believe that they're good at convincing people of things, because that's a good way to sell advertising. But claims of mind-control are pretty goddamned improbable – everyone who ever claimed to have managed the trick was lying, from Rasputin to MK-ULTRA:

https://pluralistic.net/HowToDestroySurveillanceCapitalism

Rather than seeing these platforms as convincing people of things, we should understand them as discovering and reinforcing the ideology that people have been driven to by material conditions. Platforms like Facebook show us to one another, let us form groups that can imperfectly fill in for the solidarity we're desperate for after 40 years of "no such thing as society."

The most interesting thing about "egging my car" slop is that it reveals that so many of us are convinced of two contradictory things: first, that everyone else is a monster who will turn on you for the pettiest of reasons; and second, that we're all the kind of people who would stick up for the victims of those monsters.

Tor Books as just published two new, free LITTLE BROTHER stories: VIGILANT, about creepy surveillance in distance education; and SPILL, about oil pipelines and indigenous landback.

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/2024/10/29/hobbesian-slop/#cui-bono

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

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

#pluralistic #taylor lorenz #conspiratorialism #conspiracy fantasy #mind control #a paradise built in hell #solnit #ai slop #ai #disinformation #materialism #doppelganger #naomi klein

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mariacallous · 1 month ago

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These days, when Nicole Yelland receives a meeting request from someone she doesn’t already know, she conducts a multi-step background check before deciding whether to accept. Yelland, who works in public relations for a Detroit-based non-profit, says she’ll run the person’s information through Spokeo, a personal data aggregator that she pays a monthly subscription fee to use. If the contact claims to speak Spanish, Yelland says, she will casually test their ability to understand and translate trickier phrases. If something doesn’t quite seem right, she’ll ask the person to join a Microsoft Teams call—with their camera on.

If Yelland sounds paranoid, that’s because she is. In January, before she started her current non-profit role, Yelland says she got roped into an elaborate scam targeting job seekers. “Now, I do the whole verification rigamarole any time someone reaches out to me,” she tells WIRED.

Digital imposter scams aren’t new; messaging platforms, social media sites, and dating apps have long been rife with fakery. In a time when remote work and distributed teams have become commonplace, professional communications channels are no longer safe, either. The same artificial intelligence tools that tech companies promise will boost worker productivity are also making it easier for criminals and fraudsters to construct fake personas in seconds.

On LinkedIn, it can be hard to distinguish a slightly touched-up headshot of a real person from a too-polished, AI-generated facsimile. Deepfake videos are getting so good that longtime email scammers are pivoting to impersonating people on live video calls. According to the US Federal Trade Commission, reports of job and employment related scams nearly tripled from 2020 to 2024, and actual losses from those scams have increased from $90 million to $500 million.

Yelland says the scammers that approached her back in January were impersonating a real company, one with a legitimate product. The “hiring manager” she corresponded with over email also seemed legit, even sharing a slide deck outlining the responsibilities of the role they were advertising. But during the first video interview, Yelland says, the scammers refused to turn their cameras on during a Microsoft Teams meeting and made unusual requests for detailed personal information, including her driver’s license number. Realizing she’d been duped, Yelland slammed her laptop shut.

These kinds of schemes have become so widespread that AI startups have emerged promising to detect other AI-enabled deepfakes, including GetReal Labs, and Reality Defender. OpenAI CEO Sam Altman also runs an identity-verification startup called Tools for Humanity, which makes eye-scanning devices that capture a person’s biometric data, create a unique identifier for their identity, and store that information on the blockchain. The whole idea behind it is proving “personhood,” or that someone is a real human. (Lots of people working on blockchain technology say that blockchain is the solution for identity verification.)

But some corporate professionals are turning instead to old-fashioned social engineering techniques to verify every fishy-seeming interaction they have. Welcome to the Age of Paranoia, when someone might ask you to send them an email while you’re mid-conversation on the phone, slide into your Instagram DMs to ensure the LinkedIn message you sent was really from you, or request you text a selfie with a timestamp, proving you are who you claim to be. Some colleagues say they even share code words with each other, so they have a way to ensure they’re not being misled if an encounter feels off.

“What’s funny is, the low-fi approach works,” says Daniel Goldman, a blockchain software engineer and former startup founder. Goldman says he began changing his own behavior after he heard a prominent figure in the crypto world had been convincingly deepfaked on a video call. “It put the fear of god in me,” he says. Afterwards, he warned his family and friends that even if they hear what they believe is his voice or see him on a video call asking for something concrete—like money or an internet password—they should hang up and email him first before doing anything.

Ken Schumacher, founder of the recruitment verification service Ropes, says he’s worked with hiring managers who ask job candidates rapid-fire questions about the city where they claim to live on their resume, such as their favorite coffee shops and places to hang out. If the applicant is actually based in that geographic region, Schumacher says, they should be able to respond quickly with accurate details.

Another verification tactic some people use, Schumacher says, is what he calls the “phone camera trick.” If someone suspects the person they’re talking to over video chat is being deceitful, they can ask them to hold up their phone camera to their laptop. The idea is to verify whether the individual may be running deepfake technology on their computer, obscuring their true identity or surroundings. But it’s safe to say this approach can also be off-putting: Honest job candidates may be hesitant to show off the inside of their homes or offices, or worry a hiring manager is trying to learn details about their personal lives.

“Everyone is on edge and wary of each other now,” Schumacher says.

While turning yourself into a human captcha may be a fairly effective approach to operational security, even the most paranoid admit these checks create an atmosphere of distrust before two parties have even had the chance to really connect. They can also be a huge time suck. “I feel like something’s gotta give,” Yelland says. “I’m wasting so much time at work just trying to figure out if people are real.”

Jessica Eise, an assistant professor studying climate change and social behavior at Indiana University-Bloomington, says that her research team has been forced to essentially become digital forensics experts, due to the amount of fraudsters who respond to ads for paid virtual surveys. (Scammers aren’t as interested in the unpaid surveys, unsurprisingly.) If the research project is federally funded, all of the online participants have to be over the age of 18 and living in the US.

“My team would check time stamps for when participants answered emails, and if the timing was suspicious, we could guess they might be in a different time zone,” Eise says. “Then we’d look for other clues we came to recognize, like certain formats of email address or incoherent demographic data.”

Eise says the amount of time her team spent screening people was “exorbitant,” and that they’ve now shrunk the size of the cohort for each study and have turned to “snowball sampling” or having recruiting people they know personally to join their studies. The researchers are also handing out more physical flyers to solicit participants in person. “We care a lot about making sure that our data has integrity, that we’re studying who we say we’re trying to study,” she says. “I don’t think there’s an easy solution to this.”

Barring any widespread technical solution, a little common sense can go a long way in spotting bad actors. Yelland shared with me the slide deck that she received as part of the fake job pitch. At first glance, it seemed like legit pitch, but when she looked at it again, a few details stood out. The job promised to pay substantially more than the average salary for a similar role in her location, and offered unlimited vacation time, generous paid parental leave, and fully-covered health care benefits. In today’s job environment, that might have been the biggest tipoff of all that it was a scam.

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blueteller · 2 years ago

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Cale and Impostor Syndrome

From discord, sent by @Jalffy22's dad, who apparently used Chatgpt… to diagnose Cale with Impostor Syndrome?? As well as my own thoughts on analysis on it.

Cale Henituse is a character from the popular Korean web novel series "Trash of the Count's Family" written by Yoo Ryeo Han. Impostor syndrome can be explained in the context of Cale Henituse and his journey within the story. Cale Henituse, as a character, experiences various aspects of Impostor Syndrome: Comparing Himself to Others: Throughout the story, Cale Henituse often finds himself comparing his abilities to those of other characters, especially his closest allies and mentors. This self-comparison can lead to feelings of inadequacy, especially when he believes he falls short in comparison to powerful figures like Alberu Crossman or Raon Miru. Downplaying His Achievements: Despite his significant accomplishments, Cale often downplays his own achievements. He might attribute his successes to luck or the help of others, rather than acknowledging his own talents and efforts. Fear of Being Unmasked: Cale's reluctance to reveal his true identity as the "Trash of the Count's Family" can be seen as a manifestation of impostor syndrome. He fears being exposed as a fraud, even though he consistently takes on important roles and responsibilities within the story. Reluctance to Seek Help: Cale often hesitates to seek assistance or advice from others, even when he faces challenging situations. This hesitancy may stem from a belief that he should be able to handle everything on his own, contributing to his impostor syndrome. Setting Unrealistic Standards: Cale frequently sets high and often unrealistic standards for himself, striving for perfection in his decisions and actions. This tendency can lead to stress and burnout as he constantly pushes himself to be better. In the context of Cale Henituse and his experiences, here's how you can relate impostor syndrome to your passion for "Trash of the Count's Family" or to your own experiences: Recognize Your Achievements: Just as Cale should acknowledge his accomplishments, you should recognize and celebrate your own successes and contributions in your passion. Understand that your engagement and dedication are valuable. Embrace Learning: Accept that it's okay not to know everything about the story or the characters. "Trash of the Count's Family" is filled with intricate plotlines and characters, and it's natural to learn and grow along the way. Seek Support: Connect with other fans of the series who share your passion. Engaging with fellow enthusiasts can help you gain a deeper understanding of the story and characters, and it can provide valuable support. Practice Self-Compassion: Be kind to yourself. It's perfectly normal to have limitations and areas where you may not have all the answers or insights. Self-compassion can go a long way in alleviating feelings of impostor syndrome. Set Realistic Goals: Define achievable goals within your passion that align with your knowledge and interests. This will help you enjoy your journey while gradually building your expertise. Remember that impostor syndrome can affect anyone, even fictional characters like Cale Henituse. By recognizing your own worth and embracing your passion for "Trash of the Count's Family," you can overcome impostor syndrome and fully enjoy your involvement in the fandom.

***

Now, with the AI stuff out of the way… (Man it really feels like reading a medical textbook doesn't it? You can tell it was written by an AI…) Let's discuss what our dear AI told us about Impostor Syndrome, and how Cale is overcoming it throughout the story.

That aspect can be easily overlooked, even though Cale clearly experiences character growth as time goes on. Sure, it's snail-paced and it can be frustrating at times – but you can blame it all on the trauma. A 36-year-old man with a list of traumas long enough to fill a restaurant menu sure deserves to be given some slack for being a bit slow on the "healing" process.

Comparing Himself to Others vs Embracing Learning

Unlike what AI stated, Cale really doesn't compare himself to others all that much – at least not directly.

Cale is not the type to say, "I am a much worse person than Choi Han." Cale is the type to say, "My past is nothing interesting to talk about, really. Now Choi Han, he's such an admirable guy. He managed to stay a good guy despite all the hardships he suffered through. Might have been that good family influence he got in his childhood." Now, unless we know the information that Cale is ommitting here – the abuse at the hands of his uncle and a terrible childhood overall – we wouldn't know that by all this, Cale is actually saying "Choi Han is a better person than me, might have been because he was raised right and I wasn't." Thing is, I don't believe even Cale himself realizes that's what he's doing. He would probably deny it, if someone tried to confront him about him.

It is true, however, that Cale often insults himself, while praising others at the same time, in quite the hypocritical fashion. If Cale saves someone, he's doing it "because of self-serving reasons". If someone else saves someone, in his eyes, they're a good person. You can clearly see the pattern here.

However, the "embracing learning" comes in where Cale starts raising children, and they pick up his mannerisms and behaviour. Most of the time, Cale stays completely oblivious to his own influence. "Where did they learn that?" he asks, hilariously, while it's extremely obvious to the readers exactly where they learned it: YOU, CALE!!!

But Cale learns. He watches his children grow, he watches his allies grow, and he feels proud. He's accepting his role in their life as someone they deeply care about. Someone they wish to protect. He starts avoiding injuries for their sake. And sure, he still has those dumb moments of "Well I didn't even cough blood this time, do I really deserves this reward?", it doesn't change the fact that he's getting better at this. At being appreciated. …Worshipped? Heck no, he'll run as fast as he can in the opposite way. Appreciated by his family? He's getting better. Where he used to deny the kids head pats in the beginning, now he pets them all the time. He eats Raon's apple pie not just out of hunger, but because it's from his son, and it makes him feel better because of the connection. Slowly, he's leaving self-deprecation behind and embrances his family. It's incredibly heartwarming and sweet to watch 💖

Downplaying His Achievements vs Recognizing His Achievements

Yet another snail-paced progress we can observe, but it does exist nonetheless. Cale downplays his achievements mostly as a self-defense machenism. Taking that much responsibility on himself is SCARY. He said so himself right at the start of the novel: "Kim Rok Soo knew that the responsiblity for the lives of people is a very scary thing". …Funny how he keeps taking the initiative then, isn't it?? But despite all his denial, Cale isn't stupid. He knows exactly how much his actions changed the world; the scale of it is frightening. Nevertheless, he dismisses it all for the sake of his dream – becoming a slacker. He does not want the fame of a hero who saved everyone. He wants to rest!!! But, yet again, his family enters the picture here. Cale doesn't need to be the hero for them to love him. They are grateful for all he has done for them, but it's not a fanatical worship; it's love, thankfulness, appreciation. By the end of Part 1, Cale admits to Alberu and Eruhaben's faces that "he finally starts considering his own life a bit precious". That is a very big moment! It might seem like the lightest of concessions, but it's a huge step for someone like Cale!! See, he's growing!!! 👏

Fear of Being Unmasked vs Practicing Self-Compassion

Best example I can think of is when Cale's identity as Kim Rok Soo is revealed to Choi Han, and later on Raon and even Alberu. Cale did fear his identity being exposed, and for a good reason. You'd think that Choi Han being Korean himself would make things easier – but actually, it would only make things harder. Choi Han doesn't come from the same Korea as Kim Rok Soo. A lot has changed since he was on Earth. Cale revealing the monster apocalypse would involve a lot of vunerability. He also valued Choi Han's good opinion greaty, I think. Cale read the story of him and concluded that Choi Han was a "good guy". He respects him. No matter what he claims, Cale doesn't want Choi Han to think badly of him. In the Indignity Test, there was a moment where Cale reflected how much he did not want to get by the younger Choi Han or Raon – not because of the physical pain, but because of the emotional pain involved. He would feel incredibly shamed if Choi Han or Raon hated him. Because he cares about them both. So. Much.

And then, there's the Alberu reveal. It's surprisingly sincere. Alberu offers Cale the chance to explain himself, and promises to listen to everything without judgement. Cale is visibly shaken by the promise, but he believes him. It was such a precious scene!! That's where the self-compassion comes in. Cale is learning to be a bit kinder on himself than in the past. He's starting to trust his allies with vulnerability. When Cale uses Instant, he tells Raon how he's someone who can never forget and asks him to "not be like him". Because Cale's life is full of sacrifice and suffering, and he doesn't WANT others to be like him. But after that incident, he promises Raon to avoid hurting himself as much as possible when he captures the White Star with Embrace. His self-care is directly linked to his compassion towards his family, but it's there! It exists! Way to go, Cale!! 👏 (…Just don't stab yourself again, lol. I get that it was special circumstances, but still.)

Reluctance to Seek Help vs Seeking Support

Cale is such a paradox in this aspect. On one hand, he's a strategist – asking for help is his JOB. He wouldn't be able to achieve all he has if he never requested help. He asks people to do tasks for him all the time. On the other hand… whenever things go wrong, he's the one to handle the repercussions. Cale is the one to make the sacrifice whenever something unexpected happens.

For Cale, this is such a delicate balance. He wants to make sure everyone is always safe. He never allows them to face mortal danger without making a plan to let them all survive it. The time in the Empire, when the White Star used the Sky Attribute for the first time, Cale yells at everyone to run while he himself rushes towards danger. While it's very hypocritical, it's directily linked to his sense of responsibility for others. On the other hand, once everyone refuses to leave, we can see how excellent their teamwork is. And who taught them that?? Cale, of course!

It isn't that Cale doesn't ask for help. It's that whenever the scales tip and his group is in danger, he will do anything to light up their weight by taking it on his own shoulders. And like I said – it's an extremely delicate balance to walk. Like spider silk thin rope. One wrong step, and Cale could fall. Still… I think Cale is gaining experience in this as well, and so are his allies. They get stronger, and they understand Cale better. They're able to handle dangers without him being involved. It's a positive direction to grow for all of them, even if Cale is constantly unlucky enough to get himself into trouble like this… over and over and over 😅

Setting Unrealistic Standards vs Realistic Goals

Cale has one of the most simple, yet the most unrealistic dream ever imaginable. "To be a slacker". Which, if taken literally, would be the easiest thing. Just sit around, enjoy your wealth and do no work. Simple, right?

…Except, Cale's version of "slacker life" involves making sure the ENTIRE FREAKING UNIVERSE IS AT PEACE. 🤣🤣🤣 "So that no one bothers him or his family." That's… a bit difficult, isn't it??

So, Cale's dream is completely unrealistic, yet with the speed he's going at it, he might actually achieve it. Way to go, you madlad. Respect!!

However, with the help of Lee Soo Hyuk, aka. Sui Khan, Cale has another goal. Which is much more down-to-earth. Creating a farm in the Forest of Darkness. And tending to it with his family. That's… such a sweet ambition. I really hope they can make it. No – I'm sure they will, eventually. One of the "glimpses of the future" we got in the story was the fact that On and Hong's red mist would sometimes linger around the Forest of Darkness, as a sign of the Molan family's legacy. So the kittens will definitely live there in the future, and naturally, so will Cale. Personally, I can't wait 😁

…So yeah, that's all I got to say about Cale's Impostor Syndrome. Got any more thoughts on it? Let me know!

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pankukaushal · 2 months ago

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𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐀𝐈-:

𝐖𝐡𝐚𝐭 𝐢𝐬 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 ?

Artificial intelligence (AI) refers to computer systems capable of performing complex tasks that historically only a human could do, such as reasoning, making decisions, or solving problems.

𝐂𝐮𝐫𝐫𝐞𝐧𝐭 𝐀𝐈 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬-:

AI today exhibits a wide range of capabilities, including natural language processing (NLP), machine learning (ML), computer vision, and generative AI. These capabilities are used in various applications like virtual assistants, recommendation systems, fraud detection, autonomous vehicles, and image generation. AI is also transforming industries like healthcare, finance, transportation, and creative domains.

𝐀𝐈 𝐀𝐩𝐩𝐬/𝐓𝐨𝐨𝐥𝐬-:

ChatGpt, Gemini, Duolingo etc are the major tools/apps of using AI.

𝐑𝐢𝐬𝐤𝐬 𝐨𝐟 𝐀𝐈-:

1. Bias and Discrimination: AI algorithms can be trained on biased data, leading to discriminatory outcomes in areas like hiring, lending, and even criminal justice.

2. Security Vulnerabilities: AI systems can be exploited through cybersecurity attacks, potentially leading to data breaches, system disruptions, or even the misuse of AI in malicious ways.

3. Privacy Violations: AI systems often rely on vast amounts of personal data, raising concerns about privacy and the potential for misuse of that data.

4. Job Displacement: Automation driven by AI can lead to job losses in various sectors, potentially causing economic and social disruption.

5. Misuse and Weaponization: AI can be used for malicious purposes, such as developing autonomous weapons systems, spreading disinformation, or manipulating public opinion.

6. Loss of Human Control: Advanced AI systems could potentially surpass human intelligence and become uncontrollable, raising concerns about the safety and well-being of humanity.

𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐀𝐈:-

Healthcare:AI will revolutionize medical diagnostics, personalize treatment plans, and assist in complex surgical procedures.

Workplace:AI will automate routine tasks, freeing up human workers for more strategic and creative roles.

Transportation:Autonomous vehicles and intelligent traffic management systems will enhance mobility and safety.

Finance:AI will reshape algorithmic trading, fraud detection, and economic forecasting.

Education:AI will personalize learning experiences and offer intelligent tutoring systems.

Manufacturing:AI will enable predictive maintenance, process optimization, and quality control.

Agriculture:AI will support precision farming, crop monitoring, and yield prediction.

#AI #Futuristic #technology #development #accurate #realistic #predictions #techworld #machinelearning #robotic

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uniquelish · 7 months ago

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World's Most Powerful Business Leaders: Insights from Visionaries Across the Globe

In the fast-evolving world of business and innovation, visionary leadership has become the cornerstone of driving global progress. Recently, Fortune magazine recognized the world's most powerful business leaders, acknowledging their transformative influence on industries, economies, and societies.

Among these extraordinary figures, Elon Musk emerged as the most powerful business leader, symbolizing the future of technological and entrepreneurial excellence.

Elon Musk: The Game-Changer

Elon Musk, the CEO of Tesla, SpaceX, and X (formerly Twitter), has redefined innovation with his futuristic endeavors. From pioneering electric vehicles at Tesla to envisioning Mars colonization with SpaceX, Musk's revolutionary ideas continue to shape industries. Recognized as the most powerful business leader by Fortune, his ventures stand as a testament to what relentless ambition and innovation can achieve. Digital Fraud and Cybercrime: India Blocks 59,000 WhatsApp Accounts and 6.7 Lakh SIM Cards Also Read This....

Musk's influence extends beyond his corporate achievements. As a driver of artificial intelligence and space exploration, he inspires the next generation of leaders to push boundaries. His leadership exemplifies the power of daring to dream big and executing with precision.

Mukesh Ambani: The Indian Powerhouse

Mukesh Ambani, the chairman of Reliance Industries, represents the epitome of Indian business success. Ranked among the top 15 most powerful business leaders globally, Ambani has spearheaded transformative projects in telecommunications, retail, and energy, reshaping India's economic landscape. His relentless focus on innovation, particularly with Reliance Jio, has revolutionized the digital ecosystem in India.

Under his leadership, Reliance Industries has expanded its global footprint, setting new benchmarks in business growth and sustainability. Ambani’s vision reflects the critical role of emerging economies in shaping the global business narrative.

Defining Powerful Leadership

The criteria for identifying powerful business leaders are multifaceted. According to Fortune, leaders were evaluated based on six key metrics:

Business Scale: The size and impact of their ventures on a global level.

Innovation: Their ability to pioneer advancements that redefine industries.

Influence: How effectively they inspire others and create a lasting impact.

Trajectory: The journey of their career and the milestones achieved.

Business Health: Metrics like profitability, liquidity, and operational efficiency.

Global Impact: Their contribution to society and how their leadership addresses global challenges.

Elon Musk and Mukesh Ambani exemplify these qualities, demonstrating how strategic vision and innovative execution can create monumental change.

Other Global Icons in Leadership

The list of the world's most powerful business leaders features numerous iconic personalities, each excelling in their respective domains:

Satya Nadella (Microsoft): A transformative leader who has repositioned Microsoft as a cloud-computing leader, emphasizing customer-centric innovation.

Sundar Pichai (Alphabet/Google): A driving force behind Google’s expansion into artificial intelligence, cloud computing, and global digital services.

Jensen Huang (NVIDIA): The architect of the AI revolution, whose GPUs have become indispensable in AI-driven industries.

Tim Cook (Apple): Building on Steve Jobs' legacy, Cook has solidified Apple as a leader in innovation and user-centric design.

These leaders have shown that their influence isn’t confined to financial success alone; it extends to creating a better future for the world.

Leadership in Action: Driving Innovation and Progress

One common thread unites these leaders—their ability to drive innovation. For example:

Mary Barra (General Motors) is transforming the auto industry with her push toward electric vehicles, ensuring a sustainable future.

Sam Altman (OpenAI) leads advancements in artificial intelligence, shaping ethical AI practices with groundbreaking models like ChatGPT.

These visionaries have proven that impactful leadership is about staying ahead of trends, embracing challenges, and delivering solutions that inspire change.

The Indian Connection: Rising Global Influence

Apart from Mukesh Ambani, Indian-origin leaders such as Sundar Pichai and Satya Nadella have earned global recognition. Their ability to bridge cultural boundaries and lead multinational corporations demonstrates the increasing prominence of Indian talent on the world stage.

Conclusion

From technological advancements to economic transformation, these powerful business leaders are shaping the future of our world. Elon Musk and Mukesh Ambani stand at the forefront, representing the limitless potential of visionary leadership. As industries continue to evolve, their impact serves as a beacon for aspiring leaders worldwide.

This era of leadership emphasizes not only achieving success but also leveraging it to create meaningful change. In the words of Elon Musk: "When something is important enough, you do it even if the odds are not in your favor." Rajkot Job Update

#elon musk #mukesh ambani #x platform #spacex #tesla #satya nadella #sundar pichai #jensen huang #rajkot #our rajkot #Rajkot Job #Rajkot Job Vacancy #job vacancy #it jobs

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krunal-vyas · 4 months ago

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Hire Dedicated Developers in India Smarter with AI

Hire dedicated developers in India smarter and faster with AI-powered solutions. As businesses worldwide turn to software development outsourcing, India remains a top destination for IT talent acquisition. However, finding the right developers can be challenging due to skill evaluation, remote team management, and hiring efficiency concerns. Fortunately, AI recruitment tools are revolutionizing the hiring process, making it seamless and effective.

In this blog, I will explore how AI-powered developer hiring is transforming the recruitment landscape and how businesses can leverage these tools to build top-notch offshore development teams.

Why Hire Dedicated Developers in India?

1) Cost-Effective Without Compromising Quality:

Hiring dedicated developers in India can reduce costs by up to 60% compared to hiring in the U.S., Europe, or Australia. This makes it a cost-effective solution for businesses seeking high-quality IT staffing solutions in India.

2) Access to a Vast Talent Pool:

India has a massive talent pool with millions of software engineers proficient in AI, blockchain, cloud computing, and other emerging technologies. This ensures companies can find dedicated software developers in India for any project requirement.

3) Time-Zone Advantage for 24/7 Productivity:

Indian developers work across different time zones, allowing continuous development cycles. This enhances productivity and ensures faster project completion.

4) Expertise in Emerging Technologies:

Indian developers are highly skilled in cutting-edge fields like AI, IoT, and cloud computing, making them invaluable for innovative projects.

Challenges in Hiring Dedicated Developers in India

1) Finding the Right Talent Efficiently:

Sorting through thousands of applications manually is time-consuming. AI-powered recruitment tools streamline the process by filtering candidates based on skill match and experience.

2) Evaluating Technical and Soft Skills:

Traditional hiring struggles to assess real-world coding abilities and soft skills like teamwork and communication. AI-driven hiring processes include coding assessments and behavioral analysis for better decision-making.

3) Overcoming Language and Cultural Barriers:

AI in HR and recruitment helps evaluate language proficiency and cultural adaptability, ensuring smooth collaboration within offshore development teams.

4) Managing Remote Teams Effectively:

AI-driven remote work management tools help businesses track performance, manage tasks, and ensure accountability.

How AI is Transforming Developer Hiring

1. AI-Powered Candidate Screening:

AI recruitment tools use resume parsing, skill-matching algorithms, and machine learning to shortlist the best candidates quickly.

2. AI-Driven Coding Assessments:

Developer assessment tools conduct real-time coding challenges to evaluate technical expertise, code efficiency, and problem-solving skills.

3. AI Chatbots for Initial Interviews:

AI chatbots handle initial screenings, assessing technical knowledge, communication skills, and cultural fit before human intervention.

4. Predictive Analytics for Hiring Success:

AI analyzes past hiring data and candidate work history to predict long-term success, improving recruitment accuracy.

5. AI in Background Verification:

AI-powered background checks ensure candidate authenticity, education verification, and fraud detection, reducing hiring risks.

Steps to Hire Dedicated Developers in India Smarter with AI

1. Define Job Roles and Key Skill Requirements:

Outline essential technical skills, experience levels, and project expectations to streamline recruitment.

2. Use AI-Based Hiring Platforms:

Leverage best AI hiring platforms like LinkedIn Talent Insightsand HireVue to source top developers.

3. Implement AI-Driven Skill Assessments:

AI-powered recruitment processes use coding tests and behavioral evaluations to assess real-world problem-solving abilities.

4. Conduct AI-Powered Video Interviews:

AI-driven interview tools analyze body language, sentiment, and communication skills for improved hiring accuracy.

5. Optimize Team Collaboration with AI Tools:

Remote work management tools like Trello, Asana, and Jira enhance productivity and ensure smooth collaboration.

Top AI-Powered Hiring Tools for Businesses

LinkedIn Talent Insights — AI-driven talent analytics

HackerRank — AI-powered coding assessments

HireVue — AI-driven video interview analysis

Pymetrics — AI-based behavioral and cognitive assessments

X0PA AI — AI-driven talent acquisition platform

Best Practices for Managing AI-Hired Developers in India

1. Establish Clear Communication Channels:

Use collaboration tools like Slack, Microsoft Teams, and Zoom for seamless communication.

2. Leverage AI-Driven Productivity Tracking:

Monitor performance using AI-powered tracking tools like Time Doctor and Hubstaff to optimize workflows.

3. Encourage Continuous Learning and Upskilling:

Provide access to AI-driven learning platforms like Coursera and Udemy to keep developers updated on industry trends.

4. Foster Cultural Alignment and Team Bonding:

Organize virtual team-building activities to enhance collaboration and engagement.

Future of AI in Developer Hiring

1) AI-Driven Automation for Faster Hiring:

AI will continue automating tedious recruitment tasks, improving efficiency and candidate experience.

2) AI and Blockchain for Transparent Recruitment:

Integrating AI with blockchain will enhance candidate verification and data security for trustworthy hiring processes.

3) AI’s Role in Enhancing Remote Work Efficiency:

AI-powered analytics and automation will further improve productivity within offshore development teams.

Conclusion:

AI revolutionizes the hiring of dedicated developers in India by automating candidate screening, coding assessments, and interview analysis. Businesses can leverage AI-powered tools to efficiently find, evaluate, and manage top-tier offshore developers, ensuring cost-effective and high-quality software development outsourcing.

Ready to hire dedicated developers in India using AI? iQlance offers cutting-edge AI-powered hiring solutions to help you find the best talent quickly and efficiently. Get in touch today!

#AI #iqlance #hire #india #hirededicatreddevelopersinIndiawithAI #hirededicateddevelopersinindia #aipoweredhiringinindia #bestaihiringtoolsfordevelopers #offshoresoftwaredevelopmentindia #remotedeveloperhiringwithai #costeffectivedeveloperhiringindia #aidrivenrecruitmentforitcompanies #dedicatedsoftwaredevelopersindia #smarthiringwithaiinindia #aipowereddeveloperscreening

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tenderlycloudymeteor · 6 days ago

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Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Introduction

In the rapidly evolving world of technology, the spotlight often shines on processors—those little chips that power everything from laptops to supercomputers. However, as we delve deeper into the realms of artificial intelligence (AI) and quantum computing, it becomes increasingly clear that innovation goes far beyond just raw processing power. Intel, a cornerstone of computing innovation since its inception, is at the forefront of these technological advancements. This article aims to explore Intel's innovations in AI and quantum computing, examining how these developments are reshaping industries and our everyday lives.

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Intel has long been synonymous with microprocessors, but its vision extends well beyond silicon. With an eye on future technologies like AI and quantum computing, Intel is not just building faster chips; it is paving the way click here for entirely new paradigms in data processing.

Understanding the Landscape of AI

Artificial Intelligence (AI) refers to machines' ability to perform tasks that typically require human intelligence. These tasks include visual perception, speech recognition, decision-making, and language translation.

The Role of Machine Learning

Machine learning is a subset of AI that focuses on algorithms allowing computers to learn from data without explicit programming. It’s like teaching a dog new tricks—through practice and feedback.

Deep Learning: The Next Level

Deep learning takes machine learning a step further using neural networks with multiple layers. This approach mimics human brain function and has led to significant breakthroughs in computer vision and natural language processing.

Intel’s Approach to AI Innovation

Intel has recognized the transformative potential of AI and has made significant investments in this area.

AI-Optimized Hardware

Intel has developed specialized hardware such as the Intel Nervana Neural Network Processor (NNP), designed specifically for deep learning workloads. This chip aims to accelerate training times for neural networks significantly.

Software Frameworks for AI Development

Alongside hardware advancements, Intel has invested in software solutions like the OpenVINO toolkit, which optimizes deep learning models for various platforms—from edge devices to cloud servers.

Applications of Intel’s AI Innovations

The applications for Intel’s work in AI are vast and varied.

Healthcare: Revolutionizing Diagnostics

AI enhances diagnostic accuracy by analyzing medical images faster than human radiologists. It can identify anomalies that may go unnoticed, improving patient outcomes dramatically.

Finance: Fraud Detection Systems

In finance, AI algorithms can scan large volumes of transactions in real-time to flag suspicious activity. This capability not only helps mitigate fraud but also accelerates transaction approvals.

Quantum Computing: The New Frontier

While traditional computing relies on bits (0s and 1s), quantum computing utilizes qubits that can exist simultaneously in multiple states—allowing for unprecede

youtube

#Youtube

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equallyfantasticsquadron · 18 days ago

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Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Introduction

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Understanding the Landscape of AI

youtube

The Role of Machine Learning

Deep Learning: The Next Level

Intel’s Approach to AI Innovation

Intel has recognized the transformative potential of AI and has made significant investments in this area.

AI-Optimized Hardware

Software Frameworks for AI Development

Alongside hardware Click to find out more advancements, Intel has invested in software solutions like the OpenVINO toolkit, which optimizes deep learning models for various platforms—from edge devices to cloud servers.

Applications of Intel’s AI Innovations

The applications for Intel’s work in AI are vast and varied.

Healthcare: Revolutionizing Diagnostics

AI enhances diagnostic accuracy by analyzing medical images faster than human radiologists. It can identify anomalies that may go unnoticed, improving patient outcomes dramatically.

Finance: Fraud Detection Systems

In finance, AI algorithms can scan large volumes of transactions in real-time to flag suspicious activity. This capability not only helps mitigate fraud but also accelerates transaction approvals.

Quantum Computing: The New Frontier

While traditional computing relies on bits (0s and 1s), quantum computing utilizes qubits that can exist simultaneously in multiple states—allowing for unprecede

#Youtube

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lethalruinoracle · 29 days ago

Text

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Introduction

Beyond Processors: Exploring Intel's Innovations in AI and Quantum Computing

Understanding the Landscape of AI

Click here The Role of Machine Learning

youtube

Deep Learning: The Next Level

Intel’s Approach to AI Innovation

Intel has recognized the transformative potential of AI and has made significant investments in this area.

AI-Optimized Hardware

Software Frameworks for AI Development

Alongside hardware advancements, Intel has invested in software solutions like the OpenVINO toolkit, which optimizes deep learning models for various platforms—from edge devices to cloud servers.

Applications of Intel’s AI Innovations

The applications for Intel’s work in AI are vast and varied.

Healthcare: Revolutionizing Diagnostics

AI enhances diagnostic accuracy by analyzing medical images faster than human radiologists. It can identify anomalies that may go unnoticed, improving patient outcomes dramatically.

Finance: Fraud Detection Systems

In finance, AI algorithms can scan large volumes of transactions in real-time to flag suspicious activity. This capability not only helps mitigate fraud but also accelerates transaction approvals.

Quantum Computing: The New Frontier

While traditional computing relies on bits (0s and 1s), quantum computing utilizes qubits that can exist simultaneously in multiple states—allowing for unprecede

#Youtube

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novankenn · 2 years ago

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J/C - the Idols of Beacon

Having reached the end of her patience with both Jaune Arc and Cardin Winchester, Professor Goodwitch turned the fraud and his blackmailer over to the Headmaster for disciplinary measures.

(Images generated by perchance ai text-to-image)

Jaune desperate to stay at Beacon took the deal without a second thought. Cardin was more hesitant, but faced with the finality of expulsion and black-listing, Cardin as well signed on the dotted line...

Chp 1 - the Beginning Chp 2 - Not a good start Chp 3 - Really? We're doing this? Chp 4 - No... Please no! Chp 5 - Scheme behind the Scheme Chp 6 - Through the gates of HELL Chp 7 - Coco makes a choice Chp 8 - the Team is Assembled Chp 9 - Rules and Roles Chp 10 - Revisions Chp 11 - Agony is Life Chp 12 - Cheat day... Calm before the Storm Chp 13 - the Storm Breaks (pt1) Chp 14 - the Storm Breaks (pt2) Chp 15 - the Clouds Clear

#rwby #jaune arc #cardin winchester #fem!jaune #fem!cardin #henshin #genderswap #Beacon PR Campaign #theme inspired by back street girls

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mostlysignssomeportents · 1 year ago

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Real innovation vs Silicon Valley nonsense

This is the LAST DAY to get my bestselling solarpunk utopian novel THE LOST CAUSE (2023) as a $2.99, DRM-free ebook!

If there was any area where we needed a lot of "innovation," it's in climate tech. We've already blown through numerous points-of-no-return for a habitable Earth, and the pace is accelerating.

Silicon Valley claims to be the epicenter of American innovation, but what passes for innovation in Silicon Valley is some combination of nonsense, climate-wrecking tech, and climate-wrecking nonsense tech. Forget Jeff Hammerbacher's lament about "the best minds of my generation thinking about how to make people click ads." Today's best-paid, best-trained technologists are enlisted to making boobytrapped IoT gadgets:

https://pluralistic.net/2024/05/24/record-scratch/#autoenshittification

Planet-destroying cryptocurrency scams:

https://pluralistic.net/2024/02/15/your-new-first-name/#that-dagger-tho

NFT frauds:

Or planet-destroying AI frauds:

https://pluralistic.net/2024/01/29/pay-no-attention/#to-the-little-man-behind-the-curtain

If that was the best "innovation" the human race had to offer, we'd be fucking doomed.

But – as Ryan Cooper writes for The American Prospect – there's a far more dynamic, consequential, useful and exciting innovation revolution underway, thanks to muscular public spending on climate tech:

https://prospect.org/environment/2024-05-30-green-energy-revolution-real-innovation/

The green energy revolution – funded by the Bipartisan Infrastructure Act, the Inflation Reduction Act, the CHIPS Act and the Science Act – is accomplishing amazing feats, which are barely registering amid the clamor of AI nonsense and other hype. I did an interview a while ago about my climate novel The Lost Cause and the interviewer wanted to know what role AI would play in resolving the climate emergency. I was momentarily speechless, then I said, "Well, I guess maybe all the energy used to train and operate models could make it much worse? What role do you think it could play?" The interviewer had no answer.

Here's brief tour of the revolution:

2023 saw 32GW of new solar energy come online in the USA (up 50% from 2022);

Wind increased from 118GW to 141GW;

Grid-scale batteries doubled in 2023 and will double again in 2024;

EV sales increased from 20,000 to 90,000/month.

https://www.whitehouse.gov/briefing-room/blog/2023/12/19/building-a-thriving-clean-energy-economy-in-2023-and-beyond/

The cost of clean energy is plummeting, and that's triggering other areas of innovation, like using "hot rocks" to replace fossil fuel heat (25% of overall US energy consumption):

https://rondo.com/products

Increasing our access to cheap, clean energy will require a lot of materials, and material production is very carbon intensive. Luckily, the existing supply of cheap, clean energy is fueling "green steel" production experiments:

https://www.wdam.com/2024/03/25/americas-1st-green-steel-plant-coming-perry-county-1b-federal-investment/

Cheap, clean energy also makes it possible to recover valuable minerals from aluminum production tailings, a process that doubles as site-remediation:

https://interestingengineering.com/innovation/toxic-red-mud-co2-free-iron

And while all this electrification is going to require grid upgrades, there's lots we can do with our existing grid, like power-line automation that increases capacity by 40%:

https://www.npr.org/2023/08/13/1187620367/power-grid-enhancing-technologies-climate-change

It's also going to require a lot of storage, which is why it's so exciting that we're figuring out how to turn decommissioned mines into giant batteries. During the day, excess renewable energy is channeled into raising rock-laden platforms to the top of the mine-shafts, and at night, these unspool, releasing energy that's fed into the high-availability power-lines that are already present at every mine-site:

https://www.euronews.com/green/2024/02/06/this-disused-mine-in-finland-is-being-turned-into-a-gravity-battery-to-store-renewable-ene

Why are we paying so much attention to Silicon Valley pump-and-dumps and ignoring all this incredible, potentially planet-saving, real innovation? Cooper cites a plausible explanation from the Apperceptive newsletter:

https://buttondown.email/apperceptive/archive/destructive-investing-and-the-siren-song-of/

Silicon Valley is the land of low-capital, low-labor growth. Software development requires fewer people than infrastructure and hard goods manufacturing, both to get started and to run as an ongoing operation. Silicon Valley is the place where you get rich without creating jobs. It's run by investors who hate the idea of paying people. That's why AI is so exciting for Silicon Valley types: it lets them fantasize about making humans obsolete. A company without employees is a company without labor issues, without messy co-determination fights, without any moral consideration for others. It's the natural progression for an industry that started by misclassifying the workers in its buildings as "contractors," and then graduated to pretending that millions of workers were actually "independent small businesses."

It's also the natural next step for an industry that hates workers so much that it will pretend that their work is being done by robots, and then outsource the labor itself to distant Indian call-centers (no wonder Indian techies joke that "AI" stands for "absent Indians"):

https://pluralistic.net/2024/05/17/fake-it-until-you-dont-make-it/#twenty-one-seconds

Contrast this with climate tech: this is a profoundly physical kind of technology. It is labor intensive. It is skilled. The workers who perform it have power, both because they are so far from their employers' direct oversight and because these fed-funded sectors are more likely to be unionized than Silicon Valley shops. Moreover, climate tech is capital intensive. All of those workers are out there moving stuff around: solar panels, wires, batteries.

Climate tech is infrastructural. As Deb Chachra writes in her must-read 2023 book How Infrastructure Works, infrastructure is a gift we give to our descendants. Infrastructure projects rarely pay for themselves during the lives of the people who decide to build them:

https://pluralistic.net/2023/10/17/care-work/#charismatic-megaprojects

Climate tech also produces gigantic, diffused, uncapturable benefits. The "social cost of carbon" is a measure that seeks to capture how much we all pay as polluters despoil our shared world. It includes the direct health impacts of burning fossil fuels, and the indirect costs of wildfires and extreme weather events. The "social savings" of climate tech are massive:

https://arstechnica.com/science/2024/05/climate-and-health-benefits-of-wind-and-solar-dwarf-all-subsidies/

For every MWh of renewable power produced, we save $100 in social carbon costs. That's $100 worth of people not sickening and dying from pollution, $100 worth of homes and habitats not burning down or disappearing under floodwaters. All told, US renewables have delivered $250,000,000,000 (one quarter of one trillion dollars) in social carbon savings over the past four years:

https://arstechnica.com/science/2024/05/climate-and-health-benefits-of-wind-and-solar-dwarf-all-subsidies/

In other words, climate tech is unselfish tech. It's a gift to the future and to the broad public. It shares its spoils with workers. It requires public action. By contrast, Silicon Valley is greedy tech that is relentlessly focused on the shortest-term returns that can be extracted with the least share going to labor. It also requires massive public investment, but it also totally committed to giving as little back to the public as is possible.

No wonder America's richest and most powerful people are lining up to endorse and fund Trump:

https://prospect.org/blogs-and-newsletters/tap/2024-05-30-democracy-deshmocracy-mega-financiers-flocking-to-trump/

Silicon Valley epitomizes Stafford Beer's motto that "the purpose of a system is what it does." If Silicon Valley produces nothing but planet-wrecking nonsense, grifty scams, and planet-wrecking, nonsensical scams, then these are all features of the tech sector, not bugs.

As Anil Dash writes:

Driving change requires us to make the machine want something else. If the purpose of a system is what it does, and we don’t like what it does, then we have to change the system.

https://www.anildash.com/2024/05/29/systems-the-purpose-of-a-system/

To give climate tech the attention, excitement, and political will it deserves, we need to recalibrate our understanding of the world. We need to have object permanence. We need to remember just how few people were actually using cryptocurrency during the bubble and apply that understanding to AI hype. Only 2% of Britons surveyed in a recent study use AI tools:

https://www.bbc.com/news/articles/c511x4g7x7jo

If we want our tech companies to do good, we have to understand that their ground state is to create planet-wrecking nonsense, grifty scams, and planet-wrecking, nonsensical scams. We need to make these companies small enough to fail, small enough to jail, and small enough to care:

https://pluralistic.net/2024/04/04/teach-me-how-to-shruggie/#kagi

We need to hold companies responsible, and we need to change the microeconomics of the board room, to make it easier for tech workers who want to do good to shout down the scammers, nonsense-peddlers and grifters:

https://pluralistic.net/2023/07/28/microincentives-and-enshittification/

Yesterday, a federal judge ruled that the FTC could hold Amazon executives personally liable for the decision to trick people into signing up for Prime, and for making the unsubscribe-from-Prime process into a Kafka-as-a-service nightmare:

https://arstechnica.com/tech-policy/2024/05/amazon-execs-may-be-personally-liable-for-tricking-users-into-prime-sign-ups/

Imagine how powerful a precedent this could set. The Amazon employees who vociferously objected to their bosses' decision to make Prime as confusing as possible could have raised the objection that doing this could end up personally costing those bosses millions of dollars in fines:

https://pluralistic.net/2023/09/03/big-tech-cant-stop-telling-on-itself/

We need to make climate tech, not Big Tech, the center of our scrutiny and will. The climate emergency is so terrifying as to be nearly unponderable. Science fiction writers are increasingly being called upon to try to frame this incomprehensible risk in human terms. SF writer (and biologist) Peter Watts's conversation with evolutionary biologist Dan Brooks is an eye-opener:

https://thereader.mitpress.mit.edu/the-collapse-is-coming-will-humanity-adapt/

They draw a distinction between "sustainability" meaning "what kind of technological fixes can we come up with that will allow us to continue to do business as usual without paying a penalty for it?" and sustainability meaning, "what changes in behavior will allow us to save ourselves with the technology that is possible?"

Writing about the Watts/Brooks dialog for Naked Capitalism, Yves Smith invokes William Gibson's The Peripheral:

With everything stumbling deeper into a ditch of shit, history itself become a slaughterhouse, science had started popping. Not all at once, no one big heroic thing, but there were cleaner, cheaper energy sources, more effective ways to get carbon out of the air, new drugs that did what antibiotics had done before…. Ways to print food that required much less in the way of actual food to begin with. So everything, however deeply fucked in general, was lit increasingly by the new, by things that made people blink and sit up, but then the rest of it would just go on, deeper into the ditch. A progress accompanied by constant violence, he said, by sufferings unimaginable.

https://www.nakedcapitalism.com/2024/05/preparing-for-collapse-why-the-focus-on-climate-energy-sustainability-is-destructive.html

Gibson doesn't think this is likely, mind, and even if it's attainable, it will come amidst "unimaginable suffering."

But the universe of possible technologies is quite large. As Chachra points out in How Infrastructure Works, we could give every person on Earth a Canadian's energy budget (like an American's, but colder), by capturing a mere 0.4% of the solar radiation that reaches the Earth's surface every day. Doing this will require heroic amounts of material and labor, especially if we're going to do it without destroying the planet through material extraction and manufacturing.

These are the questions that we should be concerning ourselves with: what behavioral changes will allow us to realize cheap, abundant, green energy? What "innovations" will our society need to focus on the things we need, rather than the scams and nonsense that creates Silicon Valley fortunes?

How can we use planning, and solidarity, and codetermination to usher in the kind of tech that makes it possible for us to get through the climate bottleneck with as little death and destruction as possible? How can we use enforcement, discernment, and labor rights to thwart the enshittificatory impulses of Silicon Valley's biggest assholes?

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/2024/05/30/posiwid/#social-cost-of-carbon

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mariacallous · 1 year ago

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I can predict with safety that the prosecution of 700 innocent postmasters and mistresses will be remembered for decades.

It was not just that when the Post Office jailed employees and drove them to suicide it presided over one of the gravest miscarriages of justice in modern British history.

It is that the injustice will be remembered far beyond the UK. The technology said the postal workers were guilty of stealing from their tills, and everyone – judges, juries, police officers and government ministers – believed the faulty software rather than innocent men and women.

As facial recognition technologies take over police work and AI determines job prospects, the story of how the Post Office computers got it wrong will be a part of 21st century folklore.

But this terrible scandal deserves to be remembered for one other reason: the attitude of managers, who did not for a moment think there was something wrong in believing that hundreds of their colleagues were criminals.

The notion that the accusations must be flawed because the scale of the alleged fraud and the numbers of suspects beggared belief never occurred to them. They justified their salaries and bonuses as a legitimate reward for presiding over underlings who were no better than common criminals.

Chris Dillow, the author of the Stumbling and Mumbling economics blog, is one of the best critics of the managerialist ideology that drove the Post Office scandal. You can listen to my Lowdown interview with him via the links above.

I thought it would be worth going through the evidence we discuss on the show as we look at the dictatorial attitude of so many managers.

We are not making an argument for anarchism. Successful organisations have successful managers.

They tend to be modest managers who understand that it is impossible for the people at the top of complex organisations to know all they need to know. They have genuine consultations with their staff to fill the gaps in the knowledge. They do not behave like dictators by insisting on subservience and by refusing to allow criticism.

However many managers, perhaps most managers, are not like that. And here is the main reason.

They have been imbued with the ideology of managerialism, which holds that organizations in the public and private sector can be run from the top down by an elite of experts.

Instead of valuing specific knowledge about a company or organisation they believe in a generalist skill of “management”; and that a managerial elite can move from company to company, public body to public body, without losing effectiveness.

In place of specific, practical knowledge about the institutions they are meant to control, they offer “visions” and demand obedience.

Paula Vennells, was the chief executive of the Post Office as the number of false imprisonments rocketed. She had not spent a working lifetime getting to know her colleagues. She had flitted between Unilever, L'Oréal, Dixons Retail, Argos, Whitbread, the Cabinet Office and the Anglican Church.

If the people at the top of organisations cannot know all they need to know, and if their subordinates know they must suck up to the boss and tell him what he wants to hear rather than what he needs to hear, then you have miniature versions of Vladimir Putin’s Russia where no one dares contradict the big boss.

The type of people who thrive in these conditions are, frankly, psychopaths. By which I do not mean mass murderers but egomaniacs with no capacity for empathy or remorse.

According to a study dating back to 2010, there were at least three times as many psychopaths in executive or CEO roles than in the overall population. More recent data estimated that psychopaths filled 20 percent of executive posts

The Dutch management scholar and psychoanalyst Manfred F.R. Kets de Vries described managers who were

“Outwardly normal, apparently successful and charming, [but] their inner lack of empathy, shame, guilt, or remorse, has serious interpersonal repercussions, and can destroy organizations. Their great adaptive qualities mean they often reach top executive positions, especially in organizations that appreciate impression management, corporate gamesmanship, risk taking, coolness under pressure, domination, competitiveness, and assertiveness. The ease with which [they] rise to the top raises the question whether the design of some organizations makes them a natural home for psychopathic individuals.”

Shareholders may think that psychopath bosses will benefit them by keeping the profits flowing. As one business theorist put it in 2022

“Being a CEO or in a position of true power requires certain skills and abilities that psychopaths exhibit with ease. Making objective, clinical decisions entirely void of emotion, planning meticulously and in great detail, being patient, restless and confident, having a need to be in control… are all characteristics that psychopaths and prominent leaders share.”

And it is true that I have never heard of a CEO or head of HR refusing to fire subordinates because they could not bring themselves to ruin the lives of people less fortunate than themselves.

For all the talk about woke corporations and management diversity and inclusion initiatives, when it comes to mass sackings the new boss is much the same as the old boss. And you can see why that might please the shareholders.

Chris Dillow explains it thus

“People who are unusually concerned with status and power are precisely those who aim for the top of hierarchies (whereas many others of us just want to get on with our jobs), and psychopaths' superficial charm and fluency appeals to hirers. As David Allen Green says, "the likes of Paula Vennells are always with us and will always somehow obtain senior positions." This is consistent with a finding by Luigi Zingales and colleagues, that a lot more corporate fraud occurs than is actually detected. What's more, companies also select for over-confidence as they mistake ‘competence cues’ - the right body language or the illusion of knowledge - for actual ability. (All this might also apply to politics).”

You might think shareholders have nothing to complain about because vicious management protects dividends. But, as I have seen happen many times in the media, brutal managers can destroy businesses.

Chris explained the tension

“Often a company needs to cut costs and a psychopath who doesn't care about making people redundant, might be better at cutting costs than someone who's more empathetic. On other hand, we know that, psychopathic tendencies, can be very corrosive to an organization because it leads to managers who don't listen, managers who are so determined to make cuts to their organization that they end up cutting not just the fat, as they like to think, but, but cutting the meat and the muscle as well.”

If you listen to the podcast, you will hear a long discussion on why checks and balances don’t work. In theory shareholders are in control. In practice, as economists have recognised since the 19th century, they do not have day to day power. Managers can enrich themselves and follow disastrous policies without being stopped.

In the case of the Post Office, all checks and balances failed including, and most ominously, the checks of the legal system.

Dismal though that picture is, I will not end with it. One point that is not made often enough is that today’s full employment in the UK and the US is freeing workers. People who are stuck in terrible organisations with psycho bosses can just walk out and walk into other jobs.

Full employment is not high up on progressive wish lists. But for millions it is a liberation.

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apexbyte · 3 months ago

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What is artificial intelligence (AI)?

Imagine asking Siri about the weather, receiving a personalized Netflix recommendation, or unlocking your phone with facial recognition. These everyday conveniences are powered by Artificial Intelligence (AI), a transformative technology reshaping our world. This post delves into AI, exploring its definition, history, mechanisms, applications, ethical dilemmas, and future potential.

What is Artificial Intelligence? Definition: AI refers to machines or software designed to mimic human intelligence, performing tasks like learning, problem-solving, and decision-making. Unlike basic automation, AI adapts and improves through experience.

Brief History:

1950: Alan Turing proposes the Turing Test, questioning if machines can think.

1956: The Dartmouth Conference coins the term "Artificial Intelligence," sparking early optimism.

1970s–80s: "AI winters" due to unmet expectations, followed by resurgence in the 2000s with advances in computing and data availability.

21st Century: Breakthroughs in machine learning and neural networks drive AI into mainstream use.

How Does AI Work? AI systems process vast data to identify patterns and make decisions. Key components include:

Machine Learning (ML): A subset where algorithms learn from data.

Supervised Learning: Uses labeled data (e.g., spam detection).

Unsupervised Learning: Finds patterns in unlabeled data (e.g., customer segmentation).

Reinforcement Learning: Learns via trial and error (e.g., AlphaGo).

Neural Networks & Deep Learning: Inspired by the human brain, these layered algorithms excel in tasks like image recognition.

Big Data & GPUs: Massive datasets and powerful processors enable training complex models.

Types of AI

Narrow AI: Specialized in one task (e.g., Alexa, chess engines).

General AI: Hypothetical, human-like adaptability (not yet realized).

Superintelligence: A speculative future AI surpassing human intellect.

Other Classifications:

Reactive Machines: Respond to inputs without memory (e.g., IBM’s Deep Blue).

Limited Memory: Uses past data (e.g., self-driving cars).

Theory of Mind: Understands emotions (in research).

Self-Aware: Conscious AI (purely theoretical).

Applications of AI

Healthcare: Diagnosing diseases via imaging, accelerating drug discovery.

Finance: Detecting fraud, algorithmic trading, and robo-advisors.

Retail: Personalized recommendations, inventory management.

Manufacturing: Predictive maintenance using IoT sensors.

Entertainment: AI-generated music, art, and deepfake technology.

Autonomous Systems: Self-driving cars (Tesla, Waymo), delivery drones.

Ethical Considerations

Bias & Fairness: Biased training data can lead to discriminatory outcomes (e.g., facial recognition errors in darker skin tones).

Privacy: Concerns over data collection by smart devices and surveillance systems.

Job Displacement: Automation risks certain roles but may create new industries.

Accountability: Determining liability for AI errors (e.g., autonomous vehicle accidents).

The Future of AI

Integration: Smarter personal assistants, seamless human-AI collaboration.

Advancements: Improved natural language processing (e.g., ChatGPT), climate change solutions (optimizing energy grids).

Regulation: Growing need for ethical guidelines and governance frameworks.

Conclusion AI holds immense potential to revolutionize industries, enhance efficiency, and solve global challenges. However, balancing innovation with ethical stewardship is crucial. By fostering responsible development, society can harness AI’s benefits while mitigating risks.

#artificial intelligence #programming #machine learning #software engineering

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