Week Notes November 15, 2026
Living room and libraries
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I'm an educator, coder, and photographer in Massachusetts.
NY Times: The High Cost of Silent Classrooms
by Shael Polakow-Suransky
A.I. also risks becoming a new instrument for educational segregation. In wealthy districts, parents will demand schools centered on human interaction: seminar tables, heated debates, messy projects. Students in poorer schools, often Black and Latino children, will be handed laptops and headphones, “learning” from machines that can correct their algebra but will never care about their curiosity.
We Updated Our Privacy Policy. Here's What Changed and Why.
by Lena Gunn
This should be the bar for privacy policy updates. It’s written in a way that’s thorough but still easy to understand without a law degree. And most importantly, privacy and consent remain the default. Users have the opportunity to review the rationale behind collecting additional data, but nothing will change unless they opt-in.
The political effects of X’s feed algorithm
by Ben Werdmuller
This should be a wakeup call for politically-engaged funders and anyone who cares about civil society. It’s not that we need to have less conservative algorithms; it’s that whoever controls the algorithms has a disproportionate say over the electorate’s view of the world.
A Startup is Selling Data Hacked from Peoples’ Computers to Debt Collectors
by Joseph Cox
A private intelligence company run by a young founder is now taking that hacked data from what it says are more than 50 million computers, and reselling it for profit to a wide range of different industries, including debt collectors; couples in divorce proceedings; and even companies looking to poach their rivals’ customers.
Budget Bill Signals New Era in Federal Surveillance
by Dean Jackson
“The golden rule of privacy… is that information collected for one purpose can’t be repurposed without permission. We don’t have that rule.” Instead, Nojeim explained, the US has a “sectoral approach” which is weakest in areas related to law enforcement access. “We’re at a point in the march forward of technology,” he said, where ”more human thought than ever in the history of mankind is becoming available to the government without the need for a warrant or court permission. Where that goes depends entirely on the goodwill of professionals who enforce vague laws that have been designed intentionally to give them flexibility in emergencies. Unfortunately, those laws are being exploited by the Administration, which is making false claims about emergency [and] national security risk.”
The New Surveillance State: Why Data Privacy Is Now Essential to Democracy
by Laura MacCleery
When the government can track where you go, whom you associate with, and what you spend your money on, it violates the Fourth Amendment. It also chills First Amendment freedom of expression, undermines your freedom to travel, and destroys what Justice Louis Brandeis famously called “the right to be left alone” — the fundamental privacy right that underlies American liberty.
A Starter Guide to Protecting Your Data From Hackers and Corporations
by Matt Burgess, Sophie Johal, Michaela Neville
I think in a lot of cases when people claim they have nothing to hide, they often jump to thinking about illegal or malicious things. When in fact, privacy, for me, isn’t about “hiding” things at all. You should be able to have the space—both in the physical and digital world—to not be surveilled or have your actions tracked. People should be able to act without intrusion from others—that doesn’t mean you’re hiding anything, but you just don’t want to share everything you do with everyone (or anyone). And really that’s why privacy is considered a fundamental human right.
23andMe (andMyGeneticData)
To prevent the sale of your genetic information to whoever acquires 23andMe, consider deleting your data from the platform.
Reports of LLMs mastering math have been greatly exaggerated
by Ernest Davis
The refusal of these kinds of AI to admit ignorance or incapacity and their obstinate preference for generating incorrect but plausible-looking answers instead are one of their most dangerous characteristics. It is extremely easy for a user to pose a question to an LLM, get what looks like a valid answer, and then trust to it, without doing the careful inspection necessary to check that it is actually right.
This is an area where human experts and LLMs diverge. Both are capable of making mistakes, but humans who have expertise in a certain area are generally more aware of the limits and gaps in their knowledge.