For eight-year-old Toby. who is deaf, watching films or TV can sometimes be a bit pointless, because so many of them don't have sign language versions. "We have subtitles but it goes too fast," his dad Jarod Mills said. But now, Toby has some help thanks to an app developed by a 17-year-old student, Mariella Satow, who created a signing app called SignUp.

She got the idea when she was teaching herself American Sign Language(ASL)— one of hundreds of sign languages used across the world. Mariella wanted to watch TV shows to help her learn, and she was disappointed to discover how few had signed versions. It's taken a year for Mariella to develop the technology, with lots of help from ASL teachers and the deaf community.

The app is available in the US as a browser extension — with an interpreter appearing in a box once the film starts playing. It only works on Disney Plus films at the moment, because that's where Mariella thought she could help the most children. Jarod, who works at a school for deaf children, says it was "exciting" watching Toby use Mariella's invention. He says, "Kids are getting information like any hearing child does."

Deaf people in the UK face many of the same barriers when it comes to cinema and TV. “A hearing person can go to the cinema any time whereas deaf people have to make sure there's a suitable viewing a time we're free,” says 27-year-old Stacey Worboys from Cardiff. She has learned British Sign Language (BSL), and is comfortable using subtitles when watching TV shows and films. But she feels having an interpreter would make things "more inclusive", especially for someone who might struggle with subtitles. Stacey and Toby aren't the only people to be welcoming Mariella's app. It's now got thousands of users.

Stacey says a UK version of an app like SignUp would make films and TV "more accessible" for the deaf community. Mariella is up for the challenge — and hopes to make a British Sign Language version of her app for other streaming platforms such as Netflix and Amazon Prime. “There are more than 300 sign languages used worldwide, so it'll take a long time to get all of those versions out,” she says.

Self-driving cars are hitting city streets like never before. In August the California Public Utilities Commission (CPUC) granted (授予) two companies, Cruise and Waymo, permits to run driverless robo-taxis 24/7 in San Francisco and to charge passengers for those rides. This was just the latest in a series of green lights that have allowed progressively more freedom for autonomous vehicles (AVs) in the city in recent years.

Almost immediately, Cruise was criticized for its vehicles behaving unpredictably. One blocked the road outside a large music festival, and another got stuck in wet concrete. The incidents have brought renewed attention to the potential difficulties of integrating self-driving cars into the urban environment.

Yet despite some ongoing opposition, self-driving car companies have continued to expand testing and operations to more US cities. Many supporters say these vehicles could offer a safer alternative to human drivers, make transportation accessible to more people, improve traffic flows around cities and decrease the environmental impact of cars. So far, though, most of those promised benefits remain squarely in a possible future. Meanwhile, here in the present, complications have become plainly apparent.

AVs, such as those operated by Cruise and Waymo, shouldn’t be confused with commercially available cars, such as electric cars, which come with some driver-assistance features. Unlike those vehicles, which require a human driver to oversee control at all times, robo-taxis run on the road without a person monitoring and managing each movement from behind a steering wheel (方向盘). This is made possible by a very detailed internal map.

Waymo and Cruise maintain that their AVs are safer than human drivers. Both companies have released data that they claim support this, yet some researchers have their doubts. “I actually think there is not yet enough data available to the public, including researchers like me, to be able to judge relative safety,” says Steven Shladover, an engineer at the University of California.

Artificial Intelligence (AI) advice is as influential as human’s, but positive crowd views still overpower.

In a study, researchers found that machines that make recommendations—or AI experts—were as influential as human experts when the AI experts recommended which photo users should add to their online business profiles. However, both AI and human experts failed to budge them if their feedback was negative and went against popular views among other users, said S. Shyam Sundar, a professor of Media Effects.

Because people are increasingly using social media to look for feedback, studies suggest that expert opinions and the bandwagon（从众效应）effect may be important factors in influencing decisions, according to Jinping Wang, a doctoral candidate in mass communication and first author of the study. “Nowadays, we often turn to online platforms for opinions from other people—like our peers and experts—before making a decision,” said Wang. AI experts are often less expensive than human experts and they can also work 24 hours a day, which, Wang suggests, might make them appealing to online business.

The researchers also found that the AI’s group status—in this case, national origin was pointed out—did not seem to affect a person’s acceptance of its recommendation. Among human experts, however, an expert from a similar national origin who offered a negative opinion of a photograph tended to be more influential than a human expert from an unknown country who offered a similar negative rating of a photograph.

While findings that suggest group status may not affect whether a person values the view of AI experts sound like good news, Sundar suggests that the same cultural prejudice might still be at work in AI experts for they could be hidden in the programming and training data.

“It can be both good—and bad—because it all depends on what you feed the AI,” said Sundar. “While it is good to believe in AI’s ability to transcend（超越）cultural prejudice, we have to keep in mind that if you train the AI on pictures from one culture, they could give misleading recommendations on pictures meant for use in other cultural contexts.”