With its durability and its unique color and patterns, tortoiseshell (龟甲) has been used to make everything from jewelry to combs and dishware. Tortoiseshell does not come from tortoises. It comes from hawksbill (玳瑁) turtles, which are not particularly large compared to other sea turtles and grow up to about 45 inches in shell and 150 pounds in weight. Between 1884 and 1992, data shows that at least nine million hawksbills were killed and sold for their shells. But now, their international commercial trade is banned.

Brad Nahill, co-founder and president of turtle conservation group SEE Turtles and a National Geographic Explorer is leading an effort to use modern technology to fight the illegal trade of this age-old material. Tortoiseshell is widely and accurately copied with an artificial material, making it difficult to tell real from fake. SEE Turtles with its partners built an app to help. Named SEE Shell, the app uses Machine Learning to identify with 94 percent accuracy whether a photo of something with a tortoiseshell pattern is real or artificial. It’s the first mobile app to use computer vision to fight the illegal wildlife trade, and it will help inform conservation-minded shoppers and law enforcement.

The app is also valuable for the wealth of information it can provide. All images are uploaded to a private, centralized database, with GPS coordinates (坐标) for each, allowing SEE Turtles to identify hot spots for illegal sales. Through the app, scientists have already come across tortoiseshell products they didn’t know. The app will help local conservation groups identify illegal products.

SEE Turtles hopes to bring the technology to online platforms, which have seen a sharp rise in the illegal wildlife trade in recent years. This visual learning technology potentially can be adapted for other wildlife materials. For example, the ability to identify real elephant ivory in an instant would be particularly valuable. Nahill says, “There’s a whole world of possibilities for applying Machine Learning to conservation issues.”

Do you want to get some information about the latest inventions? Read the text and know how science and technology is helping to change the world positively.

In the airport, birds are the main threat. When airplanes try to take off, birds often hit the airplanes and die. These robot birds can rescue the real birds! The inventors will experiment with them at the Edmonton International Airport. So if the robot birds can work adequately in the long run, it will be great news for the birds and us too!

Here is a fantastic invention for basketball players who can’t spend much time training. This practice net has unique features. It can catch the basketball when a player shoots it into the net and send the ball back to the player automatically. The company is designing the practice nets which will come on the market soon.

Fish robots are invented by a team of Swiss scientists and look like minnows (米诺鱼). Scientists have used them to discover underwater lifestyles. When scientists put them under the sea, the result was terrific. All the real fish behaved naturally towards them. These fish robots could move like fish and change directions randomly. The scientists are now planning to add more real fish’s behavior to those fish robots.

Every year, many people die from shark attacks. The creators of lifesaver drones will make sure that the drone can spot any shark in the water. After detecting the shark, the drone will then search if there is any swimmer near the creature. If the shark tries to attack, it will rescue the swimmer and then take him to the dry land. These lifesaver drones will be deployed at the Oasis which is popular among surfers and swimmers in 2023.

Advances in artificial intelligence and the use of big data are changing the way many large companies recruit (招募) entry level and junior management positions. These days, graduates’ CVs may well have to impress an algorithm (算法) rather than an (human resources) manager.

While algorithms supposedly treat each application equally, experts are divided about whether so-called robo-recruitment promises an end to human prejudice in the selection process —or whether it may in fact add to it.

“AI systems are not all equal,” says Loren Larsen, chief technology officer for HireVue, which has developed an automated video interview analysis system. “I think you have to look at the science team behind the work,” says Mr Larsen.

The problem, experts say, is that to find the best candidates an algorithm has first to be told what “good” looks like in any given organization. Even if it is not given criteria that seem discriminatory, a powerful machine-learning system will quickly be able to copy the characteristics of existing workers. If an organization has favoured white male graduates from well-known universities, the algorithm will learn to select more of the same.

The growing dependence on automation to judge suitability for everything from a loan to a job worries Yuriy Brun, an associate professor specializing in software engineering. “It takes a lot of the time for a company to put out software but it doesn’t know if it is discriminatory” he says. Prof Brun explains that, considering the use of big data, algorithms will unavoidably learn to discriminate.

Many of those working with robo-recruiters are more optimistic. Kate Glazebrook, the leader and co-founder of Applied, a hiring platform, says her task is to encourage hiring manager to move away from such indicators of quality as schools or universities and move to more evidence-based methods. When candidates complete tests online, Applied hides their names and shows the tests the candidates have completed, question by question, to human assessors. Every stage of the process has been designed to remove prejudice.

With the same aim, Unilever decided in 2016 to switch to a more automated process for its graduate-level entry programme. Unilever worked with HireVue, Amberjack, which provides and advises on automated recruitment processes, and Pymetrics, another high volume recruitment company, which developed a game-based test in which candidates are scored on their ability to take risks and learn from mistakes, as well as on emotional intelligence. Unilever says the process has increased the ethnic diversity of its listed candidates and has been more successful at selecting candidates who will eventually be hired.

“The things that we can do right now are impressive, but not as impressive as we’re going to be able to do next year or the year after,” says Mr Larsen.

Still, robo-recruiters must be regularly tested in case prejudice has occurred without anyone realizing it, says Frida Polli, the leader and co-founder of Pymetrics. “The majority of algorithmic tools are most likely causing prejudice to continue existing. The good ones should be examined.”