Why we need AI more than ever
Traditional technologies (such as infrared-guide sorters and mechanical systems for waste disposal) were certainly a valuable tool, but still not smart enough to get the job done alone.
Why? Let me explain…
After sorting, processing, and packaging the recyclable materials, MRFs (material recycling facilities) can sell what they got to brokers or manufacturing facilities.
The process can seem pretty straightforward, but believe me, it’s not!
Brokers are difficult clients
Buyers are very selective and accept the materials according to specific requirements. For example, they could refuse materials that risk being food-contaminated.
This means, for example, that the MRF won’t be able to sell a plastic bottle and a plastic package of delicious prosciutto to the same broker, even if these materials are indistinguishable from the electronic eyes of an infrared camera.
That’s why we still need teams of human workers to watch over the action of the machines, preventing pizza boxes from ending up with used ketchup bottles.
NO KETCHUP WITH PIZZA. NEVER. EVEN IN DEATH.
Working in recycling facilities is a hard job
So, we service the machines with human operators and everything is solved. Right? Hey, not so fast!
Another issue to consider is the safety of workers in the field of waste recycling, who are much more at risk of injury than the average, according to research from the University of Illinois.
Beyond that, we’re talking about a particularly hard, repetitive, and boring, albeit well-paid, job, carried out in a working environment that is certainly not healthy.
That’s why employee turnover in modern recycling centers is so high and companies struggle to find new workers.
Of course, even the fact that every mother points out waste workers as “what you will become if you don’t study” does not improve the reputation of these jobs…
“Another issue to consider is the safety of workers in the field of waste recycling, who are much more at risk of injury than the average.”
Let others handle your garbage (?)
In the past years, the problems described above have been partially compensated by delegating the assignment to foreign countries, which dealt with both recycling and landfill storage.
And by “foreign countries” I essentially mean developing countries ready to pocket money to do the (literally) dirty work.
But like a hydra that grows many heads after cutting off one, the solution has also been the source of further problems.
First, recycling techniques were often not up to Western standards and, as a result, raw materials received back from foreign companies were often contaminated or of poor quality.
Secondly, such a choice has made America and Europe dependent on external agents, primarily China. That worked until China said: “not anymore” in 2018.
China doesn’t want bad quality waste
For many years, China has been committed to recycling much of its waste from the United States, for example by turning plastics into pellets.
The problem was that more and more garbage was sent without being previously and properly sorted. It is estimated that a quarter of the material received was not recyclable and therefore had to be buried or incinerated.
Consequently, the Chinese government determined that only cargoes containing up to half a percent of contaminated materials (such as food packages) would be accepted.
From great crises come great technologies
The challenges associated with waste disposal and the optimization of recycling operations have led companies to seek technologically advanced solutions based on AI and machine learning.
Great steps have already been taken in this direction. For example, robots have become much cheaper and more efficient at sorting waste on conveyor belts, going from around 40 to over 80 items per minute in just two years.
This means that over the years machines will be able to take on more and more tasks and lighten the human workload.
However, this does not mean that artificial intelligence can reduce the amount of waste that goes to landfills or lead people to a more sustainable lifestyle.
For that, we need education, a long-term vision, and a little bit of HUMAN intelligence.