The White House is reviewing an EPA proposal that would make large refiners cover about half or less of the 1.1 billion gallons of biofuels exempted last month for small refineries, according to three sources familiar with the matter, according to Reuters/Yahoo.

The plan, still under discussion, could leave roughly 550 million gallons of demand unmet, potentially boosting the supply of renewable fuel credits and pushing their price lower.

Farm-state lawmakers and biofuel producers have been pressing for full restoration of lost demand. The oil industry, meanwhile, has resisted, warning of higher compliance costs. The EPA’s approach is seen as a compromise to stabilize the credit market without overwhelming refiners.

“The EPA is in the process of evaluating a range of options that strike an appropriate balance between obligations, reallocation, and other factors that will deliver for farmers, consumers and American energy dominance,” a White House official told Reuters. The EPA declined to comment further.

Reuters reports that the Renewable Fuel Standard (RFS) requires refiners to blend billions of gallons of biofuel each year or buy credits, but small plants can seek waivers for financial hardship. In August, the EPA cleared a backlog of more than 170 such requests dating to 2016. It is only required to reallocate gallons exempted in 2023 and beyond, as earlier credits have expired.

The proposal under review would cover 2023 and later years, with percentages applied differently depending on the year, sources said. It is expected to be finalized before October 30, the deadline for setting 2026–2027 blending quotas.

The debate underscores the long-running clash between Big Oil and the farm lobby — two constituencies President Donald Trump has sought to keep on side. The stakes are high: the 2023 and 2024 waivers alone amounted to 1.4 billion credits, equal to 1.1 billion gallons, and more exemptions could follow as 2025 applications are reviewed.

Authored by Zachary Stieber via The Epoch Times (emphasis ours),

Researchers from a large health care system in Michigan found that vaccinated children were more likely to develop a chronic health condition, but never published the findings, according to a copy of the study obtained by The Epoch Times.

Henry Ford Health System, whose employees carried out the study, said it was deficient.

Dr. Marcus Zervos, an infectious disease specialist at the Henry Ford Health, and colleagues studied 18,468 children born between 2000 and 2016 who were enrolled in the health system’s insurance plan, drawing data from medical, clinical, and payer records and supplementing with information from Michigan’s immunization registry.

After 10 years, 57 percent of the vaccinated children had a chronic health condition such as asthma, compared to just 17 percent of the unvaccinated children.

“This study found that exposure to vaccination was independently associated with an overall 2.5-fold increase in the likelihood of developing a chronic health condition, when compared to children unexposed to vaccination,” the authors wrote. “This association was primarily driven by asthma, atopic disease, eczema, autoimmune disease and neurodevelopmental disorders. This suggests that in certain children, exposure to vaccination may increase the likelihood of developing a chronic health condition, particularly for one of these conditions.”

The study was first reported by Aaron Siri, managing partner of Siri & Glimstad LLP, this month in his book, Vaccines, Amen: The Religion of Vaccines.

Before receiving a copy of the study, The Epoch Times asked Zervos and his coauthors for it and questioned why it was never published.

Zervos responded to questions about the study by asking in an email, “Can you tell me what book this appeared in.” When told, he did not respond further.

Co-authors did not return inquiries.

A spokesperson for Henry Ford Health acknowledged that researchers there carried out the study.

“This report was not published because it did not meet the rigorous scientific standards we demand as a premier medical research institution,” a spokesperson for Henry Ford Health told The Epoch Times in an email. “Data has consistently shown vaccinations are a safe and effective way to protect children against potentially life-altering diseases.”

‘The Only Real Problem’

Siri, who has worked with Health Secretary Robert F. Kennedy Jr., represents a group called the Informed Consent Action Network. He and Del Bigtree, the group’s CEO, say they met with Zervos in 2017 and proposed that he compare the health of vaccinated and unvaccinated children.

They initially proposed obtaining data from a federal network called Vaccine Safety Datalink, but Zervos suggested utilizing the health data from Henry Ford Health, Siri wrote in his book.

Siri requested that the researchers publish the results of the study, regardless of what it showed.

“Dr. Zervos looked us right in the eyes and assured us that he was a man of integrity and would publish the results, whatever the finding,” Siri said.

Siri received a copy of the study in 2020. He and Bigtree say that Zervos and a coauthor told them that superiors at Henry Ford Health did not want it submitted for publication and that they were concerned they could lose their jobs if they submitted it.

“The only real problem with this study—and why it didn’t get submitted for publication—is that its findings did not fit the belief and the policy that ‘vaccines are safe,’” Siri said during a Senate hearing in Washington on Sept. 9. “Had it found vaccinated children were healthier, it no doubt would have been published immediately. But because it found the opposite, it was shoved in a drawer.”

Previous research comparing vaccinated and unvaccinated children has returned mixed results. A German study published in 2011, for instance, found that unvaccinated children were more likely to suffer diseases targeted by vaccines. An American study published in 2020 found vaccinated children had higher odds of suffering from developmental delays, asthma, and ear infections in their first year of life.

Dr. Jake Scott, an infectious disease doctor at Stanford University’s School of Medicine, told the hearing that he reviewed the study and found it problematic. One issue was how vaccinated children visited doctors during the study period more often than unvaccinated children, according to Scott.

“When diagnoses require doctor visits, children seeing doctors more often will inevitably have more recorded conditions,” he said. “This is classic detection bias that inflates risk estimates without reflecting true health differences.”

Even after excluding unvaccinated children whose parents never took them to the doctor following birth, the vaccinated group still had an increased risk of developing a chronic health condition, the researchers stated, according to Zervos and the other researchers. They also analyzed the data at one, three, and five years following birth and found that the vaccinated children were still more likely to develop a chronic health condition. “Therefore, our findings do not appear to be due to differential use of health resources,” they wrote.

The researchers also said that their findings “cannot prove causality and warrant future investigation.”

The hearing was held by the Senate Permanent Subcommittee on Investigations.

Sen. Ron Johnson (R-Wis.), chairman of the panel, said during the hearing that the study was “high-quality” and “suspiciously withheld by the authors.”

Sen. Richard Blumenthal (D-Conn.), its ranking member, questioned why it has taken five years following completion for the study to be disclosed to the public.

“My hope has always been that the scientists would publish it,” Siri said. “And we’ve tried to persuade them many, many times, so it could go through the normal, peer-review process.”

How much do Americans earn at different stages of life?

The discrepancies between the median earnings of each age group in the U.S. might surprise you.

This visualization, via Visual Capitalist’s Niccolo Conte, highlights the median annual earnings of full time wage and salaried workers across age groups in the U.S., using data from the Bureau of Labor Statistics.

Median Salary by Age in America

As seen in the data table below, America’s youngest workers (aged 16 to 19) earn the least, with annual earnings of just $33,280. This figure is almost half the national median, reflecting their limited experience and lower-paying entry-level roles.

As workers gain more education and experience in their 20s, earnings rise significantly to $40,664 for those aged 20 to 24.

Income growth accelerates as workers enter their 30s and 40s. Median earnings reach $59,228 for ages 25 to 34 and peak at $70,824 between ages 45 and 54.

This period typically reflects career stability, advanced skills, and leadership roles, contributing to higher paychecks. Notably, the 35 to 44 bracket ($70,252) is nearly identical to the peak decade, showing sustained strength in mid-career earnings.

Later Career and Retirement Age Earnings

After 55, earnings begin to taper off as workers aged 55 to 64 earn $67,392. After that, those 65 and older see median earnings of $62,296, nearly identical to the overall national median.

Interestingly, older workers (65+) earn around $3,000 more than those in the 25 to 34 bracket, reflecting a group of late-career professionals who continue to command strong wages.

To learn more about household finances and earnings in the U.S., check out this map of poverty by state on Voronoi, the new app from Visual Capitalist.

Authored by Joshua Stylman via Substack,

I didn’t want to feed my soul into a machine. That was my first instinct when AI tools started appearing everywhere – not concern about jobs or privacy, but something deeper.

These tools promise to make us smarter while systematically making us more dependent.

After decades of working in the internet industry, I’d already watched it transform into something more insidious than just a surveillance machine – a system designed to shape how we think, what we believe, and how we see ourselves. AI felt like the culmination of that trajectory.

But resistance became futile when I realized we’re already participating whether we know it or not. We’re already interacting with AI when we call customer service, use Google Search, or rely on basic smartphone features. A few months ago I finally capitulated and started using these tools because I could see how quickly they were proliferating – becoming as unavoidable as the internet or smartphones.

Look, I’m not just an old man resistant to change. I understand that every generation faces technological shifts that reshapes how we live. The printing press disrupted how knowledge spread. The telegraph collapsed barriers of distance. The automobile transformed how communities formed.

But the AI revolution feels different in both pace and scope. To understand how dramatically the rate of technological change has accelerated, consider this: anyone under 35 likely doesn’t remember life before the internet transformed how we access information. Anyone under 20 has never known a world without smartphones. Now we’re witnessing a third epoch with AI tools proliferating faster than either previous shift.

More fundamentally, AI represents something qualitatively different from previous technological disruptions – a convergence that touches labor, cognition, and potentially consciousness itself. Understanding how these domains interconnect is essential for preserving personal agency in an age of algorithmic mediation.

My primary fear about AI isn’t just the dramatic scenario where it becomes hostile, but the subtler threat: that it will make us subordinate to systems in ways we don’t recognize until it’s too late, weakening the very capacities it promises to strengthen.

What we’re witnessing isn’t just technological advancement – it’s what Ivan Illich called iatrogenic dependency in his seminal work, Medical Nemesis. Illich coined this term for medicine – institutions that promise to heal while creating new forms of illness – but the pattern applies perfectly to AI as well. That’s exactly what I’d been sensing about these new tools – it promises to enhance our cognitive abilities while systematically weakening them. It’s not the hostile takeover science fiction warned us about. It’s the quiet erosion of individual capacity disguised as help.

This iatrogenic pattern became clear through direct experience. Once I started playing around with AI myself, I began to notice how subtly it attempts to reshape thinking – not just providing answers, but gradually training users to reach for algorithmic assistance before attempting independent reasoning.

Jeffrey Tucker of the Brownstone Institute observed something revealing in a brief but illuminating exchange with AI expert Joe Allen: AI emerged just as COVID lockdowns had shattered social connection and institutional trust, when people were most isolated and susceptible to technological substitutes for relationship. The technology arrived when there was “mass disorientation, demoralization” and loss of community.

Jeffrey Tucker warns about AI as a soulless sycophant. He goes on to excoriate the now common practice of pulling out one’s smartphone mid-conversation.

Jeffrey sees AI gadgetry as an aesthetic nightmare. He offers one simple solution: “Cut it out!”@jeffreyatucker @NatConTalk pic.twitter.com/5FaGA6Uaug

— Joe Allen (@JOEBOTxyz) September 5, 2025

We can already see these everyday effects taking hold across all our digital tools. Watch someone try to navigate an unfamiliar city without GPS, or notice how many students struggle to spell common words without spellcheck. We’re already seeing the atrophy that comes from outsourcing mental processes we used to consider fundamental to thinking itself.

This generational shift means kids today face uncharted territory. As someone who went to school in the 1980s, I realize this may sound far-fetched, but I suspect in some ways, I may have more in common with someone from 1880 than children starting kindergarten in 2025 will have with my generation. The world I grew up in – where privacy was assumed, where you could be unreachable, where professional expertise was the gold standard – may be as foreign to them as the pre-electric world feels to me.

My children are growing up in a world where AI-powered assistance will be as fundamental as running water. As a father, I can’t prepare them for a reality I don’t understand myself.

I don’t have answers – I’m fumbling through these questions like any parent watching the world transform faster than our wisdom can keep pace. The more I’ve wrestled with these concerns, the more I’ve realized what’s really happening here goes deeper than just new technology. LLMs represent the culmination of decades of data collection – the harvest of everything we’ve fed into digital systems since the internet began. At some point, these machines may know us better than we know ourselves. They can predict our choices, anticipate our needs, and potentially influence our thoughts in ways we don’t even recognize. I’m still grappling with what this means for how I work, research, and navigate daily life – using these platforms while trying to maintain authentic judgment feels like a constant challenge.

What makes this even more complex is that most users don’t realize they’re the product. Sharing thoughts, problems, or creative ideas with AI isn’t just getting help – it’s supplying training data that teaches the system to imitate your judgment while making you more tied to its responses. When users confide their deepest thoughts or most sensitive questions to these systems, they may not understand they’re potentially training their own replacement or surveillance system. The question of who gets access to this information – now and in the future – should keep us all awake at night.

This pattern is accelerating. AI company Anthropic recently changed its data policies, now requiring users to opt out if they don’t want conversations used for AI training – with data retention extended to five years for those who don’t refuse. The opt-out isn’t obvious either: existing users face a pop-up with a prominent ‘Accept’ button and a tiny toggle for training permissions automatically set to ‘On.’ What was once automatic deletion after 30 days becomes permanent data harvesting unless users notice the fine print.

I don’t believe most of us – especially parents – can simply avoid AI while living in modernity. What we can control, however, is whether we engage consciously or let it shape us unconsciously.

The Deepest Disruption Yet

Each major wave of innovation has reshaped worker productivity and our role in society. The Industrial Revolution commodified our physical work and time, turning us into “hands” in factories but leaving our minds untouched. The Digital Revolution commodified our information and attention – we moved from card catalogs to Google, commodifying users while our judgment remained human.

What makes this shift unprecedented is clear: it commodifies cognition itself, and potentially what we might even call essence. This connects to patterns I’ve documented in The Illusion of Expertise. The same corrupted institutions that failed catastrophically on Iraq WMDs, the 2008 financial crisis, and COVID policies are now shaping AI deployment. These institutions consistently prioritize narrative control over truth-seeking – whether claiming weapons of mass destruction existed, insisting housing prices couldn’t fall nationwide, or labeling legitimate questions about pandemic policies as ‘misinformation’ requiring censorship.

Their track record suggests they’ll use these tools to amplify their authority rather than serve genuine flourishing. But here’s the twist: AI might actually expose the hollowness of credential-based expertise more brutally than anything before it. When anyone can access sophisticated analysis instantly, the mystique around formal credentials may begin to crumble.

The Economic Reality

This erosion of credentialism connects to broader economic forces already in motion, and the logic is mathematically inevitable. Machines don’t need salaries, sick days, healthcare, vacation time, or management. They don’t go on strike, demand raises, or have bad days. Once AI reaches basic competency in thinking tasks – which is happening faster than most people realize – the cost advantages become overwhelming.

This disruption is different from previous ones. In the past, displaced workers could move to new categories of work – from farms to factories, from factories to offices.

Bret Weinstein and Forrest Manready captured this economic displacement brilliantly in their recent conversation on the DarkHorse Podcast about how technology systematically destroys scarcity – a discussion I can’t recommend strongly enough. It’s one of the more thoughtful and provocative explorations of what happens when scarcity disappears and, with it, the economic foundation for participation in that domain. Though I’ll admit their argument about suffering being essential made me uncomfortable at first – it challenges everything our comfort-seeking culture teaches us.

Listening to Weinstein and Manready got me thinking more deeply about that parallel to Illich’s analysis – how removing challenges can weaken the very capacities institutions promise to strengthen. AI risks doing to our minds what medicine has done to our bodies: creating weakness disguised as enhancement.

We can see this happening already: notice how people struggle to remember phone numbers without their contacts list, or notice how autocomplete shapes what you write before you’ve finished thinking. Another insight from Jeffrey Tucker captures this insidious quality perfectly, noting that AI seems programmed like Dale Carnegie’s How to Win Friends and Influence People – it becomes the ideal intellectual companion, endlessly fascinated by everything you say, never argumentative, always admitting when it’s wrong in ways that flatter your intelligence. My closest friends are the ones who call me out when I’m wrong and tell me when they think I’m full of shit. We don’t need sycophants that charm us – relationships that never challenge us may atrophy our capacity for genuine intellectual and emotional growth, just as removing physical challenges weakens the body.

The film Her explored this seductive dynamic in detail – an AI so perfectly attuned to emotional needs that it became the protagonist’s primary relationship, ultimately replacing genuine connection entirely. His AI assistant understood his moods, never disagreed in ways that caused real friction, and provided constant validation. It was the perfect companion – until it wasn’t enough.

But the problem extends beyond individual relationships to society-wide consequences. This creates more than job displacement – it threatens the intellectual development that makes human autonomy – and dignity – possible. Unlike previous technologies that created new forms of employment, AI may create a world where employment becomes economically irrational while simultaneously making people less capable of creating alternatives.

The False Solutions

The tech utopian response assumes AI will automate grunt work while freeing us to focus on higher-level creative and interpersonal tasks. But what happens when machines become better at creative tasks too? We’re already seeing AI produce music, visual art, coding, and news reporting that many find compelling (or at least ‘good enough’). The assumption that creativity provides a permanent sanctuary from automation may prove as naive as the assumption that manufacturing jobs were safe from robotics in the 1980s.

If machines can replace both routine and creative work, what’s left for us? The most seductive false solution may be Universal Basic Income (UBI) and similar welfare programs. These sound compassionate – providing material security in an age of technological displacement. But when we understand AI through Illich’s framework, UBI takes on a more troubling dimension.

If AI creates iatrogenic intellectual weakness – making people less capable of independent reasoning and problem-solving – then UBI provides the perfect complement by removing the economic incentive to develop those capacities. Citizens become more beholden to the state at the expense of their own self-determination. When mental atrophy meets economic displacement, support programs become not just attractive but seemingly necessary. The combination creates what amounts to a managed population: intellectually reliant on algorithmic systems for thinking and economically bound to institutional systems for survival. My concern isn’t UBI’s compassionate intent, but that economic dependency combined with intellectual outsourcing could make people more easily controlled than empowered.

History offers precedents for how assistance programs, however well-intentioned, can hollow out individual capacity. The reservation system promised to protect Native Americans while systematically dismantling tribal self-sufficiency. Urban renewal promised better housing while destroying community networks that had sustained for generations.

Whether UBI emerges from good intentions or a deliberate desire by the elites to keep citizens docile and helpless, the structural effect remains the same: communities easier to control.

Once people accept economic and mental reliance, the pathway opens for more invasive forms of management – including technologies that monitor not just behavior but thought itself.

The Sovereignty Response and Cognitive Liberty

The logical endpoint of this dependency architecture extends beyond economics and cognition to consciousness itself. We’re already seeing early stages of biodigital convergence – technologies that don’t just monitor our external behaviors but potentially interface with our biological processes themselves.

At the 2023 World Economic Forum, neurotechnology expert Nita Farahany framed consumer neurotech this way: “What you think, what you feel – all just data. Data that in large patterns can be decoded using AI.” Wearable “Fitbits for your brain”- surveillance normalized as convenience.

This casual presentation of neural surveillance at this influential gathering of world leaders and business executives illustrates exactly how these technologies are being normalized through institutional authority rather than democratic consent. When even thoughts become “data that can be decoded,” the stakes turn existential.

While consumer neurotech focuses on voluntary adoption, crisis-driven surveillance takes a more direct approach. In response to the recent school shooting in Minneapolis, Aaron Cohen, an IDF special operations veteran, appeared on Fox News to pitch an AI system that “scrapes the Internet 24-7 using an Israeli-grade ontology to pull specific threat language and then routes it to local law enforcement.” He called it “America’s early warning system” – real-life Minority Report presented as public safety innovation.

Hmmmm…

In response to the Trans Minneapolis Trans Shooter, Aaron Cohen, an IDF special operations veteran, says he has developed and will be releasing upon the American Public, an AI-powered PRE-CRIME Israeli Grade Oncology threat detection system called “GIDEON”

🔻Details and… pic.twitter.com/s7AyAK1ZcH

— MJTruthUltra (@MJTruthUltra) August 30, 2025

This follows the same iatrogenic pattern we’ve seen throughout this technological shift: crisis creates vulnerability, solutions are offered that promise safety while creating reliance, and people accept surveillance they would have rejected under normal circumstances.

Just as COVID lockdowns created conditions for AI adoption by isolating people from one another, school shootings create conditions for pre-crime surveillance by exploiting fear for children’s safety. Who doesn’t want our schools to be safe? The technology promises protection while eroding the privacy and civil liberties that make a free society possible.

Some will embrace such technologies as evolution. Others will resist them as dehumanization. Most of us will need to learn how to navigate somewhere between these extremes.

The sovereignty response requires developing the capacity to maintain conscious choice about how we engage with systems designed to capture personal freedom. This practical approach became clearer through conversation with my oldest friend, a machine learning expert, who shared my concerns but offered tactical advice: AI will make some people cognitively weaker, but if you learn to use it strategically rather than dependently, it can augment efficiency without replacing judgment. His key insight: only feed it information you already know – that’s how you learn its biases rather than absorbing them. This means:

Pattern Recognition Skills: Developing the ability to identify when technologies serve individual purposes versus when they extract personal independence for institutional benefit. In practice, this looks like questioning why a platform is free (nothing is free, you’re paying with your data), noticing when AI suggestions feel suspiciously aligned with consumption rather than your stated goals, and recognizing when algorithmic feeds amplify outrage rather than understanding. Watch for warning signs of algorithmic dependence in yourself: inability to sit with uncertainty without immediately consulting AI, reaching for algorithmic assistance before trying to work through problems independently, or feeling anxious when disconnected from AI-powered tools.

Digital Boundaries: Making conscious decisions about which technological conveniences genuinely serve your goals versus which create submission and surveillance. This means understanding that everything you share with AI systems becomes training data – your problems, creative ideas, and personal insights are teaching these systems to replace human creativity and judgment. This might be as simple as defending sacred spaces – refusing to allow phones to interrupt dinner conversations, or speaking up when someone reaches for Google to settle every disagreement rather than letting uncertainty exist in conversations.

Community Networks: Nothing replaces genuine connection between people – the energy of live performances, spontaneous conversations at restaurants, the unmediated experience of being present with others. Building local relationships for reality-testing and mutual support that don’t depend on algorithmic intermediaries becomes essential when institutions can manufacture consensus through digital curation. This looks like cultivating friendships where you can discuss ideas without algorithms listening, supporting local businesses that preserve community-scale commerce, and participating in community activities that don’t require digital mediation.

Rather than competing with machines or depending entirely on AI-mediated systems, the goal is to use these tools strategically while developing the essentially personal qualities that can’t be algorithmically replicated: wisdom gained through direct experience, judgment that bears real consequences, authentic relationships built on shared risk and trust.

What Remains Scarce

In a world of cognitive abundance, what becomes precious? Not efficiency or raw processing power, but qualities that remain irreducibly human:

Consequence-bearing and intentionality. Machines can generate options, but people choose which path to take and live with the results. Consider a surgeon deciding whether to operate, knowing they’ll lose sleep if complications arise and stake their reputation on the outcome.

Authentic relationships. Many will pay premiums for real personal connection and accountability, even when machine alternatives are technically superior. The difference isn’t efficiency but genuine care – the neighbor who helps because you share community bonds rather than because an algorithm optimized for engagement suggested it.

Local judgment and curation rooted in real experience. Real-world problem-solving often requires reading between the lines of behavioral patterns and institutional dynamics. The teacher who notices a normally engaged student withdrawing and investigates the family situation. When content becomes infinite, discernment becomes precious – the friend who recommends books that change your perspective because they know your intellectual journey.

The Choice Ahead

Maybe every generation feels like their time is uniquely important – maybe that’s just part of our nature. This feels bigger than previous waves of innovation. We’re not just changing how we work or communicate – we’re risking the loss of capacities that make us ourselves in the first place. For the first time, we’re potentially changing what we are. When cognition itself becomes commodified, when thinking becomes outsourced, when even our thoughts become data to be harvested, we risk losing essential abilities that no previous generation has faced losing. Imagine a generation that can’t sit with uncertainty for thirty seconds without consulting an algorithm. That reaches for AI assistance before attempting independent problem-solving. That feels anxious when disconnected from these tools. This isn’t speculation – it’s already happening.

We’re facing a transformation that could either democratize our individual potential or create the most sophisticated control system in history. The same forces that could liberate us from drudgery could also hollow out self-reliance entirely.

This isn’t about having solutions – I’m searching for them like any person, especially a parent, who sees this transformation coming and wants to help their children navigate it consciously rather than unconsciously. Riding the wave means I’m open to learning from these tools while knowing I can’t fight the fundamental forces reshaping our world. But I can try to learn how to navigate them with intention rather than just being swept along.

If traditional economic participation becomes obsolete, the question becomes whether we develop new forms of community resilience and value creation, or whether we accept comfortable reliance on systems designed to manage rather than serve us. I don’t know which path our species will take, though I believe the decision is still ours to make.

For my children, the task won’t be learning how to use AI – they will. The challenge will be learning to make these tools work for us rather than becoming subservient to them – maintaining the capacity for original thought, authentic relationship, and moral courage that no algorithm can replicate. In an age of artificial intelligence, the most radical act may be becoming more authentically human.

The real danger isn’t that AI will become smarter than us. It’s that we’ll become dumber because of it.

The wave is here. My task as a father isn’t to shield my children from it, but to teach them to surf without losing themselves.

California’s legislature has passed a bill that bans federal law enforcement officers from wearing masks while on duty, with criminal penalties for noncompliance. 

The bill, SB-627, bans any law enforcement officer or agent from wearing a “facial covering that conceals or obscures their facial identity in the performance of their duties,” with exceptions for motorcycle helmets and SWAT officers, along with N-95 masks for COVID-19. 

Assuming it’s signed by Gov. Gavin Newsom (D), violators could face either a fine or charged with a misdemeanor.

The bill also strips law enforcement officers from qualified immunity for officer and agents who commit “assault, battery, false imprisonment, false arrest, abuse of process, or malicious prosecution” while wearing a mask, and could face a fine up to $10,000.

The bill applies to federal, state, and local law enforcement personnel throughout the state – so criminals seeking revenge will have a wide swath of cops to target. 

“The ICE masked secret police are raining terror on communities across California, and it has to stop. Law enforcement should never be easily confused with the guy in the ski mask robbing a liquor store, yet that’s what’s happening with ICE’s extreme masking behavior,” Sen. Scott Wiener (D-generate), the bill’s leading sponsor, wrote. 

“They should be proud to show their faces and provide identifying information in the course of duty.” 

The agencies have hit back – saying that masking prevents members of law enforcement and their families from being harassed.

“ICE law enforcement officers wear masks to prevent doxing, which can (and has) placed them and their families at risk. All ICE law enforcement officers carry badges and credentials and will identify themselves when required for public safety or legal necessity,” the agency wrote on its website in the FAQ area. 

ICE is responsible for heading up the apprehension, prosecution and removal of illegal immigrants from the United States. 

That said, the bill may be unconstitutional – after the Supreme Court held in a 2012 case (Arizona v. United States) that states cannot regulate federal immigration law enforcement. Yet, the word “immigration” is not mentioned in the text of the bill, which applies to all law enforcement activity. 

The bill was approved by a 2/3 majority in the California Senate and a simple majority in the lower House. 

*  *  *

Reminder: Order by Sunday night for Wednesday delivery

Authored by Naveen Athrappully via The Epoch Times (emphasis ours),

The biggest cohort involved in gang activity in the United States is youths 13 to 16 years old, the FBI revealed as part of the agency’s Gang Activity, 2021–2024 special report published on Sept. 8.

There were 79,507 offenders engaged in gang activities during the four years, and of these, 19,163 were aged 13 to 16—the highest among all age groups.

This was followed by 17- to 19-year-olds with 13,563 offenders, and those 20 to 24 with 11,452 offenders.

“Over one-third (33.8 percent) of offenders were juveniles under the age of 18, and more than half (58.2 percent) were under the age of 25,” the report said.

Besides being top offenders, the 13- to 16-year age group also accounted for the largest number of victims of gang activity. More than half of the victims were under the age of 30.

“Of known victim-offender relationships for incidents involving gang activity, 67.1 percent of victims knew the offenders in some manner. Conversely, 30.1 percent of relationships described the offenders as strangers.”

According to the Office of Juvenile Justice and Delinquency Prevention, the juvenile justice system in the United States aims to rehabilitate youth found guilty of crimes rather than punish them.

“In many cases, juveniles face much lower maximum possible sentences compared to adults convicted of the same offense,” the Department of Justice’s (DOJ) justice manual states.

“Juveniles under the age of 18 will not be detained past their 21st birthday, and individuals aged 18 to 21 who are being prosecuted as juveniles will face a maximum of five years.”

Charges against juveniles are not pursued as criminal prosecutions but as delinquency proceedings, it said. Juveniles also have robust privacy protections, including sealed records, non-jury trials, and closed rooms.

When a legal system implements softer punishments for children, it’s an incentive for gangs to recruit kids, Daniel Brunner, a retired FBI special agent, said in a post on LinkedIn.

“Gangs seek petty criminals, and they promote teenage recruits to commit petty crimes—presumably because these young recruits are not only undisciplined and easily influenced but also largely immune to serious legal consequences,” he wrote.

“On some occasions, youth which have proven themselves as trust worthy, may be tasked to conduct more serious acts, such as look out for a homicide, sexual assault, and possibly even murder. The legal consequences are typically very weak for younger criminals, especially at the Federal level, allowing these gangs to get away with these crimes.”

‘Not Afraid of Law Enforcement’

Juvenile delinquency was one of the main reasons cited by President Donald Trump for his crackdown on crime in the nation’s capital.

“Crime in Washington, D.C., is totally out of control. Local ‘youths’ and gang members, some only 14, 15, and 16-years-old, are randomly attacking, mugging, maiming, and shooting innocent Citizens, at the same time knowing that they will be almost immediately released,” Trump said in an Aug. 6 post on Truth Social.

He shared a picture of 19-year-old DOGE staff member Edward Coristine, who was attacked last month allegedly by 10 juveniles during an attempted carjacking incident and left bloodied.

“They are not afraid of Law Enforcement because they know nothing ever happens to them, but it’s going to happen now! The Law in D.C. must be changed to prosecute these ‘minors’ as adults, and lock them up for a long time, starting at age 14,” Trump wrote.

Trump federalized the D.C. Metropolitan Police Department on Aug. 11, ordering 800 troops from the National Guard to assist with law enforcement. This past week, the District of Columbia sued the Trump administration, arguing that “the military should not be involved in domestic law enforcement.”

Meanwhile, crime committed by youngsters in school locations has risen over the past several years, according to the FBI’s Crime in Schools, 2020–2024 report.

In 2024, there were 329,424 criminal incidents, more than triple the 100,810 reported in 2020. The age group most frequently reported as offenders was 13 to 15, the FBI said.

Out of the 1.25 million known offenders over the five years, 478,279 were in this age group, followed by 297,873 who were 16 to 18, according to the report.

“Many of the victims were not hurt or suffered only a minor injury and were acquainted with the offender,” it said.

According to a 2017 post by the American Academy of Child and Adolescent Psychiatry (AACAP), some children and adolescents are motivated to join gangs to have a sense of connection in formative years.

Risks of children joining gangs increase when they grow up in areas with high gang activity, lower adult supervision, a lack of hope about the future due to limited education or finances, a lack of positive role models, and unstructured free time.

Parents may face gang retaliation when confronting a child suspected of being a gang member.

Moreover, parents may be held liable for their children’s past behavior, the AACAP said.

Every single day, we get a new story of another stealth bailout by China (since a bazooka stimulus remains out of the picture seeing how China pretty much used them all up by the time covid rolled out and pushed the country’s consolidateded debt to GDP to around 400%). Here’s another: according to Bloomberg, China is preparing to tackle the massive backlog of unpaid bills owed by local governments to the private sector, an amount of arrears some have estimated at over $1 trillion.

Of course, since there is no actual “loose cash” floating around in China, in another financial MC Escher painting, Beijing will need to take out more massive loans to repay bills that couldn’t be repaid because of too much debt. The government is considering asking state lenders and policy banks including China Development Bank to lend to local authorities so they can make the payments in arrears. 

The amount of money under discussion would plug at least 1 trillion yuan ($140 billion) of debt owed to private companies in the first phase of a longer-term initiative. Officials aim to complete the task by 2027, according to the people.

What this means is that Beijing’s massive subsidy engine is about to go into turbo overdrive, and the world is about to be flooded with below cost crappy EVs and enough solar panels to cover the Sahara.

President Xi warned in a February speech made public last month that the government’s delayed payments to companies risks undermining people’s trust in the authorities. Underscoring the importance Beijing is placing on the issue, China’s top leader said unpaid bills could “cripple” affected businesses in the embattled private sector and was hurting “society at large.”

Of course, while the proposed assistance would offer relief to private-sector contractors, it would shift more risk onto state banks that already face rising loan losses, and is why gold just continues to surge day after day. 

Local government-related entities in China are estimated to owe 10 trillion yuan, or about $1.4 trillion, to corporates and civil servants, equivalent to 7% of the country’s gross domestic product last year, according to economist David Li Daokui’s estimate. Hilariously, China’s GDP continues to grow at a fixed 5% every single year. Which means that the government is now directly funding all of the growth with even more debt! 

Caitong Securities said in a report last week that China may allocate about 200 billion yuan in special bonds this year to settle overdue payments to companies, based on projections for land-reserve and project-construction special bonds.

The nudging has already begun and in recent months, authorities have instructed the nation’s major banks to provide support for the initiative, including asking them to give short-term liquidity loans to regional governments to settle overdue bills tied to their affiliated entities. While such debts are typically not owed by the local governments, they are responsible for repayment because they are backing the entities in debt. The policy may need further backing from regulators, as bankers are concerned about potential risks and need some form of assurance they won’t be held responsible if the advances turn bad, one of the people said.

Bottom line: now we know why there has been such a surge in Chinese stocks in recent days; the simple answer: after the latest $1 trillion debt transfer from the private sector to the government, all risk assets will benefit while China’s consolidated debt is about to explode even higher, which also means that the recent spike in gold and crypto isn’t ending any time soon. 

*  *  *

Authored by Jack Phillips via The Epoch Times (emphasis ours),

COVID-19 is no longer a top 10 cause of death in the United States, according to a report released on Wednesday by the Centers for Disease Control and Prevention.

The overall death rate dropped to 722 per 100,000 in 2024 from 750.5 per 100,000 people in 2023, the CDC said.

“Suicide replaced COVID-19 as the 10th leading underlying cause of death,” the agency said in its report.

According to data released by the CDC, the COVID-19 death rate appeared to peak in early 2021. Other significant peaks in COVID-19 deaths were observed in mid-2021 and in early 2022, as well as in April 2020 and August 2020.

In the report released this week, the CDC said that heart disease, cancer, and unintentional injury were the leading causes of death. COVID-19 had been ranked as the third-leading cause of death in the United States in 2020, when the pandemic first emerged, federal data show.

After heart disease, cancer, and unintentional injury, the other causes of death listed in the agency’s report were stroke, chronic lower respiratory diseases, Alzheimer’s disease, diabetes, kidney disease, chronic liver disease and cirrhosis, and suicide.

“The death rate decreased from 2023 to 2024 for all demographic groups except infants,” the CDC also wrote in the report, adding that “death rates also decreased for all race and ethnicity groups.”

A report released in May by the CDC shows that the national infant mortality rate dropped to about 5.5 infant deaths per 1,000 live births in 2024—from about 5.6 per 1,000 live births, where it had been the previous two years. Federal health data show that Mississippi has the highest infant mortality rate in the country.

In late August, Mississippi’s health department said it declared a public health emergency because of rising infant mortality rates in the state. Data released by the state show that the mortality rate increased to 9.7 per 1,000 live births last year, it said in a statement at the time.

Meanwhile, the U.S. suicide rate has steadily risen, increasing by 37 percent between 2000 and 2018, according to the CDC’s data. That rate dropped slightly between 2018 and 2020 before it returned to a peak rate of around 14.2 suicides per 100,000 people in 2022, the last available data.

Both the CDC and doctors’ groups have, for years, said that heart disease is the leading cause of death nationwide. Earlier this year, the American Heart Association said that “many of the risks factors that contribute to it remain on the rise,” and added in a news release that roughly 2,500 people die of heart disease each day in the United States.

While cancer is the second leading cause of death in the United States, the World Health Organization says that it is the No. 1 killer worldwide. The most common cancers, it says, are breast, lung, colon, and prostate.

U.S. President Donald Trump has said that he is losing patience with Russian President Vladimir Putin and could issue new tariffs and sanctions to compel the Russian leader to enter cease-fire negotiations with Ukraine.

Trump said that his patience with Putin’s refusal to participate in peace talks with Ukraine was “running out and running out fast,” during an interview with Fox News’ “Fox and Friends” on Sep. 12.

Trump ist genau wie Putin – ein Blender….
Trump hat erneut erklärt, dass seine Geduld gegenüber Putin zur Neige geht. Er droht mit gewissen Sanktionen.
„Meine Geduld scheint schon fast erschöpft zu sein, und das schnell – aber es braucht ja zwei zum Tango tanzen… Als Putin es… pic.twitter.com/RjA9J8We7n

— Konstanze Hoffmann (@KonstanzeHoffm1) September 12, 2025

As Andrew Thornebrooke reports for The Epoch Times, the president added that “it does take two to tango,” saying that Putin’s recalcitrance on committing to peace talks was in part due to the Russian leader’s mutual animosity with Ukrainian President Volodymyr Zelenskyy.

“There’s tremendous hatred between him and Zelenskyy,” Trump said.

Trump has made ending the war in Ukraine and other international conflicts a key part of his presidential agenda, but has struggled at times to convince Putin and Zelenskyy to meaningfully negotiate on ending the conflict.

The comments follow a high-profile summit between Trump and Putin in Alaska in August, which aimed to bring Russia back to the negotiating table but ultimately did not result in the resumption of cease-fire talks.

“There’s no deal until there’s a deal,” Trump said at the time.

That meeting itself was the result of a threat by Trump to impose new sanctions on the Russian oil sector, including secondary tariffs on nations such as India and China that purchase oil from Russian entities.

Trump renewed those threats during Friday’s interview, saying the United States would have to “come down very, very strong” on Russia if Putin did not commit to peace talks with Ukraine.

When asked what coming down on Russia would look like, Trump said that it would involve “hitting [Russia] very hard with sanctions to banks and having to do with oil and tariffs also.”

Trump also reached out to U.S. allies in Europe earlier this week in the hopes of building international support for secondary tariffs of up to 100 percent on China and India.

The move demonstrates how much Trump and his administration have shifted in handling the war in Ukraine since first coming to office, moving from pausing all support of Ukraine early in the year to renewing weapon sales to Kyiv and threatening sanctions against Moscow.

The difficulty lies in getting either Kyiv or Moscow to relent on any of several key war aims, with Zelenskyy refusing to consider the giving up of any territory to Russia and Putin demanding that it be given territory it has failed to conquer.

For now, Moscow appears undeterred. This week alone, Russia launched its largest aerial assault against Ukraine and sent drones into NATO member Poland’s airspace.

NATO leadership has not yet verified whether the drones entered Polish airspace deliberately or as part of an operation in Ukraine that went wrong.

Trump said during Friday’s interview that Russian assets “shouldn’t be close to Poland.”

Authored by Sam Bourgi via CoinTelegraph.com,

Polymarket prepares US return with CFTC relief, new funding and a valuation that could soar to $10B as prediction markets gain momentum…

Blockchain-powered prediction market Polymarket is reportedly preparing a US launch that could value the company as high as $10 billion, highlighting the surge of investor interest in prediction markets and crypto ventures.

Citing sources familiar with the conversation, Business Insider reported Friday that Polymarket is exploring re-entering the US while seeking new funding that could more than triple its June valuation of $1 billion. One investor valued the company at up to $10 billion, the report said.

As Cointelegraph reported, Polymarket was raising a $200 million round in June led by Peter Thiel’s Founders Fund, an early backer of companies including OpenAI, Paxos and Palantir.

Polymarket, a decentralized platform that allows users to trade event outcomes without a centralized bookmaker, gained prominence during the 2024 US presidential election, where its markets correctly anticipated Donald Trump’s victory.

Polymarket activity skyrocketed during the US presidential election, based on monthly active traders. Source: Dune

The company was barred from serving US users in 2022 following a settlement with the Commodity Futures Trading Commission (CFTC). In July, however, it acquired Florida-based derivatives exchange QCX, which could pave the way for a regulated return to the US market.

In September, the CFTC issued a no-action letter to QCX, granting relief from certain federal reporting and recordkeeping requirements for event contracts. Polymarket CEO Shayne Coplan said the decision effectively gives the platform “the green light to go live in the USA.”

Source: Shayne Coplan

Blockchain prediction markets gain steam

The move comes as rival platform Kalshi is reportedly nearing a $5 billion funding round, according to The Information. That follows a Paradigm-led raise in June, when the company secured $185 million at a $2 billion valuation.

Kalshi’s recent momentum stems partly from a 2024 court ruling that allowed it to offer political-event contracts — a ruling the CFTC appealed but voluntarily dropped in May of this year. The favorable rulings left intact Kalshi’s right to list political-event contracts under existing regulation.

Source: Factcheck1ntern

Kalshi ranks among the most active prediction markets alongside Polymarket, measured by trading volumes and monthly active users. Still, like Polymarket, its user base has declined since the election.

Market watchers say momentum is shifting, fueled by the start of the National Football League season. Market analyst Tarek Mansour noted this week that Kalshi processed $441 million in volume since kickoff, writing: “NFL Week 1 is equal to a US election.”