Trump named Pulte, a top housing official who has no experience in intelligence, as his acting director of national intelligence this week.
Jacob Knutson at Democracy Docket:
President Donald Trump said Bill Pulte, his incoming acting director of national intelligence (DNI), will investigate elections that the president falsely claimed were “rigged.”
Asked by a reporter what made Pulte, a top federal housing official who has no known experience in intelligence, qualified for the DNI role, Trump said he’s a “smart guy” who would probe elections on his behalf — an alarming task for the country’s top intelligence officer.
“He’s a very smart guy,” Trump said in the Oval Office Thursday. “And he may find out some things about the rigged elections.”
“I think he’d like to do it,” the president added. “I’d like to. I think he wants to do it very much.”
On Tuesday, Trump named Pulte, who currently leads the Federal Housing Finance Agency (FHFA), to replace outgoing DNI Tulsi Gabbard, who announced last month that she will resign from her post later this summer.
Throughout her tenure, Gabbard has been heavily involved in probing conspiracy theories related to the 2020 election, which Trump has repeatedly falsely claimed was stolen from him. After assuming the acting position later this year, Pulte will likely follow Trump’s order and continue — if not greatly expand — the elections-related probes Gabbard initiated.
Known in MAGA circles as “Little Trump,” Pulte has used his relatively minor federal housing post — and his chairmanship of mortgage groups Fannie Mae and Freddie Mac — to help initiate mortgage-related criminal investigations against a swath of the president’s enemies.
Donald Trump’s pick to lead the DNI, Bill Pulte, will conduct sham politically-motivated probes into elections falsely deemed to be “rigged” according to the whims of 47.
The U.S. Postal Service has proposed new rules that would implement parts of President Donald Trump’s executive order on voting by mail, rai
Austin (KXAN) — The U.S. Postal Service has proposed new rules that would implement parts of President Donald Trump’s executive order on voting by mail, raising concerns among election officials and voting rights advocates.
The proposal would require states to provide USPS with lists of voters receiving mail-in and absentee ballots in federal elections. It would also require ballot envelopes to carry unique Postal Service barcodes, allowing USPS to verify mailings against state-submitted voter data.
“There are a couple of levels to this,” VoteBeat senior national reporter Dion Nissenbaum said. “One is it would require all states to submit a list of everybody in their state that wants to vote by mail 60 days before the November election.”
Election officials say the changes could force counties to purchase new technology, redesign ballot envelopes and update ballot-tracking systems before the 2026 midterm elections.
The proposed rules would not actually catch any election fraud. They would just make the process of mailing out blank ballots arbitrarily difficult, resulting in delayed mail and some ballots not being accepted for mailing at all.
The end result would be to make voting by mail less reliable and fewer people would use it. That's what Donald Trump wants, because he hates voting by mail except when he does it.
But you can't just say "Fuck Trump!" and expect bureaucrats to change their minds. So I drew on my professional experience to submit a public comment that addressed the principles and practicalities. Here's what I wrote:
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I am writing to oppose portions of the proposed Ballot Mail for Federal Elections rule, namely Domestic Mail Manual sections 705.24.4 and 705.24.5, for these reasons:
The proposed rules are unlikely to detect any significant number of cases of election fraud.
The proposed rules would impose additional burdens on both election officials and the Postal Service, for no good reason, with the risk of delay and mistakenly rejecting legitimate ballots.
The spirit of the rules is counter to the Postal Service's universal service mission.
To go into each of these points in more detail:
Most cases of ballot fraud occur when an ineligible person registers to vote (we had exactly one case of this in Iowa in 2024), a person is registered in two states, or someone casts a ballot that was issued in the name of a deceased family member. In all of these cases, the voter in question would be included in the participation list that election officials furnish to the Postal Service. Election officials will use their same internal database to generate the actual mail-in ballots, so assuming that the verification is done correctly, no mismatches would ever be found.
The verification requirements in section 24.5.1 are more detailed and involved than any current mail acceptance procedures. This risks delay of ballots. Furthermore, any error in the procedure -- for example, if Postal Service personnel mistakenly use an out-of-date version of a participation list -- will result in legitimate ballots being rejected. As I read the rule, the entire batch of mail would be rejected, not just the mismatches.
The Postal Service's mission is to deliver the mail to everyone in the United States. Presently, mail acceptance procedures are only concerned with whether the sender paid the correct postage, whether the mailing contains any hazardous materials, and whether the mailing meets machinability requirements (mailpiece dimensions, barcoding, sorting, etc.). Mail fraud is traditionally prosecuted after the fact rather than by inspection of the mail as it is submitted. The new rules would restrict who is allowed to send mail to whom. This is censorship.
I have no objection to the ballot mail envelope standards in section 705.24.3.
Background: I have professional experience in Zip+4 coding, NCOA, mail sorting, and other postal regulations through my former employer [name of former employer, which some Postal Service personnel would recognize, but probably not the people writing these rules].
Defense Secretary Hegseth previously announced the change due to an "impractical" system.
Military.com has learned that the Department of Defense, for the first time in almost 10 years, has dramatically reduced its number of recognized religious faiths and belief systems by approximately 180.
Military.com has learned that the Department of Defense, for the first time in almost 10 years, has dramatically reduced its number of recognized religious faiths and belief systems by approximately 180.
The reforms mark the first time the list has been officially revised since a memo was issued March 27, 2017, decreasing the total number of faiths from roughly 211 to its new number of 31. The changes were iterated in a May 20, 2026, memorandum issued by the Under Secretary of War and signed by Anthony Tata, under secretary of defense for personnel and readiness of the United States, and obtained by Military.com.
This latest revision to the faith codes comes at the direction of Defense Secretary Pete Hegseth, according to the Tata-signed memo, done to “streamline the DoW collection of religious preferences collection for service members to enhance the delivery of targeted religious support from the Chaplaincy.” It calls for the previously instituted faith and belief codes to be revised within a 60-day period from the issuance of the memorandum.
This restructuring of faith codes, which help identify service members as well as the military in planning for appropriated religious coverage to include them, has now excluded minority faith/worldview groups including Atheists, Asatru, Deists, Druids, Eckankar, Heathens, Humanists, Magick, New Age churches, Pagan, Rosicrucianism, Shaman, Spiritualists, Troth, Unitarian Universalists and various Wiccans.
The Reagan Administration’s Horrid Response to the AIDS Epidemic
Ignored AIDS Epidemic While Tens of Thousands Died
Many conservatives (Republicans) in the 1980s believed that AIDS was God’s punishment for being gay. Ronald Reagan did not publicly talk about AIDS until the sixth year of his presidency. In 1986, when AIDS fatalities were doubling every year, Reagan proposed cuts in funding for AIDS research.
A huge fraction of people who are intersex are completely unaware that they are. So, in preparation for Pride Month:
Here are tons of signs that you're intersex:
You naturally have a large clitoris (numbers are complicated) or small phallus (<2.7 inches erect or <1.5 inches flaccid)
You have parts that look like an intermediate between a clitoris and a phallus (clitorophallus)
You do not have a clitorophallus at all (ie, no clitoris, no phallus; nothing)
Your urethra is lower or higher than usual (for phalluses: should be centered on top of the glans -- for vulvas: should have several millimeters of space between the clitoris, urethra, and vagina)
Your urethra is not externally visible
You have a penis or phallus with an opening between the base of phallus and anus.
You have a vulva without a vaginal opening, or have a small, easily irritated or nonelastic opening
You have a vulva with partially or completely fused labia (begins from the bottom of the vulva or from the clitoris - may have a webbed appearance rather than flush skin)
You have a penis with very small or undescended testes
You went through androgenizing puberty and have prominent breast tissue
You went through estrogeninizing puberty and have little to no breast tissue.
You went through both androgenizing and estrogenizing puberty
You never hit puberty, had very little development during puberty, or had a late onset puberty.
You have had imaging tests that show "missing," differently shaped, mixed, or otherwise unexpected internal genitalia.
You have had unexplained medical issues regarding sex traits or genitalia since childhood or adolescence.
You have any of the above signs and are struggling with fertility
Other family members display similar traits (note: this is *not* necessary as not all intersex variations are inherited)
You have had DNA testing and the karyotype came back with an unexpected result (ex: XX instead of XY, or an error message)
You have had high or low levels of sex hormones since puberty (it's okay if all you have are signs that they were high or low in childhood)
You have widespread body hair or any amount of facial hair alongside an estrogenizing puberty
You are experiencing androgenic alopecia and have close-to-female anatomy.
You are unable to grow body/facial hair and have close-to-male anatomy.
You have a very androgynous face, or your face passes as a different gender from your body (this one is Subjective and not indicative on its own)
You have unexplained scarring in the genitalia area. If this one is you, please get in touch with InterAct Advocates, Genital Autonomy, or online Intersex communities before you dig for info.
This is an extremely sensitive topic and may be traumatizing (CIMI / IGM). You also want to make sure what you've found are scars, instead of natural tissue - intersex bodies may develop extra tissue in some places (ex: vulvar hypospadias and hooding of the urethra)
Alright. That's all I got for now. If you're starting to question things now, it may feel scary at first, but you don't have to do it alone. The intersex community online has so many amazing resources and wonderful helpful people in it.
For some primers, check out InterAct Advocates! Happy almost Pride! I'm excited to celebrate with you with us <3
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:
One of the best ways to evaluate your own understanding of a subject is to attempt to explain it to someone else. Through explaining things, we discover how much of the "totally obvious" world is actually full of ambiguity, mystery and contradiction.
There's a great bit in Rowan Atkinson's historical sitcom Blackadder that illustrates this principle. In "Ink and Incapability" Blackadder and friends have accidentally burned the only copy of Samuel Johnson's original dictionary of the English language. To cover up their mistake, they decide that they will recreate the dictionary themselves. However, they founder on the first word they try to define, "A":
Blackadder: Let's start at the beginning, shall we? First: 'A.' How would you define 'A'?
Prince George: Ohh…'A' (continues this in background). Oh, I love this! I love this! Quizzies! Erm, hang on, it’s coming. Ooh, crikey, erm, oh yes, I’ve got it!
B: What?
PG: Well, it doesn’t really mean anything, does it?
B: Good. So we're well on the way, then. "'A'; impersonal pronoun; doesn't really mean anything."
I mean, what does "A" mean? The Oxford English Dictionary has more than a dozen definitions, and just the first one runs to more than 1,500 words:
Now, normal life involves a lot of explaining things to other people. You have to explain your problems to customer service reps, who have to explain why they can't solve those problems to you. You need to explain to your loved ones why you want to leave your toothbrush in the shower, and they have to explain why they hate having your toothbrush in the shower. These explanation-exchanges teach you as much as they teach the person you're locked in dialog with. The reasons for leaving your toothbrush in the shower may seem totally obvious to you, and your partner's inability to understand this reveals the assumptions you've never even considered.
For the past four decades, an increasing proportion of the population have spent an increasing proportion of their lives explaining things to machines that have no assumptions or shared context: computers. What we call "programming a computer" is really "breaking down a thing that seems obvious to you into increasingly simple instructions that will be followed to the letter."
Computers are like the genies of legend, bloody-minded literalists who will do exactly what you say, in the way that is perversely furthest from what you mean. To get a computer to do anything, you must first understand it to a degree that far exceeds the understanding needed to explain something to any other human, even a small child.
To take just one example: yesterday, I was on a plane, and the seatback video started cycling through its video-on-demand offerings. All of the movie titles that began with "the" were rewritten to put "the" at the end of the title (for example, "The Sting" was written as "Sting, The"). It's obvious why the system's designer had done this: we expect to find movies whose titles begin with "The" alphabetized under their second word ("The Sting" should appear between "Star Wars" and "Story of a Love Affair"; not between "The Godfather" and "The Untouchables").
I remember when I learned this from my elementary school's teacher-librarian, when I was seven and my class got a tutorial on the school library's card catalog. The librarian explained this principle to us in a matter of minutes, as part of a longer set of instructions, and still, it stuck with me forever.
But here we are, 48 years later, and we still haven't standardized a way to get computers to grasp this foundational principle of alphabetization. Many different databases handle this, to be sure, but it's so inconsistent across so many platforms that someone at the head-end of the video distribution system that feeds American Airlines' VOD system decided, "Fuck it, I'm just gonna put the 'The' at the end of these titles."
Computers are stupid, in other words, which means that the people who program them have to have smarts enough for both of them. Unfortunately for our entire species and civilization, the software industry has historically valued skill at writing efficient and reliable software over writing software that adequately reflects reality. There is an entire genre of lists that illustrate the problem with this; the "falsehoods programmers believe" lists:
https://github.com/kdeldycke/awesome-falsehood
From "names of people" and "street addresses"; from "prices" to "time"; from "email addresses" to "phone numbers"; the "awesome falsehoods" lists are awesome because they reveal how much subtlety and complexity is lurking in these seemingly simple and intuitive concepts. This subtlety and complexity might never emerge through the process of trying to teach a person about them, but when you try to teach a computer about them, you have to confront them in all their awesome fuggliness.
That's because humans have context, agency and flexibility. Sure, the person who designs a form with a blank for "name" might never have met a Malagasy person whose first name is Randriamananjararadofabesata, but in the pre-digital world, when Madagascar Slim met a public official who had to transcribe his name onto a paper form, that official could simply draw an arrow in the margin next to the "name" blank, turn the form over, and write out all 28 characters on the reverse:
https://en.wikipedia.org/wiki/Madagascar_Slim
Computers can't do this. If the programmer doesn't know about Malagasy first names, the computer doesn't know about them either, and the only person who can "teach" the computer about these names is a programmer with access to the code for the database, who has to manually alter the code, compile it, and distribute it to everyone who uses it.
This is partly why digitization has been accompanied by a rise in people asserting that they exist on spectrums rather than in binaries. There were always people whose names, genders, races, and other biographic "immutables" changed, or failed to fit within the blanks on the forms. When those people's realities ran up against failures in the system's abstractions, they could petition a bureaucrat to turn the paper over and write an explanatory note, or to write really small to fill in a blank:
Getting a human official to turn the paper over and write something that didn't fit in the blank is a personal challenge. It requires that a subject convince the person who controls the form to make an exception. This isn't always easy, but officials on the front lines necessarily deal with reality, and they can't get their jobs done unless they're capable of interpreting the necessarily incomplete procedures they operate under to fit things as they really are.
But a computer doesn't have any agency or context or flexibility. If the computer says your name isn't valid, you can't argue the computer into accepting it. The only way to get a digital world to acknowledge your existence is to campaign for systemic change. A trans person might (with great difficulty, to be sure) convince the regional registrar to white-out an old X on one "gender" box and mark a new X in the other box. But the only way to make that change in a software system that has been programmed to treat the "gender" field as immutable is to change society itself.
In this way, computers are machines for teaching us what we don't know about ourselves. They require that we interrogate and faithfully recreate our personal tacit knowledge, and they require that our societies interrogate their tacit presumptions as well. When you are forced to turn your tacit knowledge into explicit knowledge, you're also forced to confront how many broken assumptions lurk inside your reasoning. At best, it's a clarifying process.
Computers don't just clarify what we know and how we organize our society: they also clarify what we are. There are lots of things that we have supposed that a computer would never do, because we believed that these things required something that only humans could do.
Take chess: there are more possible chess games than there are hydrogen atoms in the universe, so brute-forcing chess by running all possible games is a technological impossibility. The best human chess players do something we don't quite understand, mixing their recollections of previous games with rules-of-thumb about the best strategies, with "creativity" (whatever that is) that lets them spontaneously develop new strategies. We can easily get a computer to memorize all the known-good chess sequences and all the rules of thumb, but we don't know what "creativity" is, so we can't encode it as a series of instructions.
But thanks to breakthroughs in machine learning and its successor, "deep learning," we have created chess-playing software that can beat every human, partly by assaying gambits that we would term "creative" if they originated with a human player.
What we make of this new fact is controversial. For many people (myself included), this is a refinement: it tells me that behaviors that are indistinguishable from "creativity" can, at least some of the time, be created by mechanical processes, and the mere fact that a machine does something that appears "creative" doesn't mean that machines are human.
For others, the fact that a mechanical system can evince a behavior that we would call "creative" in a human doesn't mean that we defined "creativity" too broadly, it means that we defined "human" too narrowly, and now we have made a machine that is, at least partially, a person.
I think this is the wrong conclusion to draw, for reasons that Ted Chiang sets out with luminous brilliance in a recent Atlantic article entitled "No, Artificial Intelligence Is Not Conscious":
(If you're hitting the paywall on that one and you're on Firefox, you can try my favorite trick: switch to "Reader Mode" and hit "reload" – your mileage may vary.)
For all the reasons Chiang articulates, I think that drawing the "personhood" line to include machines is a technical mistake, but it's worse than that. Admitting machines to the "personhood" club is a tactical mistake, on par with the mistake we made when we admitted corporations to the personhood club. We should absolutely consider expanding personhood to incorporate living things, including animals and ecosystems, but at the same time, we must purge these dead, artificial constructs from the club:
There is a way in which the recognition of new capabilities in machines parallels the recognition of new capabilities in animals other than ourselves. When those animals manage to do things that we once thought were the exclusive province of humans, we (should) take that as an opportunity to refine our conception of humanity. We're not "the animals that use tools" or "the animals that make plans" or "the animals that recognize themselves in mirrors," because there are other animals that do those things. We are an "animal that uses tools"; not the animal that does so.
Likewise, if we thought that some activity was unique to humans, or to living beings, and we manage to get a machine to replicate that activity, we should revise our view of the activity – not our view of the machine. Creative breakthroughs in chess are not "a thing that requires a human mind," they're "things that can be done by human minds and by machines."
Edsger Dijkstra once famously asked "can a submarine swim?"
Submarines and fish and humans and dolphins all propel themselves through water by different means. But when an animal swims, it does something that is different from what a submarine does. The submarine has no intention, while (complex multicellular) animals swim to pursue goals. Building machines that propel themselves through water is very useful, but it's not the same thing as creating life. In some ways, it's better than creating life: for one thing, we owe other living things moral consideration that is not due to machines. Harnessing a machine to accomplish our own goals is more morally clear than controlling living things to achieve those goals. By the same token, creating machines that can do some of the tasks that we ask of other humans can be the superior moral course. I'd rather have a machine remove mines from a minefield than getting humans to do it.
But beyond this moral relief, creating machines is a fantastic way to learn more about ourselves – making explicit our tacit knowledge, our implicit social assumptions, and the limitations of our conception of what sets us apart from the rest of the universe.
One way in which AI is exceptional is in how it undermines this principle. Conventional software techniques struggled to produce a program that could identify objects in photographs. It turns out that defining all the visual correlates of "cat" is even harder than defining the letter "A." Deep learning techniques solved this previous insoluble problem by relieving us of the job of making explicit all the implicit factors that we deploy when distinguishing an image of a "cat" from an image of a "dog" or a "tiger" (or a "tractor").
Instead of forcing humans to engage in introspection until we'd made a list of every factor we use to identify cat pictures, we simply identified pictures of cats and fed them to a program that tried to find the commonalities among them. The more pictures we fed to that program, the better it got at identifying cats. Today, we have programs that can reliably distinguish an image of a cat from an image of a tiger cub!
This represents a major breakthrough in the power of computers to perform useful work for us, but it's also a huge regression in computers' role in forcing us to make our tacit thought processes explicit through systematic introspection. That's probably fine: we didn't create computers to make us introspect, we created them to do useful work for us. All things considered, it might be better to have genies who grant our wishes according to the spirit of our words, not their letter.
AI may not force us to render our implicit thoughts as explicit instructions, but it absolutely forces us to reconsider and narrow the realm of the numinous. Our own creativity is still delightful and important, but the fact that this squishy, amazing process can (sometimes) be replicated by procedural machines changes the definition of living things. We're "a thing that can produce creative outcomes" but not "the things that can produce creative outcomes." The machines aren't being creative (any more than a submarine is swimming) but they're outputting things that we used to only achieve by means of creativity.
An AI that does something that used to require creativity is fulfilling my favorite of Brian Eno and Peter Schmidt's Oblique Strategies: "Be the first person to not do something that no one else has not done before":
https://stoney.sb.org/eno/oblique.html
Just as bosses fantasize about AI bringing about a worksite without workers, and Zuckerberg is trying to build social media without socializing, and politicians want a bureaucracy without bureaucrats, we can sometimes use AI to produce creative outcomes without creativity:
But art isn't the only realm that we apply creativity to. There are plenty of outcomes that we've always believed we couldn't bring about without applying creativity. AI – like all software – is making us realize that an ingredient we once deemed uniquely essential turns out to have substitutes. AI can sometimes accomplish things without us explaining how we do them. That relieves us of a useful but difficult chore – but in so doing, it forces us (yet again!) to revisit what sorts of things are needed to do the things that matter to us, and therefore, what makes us special.
Jill Biden has released View From The East Wing, a memoir detailing her time as first lady of the United States. Here are the book’s biggest revelations.
