[vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column][vc_column_text]”Technology and sustainability are the two most talked-about topics in our world”. While the global repercussions of the climate crisis continue on the one hand, artificial intelligence is being developed at a dizzying pace on the other… The path that artificial intelligence (AI) and machine learning will take to overcome global greenhouse gas emissions is a matter of curiosity.[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column]
Experts, who make some partial estimates, although difficult to measure, evaluate the issue through some studies conducted with the contributions of the Berlin-based climate research Institute MCC (Mercator Research Institute on Global Commons and Climate Change) and published in Nature Climate Change Magazine. The author of the study, Felix Creutzig, explains the term “hammer” as follows: “Artificial intelligence can do useful things, but it can also break a lot. That’s why it’s high time to steer them in the right direction with intelligently set rules. This applies not only to the effects on the labour market or data protection, but also to a large extent to the climate. Here, for the first time, we provide an analytical framework to guide policymakers in capturing the various impacts of AI on greenhouse gas emissions as fully as possible”.
People, companies, devices are intertwined with every moment of life… From social media to online banking, from car rental to communication, data stacks include billions of online connections… According to the data, the internet is responsible for 1.6 billion tonnes of greenhouse gas emissions annually with approximately 60% of the global population, i.e. 4.66 billion active users. A paper printout of a credit card statement has a carbon footprint, so does a digitally transmitted file. Smartphones, cloud computing, data centres, artificial intelligence and cryptocurrencies trigger high consumption of electricity from thermal power plants. For example, it is stated that the amount of energy required for the production of blockchain cryptocurrencies is twice as much as mining the same value of copper, gold or platinum. According to the statement made by Digiconomist founder Alex de Vries, it was stated that a single Bitcoin transaction leaves a carbon footprint of 360 kilograms, compared to the 500 milligram carbon footprint of an average Visa transaction. From the message stacks in your Whatsapp messages to our e-mail messages, from the videos we watch to our online meetings, there is a carbon footprint cost created by our internet actions. For example, the carbon footprint of social media, which is among the first ones that come to mind, corresponds to an annual equivalent of 299 grams of carbon dioxide (close to running a blow dryer). Considering all systems, including our devices and the internet, such costs account for almost 3.7 per cent of global greenhouse gas emissions, and this rate is predicted to double by 2025. Artificial intelligence is criticised for arguments based on carbon footprint calculations, the amount of which can change. So the only question on our minds is: when will a future with carbon-neutral artificial intelligence come?[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column]
Thanks to the predictions of artificial intelligence, the acceleration of many processes and the correct and strategic progress of many processes also reduce the carbon footprint. For example, it is possible to predict wind patterns up to 36 hours in advance to optimize wind farms. It also becomes possible to track a cold chain food consumer product or raw material until it reaches the consumer without spoilage with digital equipment on how it can be protected, stored or transferred during the storage and distribution stages. Machine learning can calculate the vast energy generated by electrical systems, scan and interpret data to understand and predict energy production, and help suppliers plan how to strategically utilise resources more effectively. Thus, it also contributes to issues such as reducing waste, meeting the need with renewable resources, waste management and planning. The use of AI for energy efficiency will make a big difference to the carbon footprint as it is used much more effectively at the industry level over the years. Companies, governments and leaders reduce greenhouse gas from transport, which accounts for around 25 per cent of CO2 emissions, and energy waste from buildings. AI benefits as a technology that powers autonomous vehicles, including shared cars, fleets and intelligent transport systems in some cities. To a large extent, it reduces waste in many areas such as time, money, materials, etc. It powers climate change strategy by enabling faster, more accurate, more cost-efficient, predictive and strategically calculable operations in almost all business processes.[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column]
Allocating a budget for carbon offset projects, making investments and developing planned annual practices in the field are among the things that organizations can do. It is stated that even very simple behaviors such as users adjusting their automatic settings, backing up when not necessary, giving up automatic updates and lowering resolutions can make a difference. Sharing the carbon label or statements regarding the relevant efforts with the target audience by the enterprises working with zero carbon target can be a reason for preference on the customer side, as well as contributing to reputation in the eyes of stakeholders, the press and other interlocutors.[/vc_column_text][/vc_column][/vc_row]