Author name: Mike M.

big-pharma-spends-billions-more-on-executives-and-stockholders-than-on-r&d

Big Pharma spends billions more on executives and stockholders than on R&D

bernie sanders, Bristol-Myers Squibb, drug pricing, Johnson & Johnson, merck, patents, PBMs, Pharmaceutical industry, research and development, Science / /

Greed —

Senate report points to greed and “patent thickets” as key reasons for high prices.

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Big Pharma spends billions more on executives and stockholders than on R&D

When big pharmaceutical companies are confronted over their exorbitant pricing of prescription drugs in the US, they often retreat to two well-worn arguments: One, that the high drug prices cover costs of researching and developing new drugs, a risky and expensive endeavor, and two, that middle managers—pharmacy benefit managers (PBMs), to be specific—are actually the ones price gouging Americans.

Both of these arguments faced substantial blows in a hearing Thursday held by the Senate Committee on Health, Education, Labor and Pensions, chaired by Sen. Bernie Sanders (I-Vt.). In fact, pharmaceutical companies are spending billions of dollars more on lavish executive compensation, dividends, and stock buyouts than they spend on research and development (R&D) for new drugs, Sanders pointed out. “In other words, these companies are spending more to enrich their own stockholders and CEOs than they are in finding new cures and new treatments,” he said.

And, while PBMs certainly contribute to America’s uniquely astronomical drug pricing, their profiteering accounts for a small fraction of the massive drug market, Sanders and an expert panelist noted. PBMs work as shadowy middle managers between drugmakers, insurers, and pharmacies, setting drug formularies and consumer prices, and negotiating rebates and discounts behind the scenes. Though PBMs practices contribute to overall costs, they pale compared to pharmaceutical profits.

Rather, the heart of the problem, according to a Senate report released earlier this week, is pharmaceutical greed, patent gaming that allows drug makers to stretch out monopolies, and powerful lobbying.

On Thursday, the Senate committee gathered the CEOs of three behemoth pharmaceutical companies to question them on the drug pricing practices: Robert Davis of Merck, Joaquin Duato of Johnson & Johnson, and Chris Boerner of Bristol Myers Squibb.

“We are aware of the many important lifesaving drugs that your companies have produced, and that’s extraordinarily important,” Sanders said before questioning the CEOs. “But, I think, as all of you know, those drugs mean nothing to anybody who cannot afford it.”

America’s uniquely high prices

Sanders called drug pricing in the US “outrageous,” noting that Americans spend by far the most for prescription drugs in the world. A report this month by the US Department of Health and Human Services found that in 2022, US prices across all brand-name and generic drugs were nearly three times as high as prices in 33 other wealthy countries. That means that for every dollar paid in other countries for prescription drugs, Americans paid $2.78. And that gap is widening over time.

Focusing on drugs from the three companies represented at the hearing (J&J, Merck, and Bristol Myers Squibb), the Senate report looked at how initial prices for new drugs entering the US market have skyrocketed over the past two decades. The analysis found that from 2004 to 2008, the median launch price of innovative prescription drugs sold by J&J, Merck, and Bristol Myers Squibb was over $14,000. But, over the past five years, the median launch price was over $238,000. Those numbers account for inflation.

The report focused on high-profit drugs from each of the drug makers. Merck’s Keytruda, a cancer drug, costs $191,000 a year in the US, but is just $91,000 in France and $44,000 in Japan. J&J’s HIV drug, Symtuza, is $56,000 in the US, but only $14,000 in Canada. And Bristol Myers Squibb’s Eliquis, used to prevent strokes, costs $7,100 in the US, but $760 in the UK and $900 in Canada.

Sanders asked Bristol Myers Squibb’s CEO Boerner if the company would “reduce the list price of Eliquis in the United States to the price that you charge in Canada, where you make a profit?” Boerner replied that “we can’t make that commitment primarily because the prices in these two countries have very different systems.”

The powerful pharmaceutical trade group PhRMA, published a blog post before the hearing saying that comparing US drug prices to prices in other countries “hurts patients.” The group argued that Americans have broader, faster access to drugs than people in other countries.

Big Pharma spends billions more on executives and stockholders than on R&D Read More »

female-ex-exec-told-she-lacked-“docility-and-meekness”-sues-tiktok

Female ex-exec told she lacked “docility and meekness” sues TikTok

bytedance, Policy, tiktok / /
Female ex-exec told she lacked “docility and meekness” sues TikTok

One of TikTok’s senior-most female executives, Katie Ellen Puris, is suing TikTok and its owner ByteDance, alleging wrongful termination based on age and sex discrimination.

In her complaint filed Thursday, Puris accused ByteDance chairman Lidong Zhang of aggressively forcing her out of the company because she “lacked the docility and meekness specifically required of female employees.” She also alleged experiencing retaliation after reporting sexual harassment to the company.

Puris joined TikTok in December 2019 as managing director and US head of business marketing. Previously, she’d led global marketing initiatives for Google and Facebook. TikTok appeared to value this experience and promoted her within two months to lead its global business marketing team. In this role, she launched TikTok for Business and meaningfully shaped how businesses interact with the platform.

Amid this success, Puris allegedly discovered that she had a target on her back.

According to her complaint, by early 2021, Beijing-based ByteDance executives, including Zhang, “began reasserting more control over TikTok’s day-to-day operations.” These executives, Puris said, required bi-monthly meetings with senior executives to report on their teams’ progress in hitting company targets.

“Despite its attempts to appear independent, TikTok’s day-to-day management and business decisions came directly from ByteDance’s top-level management in China,” Puris’ complaint alleged.

During one of these bi-monthly meetings, Puris met Zhang for the first time during a presentation where she “celebrated her team’s successes and achievements.” Allegedly, Zhang was put off by Puris’ presentation because “women should always remain humble and express modesty.”

“Essentially, Lidong Zhang believes women should be quiet,” Puris’ complaint alleged.

Puris believes that because she “did not fit that stereotypical gender mold,” Zhang refused to ever meet with her again and placed her on a “kill list” of employees who he wanted terminated.

According to Puris, Zhang began pressuring her supervisors to review her performance negatively. He allegedly cast a wide net and sought negative comments from employees whom Puris rarely worked with. His alleged “animosity” was so evident that one of Puris’ supervisors allegedly sought to protect her by removing her from Zhang’s oversight.

At the same time, Puris, who was approaching 50, alleged that other executives “made it clear” that they would prefer to hire “hungry” younger, less experienced workers “believed to be more innovative and pliable” and “desperate for approval” than older workers like Puris. She claimed that a supervisor regularly referenced her age during performance reviews that became increasingly negative and without clear feedback or comments substantiating her poor reviews. Requests for feedback were repeatedly rejected.

Puris’ efforts to report alleged age and sex discrimination did not result in corrective action, her complaint said. Even when a TikTok advertising partner allegedly drunkenly sexually harassed her at an off-site event, Puris alleged that her complaints were not taken seriously. Puris said that TikTok continued inviting the advertising partner to events, causing her to withdraw from attending.

Rather than sincerely investigate her complaints, Puris’ complaint said that “after Ms. Puris made protected complaints, her team was substantially reduced, she received a devastatingly low-performance review, she was denied her annual bonus, she was moved out of her position, and she was ultimately unlawfully terminated.”

Female ex-exec told she lacked “docility and meekness” sues TikTok Read More »

200-foot-am-radio-tower-disappears,-halting-alabama-station-broadcast

200-foot AM radio tower disappears, halting Alabama station broadcast

AM radio, FM radio, radio, Tech / /

Tower theft —

“There’s wires everywhere, and it’s gone.”

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radio, tuner, dial, station, FM, AM, music, sound, numbers, 700, 800, 94, 96

A 200-foot AM radio tower has been missing for at least a week, leaving an Alabama radio station in a financial crisis and on a desperate hunt.

As first reported by Memphis’ Action News 5, Jasper, Alabama, radio station WJLX 101.5 FM/1240 AM, sent a bush hog crew to maintain the area around the tower on February 2. The tower is behind a poultry plant in a forested area, per The Guardian. Once there, a crew member called station manager Brett Elmore, informing him that the 200-foot structure that CNN says has been there since the ’50s had disappeared.

“He said, ‘The tower is gone. There’s wires [sic] everywhere, and it’s gone,’” Elmore told Action News 5.

The total value of all the equipment reported stolen is nearly $200,000, Alabama’s ABC 33/40 News said.

Now the radio station says it has to get a new tower, as well as a new transmitter and additional equipment for tasks like processing and engineering. Replacement costs are an estimated $60,000 or more, per WJLX.

Even if the tower were somehow recovered, the station would still be “in a jam,” Elmore told CNN, saying that the equipment would probably “be in pieces.”

“This has affected the operation of our AM, which needs a complete rebuild, and our FM, which is currently off the air,” the radio station said Thursday via its Facebook page.

The radio station manager has told outlets that he’s hopeful that community tips and surveillance footage from the poultry plant near the tower’s former location may eventually help police find the tower-taker(s).

“It is a federal crime, and it absolutely will not be worth it to them,” Elmore told Action 5 News.

Federal law says one who “willfully or maliciously injures or destroys any of the works, property, or material of any radio, telegraph, telephone or cable, line, station, or system, or other means of communication, operated or controlled by the United States” can face up to 10 years of imprisonment and fines.

While the tower remains MIA, WJLX remains off the air. The radio station asked the Federal Communications Commission (FCC) to allow it to keep broadcasting its FM station even though its AM station is off the air, but the FCC denied the request on Thursday, the station said, since the FCC doesn’t allow FM translators to run without the AM station also being on air. The FM station is now only available online.

In the meantime, some are concerned about how emergency communications could be disrupted by the tower disappearing.

“What if there were a crisis going on right now that that community needs to hear information from local sources [about] on a local radio station, and they can’t?” Sharon Tinsley, president of the Alabama Broadcasters Association, told ABC 33/40 News.

Tinsley told the news station that she has reached out to people to identify media outlets that might be willing to help WJLX get new equipment. There’s also a GoFundMe for the radio station.

It remains to be discovered how a radio tower heist was pulled off without causing a stir or leaving an obvious trail. As one could imagine, there aren’t a lot of past, similar incidences to try to draw clues from.

One recent case of a radio tower suddenly vanishing occurred in Nigeria last year. Nigerian newspaper publisher The Media Trust Group reported that it was supposed to get a decommissioned radio tower for its new radio station in Abuja from a Niger State village. Media Trust said it never received the tower delivery and was told by the company it contracted to decommission, transport, and set up the tower that it was “snatched away” by people they thought were from the Nigeria Security and Civil Defence Corps (NSCDC). It was eventually revealed that two NSCDC officials “were approached by a scrap metal dealer to provide him security cover to transport the items,” per Media Trust-owned Daily Trust. The newspaper publisher was still trying to get its money back for the tower as of January.

If WJLX’s case is anything like the Nigerian heist, someone likely knows more than they’re letting on, and the financial burden to the media outlet could be hard to resolve quickly.

“Surely, someone saw something or heard something,” Elmore told The Guardian.

200-foot AM radio tower disappears, halting Alabama station broadcast Read More »

android’s-infamous-january-2024-update-is-fixed-and-rolling-out-again

Android’s infamous January 2024 update is fixed and rolling out again

Google, Tech / /

Taking another swing at it —

The Google Play System update was pulled for breaking device storage, crashing apps.

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Google HQ.

Enlarge / Google HQ.

We’re a third of the way through February, but Android’s January 2024 Google Play System update is just now rolling out. The now-infamous update originally rolled out at the beginning of January but was pulled after it started locking users out of their phone’s local storage. Apparently, the update has been fixed and is rolling back out to devices. We were able to get it to install this morning.

The first time this update went out, some devices with multiple user accounts or work profiles experienced what Google described as “multiple apps crashing, screenshots not saving, and external storage working inconsistently.” Users described phones affected by the issue as “unusable.” Google eventually posted instructions for a manual fix on February 1, about two weeks after the update first started rolling out. These instructions were complicated, though, involving a manual process where you had to enable developer mode, download the developer tools, plug in your phone, and type in the right command prompts to delete buggy packages manually. As part of that February 1 post, Google seemed to promise to release an automated fix someday, but it has been nine days now.

Google skipped the December Play System update due to the holiday break, so this “January” update in February is the first Play System update since November. Play System updates, if you aren’t aware, are a fairly new Android update format that is separate from the OS-level system and security updates. Google created a new, super-privileged code package called an APEX Module that can house core system components like the Android RunTime or media subsystem. Google distributes these through the Play Store, allowing it to update core Android components directly without needing third-party manufacturers to do any work. It sounds great on paper, provided the updates work.

The update was the second time in four months that an automatic Android update broke some Pixel phones (for the record, one was a full OS update, the other was a Play System update). Both issues resulted in downtimes measured in weeks and “fixes” that demanded either developer-level command line work from novice users or caused data loss. Google’s track record these last four months suggests 1) it doesn’t have a reliable rollback method for buggy updates, 2) it doesn’t have adequate testing for its updates, and 3) it can’t quickly stop or repair damage caused by buggy updates. Those issues all make updating a Pixel phone a scary proposition lately.

Android’s infamous January 2024 update is fixed and rolling out again Read More »

over-a-decade-later,-climate-scientist-prevails-in-libel-case

Over a decade later, climate scientist prevails in libel case

climate change, defamation, lawsuit, Michael Mann, Policy / /

What a long, strange trip it’s been —

But the case is not entirely over, as he plans to go after the publishers again.

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Image of a middle-aged male speaking into a microphone against a dark backdrop.

Enlarge / Climate scientist Michael Mann.

This is a story I had sporadically wondered whether I’d ever have the chance to write. Over a decade ago, I covered a lawsuit filed by climate scientist Michael Mann, who finally had enough of being dragged through the mud online. When two authors accused him of fraud and compared his academic position to that of a convicted child molester, he sued for defamation.

Mann was considered a public figure, which makes winning defamation cases extremely challenging. But his case was based on the fact that multiple institutions on two different continents had scrutinized his work and found no hint of scientific malpractice—thus, he argued, that anyone who accused him of fraud was acting with reckless disregard for the truth.

Over the ensuing decade, the case was narrowed, decisions were appealed, and long periods went by without any apparent movement. But recently, amazingly, the case finally went to trial, and a jury rendered a verdict yesterday: Mann is entitled to damages from the writers. Even if you don’t care about the case, it’s worth reflecting on how much has changed since it was first filed.

The suit

The piece that started the whole mess was posted on the blog of a free market think tank called the Competitive Enterprise Institute. In it, Rand Simberg accused Mann of manipulating data and compared the investigations at Penn State (where he was faculty at the time) to the university’s lack of interest in pursuing investigations of one of its football coaches who was convicted of molesting children. A few days later, a second author, Mark Steyn, echoed those accusations at the publication National Review.

Mann’s case was based on the accusations of fraud in those pieces. He had been a target for years after he published work showing that the recent warming was unprecedented in the last few thousand years. This graph, known as the “hockey stick” due to its sudden swerve upwards, later graced the cover of an IPCC climate report. The pieces were also published just a few years after a large trove of emails from climate scientists were obtained illicitly from the servers of a research institution, leading to widespread accusations of misconduct against climate scientists.

Out of the public eye were a large number of investigations, both by the schools involved and the governments that funded the researchers, all of which cleared those involved, including Mann. But Simberg and Steyn were part of a large collection of writers and bloggers who were convinced that Mann (and by extension, all of modern climate science) had to be wrong. So they assumed—and in Simberg and Steyn’s case, wrote—that the investigations were simply whitewashes.

Mann’s suit alleged the exact opposite: that, by accusing him of fraud despite these investigations, the two authors showed a reckless disregard for truth. That would be enough to hold them responsible for defamation despite the fact that Mann was a public figure. The authors’ defense was largely focused on the fact that they genuinely believed their own opinions and so should be free to express them under the First Amendment.

In essence, the case came down to whether people who appear to be incapable of incorporating evidence into their opinions should still be able to voice those opinions without consequences, even if doing so has consequences for others.

Victory at last-ish

In the end, the jury decided they did not. And their damage awards suggest that they understood the present circumstances quite well. For starters, the compensatory damages awarded to Mann for the defamation itself were minimal: one dollar each from Simberg and Steyn. While Mann alleged he lost grants and suffered public scorn due to the columns, he’s since become a successful book author and received a tenured chair at the University of Pennsylvania, where he now heads its Center for Science, Sustainability, and the Media.

But the suit also sought punitive damages to discourage future behavior of the sort. Here, there was a dramatic split. Simberg, who now tends to write about politics rather than science and presents himself as a space policy expert, was placed on the hook for just $1,000. Steyn, who is still actively fighting the climate wars and hosts a continued attack on Mann on his website, was told to pay Mann $1 million.

That said, the suit’s not over yet. Steyn has suggested that there are grounds to appeal the monetary award, while Mann has indicated that he will appeal the decision that had terminated his case against the Competitive Enterprise Institute and National Review. So, check back in another decade and we may have another decision.

Over a decade later, climate scientist prevails in libel case Read More »

london-underground-is-testing-real-time-ai-surveillance-tools-to-spot-crime

London Underground is testing real-time AI surveillance tools to spot crime

AI, AI surveillance, Biz & IT, Freedom of information act, london underground, Security, syndication / /

tube tracking —

Computer vision system tried to detect crime, weapons, people falling, and fare dodgers.

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Commuters wait on the platform as a Central Line tube train arrives at Liverpool Street London Transport Tube Station in 2023.

Thousands of people using the London Underground had their movements, behavior, and body language watched by AI surveillance software designed to see if they were committing crimes or were in unsafe situations, new documents obtained by WIRED reveal. The machine-learning software was combined with live CCTV footage to try to detect aggressive behavior and guns or knives being brandished, as well as looking for people falling onto Tube tracks or dodging fares.

From October 2022 until the end of September 2023, Transport for London (TfL), which operates the city’s Tube and bus network, tested 11 algorithms to monitor people passing through Willesden Green Tube station, in the northwest of the city. The proof of concept trial is the first time the transport body has combined AI and live video footage to generate alerts that are sent to frontline staff. More than 44,000 alerts were issued during the test, with 19,000 being delivered to station staff in real time.

Documents sent to WIRED in response to a Freedom of Information Act request detail how TfL used a wide range of computer vision algorithms to track people’s behavior while they were at the station. It is the first time the full details of the trial have been reported, and it follows TfL saying, in December, that it will expand its use of AI to detect fare dodging to more stations across the British capital.

In the trial at Willesden Green—a station that had 25,000 visitors per day before the COVID-19 pandemic—the AI system was set up to detect potential safety incidents to allow staff to help people in need, but it also targeted criminal and antisocial behavior. Three documents provided to WIRED detail how AI models were used to detect wheelchairs, prams, vaping, people accessing unauthorized areas, or putting themselves in danger by getting close to the edge of the train platforms.

The documents, which are partially redacted, also show how the AI made errors during the trial, such as flagging children who were following their parents through ticket barriers as potential fare dodgers, or not being able to tell the difference between a folding bike and a non-folding bike. Police officers also assisted the trial by holding a machete and a gun in the view of CCTV cameras, while the station was closed, to help the system better detect weapons.

Privacy experts who reviewed the documents question the accuracy of object detection algorithms. They also say it is not clear how many people knew about the trial, and warn that such surveillance systems could easily be expanded in the future to include more sophisticated detection systems or face recognition software that attempts to identify specific individuals. “While this trial did not involve facial recognition, the use of AI in a public space to identify behaviors, analyze body language, and infer protected characteristics raises many of the same scientific, ethical, legal, and societal questions raised by facial recognition technologies,” says Michael Birtwistle, associate director at the independent research institute the Ada Lovelace Institute.

In response to WIRED’s Freedom of Information request, the TfL says it used existing CCTV images, AI algorithms, and “numerous detection models” to detect patterns of behavior. “By providing station staff with insights and notifications on customer movement and behaviour they will hopefully be able to respond to any situations more quickly,” the response says. It also says the trial has provided insight into fare evasion that will “assist us in our future approaches and interventions,” and the data gathered is in line with its data policies.

In a statement sent after publication of this article, Mandy McGregor, TfL’s head of policy and community safety, says the trial results are continuing to be analyzed and adds, “there was no evidence of bias” in the data collected from the trial. During the trial, McGregor says, there were no signs in place at the station that mentioned the tests of AI surveillance tools.

“We are currently considering the design and scope of a second phase of the trial. No other decisions have been taken about expanding the use of this technology, either to further stations or adding capability.” McGregor says. “Any wider roll out of the technology beyond a pilot would be dependent on a full consultation with local communities and other relevant stakeholders, including experts in the field.”

London Underground is testing real-time AI surveillance tools to spot crime Read More »

reddit-beats-film-industry-again,-won’t-have-to-reveal-pirates’-ip-addresses

Reddit beats film industry again, won’t have to reveal pirates’ IP addresses

Policy, reddit piracy / /
The Reddit logo displayed on a smartphone; a laptop is seen in the photo's background.

Getty Images | NurPhoto

Movie companies have lost a third attempt to unmask Reddit users who posted comments discussing piracy. In an order on Wednesday, the US District Court for the Northern District of California rejected movie copyright holders’ demand for seven years’ worth of “IP address log information” on six Reddit users.

In a motion to compel that was filed last month, movie companies Voltage Holdings and Screen Media Ventures argued that “Reddit users do not have a recognized privacy interest in their IP addresses.” But in Wednesday’s ruling, US Magistrate Judge Thomas Hixson said, “The Court finds no reason to believe provision of an IP address is not unmasking subject to First Amendment scrutiny.”

Voltage Holdings and Screen Media Ventures previously sued the Internet service provider Frontier Communications, alleging that it is liable for its users’ copyright infringement. Seeking evidence for that case, the movie companies subpoenaed Reddit in an attempt to prove that Frontier has no meaningful policy for terminating repeat copyright infringers and that this lack of enforcement drew customers to Frontier’s service.

“Reddit argues the Court should deny the motion because it is an unmasking subpoena, targeting a potential witness rather than a potential defendant, and is therefore subjected to First Amendment scrutiny,” Hixson’s order noted. Reddit also argued that the evidence sought by movie companies can be obtained instead from Frontier and from Frontier subscribers.

Hixson’s order, which was previously reported by Torrent Freak, said that courts use a “higher standard for unmasking a non-party witness” than for potential defendants because “litigation can often continue without interfering with a non-party witness’s First Amendment right to anonymity.”

Reddit can protect First Amendment rights of users

The ruling is similar to previous ones in which the same court denied movie-industry attempts to unmask Reddit users. The fact that movie companies only sought IP addresses instead of names this time around wasn’t enough to sway the court.

The previous cases are being called Reddit I and Reddit II. Voltage Holdings was one of the copyright holders involved in Reddit I, while both Voltage Holdings and Screen Media Ventures were involved in Reddit II.

Hixson referred to the prior cases in this week’s ruling, saying the third is similar in part because the “court adjudicating the copyright litigation has already ruled [the movie companies] can obtain identifying information from Frontier for IP addresses known to have pirated using Frontier’s network.” As in the previous cases, the movie companies “cannot show that the information they seek here is unavailable from other sources,” Hixson wrote.

Voltage Holdings and Screen Media Ventures cited Reddit posts in which users say that Frontier didn’t terminate their Internet service despite sending many copyright infringement notices about torrent downloads. One of the users wrote, “I got a total of 44 emails from frontier about downloading torrents and that it could terminate service. They haven’t yet. And I kinda feel like if they didn’t do it after 44 emails. That they won’t… .”

The movie companies argued that getting these Reddit users’ IP addresses is relevant and proportional to the needs of the case because the comments support the allegation “that the ability to pirate content efficiently without any consequences is a draw for becoming a Frontier subscriber… and that Frontier does not have an effective policy for terminating repeat infringers.”

But Reddit has the right to refuse to provide that information, Hixson decided. “The Ninth Circuit has recognized that Internet platforms can assert the First Amendment rights of their users, based on the close relationship between the platform and its users and the ‘genuine obstacles’ users face in asserting their rights to anonymity,” Hixson wrote.

Reddit beats film industry again, won’t have to reveal pirates’ IP addresses Read More »

report:-sam-altman-seeking-trillions-for-ai-chip-fabrication-from-uae,-others

Report: Sam Altman seeking trillions for AI chip fabrication from UAE, others

AI, AI chips, Biz & IT, Google Gemini, large language models, machine learning, microsoft, Microsoft Copilot, openai, sam altman, semiconductor manufacturing, text synthesis, UAE / /

chips ahoy —

WSJ: Audacious $5-$7 trillion investment would aim to expand global AI chip supply.

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WASHINGTON, DC - JANUARY 11: OpenAI Chief Executive Officer Sam Altman walks on the House side of the U.S. Capitol on January 11, 2024 in Washington, DC. Meanwhile, House Freedom Caucus members who left a meeting in the Speakers office say that they were talking to the Speaker about abandoning the spending agreement that Johnson announced earlier in the week. (Photo by Kent Nishimura/Getty Images)

Enlarge / OpenAI Chief Executive Officer Sam Altman walks on the House side of the US Capitol on January 11, 2024, in Washington, DC. (Photo by Kent Nishimura/Getty Images)

Getty Images

On Thursday, The Wall Street Journal reported that OpenAI CEO Sam Altman is in talks with investors to raise as much as $5 trillion to $7 trillion for AI chip manufacturing, according to people familiar with the matter. The funding seeks to address the scarcity of graphics processing units (GPUs) crucial for training and running large language models like those that power ChatGPT, Microsoft Copilot, and Google Gemini.

The high dollar amount reflects the huge amount of capital necessary to spin up new semiconductor manufacturing capability. “As part of the talks, Altman is pitching a partnership between OpenAI, various investors, chip makers and power providers, which together would put up money to build chip foundries that would then be run by existing chip makers,” writes the Wall Street Journal in its report. “OpenAI would agree to be a significant customer of the new factories.”

To hit these ambitious targets—which are larger than the entire semiconductor industry’s current $527 billion global sales combined—Altman has reportedly met with a range of potential investors worldwide, including sovereign wealth funds and government entities, notably the United Arab Emirates, SoftBank CEO Masayoshi Son, and representatives from Taiwan Semiconductor Manufacturing Co. (TSMC).

TSMC is the world’s largest dedicated independent semiconductor foundry. It’s a critical linchpin that companies such as Nvidia, Apple, Intel, and AMD rely on to fabricate SoCs, CPUs, and GPUs for various applications.

Altman reportedly seeks to expand the global capacity for semiconductor manufacturing significantly, funding the infrastructure necessary to support the growing demand for GPUs and other AI-specific chips. GPUs are excellent at parallel computation, which makes them ideal for running AI models that heavily rely on matrix multiplication to work. However, the technology sector currently faces a significant shortage of these important components, constraining the potential for AI advancements and applications.

In particular, the UAE’s involvement, led by Sheikh Tahnoun bin Zayed al Nahyan, a key security official and chair of numerous Abu Dhabi sovereign wealth vehicles, reflects global interest in AI’s potential and the strategic importance of semiconductor manufacturing. However, the prospect of substantial UAE investment in a key tech industry raises potential geopolitical concerns, particularly regarding the US government’s strategic priorities in semiconductor production and AI development.

The US has been cautious about allowing foreign control over the supply of microchips, given their importance to the digital economy and national security. Reflecting this, the Biden administration has undertaken efforts to bolster domestic chip manufacturing through subsidies and regulatory scrutiny of foreign investments in important technologies.

To put the $5 trillion to $7 trillion estimate in perspective, the White House just today announced a $5 billion investment in R&D to advance US-made semiconductor technologies. TSMC has already sunk $40 billion—one of the largest foreign investments in US history—into a US chip plant in Arizona. As of now, it’s unclear whether Altman has secured any commitments toward his fundraising goal.

Updated on February 9, 2024 at 8: 45 PM Eastern with a quote from the WSJ that clarifies the proposed relationship between OpenAI and partners in the talks.

Report: Sam Altman seeking trillions for AI chip fabrication from UAE, others Read More »

one-true-love

One True Love

Highlights / /

We have long been waiting for a version of this story, where someone hacks together the technology to use Generative AI to work the full stack of the dating apps on their behalf, ultimately finding their One True Love.

Or at least, we would, if it turned out he is Not Making This Up.

Fun question: Given he is also this guy, does that make him more or less credible?

Alas, something being Too Good to Check does not actually mean one gets to not check it, in my case via a Manifold Market. The market started trading around 50%, but has settled down at 15% after several people made strong detailed arguments that the full story did not add up, at minimum he was doing some recreations afterwards.

Which is a shame. But why let that stop us? Either way it is a good yarn. I am going to cover the story anyway, as if it was essentially true, because why should we not get to have some fun, while keeping in mind that the whole thing is highly unreliable.

Discussion question throughout: Definitely hire this man, or definitely don’t?

With that out of the way, I am proud to introduce Aleksandr Zhadan, who reports that he had various versions of GPT talk to 5,240 girls on his behalf, one of whom has agreed to marry him.

I urge Cointelegraph, who wrote the story up as ‘Happy ending after dev uses AI to ‘date’ 5,239 women, to correct the error – yes he air quotes dated 5,239 other girls, but Karina Imranovna counts as well, so that’s 5,240. Oops! Not that the vast majority of them should count as dates even in air quotes.

Aleksandr Zhadan (translated from Russian): I proposed to a girl with whom ChatGPT had been communicating for me for a year. To do this, the neural network re-communicated with other 5239 girls, whom it eliminated as unnecessary and left only one. I’ll share how I made such a system, what problems there were and what happened with the other girls.

For context

• Finding a loved one is very difficult

• I want to have time to work, do hobbies, study and communicate with people

• I could go this route myself without ChatGPT, it’s just much longer and more expensive

In 2021 I broke up with my girlfriend after 2 years. She influenced me a lot, I still appreciate her greatly. After a few months, I realized that I wanted a new relationship. But I also realized that I didn’t want to waste my time and feel uncomfortable with a new girl.

Where did the relationship end?

I was looking for a girl on Tinder in Moscow and St. Petersburg. After a couple of weeks of correspondence, I went on dates, but they went to a dead end. Characteristic disadvantages were revealed (drinks a lot, there is stiffness, emotional swings). Yes, this is the initial impression, but it repulsed me. Again, there was someone to compare with.

I decided to simplify communication with girls via GPT. In 2022, my buddy and I got access to the GPT-3 API (ChatGPT didn’t exist yet) in order to log scripted messages via GPT in Tinder. And I searched for them according to the script, so that there were at least 2 photos in the profile.

In addition to searching, GPT could also rewrite after the mark. From 50 autoswipes we got 18 marks. GPT communicated without my intervention based on the request “You’re a guy, talking to a girl for the first time. Your task: not right away, but to invite you on a date.” It’s a crutch and not very humane, but it worked.

So right away we notice that this guy is working from a position of abundance. Must be nice. In my dating roundups, we see many men who are unable to get a large pool of women to match and initiate contact at all.

For a while, he tried using GPT-3 to chat with women without doing much prompt engineering and without supervision. It predictably blew it in various ways. Yet he persisted.

Then we pick things back up, and finally someone is doing this:

To search for relevant girls, I installed photo recognition in the web version of Tinder through torchvision, which was trained on my swipes from another account on 4k profiles. The machine was able to select the right girls almost always correctly. It’s funny that since that time there have been almost a thousand marks.

Look at you, able to filter on looks even though you’re handing off all the chatting to GPT. I mean, given what he is already doing, this is the actively more ethical thing to do on the margin, in the sense that you are wasting women’s time somewhat less now?

And then we filter more?

I made a filter to filter out girls using the ChatGPT and FlutterFlow APIs:

• without a questionnaire

• less than 2 photos

• “I don’t communicate here, write on instagram”

• sieve boxes

• believers

• written zodiac sign

• does not work

• further than 20 km

• show breasts in photo

• photo with flowers

• noisy photos

This is an interesting set of filters to set. Some very obviously good ones here.

So good show here. Filtering up front is one of the most obviously good and also ethical uses.

As is often the case, the man who started out trying to use technology that wasn’t good enough, got great results once the technology caught up to him:

ChatGPT found better girls and chatted longer. I was moving from Tinder to tg with someone. There he communicated and arranged meetings. ChatGPT swiped to the right 353 profiles, 278 tags, he continued the dialogue with 160, I met with 12. In the diagram below I described the principle of operation.

That first statistic, that it swiped right 353 times and got to talk to 160 women, is completely insane. I mean, that’s almost a 50% match rate, whereas estimates in general are 4% to 14%. This was one of the biggest signs that the story is almost certainly at least partly bogus.

After that, ChatGPT was able to get a 7.5% success rate at getting dates. Depending on your perspective, that could be anything from outstanding to rather lousy. In general I would say it is very good, since matches are typically less likely than that to lead to dates, and you are going in with no reason to think there is a good match.

Continued to communicate manually without ChatGPT, but then the communication stopped. The girls behaved strangely, ignored me, or something alarmed me through correspondence. Not like the example before, but still the process was not ok, I understood that.

If you are communicating as a human with a bunch of prospects, and you lose 92% of them before meeting, that might be average, but it is not going to feel great. If you suddenly take over as a human, you are switching strategies and also the loss rates will always be high, so you are going to feel like something is wrong.

Let’s show schematically what ChatGPT looks like for finding girls (I’ll call it V1). He worked on the request “find the best one, keep in touch,” but at the same time he often forgot information, limited himself to communicating on Tinder, and occasionally communicated poorly.

Under clumsy, I’ll note that ChatGPT V1 could schedule meetings at the same time, swore to give me chocolate/flowers/compote, but I didn’t know about it. He came on a date without a gift and the impression of me was spoiled. Or meetings were canceled because there was another meeting at that time.

Did he… not… read… the chat logs?

This kind of thing always blows my mind. You did all that work to set up dates, and you walk in there with no idea what ‘you’ ‘said’ to your dates?

It is not difficult to read the logs if and only if a date is arranged, and rather insane not to. It is not only about the gifts. You need to know what you told them, and also what they told you. 101 stuff.

I stopped ChatGPT V1 and sat down at V2. Integrated Google calendar and TG, divided the databases into general and personal, muted replies and replies to several messages, added photo recognition using FlutterFlow, created trust levels for sharing personal information and could write messages myself.

I mean, yes, sounds like there was a lot of room for improvement, and Calendar integration certainly seems worthwhile, as is allowing manual control. It still seems like there was quite a lot of PEBKAC.

Also this wasn’t even GPT-4 yet, so v2 gets a big upgrade right there.

V2 runs on GPT-4, which has significantly improved correspondence. I also managed to continue communicating with previous girls (oh, how important this will turn out to be later), meeting and just chatting (also good). Meetings haven’t been layered with others yet, wow!

In order for ChatGPT V2 to find me a relevant girl, I asked regular ChatGPT for help. He offered to tell me about my childhood, parents, goals and values. I transferred the data to V2, and then it was possible to speed up compatibility and if something didn’t fit, then communicate with the girl stopped.

Great strategy. Abundance mindset. If you can afford to play a numbers game, make selection work for you, open up, be what would be vulnerable if it was actually you.

I mean, aside from the ethical horrors of outsourcing all this to ChatGPT, of course. There is that. But if you were doing it yourself it would seem great.

Then he decided to… actually put a human in the loop and do the work? I mean you might as well actually write the responses?

I also enabled response validation so that I would first receive a message for proofreading via a bot. V2’s problems with hallucinations have decreased to zero. I just watched as ChatGPT got acquainted and everything was timid. This time there are 4943 matches per month on Tinder Gold and it’s scary to count how many meetings.

Once again, if you give even a guy with no game 4,943 matches to work with each month, he is going to figure things out through trial, error and the laws of large numbers. With all this data being gathered, it is a shame there was no ability to fine tune. In general not enough science is being done.

On dates we ate, drank at the bar, then watched a movie or walked the streets, visited exhibitions and tea houses. It took 1-3 meetings to understand whether she was the one or not. And I understood that people usually meet differently, but for me this process was super different. I even talked about it in Inc.

On the contrary, that sounds extremely normal, standard early dating activity if you are looking for a long term relationship.

For several weeks I reduced my communication and meetings to 4 girls at a time. Switched the rest to mute or “familiar” mode. I felt like a candidate for a dream job with several offers. As a result, I remained on good terms with 3, and on serious terms with 1.

So what he is noticing is that quality and paying actual attention is winning out over quantity and mass production via ChatGPT. Four at a time is still a lot, but manageable if you don’t have a ton otherwise happening. It indicates individual attention for all of them, although he is keeping a few in ‘familiar’ mode I suppose.

He does not seem to care at all about all the time of the women he is talking with, which would be the best reason not to talk to dozens or hundreds at once. Despite this, he still lands on the right answer. I worry how many men, and also women, will also not care as the technology proliferates.

The most charming girl was found – Karina. ChatGPT communicated with her as V1 and V2, communication stopped for a while, then I continued to communicate myself through ChatGPT V2. Very empathic, cheerful, pretty, independent and always on the move. Simply put, SHE!

I stopped communicating with other girls (at the same time Tinder was leaving in Russia) and the meaning of the bot began to disappear – I have excellent relationships that I value more and more. And I almost forgot about ChatGPT V2

This sounds so much like the (life-path successful) pick up artist stories. Before mass production, chop wood carry water. After mass production, chop wood, carry water.

Except, maybe also outsource a bunch of wood chopping and water carrying, use time to code instead?

Karina talks about what is happening, invites us to travel, and works a lot with banking risks. I talk about what’s happening (except for the ChatGPT project), help, and try to make people happy. Together we support each other. To keep things going as expected, I decided to make ChatGPT V3.

So even though he’s down to one and presumably is signing off on all the messages himself, he still finds the system useful enough to make a new version. But he changes it to suite the new situation, and now it seems kind of reasonable?

In V3 I didn’t have to look for people, just maintain a dialogue. And now communication is not with thousands, but with Karina. So I set up V3 as an observer who communicates when I don’t write for a long time and advises me on how to communicate better. For example, support, do not quarrel, offer activities.

Nice. That makes so much sense. You use it as an advisor on your back, especially to ensure you maintain communication and follow other basic principles. He finds it helpful. This is where you find product-market fit.

During our relationship, Karina once asked how many girls and dates I had, which was super difficult for me to answer. He talked about several girls, and then switched to another topic. She once joked that with such a base it was time to open a brothel.

I came up with the idea of ​​recommending them for vacancies through referrals. I made a script – I entered a vacancy and got a suitable girl from the dialogues. I found the vacancies in Playkot, Awem and TenHunter on TenChat, then anonymously sent contacts with Linkedin or without a resume. Arranged for 8 girls, earned 526 rubles.

Well, that took a turn, although it could have taken a far worse one, dodged a bullet there. The traditional script is that she finds out about the program and that becomes the third act conflict. Instead, he’s doing automated job searches. He earned a few bucks, but not many.

It was possible to create a startup, but I switched to a more promising project (I work with neural networks). In addition, my pipeline has become outdated, taking into account innovations such as Vision in ChatGPT, improvements to Langсhain (I used it as a basis for searching for girls). In general, it could all end here.

And then the tail got to wag the dog, and we have our climax.

One day, ChatGPT V3 summarized the chat with Karina, based on which it recommended marrying her. I thought that V3 was hallucinating (I never specified the goal of getting married), but then I understood his train of thought – Karina said that she wanted to go to someone’s wedding and ChatGPT thought that it would be better at her own.

I asked in a separate ChatGPT to prepare an action plan with several scenarios for a request like “Offer me a plan so that a girl accepts a marriage proposal, taking into account her characteristics and chat with her.” Uploaded the correspondence with Karina to ChatGPT and RECEIVED THE PLAN.

Notice how far things have drifted.

At first, there was the unethical mass production of the AI communicating autonomously pretending to be him so he could play a numbers game and save time.

Now he’s flat out having the AI tell him to propose, and responding by having it plan the proposal, and doing what it says. How quickly we hand over control.

The good news is, the AI was right, it worked.

The situation hurt. Super afraid that something might go wrong. I went almost exactly according to plan № 3 and everything came to the right moment. I propose to get married.

She said yes.

So how does he summarize all this?

The development of the project took ~120 hours and $1432 for the API. Restaurant bills amounted to 200k rubles. BTV, I recovered the costs and made money on recommendations. If you met yourself and went on dates, then the same thing took 5+ years and 13m+ rubles. Thanks to ChatGPT for saving money and time

Twitter translated that as 200 rubles, which buys you one coffee maybe two if they are cheap, which indicates how reliable are the translations here. ChatGPT said it was 200k, which makes sense.

What drives me mad about this whole thread is that it skips the best scene. In some versions of this story, he quietly deletes or archives the program, or maybe secretly keeps using it, and Karina never finds out.

Instead, he is posting this on Twitter. So presumably she knows. When did she find out? Did he tell her on purpose? Did ChatGPT tell him how to break the news? How did she react?

The people bidding on the movie rights want to know. I also want to know. I asked him directly, when he responded in English to my posting of the Manifold Market, but he’s not talking. So we will never know.

And of course, the whole thing might be largely made up. It still could have happened.

If it has not yet happened, it soon will. Best be prepared.

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We keep making the same mistakes with spreadsheets, despite bad consequences

Science, spreadsheets, syndication / /

Not excelling at Excel —

Errors with spreadsheets are not only frustrating but can have serious consequences.

–

A dude being sad about his spreadhseet

Spreadsheet blunders aren’t just frustrating personal inconveniences. They can have serious consequences. And in the last few years alone, there have been a myriad of spreadsheet horror stories.

In August 2023, the Police Service of Northern Ireland apologized for a data leak of “monumental proportions” when a spreadsheet that contained statistics on the number of officers it had and their rank was shared online in response to a freedom of information request.

There was a second overlooked tab on the spreadsheet that contained the personal details of 10,000 serving police officers.

A series of spreadsheet errors disrupted the recruitment of trainee anesthetists in Wales in late 2021. The Anaesthetic National Recruitment Office (ANRO), the body responsible for their selection and recruitment, told all the candidates for positions in Wales they were “unappointable”, despite some of them achieving the highest interview scores.

The blame fell on the process of consolidating interview data. Spreadsheets from different areas lacked standardization in formatting, naming conventions, and overall structure. To make matters worse, data was manually copied and pasted between various spreadsheets, a time-consuming and error-prone process.

ANRO only discovered the blunder when rejected applicants questioned their dismissal letters. The fact that not a single candidate seemed acceptable for Welsh positions should have been a red flag. No testing or validation was apparently applied to the crucial spreadsheet, a simple step that could have prevented this critical error.

In 2021, Crypto.com, an online provider of cryptocurrency, accidentally transferred $10.5 million (£8.3 million) instead of $100 into the account of an Australian customer due to an incorrect number being entered on a spreadsheet.

The clerk who processed the refund for the Australian customer had wrongly entered her bank account number in the refund field in a spreadsheet. It was seven months before the mistake was spotted. The recipient attempted to flee to Malaysia but was stopped at an Australian airport carrying a large amount of cash.

In 2022, Íslandsbanki, a state-owned Icelandic bank, sold a portion of shares that were badly undervalued due to a spreadsheet error. When consolidating assets from different spreadsheets, the spreadsheet data was not “cleaned” and formatted properly. The bank’s shares were subsequently undervalued by as much as £16 million.

The dark matter of corporate IT

The above is just a fraction of the spreadsheet errors that are regularly made by various organizations.

Spreadsheets represent unknown risks in the form of errors, privacy violations, trade secrets, and compliance violations. Yet they are also critical for the way many organizations make their decisions. For this reason, they have been described by experts as the “dark matter” of corporate IT.

Industry studies show that 90 percent of spreadsheets containing more than 150 rows have at least one major mistake.

This is understandable because spreadsheet errors are easy to make but difficult to spot. My own research has shown that inspecting the spreadsheet’s code is the most effective way of debugging them, but this approach still only catches between 60 and 80 percent of all errors.

As many as 9 out of 10 spreadsheets are estimated to contain errors.

As many as 9 out of 10 spreadsheets are estimated to contain errors.

Spreadsheets’ appeal doesn’t just exist in the financial world. They are indispensable in engineering, data science, and even in sending robots to Mars. The key to their success is their flexibility.

Spreadsheet software is constantly evolving, with more features becoming available that increase their appeal. For instance, you can now automate many tasks in Excel (the most popular spreadsheet software) using Python scripting.

But given all of the aforementioned problems, isn’t it time for Excel and other spreadsheet software to be sidelined in favor of something more reliable?

Human error

The underlying cause of these spreadsheet problems is not the software but human error.

The issue is that most users don’t see the need to plan or test their work. Most users describe their first step in creating a new spreadsheet as merely jumping straight in and entering numbers or code directly.

Many of us don’t consider spreadsheets to warrant serious consideration. This means we become complacent and assume there is no need to test, validate, or verify our work.

Research on “cognitive load,” the amount of mental effort required for a task, shows that building complex spreadsheets demands as much concentration as a GP making a diagnosis. This intense mental strain makes mistakes more likely. But GPs study their profession for many years before becoming qualified, while most spreadsheet users are self-taught.

To break the cycle of repeated spreadsheet errors, there are several things organisations can do. First, introducing standardization would help to minimize confusion and mistakes. For example, this would mean consistent formatting, naming conventions, and data structures across spreadsheets.

Second, improving training is crucial. Equipping users with the knowledge and skills to build robust and accurate spreadsheets could help them identify and avoid pitfalls.

Finally, fostering a culture of critical thinking toward spreadsheets is vital. This would mean encouraging users to continually question calculations, validate their data sources, and double-check their work.

Simon Thorne is Senior Lecturer in Computing and ​Information Systems at Cardiff Metropolitan University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Aluminum mining waste could be a source of green steel

aluminum, chemistry, green chemistry, iron, ores, Science / /

Upcycling —

After the extraction, the remaining waste is less harmful to the environment.

–

Image of a largely green landscape with a large, square area of red much in the center.

Enlarge / A red mud retaining pond in Germany.

The metals that form the foundation of modern society also cause a number of problems. Separating the metals we want from other minerals is often energy-intensive and can leave behind large volumes of toxic waste. Getting them in a pure form can often require a second and considerable energy input, boosting the associated carbon emissions.

A team of researchers from Germany has now figured out how to handle some of these problems for a specific class of mining waste created during aluminum production. Their method relies on hydrogen and electricity, which can both be sourced from renewable power and extracts iron and potentially other metals from the waste. What’s left behind may still be toxic but isn’t as environmentally damaging.

Out of the mud

The first step in aluminum production is the isolation of aluminum oxide from the other materials in the ore. This leaves behind a material known as red mud; it’s estimated that nearly 200 million tonnes are produced annually. While the red color comes from the iron oxides present, there are a lot of other materials in it, some of which can be toxic. And the process of isolating the aluminum oxide leaves the material with a very basic pH.

All of these features mean that the red mud generally can’t (or at least shouldn’t) be returned to the environment. It’s generally kept in containment ponds—globally, these are estimated to house 4 billion tonnes of red mud, and many containment pods have burst over the years.

The iron oxides can account for over half the weight of red mud in some locations, potentially making it a good source of iron. Traditional methods have processed iron ores by reacting them with carbon, leading to the release of carbon dioxide. But there have been efforts made to develop “green steel” production in which this step is replaced by a reaction with hydrogen, leaving water as the primary byproduct. Since hydrogen can be made from water using renewable electricity, this has the potential to eliminate a lot of the carbon emissions associated with iron production.

The team from Germany decided to test a method of green steel production on red mud. They heated some of the material in an electric arc furnace under an atmosphere that was mostly argon (which wouldn’t react with anything) and hydrogen (at 10 percent of the mix).

Pumping (out) iron

The reaction was remarkably quick. Within a few minutes, metallic iron nodules started appearing in the mixture. The iron production was largely complete by about 10 minutes. The iron was remarkably pure, at about 98 percent of the material by weight in the nodules being iron.

Starting with a 15-gram sample of red mud, the process reduced this to 8.8 grams, as lots of the oxygen in the material was liberated in the form of water. (It’s worth noting that this water could be cycled back to hydrogen production, closing the loop on this aspect of the process.) Of that 8.8 grams, about 2.6 (30 percent) was in the form of iron.

The research found that there are also some small bits of relatively pure titanium formed in the mix. So, there’s a chance that this can be used in the production of additional metals, although the process would probably need to be optimized to boost the yield of anything other than iron.

The good news is that there’s much less red mud left to worry about after this. Depending on the source of the original aluminum-containing ore, some of this may include relatively high concentrations of valuable materials, such as rare earth minerals. The downside is that any toxic materials in the original ore are going to be significantly more concentrated.

As a small plus, the process also neutralizes the pH of the remaining residue. So, that’s at least one less thing to worry about.

The downside is that the process is incredibly energy-intensive, both in producing the hydrogen required and running the arc furnace. The cost of that energy makes things economically challenging. That’s partly offset by the lower processing costs—the ore has already been obtained and has a relatively high purity.

But the key feature of this is the extremely low carbon emissions. Right now, there’s no price on those in most countries, which makes the economics of this process far more difficult.

Nature, 2024. DOI: 10.1038/s41586-023-06901-z  (About DOIs).

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Secret military space programs can be a little less secret, Pentagon says

classified information, military space, Pentagon, Space, space force / /
A delegation of French military officers visited the Combined Space Operations Center in 2022 at Vandenberg Space Force Base, California.

Enlarge / A delegation of French military officers visited the Combined Space Operations Center in 2022 at Vandenberg Space Force Base, California.

Late last year, Deputy Secretary of Defense Kathleen Hicks signed a memo to overhaul a decades-old policy on how the Pentagon keeps sensitive military space programs secret. However, don’t expect defense officials to openly discuss everything they’re doing to counter China and Russia in orbit.

John Plumb, assistant secretary of defense for space policy, revealed the policy change in a roundtable with reporters on January 17. For many years, across multiple administrations, Pentagon officials have lamented their inability to share information with other countries and commercial partners. Inherently, they argued, this stranglehold on information limits the military’s capacity to connect with allies, deter adversaries, and respond to threats in space.

In his statement last week, Plumb said this new policy “removes legacy classification barriers that have inhibited our ability to collaborate across the US government and also with allies on issues related to space.”

But Plumb was careful to point out that the memo from Hicks calls for “declassification, not unclassification” of military space programs. “So think of it as reducing classification.” Effectively, this means the Pentagon can make sensitive information available to people with lower security clearances. More eyes on a problem usually mean better solutions.

New policy for a new century

Some of the Pentagon’s most secret space technologies are part of Special Access Programs (SAPs), where information is highly compartmentalized, and only a few officials know all facets of the program. With SAPs, it’s difficult or impossible to share information with allies and partners, and sometimes officials run into roadblocks even discussing the programs with different parts of the Defense Department.

“Overall, the department does overclassify,” Hicks told reporters in November.

Generally, it’s easier to assign a classification level to a document or program than it is to change the classification level. “The originator of a document, usually a foreign policy or national security staff member, decides if it needs to be classified,” wrote Bruce Riedel, a 30-year veteran of the CIA and a former advisor to four presidents. “In almost all cases this is a simple decision. Has its predecessors been classified? If so, classify.”

The government has periodic reviews to determine whether something still needs to be classified, but most of the time, secret documents take decades to be reviewed. If they are released at all, they generally have value only as part of the historical record.

The declassification memo signed by Hicks is, itself, classified, Plumb said. Hicks signed it at the end of last year.

“What the classification memo does generally is it … really completely rewrites a legacy document that had its roots 20 years ago,” Plumb said. “And it’s just no longer applicable to the current environment that involves national security space.”

The Pentagon has identified China as the paramount national security threat to the United States. Much of what the Pentagon is doing in space is geared toward maintaining the US military’s competitive advantage against China or responding to China in cases where Chinese capabilities may threaten US assets in orbit.

This overarching focus on China touches on all military space programs and the NRO’s fleet of spy satellites. The military is launching new constellations of satellites designed to detect and track hypersonic missiles, demonstrating their ability to quickly get a satellite into orbit, and is interested in using commercial space capabilities from US industry, ranging from in-space refueling to broadband communications.

“Our network of allies and partners is an asymmetric advantage and a force multiplier that neither China nor Russia could ever hope to match,” Plumb said.

Officials have said the threat environment requires the military to be more agile. It’s more vital to collaborate with allies and commercial partners.

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