E-waste is quickly becoming one of the world’s most pressing issues, but AI and machine learning may be able to help. Technology is a vital part of the modern world and has led to countless invaluable improvements in daily life.
Unfortunately, as we develop better technology every year, old tech is getting thrown away at increasing rates. The only way to solve the e-waste crisis is with innovative new recycling technologies.
E-Waste Recycling Is Critical Today
Now, more than ever before, the world needs an effective technology recycling strategy. A number of factors are driving the need to recycle devices rather than simply toss them in a landfill. A prime example is the ongoing semiconductor chip shortage.
The rapid shift to remote work combined with the global supply chain crisis has resulted in an overwhelming shortage of computer chips. This is hurting manufacturing in everything from appliances to automobiles to laptops and smartphones. Even with manufacturers working at maximum capacity, demand continues to grow and prices continue to rise.
The problem is particularly bad for key computer parts, such as graphics processing units. Recycling technology to salvage valuable chips could help bridge the shortage.
Even if the world wasn’t desperately in need of more semiconductor chips, e-waste is creating a serious public health problem. Industry leaders estimate that 70% of toxic waste in landfills around the world is e-waste. In 2017 alone, over 44 million tons of new e-waste was created, worth a shocking $64 million.
E-waste contains chemicals and harmful substances that contaminate the environment around landfills. This often pollutes food and water supplies and creates dangerous air pollution around nearby communities. Children and pregnant mothers who have to live and work around landfills are in particular danger of e-waste-related health issues, such as respiratory disorders.
The Role of Automation
The world clearly needs a solution to ensure a future that’s safe from the e-waste crisis. The problem is, recycling e-waste is complex and time-consuming.
Disassembling electronic devices isn’t typically an efficient or even straightforward process. In fact, manufacturers often make it difficult to take apart devices in order to keep consumers from tampering with them.
Researchers think artificial intelligence and machine learning could be the fix that e-waste recycling needs. With ML, AI algorithms can learn quickly and effectively. Research studies have found that implementing deep learning results in upwards of 90% accuracy in identifying electronic components.
So, AI definitely has the capability to perform this job well. With a robot with AI and ML, the health risk associated with e-waste recycling would be eliminated. Additionally, one of AI’s greatest strengths is efficiency. By automating the process, e-waste recycling could become fast and affordable.
Multiple research teams are working to develop an automated AI system that can recycle e-waste. In 2021, the U.S. Department of Energy even awarded over $400,000 to researchers from three different U.S. universities developing e-waste recycling robotics.
Certainly, given today’s challenges, there is a market for an AI-powered e-waste recycling system. An effective electronics recycling robot could save companies in numerous fields millions of dollars while also providing a scalable solution to chip shortages.
If it was easy to recycle electronics, e-waste would become much less of a problem. Additionally, existing e-waste could be collected and sent to robotic recycling centers, which would protect civilians in poorer regions who have to work up close with e-waste.
AI, ML, and Long-Term Solutions
As mentioned above, one of the major obstacles to e-waste recycling is design strategies from manufacturers. Electronics manufacturers tend to focus on the initial customer experience using their electronics. Some, such as Apple, even make it infamously difficult for the average user to open up or take apart their devices.
This makes simple repairs like replacing a battery or a cracked screen an expensive hassle, with some manufacturers even requiring users to mail in their devices to get a new battery. It also makes recycling these devices unnecessarily complicated.
Leaders in the e-waste recycling field have stressed the importance of standardization for reducing e-waste. A “jack-of-all-trades” AI robot would be the ideal recycling solution, one that could easily be adapted to work with any kind of device. However, manufacturers make this a challenge when they do everything completely differently and use counterproductive techniques, such as gluing in batteries.
AI and ML are efficient, adaptable technologies. They still take significant amounts of time and money to train, though. So, working with such a wide variety of disassembly approaches makes development far more expensive and complicated.
AI robots are the key to solving the e-waste crisis. In order for them to be successful, though, electronics manufacturers need to get on board and make devices built to be recycled eventually.
Solving the E-Waste Crisis With Tech
It may sound ironic, but technology is the answer to the e-waste crisis. Disassembling and recycling electronics by hand is dangerous and time-consuming. With AI, ML, and robotics, though, electronics can be recycled rapidly and invaluable parts salvaged for reuse. Applying AI and ML to the e-waste crisis could save electronics manufacturers billions of dollars and end e-waste pollution.
The world can no longer afford to simply throw away, shred, or burn old electronics. Technology is part of the fabric of the future, so recycling devices is a necessary step to ensuring everyone gets to live in a safe, tech-powered tomorrow.
