As a six-year-old growing up in Barcelona, Spain, during the 1940s, Maria would visit a neighbor's apartment in her building when she wanted to see her father. From there, she could try and try to catch a glimpse of him in the prison below, where he was locked up for opposing the dictatorship of Francisco Franco. There is no photo of Maria on that balcony. But she can now hold something like it: a fake photo--or memory-based reconstruction, as the Barcelona-based design studio Domestic Data Streamers puts it--of the scene that a real photo might have captured.The studio uses generative image models, such as OpenAI's DALL-E, to bring people's memories to life. The fake snapshots are blurred and distorted, but they can still rewind a lifetime in an instant.

So I was inspired after talking to Angela Huyue Zhang, a law professor in Hong Kong who's coming to teach at the University of Southern California this fall, about her new book on interpreting the logic and patterns behind China's tech regulations. We talked about how the Chinese government almost always swings back and forth between regulating tech too much and not enough, how local governments have gone to great lengths to protect local tech companies, and why AI companies in China are receiving more government goodwill than other sectors today. To learn more about Zhang's fascinating interpretation of the tech regulations in China, read my story published today. In this newsletter, I want to show you a particularly interesting part of the conversation we had, where Zhang expanded on how market overreactions to Chinese tech policies have become an integral part of the tech regulator's toolbox today. The capital markets, perpetually betting on whether tech companies are going to fare better or worse, are always looking for policy signals on whether China is going to start a new crackdown on certain technologies. As a result, they often overreact to every move by the Chinese government.

Draft legislation, leaked ahead of its official release later this month, suggests the EU is attempting to find a "third way" on AI regulation, between the free market US and authoritarian China. In a way, the news is no surprise, as the president of the European Commission, Ursula von der Leyen, promised to urgently bring in AI legislation when she was elected in 2019. Daniel Leufer at Access Now, one of the groups that has previously advised the EU on AI, says Europe has long had a strategy to take a third way between the US and China on tech regulation, and says the draft legislation has promise. It remains to be seen whether the UK will follow the EU in regulating AI now that it has left the bloc. The UK Department for Business, Energy & Industrial Strategy told New Scientist that the government has formed an independent panel called the Regulatory Horizons Council to advise on what regulation is needed to react to new technology such as AI.

I was first introduced to artificial intelligence (AI) through movies and media. Movies like Star Wars made me appreciate the convenience of AI; watching C-3PO and R2D2 made me wish for a world in which a sentient robot (or rather, a protocol droid) tended to my every need. Malignant AI, as seen in 2001: Space Odyssey and The Terminator were alarming but failed to completely deteriorate my view of future AI. Media portrayals of AI showed me that I was more enticed by the convenience of AI than deterred by its potential evil. Years later, as I've begun to study computer science and have further considered the ethical implications of technological innovation, I've had a change of heart.

In a year that has seen decades' worth of global shocks, bad news, and scandals squeezed into 12 excruciatingly long months, the summer already feels like a distant memory. In August 2020, the world was in the throes of a major social and racial justice movement, and I argued hopefully in VentureBeat that the term "ethical AI" was finally starting to mean something. It was not the observation of a disinterested observer but an optimistic vision for coalescing the ethical AI community around notions of power, justice, and structural change. Yet in the intervening months it has proven to be, at best, an overly simplistic vision, and at worst, a naive one. The piece critiqued "second wave" ethical AI as being preoccupied with technical fixes to problems of bias and fairness in machine learning.