Our planet is facing a serious issue. Due to rapid urbanization, people are generating a lot of waste, which is especially the case with plastic. For instance, in 2015 alone, the world produced 448 million tons of plastic waste. Most of that waste ends up in oceans, and unless we take action, we might be heading toward disaster. If we want to make our planet more sustainable, we should increase our recycling efforts.
Recycling today is a joke. Many municipal rubbish collectors just dump recycled waste in the landfill with everything else. Furthermore, because recycling is unpleasant and expensive, many first world countries ship their waste to 3rd world countries, pay them to process it, and then walk away with a clear conscience knowing it’s now someone else’s problem. Not only does shipping waste across the world emit CO2, but many of the countries that are paid to accept our waste for “recycling”, are even less capable of dealing with it than we are. The result is that “recycling” plastic may actually pollute the ocean more than just landfilling it.
My own town has bins with two holes, one marked “litter”, and one marked “recycling”, which both feed into the same bag!!!
Cynically put, perhaps the main reason we are required to sort and recycle our litter is so local governments can raise money through fines.
Thankfully, artificial intelligence could dramatically improve this woeful situation.
The task of recycling involves taking an object an owner no longer wants, and finding the path of minimum energy and waste to use that same object to satisfy someone else’s needs or desires in a manner that maximally offsets the energy consumption or waste the recipient would have expended pursuing their desire through other means.
Today, the internet and AI have greatly increased the scale of the second hand market with sites like Craigslist and eBay. And, in general, the internet can facilitate collaborative consumption which whether through car sharing or clothes swapping enables more people to obtain greater benefits from the same resources. Too Good To Go is an example of an app that enables restaurants to cut food waste by offering discount deals to people who collect meals just before closing time. This helps restaurants to manage their inventory better and reduce waste while and consumers who are flexible get high quality discount meals.
Advances in robotics could take all this to the next level. Not just increasing the efficiency of use and reuse, but also the efficiency of repair and recycling.
A big problem with mass production is that it lowers the relative cost of building something from scratch when compared to repairing it. Repair requires creativity and improvisation – both anathemas to mass production and economies of scale, which generally rely on doing the exact same thing over and over again. The result of these economies has been waste on an unparalleled scale. When something goes wrong with our widget, we almost always trash it and buy another widget.
Fortunately, the logic of economies of scale may be coming to an end. In a previous article I’ve argued that the rational for economies of scale and specialization rests upon the high cost of intelligence and information and that, as intelligence and information become cheaper, increasingly generalized functionality will also become cheaper. A 3D printer being a good example of something that can print a wide variety of general shapes if input with the right software.
But in general, highly intelligent robotic repair systems, disassembly systems and sorting systems will become increasingly economic as artificial intelligence is further developed. Larger suppliers and customers keep everything simple, but, with ever cheaper information storage and processing systems, we won’t need to keep things simple and mind-bogglingly complex logistical operations that are information intensive, but energy and materially efficient, will be accessible to the flexible manufacturing systems and 3D printing systems of the future. It will be possible, in the future, to order a product from a software procuring system and then for that system to simultaneously scan: