Video game teaches women to operate robots set to take their garment jobs

Robots are taking over the garment industry in southeast Asia. And while these machines help companies make clothes quickly and cheaply, they also spell doom for a number of garment workers. 

Enter Shimmy Upskill, a company trying to tackle the problem through an unexpected method: a video game that utilizes artificial intelligence. Using the game, the company wants to teach female workers skills that will help them run the technology in place at their jobs, ultimately helping them stay employed — and possibly make more money — even after automation. 

According to a 2016 report from the International Labor Organization, more than half of all workers in five Southeast Asian countries — Cambodia, Indonesia, the Philippines, Thailand and Vietnam — face a high risk of job loss due to automation in the coming two decades. Jobs in the garment industry are especially at-risk: 64 percent of Indonesians working in the textile, clothing, or footwear industry are at high risk of losing their jobs to automation, while in Cambodia that number climbs to 88 percent.

“These [women garment workers] really are not even considered for technical training when they enter the factories,” says Chisato Sakamoto, product manager at Shimmy Upskill. “They are not even in the pipeline, so through our software, we’re really trying to create that access and trying to chip away at some of the barriers that prevent women from even entering this pipeline.” 

Shimmy Upskill’s game consists of four lessons: It teaches workers how to identify pattern pieces used to create different types of clothes, determine the number of pieces of each pattern required to make a piece of clothing, efficiently lay out the pattern pieces, and finally, lay down pattern pieces on a mannequin in order to teach 3D modeling. The lessons also teach workers how to navigate the cartesian plane — a skill that is necessary for any job that requires workers to program a robot or lay out material to be cut, says Sarah Krasley, founder and CEO of Shimmy Upskill. 

The program uses voice recognition and videos to guide workers through the training, which is especially useful for those with limited literacy skills. Workers can either select Bahasa Indonesia (the official language of Indonesia) or Bangla (the official language of Bangladesh). The game also lets workers learn at their own pace and tells them whether their answer was right or wrong.

All the women who tested the pilot program recently in Bangladesh and Indonesia completed it. That’s important to Sakamoto, who says there’s a strong misconception that people who lack digital literacy aren’t capable of fulfilling technical jobs. 

“We had to say, no actually, these workers are completely capable of using these technologies,” she explains. 

“They just needed a design interface that was designed for them instead of shoving one in their face that’s not in a language they understand, that requires a master degree to operate, and requires a super expensive computer to run,” Krasley adds.

Once the women completed the program, Krasley says, every factory owner seemed surprised at how well the workers did. 

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Shimmy Upskill specifically hopes to fix gender gaps in the industry, operating under the assumption that female garment workers are especially vulnerable to automation. Factory owners, according to Shimmy, tend to prefer workers who can operate different types of machines, but women almost never get the opportunity to receive mechanical or technical training. For example, when Krasley and Sakamoto visited a Bangaldeshi factory, one technical position had a very masculine name: Marker Man.

Shimmy Upskill wants to prove that with the right training, women can fill any position.

“We are excited about the potential for this tool to show a factory owner a very gender-neutral view of their workforce and who can be promoted,” says Krasley. 

The team has seen results. A factory owner in Indonesia told Krasley that he hadn’t considered some of the female workers for technical, higher paid positions before the training. Because they did well, he planned to give them the opportunity to train with new automated equipment, such as cutting machines. As Sakamoto explained over email, this would be a big step up because technical and mechanical jobs in apparel manufacturing generally pay higher than sewing machine operator positions.  

“That [recognition] was extremely exciting for us because that’s what we want to do — we want to show them that women are just as good as men for these technical positions,” says Krasley. 

Not everyone is as confident about the pilot program’s potential. When asked to comment, a representative from the Clean Clothes Campaign explained that there’s still a risk that female workers will be at the bottom of the totem pole. The Clean Clothes Campaign is a network of trade unions and NGOs looking to improve working conditions in the garment industry. 

“The kind of work might have changed, but the end effect (doing repetitive digital tasks for very little pay) won’t be much different from doing manual tasks for very little pay,” Paul Roeland, the public outreach coordinator from the Clean Clothes Campaign, wrote in an email. 

In an email, Sakamoto wrote that Shimmy Upskill is aware the software only addresses one, small piece of a larger puzzle. While Shimmy’s focus is to provide female garment workers with digital skills, the company hopes to work with grassroots labor organizations and the International Labor Organization to improve working conditions for all garment workers. The company also has plans to incorporate lessons on leadership development and workplace harassment 

“We think many different types of solutions are necessary to address unfair wages in supply chains,” Sakamoto wrote. “Among these solutions, Shimmy Upskill is promoting fair wages for garment workers by protecting their access to jobs. After all, we can’t have meaningful conversations about fair wages if automation leads to massive unemployment among garment workers.” 

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