Time flows and technology grows. With every passing day, new technologies and innovations are emerging from every corner of the world. Machine learning and artificial intelligence are the newest trajectories being traced by technological experts. A seemingly bizarre intrusion into our lives has gradually become a mundane occurrence over the years. Which part of our engagements is not automated to an extent? As our dependency on AI-tools grows, we find ourselves at the cusp of humanity’s response to modern technology: What does it mean for our climate and environment?
Digital Innovations and Climate Change
Technology and industrialisation have always been the detriment of climate change. The 1880s had marked the transition to coal as a source of fuel and a century later, it had become the primary fossil fuel for industrial and technological purposes. Naturally, this meant an influx of carbon emissions and while we had become aware of the adversities posited by technology, it was also not possible to completely forego them. Energy consumption would perpetually increase with each technological milestone attained by humanity, whether it be transportation, cellular devices or even cryptocurrency.
A few years ago, cryptocurrency, especially bitcoin, emerged as an integral part of the world’s financial system. With blockchains operational, the crypto market has become a viable option for investors worldwide. However, bitcoin mining consumes a large portion of energy, making it detrimental to the environment. According to a study conducted by the United Nations in 2020, BTC mining consumed 173.42 Terawatt hours of electricity. This was equivalent to burning 84 million pounds of coal. The necessity for immediate regulatory measures was of paramount importance and scientists had begun to devise methods in which technology could assist humanity’s battle against climate change.
Sustainability and Artificial Intelligence
In the year 2015, the United Nations Development Programme adopted 17 primary principles known as the Sustainable Development Goals. These goals would ensure international peace and increased climate control by the year 2030 and included postulates such as Gender Equality, Climate Action and Responsible Consumption.
Several corporations have considered using AI to combat climate change– In an eye for an eye, tooth for a tooth manner– and have formulated certain preliminary project blueprints for the sole purpose of sustainability. However, AI is not exempt from consuming large amounts of energy. In fact, these softwares are growing incessantly complex and require cutting-edge technology and hardware for their creation and maintenance. According to a study conducted by UMass Amherst, training one AI model can emit 625K pounds of carbon dioxide. If that is certainly the case then how can humanity guarantee environmental conservation for the future generations?
To guarantee is one thing, to attempt is another. Green algorithms have certainly been considered as a possible solution by technological experts. These algorithms are mostly managerial in their conduct and allow users to manage complex data sets, computational costs and carbon emissions. Even workspace applications such as Notion allow its users to simplify complex data.
Recent innovations in AI have also enabled us to track the conditions of icebergs and glaciers in Antarctica. Real-time mapping is not merely limited to icebergs but can also be conducted in the case of deforestation and even recycling. These tasks are time and resource-consuming for humans, usually leaving no space for crisis mitigation and problem-solving afterwards. If AI can be utilised to analyse the trends pertaining to climate change, then human intervention can manifest in the form of ideation for sustainable designs and climate change strategies.
Solving the Climate Crisis
Can AI solve the climate crisis? The short answer is no but the longer answer is that there is a possibility. There is no scope for AI to directly solve such a crisis since the aftereffects still persist. One is still using energy to compute and calculate the amount of energy consumption they could reduce. In a way, it seems counterproductive since technology and consumption go hand-in-hand. A 2022 report by BCG on how AI tools can be employed in the fight against climate change details how AI can identify risks and mitigate the adverse effects; however, AI cannot function without the cooperation of policy-makers.
Most of these concerns operate circularly. Assuming that we adopt AI tools in our fight against climate change, what is the purpose of forecasting and predicting trends if we do not apply them in practice? Unless policy-makers are willing to adapt to the changing landscapes and actively involve AI software in their climate action schemes, there is no point in devising green algorithms in the first place. Furthermore, we severely lack proper education and training in terms of artificial intelligence. Organisations lack the confidence and access to these tools. While there have been several attempts to bridge the gaps between modern technological innovations and underdeveloped regions, especially in the case of the IKI Project in Burundi, Chad and Sudan, another major concern that arises is whether the inherent biases that these tools possess could obstruct climate change strategies. Our very first step in combating any kind of issue is accessibility and how we can ensure that the people possess the ethical education necessary to operate such tools.
Conclusion
As time flows, technology certainly grows and the planet grows even hotter. Society’s inherent thrust towards the “new” and the “modern” perpetuates an unending surge of new technologies and innovations. However, we tend to forget the effects such innovations pose upon our environment until they eventually bite us in the back and the summers suddenly begin in December. Several corporations have attempted to utilise AI in our grander scheme of climate action but have yet to bear fruitful results. Research certainly demonstrates the theoretical possibilities but praxis prevails and the questions of implementation are forefronted. However, gradual attempts are still crucial in this scheme and we cannot readily neglect them in the preliminary stages. There are miles to go before we truly achieve a sense of sustenance and stability.
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