By Tanishi Jaiswal

Abstract

The rapid technological advancements of our era have led to an increase in electronic waste
(also referred to as ‘e-waste’), posing significant environmental challenges. AI-powered
solutions, such as smart sorting systems and robotics, can become useful tools to enhance the
efficiency of e-waste segregation and recycling. AI-driven design can aid in creating
sustainable electronic products. Despite these potential benefits, it is equally pertinent to
consider the environmental footprint of AI systems themselves, thereby ensuring advocacy of
sustainable AI practices. This includes various ethical and legal considerations that
emphasise the need for regulations aligning AI’s deployment in e-waste management with
societal values and promoting responsible disposal methods. AI technology in e-waste
management also opens avenues for innovation and job creation in green industries,
fostering economic growth while preserving the environment. The following essay attempts to
portray AI as a transformative force in e-waste management essential for achieving a
circular economy and environmental sustainability.

Introduction

E-waste comprises electronic devices that are utilised, impaired, or substituted with newer
models. These items encompass household electronics like televisions, computers, mobile
phones, tablets, LED lights, and industrial equipment such as electrical enclosures, air
compressors, air conditioners, and various other electronic goods. E-waste harbours
hazardous materials such as lead, mercury, cadmium, beryllium, phthalates, and other heavy
metals. The management and recycling of e-waste highlights a significant concern, primarily
due to its detrimental impact on the environment and human well-being. Owing to the high
risk involved in its disposal mechanism, it becomes crucial that it be carried out with the
utmost precaution. It requires accurate classification between the types of waste and relevant
machinery to safely recycle the same. However, this is far from reality. Based on UN
statistics, there’s a projected rise in global e-waste generation from 52.2 million tons in 2020
to an anticipated 74.7 million tons by 2030. Alarmingly, merely around 20% of this waste
undergoes appropriate collection and disposal procedures. The remaining majority is
frequently mishandled, often ending up being dumped on streets, landfills, or incinerated,
resulting in severe environmental degradation and detrimental health impacts on humans.
When humans render themselves helpless, technology developed by humans takes over. AI or
Artificial Intelligence offers innovative solutions to the above conundrum. It reduces both –
soil degradation (via landfills), water pollution (via improper disposal) and air pollution (via
incineration), thereby significantly reversing the ill impacts of climate change. This article
attempts to flesh out a more nuanced opinion in this regard.

Outlining the various causes of e-waste
Technological Progression: The rapid advancement in technology significantly contributes
to the problem of e-waste pollution. As technology and industry demand increase, newer
electronic devices continuously replace older ones, leading to the generation of enormous e-
waste.
Growing Electronics Demand: In today’s digital era, electronic devices are indispensable for
various tasks, driving up the demand for such products. Thus, resulting in the general trend of
electronic devices being integrated into day-to-day lives.

Limited Repair Options: Electronic devices often suffer damage or wear over time, and if
they cannot be repaired or the cost of repair is too high, they are typically replaced. This
cycle perpetuates e-waste pollution as discarded devices accumulate.
Illegal E-Waste Trade: The illicit trade of e-waste exacerbates the problem. Businesses and
traders engage in illegal exports and imports of e-waste between countries, where it may be
reused or recycled through unsafe methods, further polluting the environment and posing
health risks.
Awareness Deficiency: Despite the widespread use of electronic devices, many users remain
unaware of the negative impacts of improper e-waste disposal. This lack of education and
awareness leads to careless disposal practices and worsening environmental and health issues.

The interrelationship between e-waste generation and climate change?
The global objective of reducing the rise in global temperature below 1.5 degrees Celsius can
only be achieved by significantly reducing greenhouse emissions. Unless there are cutbacks
in all sectors of the global economy, the same cannot be achieved. The electronics industry is
notorious for its heavy footprint of energy intensity and carbon emissions. Particularly
speaking, more than the production process, it is the disposal mechanism that generates large
quantities of hazardous waste. Estimates regarding the impact of digital technologies on
climate change indicate a range of 1.4%–5.9% of global greenhouse gas emissions, with
approximately 31% attributed to digital devices like smartphones, desktops, displays, and
netbooks. Additionally, the global supply chain of the electronics industry ranks among the
top eight sectors responsible for over 50% of the world’s carbon footprint. Recent data reveals
that approximately 53.6 million metric tons (MMT) of e-waste were generated globally in
2019, averaging 7.3 kilograms per capita, marking a 21% increase (9.2 MMT) since 2014.
Projections suggest that e-waste volumes will escalate to 74.7 MMT by 2030. Presently,
only 17.4% of e-waste is formally recycled. Europe and the Americas exhibit higher e-
waste generation per capita compared to other regions, with 16.2 and 13.3 kilograms per
capita, respectively, while Asia and Africa produce the least, with 5.6 and 2.5 kilograms per

capita, respectively. In terms of e-waste collection and recycling rates, Asia surpasses the
Americas with 11.7%, whereas Europe boasts the highest rate at 42.5%.
While these numbers might be quite impressive, the hard truth is that the majority of the e-
waste is being traditionally disposed of i.e. either incinerated or buried in landfills. This
results in the release of toxic chemicals (as greenhouse gases) into the atmosphere leading to
depletion of the ozone layer. Manual segregation, despite being practised to its fullest
capacity is unable to increase the maximum threshold of recyclability. For instance, even in
Europe which supposedly ‘boasts’ 42.5% of e-waste being recycled, is unable to treat the
other big chunk. The volume and the rate of e-waste generation are something that cannot be
humanely treated. In a country like India, for instance, e-waste is seldom segregated from
other forms of waste by the consumers themselves. This would mean imposing upon the
cleaning staff/workers the herculean task of manually sorting out the same. Even if one
ignores aspects of ‘unawareness’ and non-compliance, and operates at full-human capacity,
there is bound to be a huge chunk of waste that remains unprocessed. This is where it is
crucial to draw the line and develop mechanisms to help. AI can serve as an adept tool to
counter the same.

Artificial Intelligence: A tool for ‘sustainable’ change

It might seem paradoxical, but technology holds the key to solving the e-waste problem.
Manually disassembling and recycling electronics is both hazardous and labour-intensive.
However, with the use of AI, machine learning, and robotics, the recycling process can be
expedited, and valuable components can be recovered for reuse. Leveraging AI and machine
learning to tackle the e-waste issue could save electronics manufacturers billions of dollars
and eliminate e-waste pollution. The world can no longer afford to discard, shred, or
incinerate old electronics. As technology becomes increasingly integral to our future,
recycling electronic devices is essential to ensure a safe, tech-driven world for everyone.

The RcubeBot system

One can propose a robotic system for identifying and collecting household electronic waste
can address the primary challenge of segregation. This system operates at each collection
point during a garbage truck’s route around the city. At every household collection point, the
robot takes individual photographs of the waste materials intended for disposal and uses deep
learning to identify electronic waste. The identified electronic waste is then collected and
placed on the robot’s storage platform. After the collection process is complete, the robot
returns to the truck and deposits the collected waste in a designated area within the truck. For
this, the garbage truck must have segregated compartments. In India, increasingly segregated
garbage trucks are being introduced. Accelerating this process and the introduction of such
technology would solve a large chunk of the problems caused by e-waste at the pick-up point
itself.

Dataset: Segregation within electronic waste

A dataset could be used, consisting of 8,000 images of prominent consumer electronic
devices, with conditions ranging from fully functional to critically damaged. This dataset
would be divided into eight labels: computer keyboards, motherboards, mobile phones,
refrigerators, laptops, mice, radios, and televisions, with each label containing 1,000 images
of the corresponding device. The dataset could be created using a script-based image scraping
method from static pages through popular image search engines. Each image would be
verified to ensure its relevance to the corresponding label and its suitability for classification
modelling. This would result in a segregation between the different kinds of electronic waste
disposed of. Further, it could be recycled according to its respective categorisation.

Conclusion

To conclude, the growing problem of e-waste significantly contributes to environmental
pollution and climate change due to the improper disposal of electronic devices, which
release harmful greenhouse gases. Addressing this issue requires innovative solutions, and
the integration of AI and advanced technology presents a promising path forward. AI-driven
tools can revolutionise the way we manage e-waste by enhancing the efficiency of recycling processes, identifying valuable components for reuse, and minimising the release of toxic
substances into the environment.
While the idea of leveraging AI to combat e-waste might seem ambitious, the urgency of the
situation demands swift and decisive action. Implementing these technologies can
significantly reduce the environmental footprint of e-waste and help mitigate climate change.
This approach is particularly crucial for countries like India, where rapid technological
adoption and population growth exacerbate the e-waste challenge. By embracing AI and
technological advancements, we can turn the tide against e-waste pollution, ensuring a
healthier, more sustainable future for generations to come.

Author’s Bio:
Tanishi Jaiswal is currently pursuing her third-year, B.A. LLB, at Jindal Global Law
School. Her areas of interest include Corporate and Commercial law. She is also
interested in assessing the legalities associated with environmental norms and schemes.