Wikipedia:

The purpose of a system is what it does (POSIWID) is a heuristic in systems thinking coined by the British management consultant Stafford Beer, who stated that there is “no point in claiming that the purpose of a system is to do what it constantly fails to do”. It is used in systems theory, and is generally invoked to counter the notion that the purpose of a system can or should be read from the intentions of those who design, operate, or promote it. When a system’s side effects or unintended consequences reveal that its behaviour is poorly understood, then the POSIWID perspective can balance political understandings of system behaviour with a more straightforwardly descriptive view.

I don’t recall seeing POSIWID before, but I love the concept. A friend sent this to me, with the quip that I forgot to include a link to it in my “What Is the Point of the DMA?” piece this week. Indeed, it encapsulates my arguments about the DMA specifically and the European Commission generally. The purpose the DMA is what it does, not what you imagine it is intended to do.

In the same vein, I have been thinking too about the famous anecdote reported by Adam Lashinsky for Fortune back in 2011:

Steve Jobs doesn’t tolerate duds. Shortly after the launch event, he summoned the MobileMe team, gathering them in the Town Hall auditorium in Building 4 of Apple’s campus, the venue the company uses for intimate product unveilings for journalists. According to a participant in the meeting, Jobs walked in, clad in his trademark black mock turtleneck and blue jeans, clasped his hands together, and asked a simple question:

“Can anyone tell me what MobileMe is supposed to do?” Having received a satisfactory answer, he continued, “So why the fuck doesn’t it do that?”

You can argue all you want that the DMA is intended to give developers and users choice and freedom. My retort is “So why the fuck doesn’t it do that?” The DMA is what it does — and it isn’t that.

(Also, if you follow the link quoted above to Stafford Beer’s Wikipedia entry — man, put a hat on that guy and damned if he doesn’t look like Jim Dalrymple. It would be even more uncanny if his name had been Stafford Heineken.)

"The Bill’s rhetorical appeal rests on the idea that it targets under-16s. Its mechanism does not.

"To reliably prevent a 15-year-old from holding an account, a platform must satisfy itself about the age of every account-holder — which in practice means age-assuring the entire adult population as well.

"Privacy Commissioner Michael Webster made the point bluntly when the policy was first floated. Keeping under-16s out means ... everyone will have to demonstrate they are not under sixteen, including you.

"This is the paradox the Bill never resolves, and it is not a drafting quibble but the whole problem. ... "[L]iberal societies are meant to presume adults free unless there is an overwhelming reason to constrain them, not to demand identification as the price of entry to the public square.
The Bill’s privacy safeguards, though real, do not answer this."

~ David Harvey from his post 'A Law That the People It Targets Can Defeat With a Felt-Tip Pen'

It seems that everyone is talking about data centers these days; they’ve taken over the Internet with memes and conspiracy theories. As a computer professor, I decided to apply an academic research regimen to the situation and cut through the exaggeration and emotion that often accompany these current polarizing issues.

Two important points to begin with: AI’s water and power usage. As I have demonstrated in my previous article, data centers use about 0.02% of the water supply in the US according to recent sources, and most future data centers are already planned to use advanced cooling technology that requires very little water. While it is true that data centers require a lot of electricity, their impact on power systems and customers has been greatly exaggerated. Bloomberg’s often-cited piece on the subject mentions that at the highest instance, one area of the country experienced a 267% increase in wholesale costs. This data describing one area in one instance has been used incorrectly to state that it is the expected or average raise (rather than the high end), and it doesn’t even account for the fact that this is wholesale power costs, which does not translate directly into consumer costs. (Often the tech companies will offset these increases.) What this data does tell us is that there are places where we simply should not build data centers. This is one problem that should be avoided. The other problem is companies acting unethically.

One of the most egregious examples of unethical data center implementation is xAI’s Colossus near Memphis, Tennessee. The company promised years ago that it would not rely on local water supply for cooling. Not only does it continue to use local water daily, but the proposed solution has been delayed. In addition, xAI ran as many as 35 unpermitted methane gas turbines at Colossus 1 beginning in June 2024, generating up to 421 MW without any preconstruction or operating air permits under the Clean Air Act. If there was ever an example of how not to build a data center, it is this one.

Another prime example is Project Blue in Tucson, Arizona. Beale, the project developer, actively deceived the city and used the local water supply to clean dust from the data center. And they used a lot of it. This caused Tucson to shut down its water supply. Not only that, but city staff and Amazon had signed an agreement to keep knowledge about the center secret from its residents for three years. It’s no wonder that many communities are suspicious of tech companies coming into their neighborhoods and deceiving them about their plans and the benefits they will bring.

There are cases where companies are unethical in their approach to data centers, and there are cases in which the location is just not suitable. Sometimes, both points of failure occur. Colossus 1 is an example of both, where the deception was extreme and its use of water is actively causing problems with the local aquifer.

An example of poor location choice but good ethics is Microsoft’s West US 3 in the Phoenix area. Microsoft separately agreed to invest $40 million directly into the water utility. Microsoft is testing a new zero-water cooling strategy, and it published its water use and other relevant information in its Environmental Sustainability Report. However, it built these data centers in the middle of an extremely arid, low-water area. There are reasons for doing this, but, generally speaking, drawing water from a nearby desert city’s supply is not ideal. It’s not entirely bad news, in that it has spurred Microsoft to invest in new cooling strategies that do not draw on the local water supply. This problem should not affect future data centers as much because of the new cooling technologies that require little to no water from the local supply.

You probably haven’t heard of too many examples of successful data center developments, and that’s partly because “something worked; everything is just fine” is not a common news story. However, CNN recently reported on exactly that: Quincy, Washington, is home to over 30 data centers and has experienced an incredible boom as a result.

The data centers now cover an estimated 57% of Quincy’s property tax revenue, funding a wave of public infrastructure projects: a $15 million aquatic center, a 143,000-square-foot indoor sports complex, a $120 million high school, a new hospital, library, police and fire stations, paved sidewalks, sewage systems, and a wastewater treatment plant.

Residential electricity rates in the county rose 3.5% last year, while large industrial users, such as the data centers themselves, absorbed a 9.1% increase. The data centers there are paying for their own added infrastructure and generation costs rather than spreading those costs to households.

Another advantage of this site is that it has abundant cheap hydroelectric power. As for water, Microsoft partnered with the city to build a $30 million water reuse facility. The only real caveat here is that the data centers generated so much revenue and development that housing prices have risen across the area.

As you can see, there are definitely ways to build, and examples of ethical and beneficial data centers. The benefits to a local community are substantial. Not only do local tax revenues increase, but data centers come with the benefit of being a generally low-traffic, relatively quiet development. Revenues can increase without needing to build many new roads, or bring large amounts of noisy traffic.

This goes along with the fact that we simply need more data storage. Yes, AI is driving much of the current surge, but we have continually created more data and need a place to store it. We take pictures with our cell phones, leave voice notes, and write emails. With self-publishing, so many people now are writing books. So many songs are written and digital videos made. All of that goes into data centers. All of your apps: data centers. All of the Internet: data centers. Nearly all human knowledge is now stored in these data centers; they are the modern archives of human creativity, education, and achievement.

Efficiency gains in AI are real and dramatic. OpenAI’s Sam Altman has pointed out that ChatGPT models have become roughly 1,000 times more efficient at a given level of intelligence in less than two years. But this doesn’t mean data center demand will eventually shrink; it means the opposite. Every time a computing resource has gotten this much cheaper, historically we haven’t used less of it; we’ve found a thousand more uses for it. Drops in data-storage prices didn’t lead to people using less data; now no one deletes anything. Altman’s prediction that we will use AI and data in the same way that we use utilities such as water and the Internet will likely come true, and in some ways, it already has.

This is not only happening in the United States. China, Europe, the Middle East, and Southeast Asia are all rushing to build data centers, and they are encountering very similar issues. This is a global phenomenon, and, the way things are going, data centers will be as much a part of modern infrastructure as airports, phone lines, and railroads, which people once opposed. Farmers once believed sparks from railroad tracks would burn their land, and doctors at the time warned the human body couldn’t survive driving at speeds over 20 miles per hour. We see the same patterns of resistance to new technology repeated throughout history.

The truth is, data centers themselves aren’t the problem. Poor location choices and unethical business practices cause the failures we’ve seen. If we’re wise about where we build and who we trust, we can avoid the pitfalls and reap the rewards.

Over the next few years, interested users around the world will get an increasingly complete picture of how Ayn Rand developed as a thinker and writer over time. Facilitating this opportunity is the Ayn Rand Archives’ ongoing effort to digitize, transcribe, and release Ayn Rand’s manuscripts on the public internet.

Ayn Rand’s handwritten material is not easy to read. Much of it is in cursive, a writing style that fewer and fewer people learn how to read. Even for those who can read cursive, her unique penmanship can still be a challenge, as many pages of material in her personal papers were notes or drafts never intended to be legible to anyone other than herself. Therefore, just putting the scans of these pages online would not achieve the Ayn Rand Archives’ goal of making this material globally accessible.

For that, we needed to add something: typed transcripts.

Transcripts, typed copies of the handwritten words on the page, truly unlock Ayn Rand’s archival materials. Our goal is to make these transcripts as accurate as possible to Rand’s original words.

Transcription notation

While there are some limitations on this in any given typed format, our current transcription platform allows us to get very close to the originals using various formatting conventions.

The following examples are taken from this page (shown above), this page, and this page, all part of Rand’s planning material for her first novel, We the Living.

Broadly, we have attempted to match what we see on the handwritten page in the typed version. This includes line and paragraph breaks, check marks or other symbols, a certain amount of left indentation, underlines, and deletions or strikethroughs.

Deletions

For readability, these last are always represented as strikethroughs in the transcript, even if Rand used heavier markings:

Insertions

These later additions made by Rand are presented as smaller, superscripted text in the transcripts:

Uncertain Words

When the handwriting is unclear but a reasonable guess is possible, the platform presents the word in brackets, with both the word and brackets italicized.

Regularization

In some cases, Rand either misspelled a word or name or used a less common spelling of something. These words are regularized in the transcript, meaning that the correct or common spelling is given. These are presented in italicized text with a dashed underline. Hovering over these words reveals the original spelling or phrasing as it appeared in Rand’s handwriting, which allows for improved reading and searching while still providing an accurate representation of the original.

Other regularization used throughout all transcripts (which is not formatted):

• Rand used a version of the plus sign (+) for an “and” symbol; the transcripts regularize this to the ampersand (&) symbol in order to be more machine-readable.

• Quotation marks are in the standard American English convention, with both opening and closing quotation marks appearing at the top of the word (“abc” or ‘abc’); Rand herself switched to this convention later in her life, but in much of her early writing (as seen above) she used the European convention of a lower opening quotation mark that appeared at the bottom of the word.

Nonstandard elements

Some elements of the handwritten text cannot easily be reproduced through formatting within this platform, or are otherwise best handled via transcriber notes, short, written descriptions of something on the original page. These are given as italicized comments within regular brackets:

Searchability

One of the biggest benefits of these transcripts is that they are full-text searchable. Anyone can read through the complete text of this archival material, but that is not necessary to find material of interest. Keyword searches, with or without a wild card (*), are possible.

Searches can be conducted within a particular set of Ayn Rand’s papers, such as just within her We the Living material:

But they can also be conducted on all the publicly available archival materials within our transcription platform:

Within the search results, users can look at “Works” (whole documents) that contain the search keyword, or they can look at individual pages which contain the keyword:

This search will become more powerful as we continue to release more of Rand’s archival material. Thanks to the power of these digital tools, this resource is not limited to a particular physical location of the Archives, but rather is accessible to anyone with an internet connection.

We are deeply grateful to our volunteer transcribers, whose efforts have made this entire project possible.

For any questions about the archival material available through this platform, or for more information about how to become a volunteer transcriber, please contact archives@aynrand.org.

Lookout, Disney. A former employer is ready to tell his stories his way.

Creator Josh Daws is flexing the power of A.I. to create a series of satirical “Mary Sue” shorts. The narrative through line? Young Mary Sue is exactly who she sounds like, but through her adventures she realizes the folly of her woke ways.

Episode 1: Mary Sue Doesn’t Need Training pic.twitter.com/MnIzGgVy4u

— Josh Daws (@JoshDaws) July 14, 2026

It’s a thread that Hollywood, Inc. would never consider, let alone turn into a series of animated shorts. Daws has a point to make with the growing saga.

Two, actually.

He hopes to burst the woke bubble through storytelling, using fanciful settings to share his worldview. And he’s flexing the power of obtainable A.I. software to challenge the entertainment status quo.

Daws’ latest installment of “The Adventures of Mary Sue” showcases his growing confidence with the medium.

Episode 4: Mary Sue Thinks the Villain Is Misunderstood

Produced by @capcutapp using Seedance 2.5 https://t.co/XWfMsvcSrW pic.twitter.com/5EJFer82UF

— Josh Daws (@JoshDaws) August 25, 2026

Mary Sue and friends confront an evil sorceress who has an ace up her wicked sleeve. Call it Moral Relativism.

Daws’ quest is far from perfect. A Hollywood version of this short would feature more animated expressions, better music and other flourishes that come with boundless resources.

He’s still scaring all of the right people.

Then, again, the rise of A.I. should scare everyone, even those who never watched the “Terminator” series. Jobs will be lost and never come back. Relationships may be threatened on many levels.

Teens will be seduced by A.I. chatbots, confiding in them rather than parents or loved ones. And Hollywood will never be the same once A.I. is embraced on a studio level.

Many artists, and more than a few writers, will watch their livelihoods get gobbled up by the technology.

That seems inevitable and horrifying. And the genie is out of the bottle with no plan to go back in.

Earlier this month, a Chinese A.I. film turned a massive profit despite its clumsy appearance.

JUST IN: Homemade Chinese animated film “Niu Lai” surpasses $4 million at the box office on a reported budget of $200. pic.twitter.com/VFgVcOFDOb

— Polymarket (@Polymarket) August 20, 2026

Niu Lai was released on August 5 in a limited number of Chinese theaters, receiving approval from the Communist Party censorship offices presumably due to its lack of political or otherwise objectionable content. It made $995 at the box office on its first day – already representing a profit for the low-budget film – but did not truly take off until its few viewers began sharing footage of the film on Chinese regime-controlled social media. The poorly shaped characters, highly pixelated scenery, and the slightly disturbing quality of the characters’ eyes became viral hits, fueling demand nationwide for more movie theaters to carry it.

This is only the beginning.

Daws has a modest X following – just shy of 40K followers. His latest “Mary Sue” clip generated 200K views on his main post in just one day, but subsequent shares likely magnified its reach significantly.

The positive side to A.I.’s stunning rise? Storytellers who might never have had the resources or connections to share their imaginations will be able to do just that.

Daws is just one example.

More will follow. Some will be crude and infantile, much like the aforementioned Chinese film. Others will prove far more sophisticated and challenging. Audiences will have to sort out the difference.

Hollywood studios will have to improve their output to compete with the latter.

A hopeful part of this evolution? Stories that would never get a fair hearing in any studio, large or small, will suddenly get the chance to flower.

Would a Disney or Universal attempt a story like “The Adventures of Mary Sue?” Not a chance.

The post Why ‘Mary Sue’ Short Should Scare Hollywood Silly appeared first on Hollywood in Toto.