Large clothing and technology companies are developing robots to make clothes. The process of using robots or computers for human work, known as automation, has raised concerns about jobs for many people around the world.

Many clothing companies are unsure about publicly discussing automation. Such reports would cause public concern that automation will take jobs from workers in poor countries.

One industry inventor, Jonathan Zornow, said he has received online criticism, and a death threat, in connection with his work.

Sewing—the act of using a needle and thread to make clothes-is especially difficult to automate. Robots do not have the fine touch skill that human hands do. Robots are getting better, but it will take years to fully develop their ability to handle cloth.

Work at Siemens grew out of efforts to create software to guide robots that could handle all types of materials, such as thin wire cables. Researchers soon realized one of the best targets for automation was clothing.

Siemens worked with the Advanced Robotics for Manufacturing (ARM) Institute in Pittsburgh. They identified a San Francisco company with a promising way to deal with the fabric problem. The startup, Sewbo Inc. , hardens, or stiffens fabric with chemicals. The hardened fabric is then similar to other material robots can handle, like metal for example. Once the robots finish sewing the piece, the clothing is washed to remove the chemical.

There are other efforts to automate sewing factories. Software Automation Inc, a startup in Georgia, has developed a machine that can sew clothing by pulling the cloth over a special table, for example.

Sanjeev Bahl, who opened a small jeans factory called Saitex in downtown Los Angeles two years ago, has studied the Sewbo machines. He is preparing to set up his first experimental machine. At his factory in September, he said that many sewing jobs are ready for a new process.

“If it works,” he said, “I think there’s no reason not to have large—scale (jeans) manufacturing here in the U. S. again.”

Technology offers conveniences such as opening the garage door from your car or changing the television station without touching the TV.

Now one American company is offering its employees a new convenience: a microchip implanted (把……植入) in their hands. Employees who have these chips can do all kinds of things just by waving their hands. Three Square Market is offering to implant microchips in all of their employees for free. Each chip costs $ 300 and Three Square Market will pay for the chips. Employees can volunteer to have the chips implanted in their hands. 50 out of the 80 employees have chosen to do so. Todd Westby is Chief Executive Officer of Three Square Market. Westby and his wife, and their children are also getting chips implanted in their hands.

The chip is about the size of a grain of rice. Implanting the chip only takes about a second and is said to hurt only very briefly. The chips go under the skin between the thumb and forefinger. With a chip in the hand, a person can enter the office building, buy food, log in to computers and more, simply by waving that hand near a scanner. The chips will be also used to identify employees. Employees who want convenience, but do not want to have a microchip implanted under their skin, can wear a wristband(腕带) or a ring with a chip instead. They can perform the same tasks with a wave of their hands as if they had an implanted chip.

Three Square Market is the first company in the United States to offer to implant chips in its employees. Epicenter, a Digital House of Innovation in Sweden, has implanted chips in its employees for a while.

Three Square Market says the chips cannot track the employees. The company says scanners can read the chips only when they are within a few inches of them. "The chips protect against identity theft, similar to credit cards." The U. S. Food and Drug Administration agreed the chips back in 2004, so they should be safe for humans, according to the company.

In the future, people with the chips may be able to do more with them, even outside the office. Westby says, "Eventually, this technology will become standardized, allowing you to use this as your passport, for public transit, all purchasing opportunities, etc."

Robots are famously cold, hard and unfeeling, so they may not be the greatest audience for your favourite knock-knock joke. However, scientists in Japan are looking to change their reputation, by teaching them when and how to laugh using artificial intelligence.

The researchers created an android, named “Erica”, which they trained to detect laughter in conversation, then decide whether to laugh in response and what kind of laughter would be best. Her conversations and chuckles (轻笑) were then watched by volunteers, who decided whether her responses demonstrated empathy and human-likeness.

Lead author Dr Koji Inoue, from Kyoto University, said: “We think that one of the important functions of conversational AI is empathy. Conversation is, of course, multi-modal, not just responding correctly. So we decided that one way a robot can empathize (产生共鸣) with users is to share their laughter, which you cannot do with a text-based chatbot (聊天机器)”

The aim of the research was to develop an AI that can understand slight differences in humour. While it would be possible to train an algorithm (计算程序) to recognize laughter, or read out a joke, these abilities would not enable it to copy natural conversation.

The researchers first developed a “shared-laughter” model for Erica to run, which would allow her to respond to human laughter as an empathetic response. This model asks three questions in order for the robot to appropriately respond to a conversational cue. First is “Did the user laugh?”, then “Will Erica laugh in response?” and finally, if she responds yes to both, “Which type of laughter is proper?”. The types of laughter Erica would choose from are a “social laugh”, a polite chuckle to fill conversation when humour is not involved, or a “mirthful laugh” for funny situations.

To teach the AI to use the shared-laughter model effectively, the researchers gathered data by sending the robot speed dating. Erica, who was remotely operated by four female actors, had over 80 dialogues with male university students. The laughter that appeared during the conversations was then classified into solo, social or mirthful. This was then used to train Erica’s neural network how to decide when it is appropriate to laugh, and which type of laughter to use.