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citizens of What Not are ranked based on their intelligence from A to C3 and can’t marry or procreate with someone of the same rank to ensure that intelligence is evenly distributed

Brave New World is more futuristic and preoccupied with technology than What Not. In Huxley’s world, procreation and education have become completely mechanized and emotions are strictly regulated pharmaceutically. Macaulay’s Britain is just the beginning of this process, and its characters are not yet completely indoctrinated into the new ways of the state—they resist it intellectually and question its endeavors, like the newly-passed Mental Progress Act. She writes:He did not like all this interfering, socialist what-not, which was both upsetting the domestic arrangements of his tenants and trying to put into their heads more learning than was suitable for them to have. For his part he thought every man had a right to be a fool if he chose, yes, and to marry another fool, and to bring up a family of fools too.

Where Huxley pairs dumb but pretty and “pneumatic” ladies with intelligent gentlemen, Macaulay’s work is decidedly less sexist.

We was published in French, Dutch, and German. An English version was printed and sold only in the US. When Orwell wrote about We in 1946, it was only because he’d managed to borrow a hard-to-find French translation.

While Orwell never indicated that he read Macaulay, he shares her subversive and subtle linguistic skills and satirical sense. His protagonist, Winston—like Kitty—works for the government in its Ministry of Truth, or Minitrue in Newspeak, where he rewrites historical records to support whatever Big Brother currently says is good for the regime. Macaulay would no doubt have approved of Orwell’s wit. And his state ministries bear a striking similarity to those she wrote about in What Not.

Orwell was familiar with Huxley’s novel and gave it much thought before writing his own blockbuster. Indeed, in 1946, before the release of 1984, he wrote a review of Zamyatin’s We (pdf), comparing the Russian novel with Huxley’s book. Orwell declared Huxley’s text derivative, writing in his review of We in The Tribune:The first thing anyone would notice about We is the fact—never pointed out, I believe—that Aldous Huxley’s Brave New World must be partly derived from it. Both books deal with the rebellion of the primitive human spirit against a rationalised, mechanized, painless world, and both stories are supposed to take place about six hundred years hence. The atmosphere of the two books is similar, and it is roughly speaking the same kind of society that is being described, though Huxley’s book shows less political awareness and is more influenced by recent biological and psychological theories.

In We, the story is told by D-503, a male engineer, while in Brave New World we follow Bernard Marx, a protagonist with a proper name. Both characters live in artificial worlds, separated from nature, and they recoil when they first encounter people who exist outside of the state’s constructed and controlled cities.

Although We is barely known compared to Orwell and Huxley’s later works, I’d argue that it’s among the best literary science fictions of all time, and it’s highly relevant, as it was when first written. Noam Chomsky calls it “more perceptive” than both 1984 and Brave New World. Zamyatin’s futuristic society was so on point, he was exiled from the Soviet Union because it was such an accurate description of life in a totalitarian regime, though he wrote it before Stalin took power.

Macaulay’s work is more subtle and funny than Huxley’s. Despite being a century old, What Not is remarkably relevant and readable, a satire that only highlights how little has changed in the years since its publication and how dangerous and absurd state policies can be. In this sense then, What Not reads more like George Orwell’s 1949 novel 1984 

Orwell was critical of Zamyatin’s technique. “[We] has a rather weak and episodic plot which is too complex to summarize,” he wrote. Still, he admired the work as a whole. “[Its] intuitive grasp of the irrational side of totalitarianism—human sacrifice, cruelty as an end in itself, the worship of a Leader who is credited with divine attributes—[…] makes Zamyatin’s book superior to Huxley’s,”

Like our own tech magnates and nations, the United State of We is obsessed with going to space.

Perhaps in 2019 Macaulay’s What Not, a clever and subversive book, will finally get its overdue recognition.

Because the term “AI” is ambiguous, it makes having clear discussions more difficult. In one sense, it is the name of a subfield of computer science. In another, it can refer to the computing techniques developed in that subfield, most of which are now focused on pattern matching based on large data sets and the generation of new media based on those patterns. Finally, in marketing copy and start-up pitch decks, the term “AI” serves as magic fairy dust that will supercharge your business.

output can seem so plausible that without a clear indication of its synthetic origins, it becomes a noxious and insidious pollutant of our information ecosystem

Not only do we risk mistaking synthetic text for reliable information, but also that noninformation reflects and amplifies the biases encoded in its training data—in this case, every kind of bigotry exhibited on the Internet. Moreover the synthetic text sounds authoritative despite its lack of citations back to real sources. The longer this synthetic text spill continues, the worse off we are, because it gets harder to find trustworthy sources and harder to trust them when we do.

the people selling this technology propose that text synthesis machines could fix various holes in our social fabric: the lack of teachers in K–12 education, the inaccessibility of health care for low-income people and the dearth of legal aid for people who cannot afford lawyers, just to name a few

the systems rely on enormous amounts of training data that are stolen without compensation from the artists and authors who created it in the first place

the task of labeling data to create “guardrails” that are intended to prevent an AI system’s most toxic output from seeping out is repetitive and often traumatic labor carried out by gig workers and contractors, people locked in a global race to the bottom for pay and working conditions.

employers are looking to cut costs by leveraging automation, laying off people from previously stable jobs and then hiring them back as lower-paid workers to correct the output of the automated systems. This can be seen most clearly in the current actors’ and writers’ strikes in Hollywood, where grotesquely overpaid moguls scheme to buy eternal rights to use AI replacements of actors for the price of a day’s work and, on a gig basis, hire writers piecemeal to revise the incoherent scripts churned out by AI.

too many AI publications come from corporate labs or from academic groups that receive disproportionate industry funding. Much is junk science—it is nonreproducible, hides behind trade secrecy, is full of hype and uses evaluation methods that lack construct validity

We urge policymakers to instead draw on solid scholarship that investigates the harms and risks of AI—and the harms caused by delegating authority to automated systems, which include the unregulated accumulation of data and computing power, climate costs of model training and inference, damage to the welfare state and the disempowerment of the poor, as well as the intensification of policing against Black and Indigenous families. Solid research in this domain—including social science and theory building—and solid policy based on that research will keep the focus on the people hurt by this technology.