With the new global agenda of green and sustainable development to reduce climate impact (SDG13: Climate Action), it is necessary to look at how blockchain and cryptocurrencies, their mining and storage processes are affecting the world’s environment.
In recent months, the media has extensively reported on the harmful influence that cryptocurrencies like Bitcoin are having on the environment. Additionally, their volatility has been noted as a reason for concern.
Due to its dependence on energy-intensive consensus processes like proof-of-work, which are essential to preserving the security and integrity of distributed ledgers, blockchain technology has a significant environmental impact. Complex cryptographic calculations are needed to validate transactions and add them to the ledger, which uses a significant amount of electricity and processing resources. As a result, concerns over the long-term viability of blockchain networks, especially those that support cryptocurrencies, have been raised by their carbon footprint.
The carbon footprint of blockchain has substantial and varied environmental consequences for sustainability. In addition to the direct emissions brought on by energy usage, there are also indirect effects like a greater dependency on fossil fuels to the production of power and the depletion of natural resources utilized in the production of hardware. But is it even possible to resolve that problem?
Not a super obvious solution but definitely should be mentioned – Artificial Intelligence.
How does AI affect the environment itself?
In order to train and operate, AI algorithms frequently need a large amount of power, which increases energy consumption. Deep learning model training can need a large amount of power consumption from high-performance computer equipment, which increases carbon emissions and, of course, is not really great for the environment. On the other hand, improvements in AI hardware and algorithms that use less energy could mitigate this effect towards better sustainability.
The optimization of consensus procedures is one of the main areas in which artificial intelligence may have major implications. Decentralized ledger systems may be able to switch from energy-intensive proof-of-work methods to more environmentally friendly options like proof-of-stake or delegated proof-of-stake by using machine learning algorithms to examine transaction patterns and network dynamics.
Predictive analytics powered by AI also has the potential to improve resource allocation in the networks, maximizing computing resource consumption and reducing waste. To fully achieve the efficacy of blockchain solutions enhanced by artificial intelligence in mitigating crypto and other new technologies environmental impact and to develop the complicated industry, stakeholders, governments, and researchers must work together to achieve this objective. In the other case we will see even worse results than the recent ones.
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