【推荐1】Germany’s top court (法院) has ruled that parts of the country’s 2019 climate action law must be changed because they don’t do a good job of protecting young people. Nine young people aged 15 to 24 took the government to court over the law. They said that the government’s failure to plan carefully was putting their future lives in danger.

The judges (法官) of Germany’s highest court said climate change will influence young people far more than adults. That’s because climate change will become more serious over time. As young people become adults, they’ll be left to deal with any problems that today’s adults don’t deal with.

In 2019, Germany passed a new law, promising that the country would be producing no more CO2 than the forest can take in by 2050. The law made a plan of action until 2030. But the law didn’t have any plans for climate actions that would be taken between 2031 and 2050.

The court has asked the German government to fix the law by the end of 2022. The climate law will now need to have a plan for the actions that will be taken after 2030.

The German government has said that it will quickly begin working to make the needed changes. One important part of high court decisions like this is that they act as guides or examples for future decisions. This means that in the future, Germany’s lawmakers will be more likely to think about the climate future of young people as they create their laws.

【推荐1】Artificial intelligence is set to advise a defendant in court for the first time ever. The AI will run on a smartphone and listen to all speech in a courtroom before instructing the defendant on what to say via an earpiece.

The defendant is charged with speeding and will say only what DoNotPay’s tool tells them to via an earbud. The case is being considered as a test by the firm, which has agreed to pay if any fines are imposed, says its founder, Joshua Browder.

Browder says it took a long time to train the AI on the vast amounts of case law needed to make it useful. The AI had to be trained to stick to factual statements, rather than saying whatever it could to win a case regardless of the truth.

“We’re trying to minimize our legal liability,” says Browder. “And it’s not good if it actually twists facts and is too controlling.” He says his goal is that the software will eventually replace some lawyers. “It’s all about language, and that’s what lawyers charge hundreds or thousands of dollars an hour to do,” he says. “A lot of lawyers are just charging too much money to copy and paste documents.”

But when New Scientist asked the UK Ministry of Justice if such a trial would be legal, a spokesperson says, “We wouldn’t be able to say whether it was 100 percent legal or not until an application was made to carry out the system and our lawyers made a decision.”

Brown says that AI will probably play a useful role in the legal system in the future but that it would be likely to assist lawyers rather than replace them.

“When your lawyer tells you “OK, let’s do A”, we trust them that they have the expertise and the knowledge to advise us. But (with AI), it’s very hard to trust predictions. We’re quite far off being able to do these things reliably and get rid of lawyers. We have to be very careful of making such claims.”

【推荐2】While some observers worry about potential dangers in AI, others are focusing on the potential rewards and believe that AI can advance science and lead to a golden age of discovery.

Such claims are worth examining. The mechanism by which AI will supposedly solve the world’s problems has a strong historical basis because there have been periods when new approaches and new tools did indeed help bring about world-changing scientific innovation. In the 1700s microscopes and telescopes opened up new vision of discovery and scientific journals helped share and publicise researchers’ findings. In the late 1900s, research laboratories that brought together ideas, people and materials on an industrial scale, gave rise to further innovations, such as the transistor. From the 1950s, computers made the design of weapons and aircraft and weather forecasting a reality. Today AI is being employed in new ways such as identifying new antibiotics (抗生素) and spotting regional accents in wolves.

All this is to be welcomed. But the journal and the laboratory went further: they altered scientific practice and unlocked more powerful means of making discoveries, by allowing people and ideas to mix in new ways on a larger scale. AI, too, has the potential to set off such a transformation.

Two areas in particular look promising. The first is “literature-based discovery” (LBD), which involves analysing existing scientific literature, using ChatGPT-style language analysis, to look for new hypotheses (猜想), connections or ideas that humans may have missed. LBD is showing promise in identifying new experiments to try. This could stimulate interdisciplinary work and foster innovation.

The second area is “robot scientists”, also known as “self-driving labs”. These are robotic systems that use AI to form new hypotheses, based on existing data and literature, and then test those hypotheses by performing countless experiments. Unlike human scientists, robots are less attached to previous results, less driven by bias—and, crucially, easy to replicate. They could scale up experimental research, develop unexpected theories and explore avenues that researchers might not have considered.