a new reality tv show called So you think you can write Doctor Who
twelve episodes, twelve contestants - a mix of annoying middle aged sci fi authors, fan fic authors and random people off the street
a variety of against the clock writing tasks, big finish scripts, ability to interact with actors without shouting at them and challenges where you have no budget or doctor for an episode
judged by solely by christopher eccleston
this is how you find the new doctor who showrunner
ok i've gotten one too many 'this is why i don't read sci-fi' comments so here's a rec list for the people convinced all science fiction is bad and misogynistic (with something for everyone, hopefully!):
(also, btw, the book links are to the Storygraph, which includes content warnings for each one!)
smth funny and lighthearted about a security robot who'd rather watch TV then do its job? all systems red by martha wells (first novella in the The Murderbot Diaries series, 6 books, ongoing)
a complex, intricate political space opera following a warship AI who's lost (almost) everything? ancillary justice by ann leckie (first in the Imperial Radch trilogy) (fun fact! bc of space linguistics reasons, all characters in this series are referred to with she/her pronouns, making gender a non-factor - it's really cool!)
a dark story about travelling between parallel universes and a woman who is dead in almost every single one? the space between worlds by micaiah johnson (standalone) (SO good, i don't get to recommend it often enough!!!)
a story about grief and letting go, and a unique take on alien invasion? the seep by chana porter (standalone novella)
hey, how abt some dystopian YA, for old times sake? specifically, one with sapphics and sick mechas? try gearbreakers by zoe hana mikuta (first in duology)
or, if you'd prefer something a bit less angsty, YA about a ragtag group of teens and a space heist? the disasters by m. k. england (standalone)
alternate history steampunk that blurs the line btwn science fiction and fantasy? the black god's drums by p. djeli clark (standalone, novella)
a dark gone girl-esque thriller about clones? the echo wife by sarah gailey (standalone)
poetic sapphic romance and time travel? this is how you lose the time war by max gladstone and amal el-mohtar (standalone)
a hopeful utopian future and a human-robot friendship? a psalm for the wild-built by becky chambers (novella, first out of two) (this author's got a whole bunch of hopepunk sci-fi novels in general, if that's smth you're looking for!)
africanfuturism, coming-of-age, and cool jellyfish aliens? binti by nnedi okorafor (novella, first in trilogy)
spicy lesbian cyborgs? and shall machines surrender my benjanun sriduangkaew (novella, first in the Machine Mandate series, 6 books)
cosmic horror with an autistic scientist, cyborg angels and AI gods? the outside by ada hoffmann (first in trilogy, 2 books are out)
also, if you're a fan of Janelle Monáe, may i draw your attention to the fact that they've recently come out with a Dirty Computer short story collection, each story co-written with a diff writer?
this list is long enough, but have some more authors (who are not cis men) also worth checking out: rivers solomon, yoon ha lee, charlie jane anders, aliette de bodard, xiran jay zhao, mary robinette kowal, corinne duyvis
and finally, not all older/classic scifi is written by crusty old white guys who hate women!!! some iconic authors i'd particularly recommend looking into are ursula k. le guin, octavia e. butler, samuel r. delany and vonda n. mcintyre 🥰
I love that four different people on my feed scheduled this joyous person to reblog by 8am on June 1. I look forward to seeing this a dozen more times today.
An extremely cool Thing I do is take adderall, and tell myself I’m just going to scroll or read for a little while “until the meds kick in and I can be productive.” Only then I’m scrolling or reading WHEN the meds kick in, so I become VERY focused on scrolling or reading and it becomes significantly harder to detach from that activity and do something productive. And then I do it again the next time I take my adderall. Like an idiot.
Text of tweet under the cut because it is loooong.
But... Stochastic Parrots.
Timnit Gebru was fired from Google in December 2020 for refusing to retract a research paper, and every single warning that paper made about large language models has now happened at a scale the industry spent 4 years trying to make people forget about.
Her name is Timnit Gebru.
She co-led the Ethical AI team at Google. She co-wrote a paper called "On the Dangers of Stochastic Parrots" with Emily Bender at the University of Washington and two other researchers. The paper was 14 pages long. It was submitted to a top AI ethics conference. And it was the reason Google decided that one of the most senior Black women in AI research could no longer work there.
The story Google told publicly was that she resigned. The story she told, confirmed by 2,695 of her colleagues in an open letter, was that she was fired by email while on vacation because she refused to either retract the paper or remove her name from it.
The paper had not even been published yet.
Here is what she actually wrote, and why every prediction inside it has now come true.
The first warning was about scale itself. Bender and Gebru argued that training ever-larger models on ever-larger scrapes of the internet would produce systems that appeared fluent but had no actual understanding of language. They called these systems stochastic parrots because they would repeat patterns from training data with statistical confidence and zero comprehension. The paper predicted that this apparent intelligence would fool both users and developers into trusting outputs that were structurally incapable of being reliable.
This was 2020. GPT-3 had just come out. The paper predicted the hallucination problem before anyone had a word for it.
The second warning was about bias amplification. The paper documented in detail that internet-scale training data contains systematic overrepresentation of dominant viewpoints and underrepresentation of marginalized ones. The models would not just absorb this bias. They would amplify it, because the optimization process rewards confident outputs, and confidence in language patterns tracks frequency in the training set.
The prediction was that hiring tools built on these models would discriminate against women. That healthcare triage tools would underperform on Black patients. That loan approval systems would entrench inequality while presenting their decisions as neutral algorithmic judgment.
Every one of those things has now been documented in deployment.
Amazon's hiring algorithm penalized resumes that contained the word "women" in any context. Healthcare risk scoring algorithms used by major US hospitals were found to systematically underestimate the medical needs of Black patients. Apple Card's credit algorithm gave wives credit lines 10x lower than their husbands for the same financial profile.
The third warning was about environmental cost. The paper calculated that training a single large language model produced emissions equivalent to the lifetime output of 5 cars. The prediction was that the race to scale would create an environmental footprint that would eventually rival entire industries.
In 2024, Google's emissions were up 48% from 2019, and the company explicitly blamed AI infrastructure. Microsoft's were up 29%, same reason. Both companies have now quietly abandoned the climate commitments they were publicly celebrating the year Gebru was fired.
The fourth warning was about documentation. The paper argued that the training datasets being assembled were too large for anyone to actually audit. Nobody at Google, OpenAI, Meta, or any other lab could tell you with confidence what was in the data their models were trained on. This was not a temporary problem to be solved later. It was a permanent feature of the approach.
In 2023, researchers discovered that the LAION-5B dataset, used to train Stable Diffusion and other major image models, contained thousands of images of child sexual abuse material. The companies that had trained on the dataset had no way of knowing. The paper predicted that category of failure 3 years before it was found.
The fifth warning was the one Google cared about most.
Bender and Gebru argued that the deployment of these systems would centralize linguistic and cultural power in the hands of the small number of companies that could afford to train them. The internet would become a place where the dominant voice was a statistical average of dominant voices, presented as a neutral assistant. Languages underrepresented in the training data would degrade over time as more web content was generated by these systems and fed back into the next training run.
This is now happening in real time. A 2024 study found that 57% of new web content in English is AI-generated or AI-assisted. Researchers studying low-resource languages have documented active degradation in translation quality, because the synthetic content fed back into training is itself worse in those languages.
The paper Google fired her for predicted the model collapse problem before model collapse had a name.
The mechanism behind why this all happened is the part of her work that nobody quotes.
Gebru's argument was not that AI is dangerous in some abstract sci-fi sense. Her argument was that AI is dangerous in a very specific structural sense. The technology was being built by a small group of researchers who shared similar backgrounds, worked at similar companies, and were rewarded for shipping products faster than competitors. The incentive structure made it impossible for safety, ethics, and bias concerns to slow anything down. Anyone inside the system who raised those concerns was either ignored, sidelined, or removed.
She was making that argument from inside Google.
Then Google proved her right by removing her.
The team Google had built to make sure their AI was safe was dismantled in 90 days because they did the job they had been hired to do. Margaret Mitchell, the other co-lead of the Ethical AI team, was fired two months after Gebru for searching through her own emails for evidence of how Gebru had been treated.
Gebru did not stop. She founded DAIR, the Distributed AI Research Institute, in 2021. The mission is to do AI research outside the control of the companies that have a financial interest in not hearing the answers.
Every prediction in the Stochastic Parrots paper has now been validated by deployment. Hallucinations are an industry-wide problem the largest labs cannot solve. Bias amplification has been documented in hiring, healthcare, lending, and criminal justice. Environmental costs are larger than entire small countries. Training data audits remain impossible. Model collapse is an active research crisis at every major lab.
The question worth sitting with is the one almost no one in the industry will say out loud.
Every researcher with the technical credibility to call out these problems watched what happened to her in December 2020 and made a calculation about their own career. The number of people willing to speak publicly about safety and ethics issues inside the major AI labs collapsed after that firing and has not recovered.
The researcher Google fired for warning about exactly what is now happening was right.
The company that fired her is now the second-largest deployer of the technology she warned about.
And the people inside that company who agree with her are not allowed to say so.
She got the idea for the study while walking with her advisor at Stanford to discuss her thesis topic, and the paper she eventually published in the Journal of Experimental Psychology in 2014 is sharp enough that it should have ended the seated meeting on the day it came out.
She ran 4 experiments on 176 people. Same person tested twice. Once sitting, once walking. The creativity tasks were the standard ones psychologists have used for decades to measure how good a brain is at generating novel useful ideas.
81% of participants in the first experiment produced more creative ideas while walking than while sitting. In the second experiment, 88%. In the third, 100%. Every single person walked into a more creative version of themselves. On average, people generated 60% more novel useful ideas the moment their legs started moving.
The skeptical question is the obvious one. Maybe it was the fresh air. Maybe it was the scenery passing by. Maybe it was the change of environment doing the work, not the walking itself.
Oppezzo killed every one of those explanations with one experimental decision. She put people on a treadmill facing a blank wall. No scenery. No fresh air. No environmental change. Just legs moving in place while staring at white drywall. The 60% boost held.
Then she ran the experiment that closed the case completely. She took participants outside in two conditions. Half of them walked through a Stanford courtyard. The other half were pushed through the exact same courtyard in a wheelchair. Same outdoor stimulation. Same scenery passing at the same speed. The only difference was whether the legs were moving.
The walkers produced dramatically more novel high-quality ideas than the wheelchair group. The outdoors did almost nothing on its own. The walking did everything.
She also tested the opposite kind of thinking. Convergent thinking. The kind where there is one right answer and you have to narrow down to it. Word puzzles where 3 words share a hidden fourth word that connects them. The seated participants did slightly better on these. Walkers got slightly worse.
Walking is not a general intelligence enhancer. It does one specific thing. It opens up the divergent search inside your brain. The part that generates options. The part that produces unexpected connections. The part that takes a problem and finds five ways into it instead of one.
When you need to converge on the single right answer, sit down. When you need to find the answer in the first place, get up.
The mechanism is now well understood. Walking selectively activates what neuroscientists call the default mode network, the system inside your brain that runs when you are not consciously focused on anything. The DMN is where mind-wandering happens. Where memories cross-reference each other. Where ideas that have been sitting in separate folders inside your head finally bump into each other.
When you sit at a desk and force yourself to concentrate, you suppress the DMN. When you walk at a natural pace, the executive part of your brain gets just busy enough handling the walking that the DMN comes online and starts doing the work that focus was blocking.
The most useful finding in the entire paper is the one almost nobody quotes. The boost did not turn off the moment people stopped walking. Participants who walked first and then sat back down stayed elevated. Their next round of seated creativity work was still significantly better than people who had been sitting the whole time. The rest lingered for at least several minutes after the legs stopped moving.
You do not need to do creative work while walking. You need to walk before the creative work. The brain holds the state.
terfs have a lot to answer for but 1 very small facet of that im personally annoyed with right now is that they made it so pussy imagery is often sort of suspect. what the hell. the honorable pussy... he is not responsible for this madness
The Odyssey but retold as a low-stakes modern adventure of one guy out with his girlfriend leaving the bar with his buddies to do just one (1) simple thing real quick, it'll take like 15 minutes tops, he'll be right back, but then some bullshit happens and the trip keeps getting more complicated as more bullshit keeps happening while he just tries to get back to the bar because he promised his girlfriend that he'd get back and he knows that she's still there because she told him she'd wait there.
And by the time he finally gets back it's almost 3 am and the bar is about to close while she's sitting there stone cold sober, surrounded by 5 drunk guys unsuccessfully trying to convince her to give up on waiting for him and go home with one of them instead. And the guy shows up to proceed to beat the shit out of them before explaining himself to her like hey sorry bullshit kept happening, my phone fell into a storm drain and my wallet got stolen when I was trying to find someone who'd borrow me a phone so I could call and
His girlfriend had been fending off the 5 drunk guys for most of the evening by explaining that even if she was going to ditch her boyfriend, she can't possibly leave without finishing her beer, which she is keeping perpetually full via careful sleight of hand where she's just pouring it back and forth into and out of the pitcher.
However the drunk guys are also drinking, and eventually she can't afford to buy another pitcher for the table so she can't keep up the ever-full beer glass trick. At this point she has to resort to setting up the pool trick shot that she's never seen anyone but her boyfriend pull off, and says she'll leave with whoever manages the shot first.
That buys her another hour or so and then, finally, her boyfriend makes it back. He looks like shit, hair down and just a mess, he's wearing an entirely different jacket that he got from an alley, and barely recognizable—especially to 5 guys who've been drunk for hours now. He lurks for a minute, finds out what's going on, and proceeds to pull off the trick shot first try. Throws the jacket off, fixes his hair with a hair tie his girlfriend lends him, finally looks like himself again, and THEN beats the shit out of them with the pool cue.
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