#friendly AI

[ixnai]

The allure of speed in technology development is a siren’s call that has led many innovators astray. “Move fast and break things” is a mantra that has driven the tech industry for years, but when applied to artificial intelligence, it becomes a perilous gamble. The rapid iteration and deployment of AI systems without thorough vetting can lead to catastrophic consequences, akin to releasing a flawed algorithm into the wild without a safety net.

AI systems, by their very nature, are complex and opaque. They operate on layers of neural networks that mimic the human brain’s synaptic connections, yet they lack the innate understanding and ethical reasoning that guide human decision-making. The haste to deploy AI without comprehensive testing is akin to launching a spacecraft without ensuring the integrity of its navigation systems. The potential for error is not just probable; it is inevitable.

The pitfalls of AI are numerous and multifaceted. Bias in training data can lead to discriminatory outcomes, while lack of transparency in decision-making processes can result in unaccountable systems. These issues are compounded by the “black box” nature of many AI models, where even the developers cannot fully explain how inputs are transformed into outputs. This opacity is not merely a technical challenge but an ethical one, as it obscures accountability and undermines trust.

To avoid these pitfalls, a paradigm shift is necessary. The development of AI must prioritize robustness over speed, with a focus on rigorous testing and validation. This involves not only technical assessments but also ethical evaluations, ensuring that AI systems align with societal values and norms. Techniques such as adversarial testing, where AI models are subjected to challenging scenarios to identify weaknesses, are crucial. Additionally, the implementation of explainable AI (XAI) can demystify the decision-making processes, providing clarity and accountability.

Moreover, interdisciplinary collaboration is essential. AI development should not be confined to the realm of computer scientists and engineers. Ethicists, sociologists, and legal experts must be integral to the process, providing diverse perspectives that can foresee and mitigate potential harms. This collaborative approach ensures that AI systems are not only technically sound but also socially responsible.

In conclusion, the reckless pursuit of speed in AI development is a dangerous path that risks unleashing untested and potentially harmful technologies. By prioritizing thorough testing, ethical considerations, and interdisciplinary collaboration, we can harness the power of AI responsibly. The future of AI should not be about moving fast and breaking things, but about moving thoughtfully and building trust.

[sockiepuppetry]

Remember, it's never too late to pick up a pencil and learn. It may not be easy at first, but trust me it'll be worth it! Like, I know my art isn't "perfect" but I try and that what counts! "It's the journey not the destination"

And for any of you AI bros out there, you don't have to steal, you can embrace what it means to be human and create!

[kingofattolia]

Usually finding out you have something in common with a new acquaintance is a positive thing, but sometimes it's extremely dangerous. If I meet someone who's also into writing, that's like an even 50/50 on whether we should be best friends OR whether every time they open their mouth I will be manfully restraining myself from fistfighting them on the sidewalk outside this bougie downtown brunch spot.

[creampuffqueen]

“don’t blame peoples’ individual choices of using ai for climate change, blame the big corporations!!”

i’m gonna hold your hand when i say this. generative ai is the big corporation, and this product only continues to exist because of peoples’ individual choices to use it

[handsometimr]

psyncer clover au ough

[soundleer]

friendly reminder!! human art—mii art, in this case—is infinitely better!!! 💜🫶✏

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still ver:

[elbiotipo]

The easiest and sure way of telling if something is written by ChatGPT is because it always has to, in whatever it writes, to wrap it up with some kind of conclusion (con un moño as I say), and it's VERY, VERY conspicous, there is ALWAYS a conclusion. It's always "in summary/in conclusion/overall/stands as a testament". It NEVER, EVER writes anything without some sort of conclusion, and even if you ask it not to, it always tries to somehow shoehorn some sort of conclusion, summary, or a moral or a happy ending (if you ask it for prose writing), it's deeply coded into it. Another thing, it is always wholesome, eager to please and sickengly optimist, like the most eager costumer service of all time (because it was designed for it and really nothing else), it is almost impossible to ask it to write anything cynical, it's really almost funny how it is.

So, vague, cynical, esoteric, incomprehensible, resentful and rambling pointless rants is the sign of something written by a real human.

[ixnai]

AI is not a panacea. This assertion may seem counterintuitive in an era where artificial intelligence is heralded as the ultimate solution to myriad problems. However, the reality is far more nuanced and complex. AI, at its core, is a sophisticated algorithmic construct, a tapestry of neural networks and machine learning models, each with its own limitations and constraints.

The allure of AI lies in its ability to process vast datasets with speed and precision, uncovering patterns and insights that elude human cognition. Yet, this capability is not without its caveats. The architecture of AI systems, often built upon layers of deep learning frameworks, is inherently dependent on the quality and diversity of the input data. This dependency introduces a significant vulnerability: bias. When trained on skewed datasets, AI models can perpetuate and even exacerbate existing biases, leading to skewed outcomes that reflect the imperfections of their training data.

Moreover, AI’s decision-making process, often described as a “black box,” lacks transparency. The intricate web of weights and biases within a neural network is not easily interpretable, even by its creators. This opacity poses a challenge for accountability and trust, particularly in critical applications such as healthcare and autonomous vehicles, where understanding the rationale behind a decision is paramount.

The computational prowess of AI is also bounded by its reliance on hardware. The exponential growth of model sizes, exemplified by transformer architectures like GPT, demands immense computational resources. This requirement not only limits accessibility but also raises concerns about sustainability and energy consumption. The carbon footprint of training large-scale AI models is non-trivial, challenging the narrative of AI as an inherently progressive technology.

Furthermore, AI’s efficacy is context-dependent. While it excels in environments with well-defined parameters and abundant data, its performance degrades in dynamic, uncertain settings. The rigidity of algorithmic logic struggles to adapt to the fluidity of real-world scenarios, where variables are in constant flux and exceptions are the norm rather than the exception.

In conclusion, AI is a powerful tool, but it is not a magic bullet. It is a complex, multifaceted technology that requires careful consideration and responsible deployment. The promise of AI lies not in its ability to solve every problem, but in its potential to augment human capabilities and drive innovation, provided we remain vigilant to its limitations and mindful of its impact.

[kindahoping4forever]

Via Ash on IG

[frameacloud]

A Masterpost About Long-Acting Reversible Contraceptives (LARCs)

During the upcoming presidency, it is likely that people in the US will lose many options that keep them from getting pregnant (contraceptives). The right-wing Project 2025 is against birth control pills, abortion, emergency contraception, and the government-provided health insurance ("Obamacare," Medicaid, and Medicare) that helps people afford these.

If you or your partner are concerned about the possibility of losing access to those options soon, you can ask your doctor or Planned Parenthood about getting a Long-Acting Reversible Contraceptive (LARC). The two kinds of LARCs are IUDs and the implant. If you get a LARC right now, it can protect you for years, without you having to do anything to maintain it. A LARC isn't permanent, so you can get rid of it if you later decide that you're ready to have a baby.

Hormonal Intrauterine Device: 3, 5, or 8 years of protection, depending on brand

An IUD is a T-shaped object that a nurse or doctor puts into your uterus. It's tiny, just a little more than an inch. The procedure for getting an IUD isn't surgery, it lasts just a few minutes, and it goes much better if you ask for an anti-anxiety medicine and the right type of painkiller.

Hormonal IUDs work because they slowly release progestin. That's the main hormone in birth control pills. Like pills, they can make your periods get lighter or stop, which is helpful for people who need to get rid of cramps and PMS.

Of the brands of them in the US, the FDA currently approves of using Kyleena for up to five years, Liletta for eight, Mirena for eight, and Skyla for three. Kyleena and Skyla are smallest and therefore easiest to insert.

I have more info in my tags about IUDs.

Copper IUDs: 12 years of protection

The other type of IUD is a copper IUD. Instead of changing your hormones, it works because copper makes the place unfriendly to sperm. Another difference is that this kind can make your periods heavier. Its brand name is Paragard. The FDA approves of using it for ten years, but studies show it's still good at twelve or longer. More info in my tags.

The birth control implant: 5 years of protection

It's a rod the size of a matchstick. A nurse or doctor uses an applicator to put it under your skin in your arm. There, it will slowly release progestin to protect you from getting pregnant. It can make your periods get lighter or stop. The FDA approves of using it for three years, but a study shows it's still 100% effective five years later, and so does another study. Its brand name is Nexplanon, which has improvements over the older Implanon, such as being visible on X-ray. More info in my tags.

Some honorable mentions

There are some other contraceptives that last a long time but aren't considered LARCs. The diaphragm and the cervical cap are two kinds of plastic cap that you put on your cervix each time before sex, and you can keep using the same one for two years. The birth control ring, Annovera, lasts one year. Each injection of the birth control shot, Depo-Provera, lasts three months.

Only barrier methods such as condoms, internal condoms, and dental dams can protect against sexually transmitted infections. The right wing wants to stop people from getting condoms, too. That's another problem, but LARCs can help us get through the next four years without unplanned pregnancies.

[gojoest]

hello dashster, i am considering slowly making my way back here bc i miss you ! i have one tiny thing to say before i go back to my regular posting though — now this could mean 2 things, but fyi we all hate ai in this house

[annatheforgotten]

Testing out some styling for generic males and females, will make body types and androgynous ponies next. Any advice to make the style more consistent? Maybe thinner snouts?

[herssian]

do people know in divinity original sin 1 you get to play literal rock paper scissors with your fellow protagonist if you've disagreed on something and whoever wins gets to make the choice. this is a real mechanic in a real video game

[nentuaby]

Useful to remember: "AI" and "real photo" aren't a dichotomy. There's still good old-fashioned, artisanal free range fake shit out there, of both the photo-edited and in-camera varieties!

[xanderisrotting]

The absolute irony

Nothing say’s eco friendly like an ai generated image posted as an ad touting  the benefits of an eco friendly lifestyle