The Growing Environmental Impact of Artificial Intelligence
As artificial intelligence (AI) continues to expand at a rapid pace, concerns about its energy consumption are coming to the forefront. Environmental watchdogs are sounding the alarm, but it is essential to have actual data to support these warnings. In a new report by Alex de Vries, the founder of Digiconomist, the environmental impact of AI is quantified.
According to de Vries, the training phase of AI models is where most of the energy is consumed. This phase involves feeding large datasets to the program before it can answer any prompts. However, de Vries argues that the inference phase, which tests the AI against real-world data, is often overlooked and can significantly contribute to the overall energy consumption of an AI model.
For almost a decade, the sustainability of digital assets, such as Bitcoin, has been a central focus of the research conducted by Digiconomist. Now, de Vries is turning his attention to AI and its environmental impact. He acknowledges the difficulty in obtaining accurate numbers for AI’s energy use, as it is different from cryptocurrencies in terms of measurement.
One common narrative used by AI developers, similar to cryptocurrency companies, is the claim that they influence utilities to produce renewable energy. However, the construction of massive data centers required to house the AI models does not provide any real benefits to the local economy.
De Vries highlights the response time of the environmental community, comparing the scrutiny faced by Bitcoin after the 2017 bubble burst to the current hype surrounding AI. It took several years before environmental organizations seriously addressed Bitcoin’s electricity consumption, and de Vries hopes that AI will not face a similar fate.
A recent report by the Associated Press revealed that data centers, such as those used for ChatGPT, consume a significant amount of water. OpenAI’s data centers are allegedly located near water sources used for irrigation in Iowa. As AI’s energy consumption gains attention, some experts believe that the concerns will prove to be overblown, just as they were for blockchains.
Adam Sharp, HIVE Research Director, dismisses the apocalyptic predictions about AI’s energy use and expects efficiency to improve in the coming years. He references the inaccurate prediction that Bitcoin would consume 100% of the world’s energy by 2020 to emphasize that technology often becomes more efficient over time.
While de Vries acknowledges the potential for improvements in hardware and software efficiencies, he cautions against relying solely on these advancements to solve AI’s environmental issues. Increased efficiency can lead to higher demand for AI, offsetting the gains made in energy consumption reduction.
De Vries hopes that as more headlines highlight AI’s electricity consumption, environmental groups will pay attention and learn from past experiences with cryptocurrencies. However, limited available data may delay the prioritization of AI’s energy consumption.
Considering the known limitations and concerns surrounding AI, de Vries encourages people to factor sustainability into their use of AI. Researchers have already highlighted issues such as data privacy, bias/racism in responses, and the generation of false information. It is crucial to not get swept away by the hype surrounding emerging technologies and remember to consider the end user.
As AI becomes increasingly ubiquitous, it is essential to address its environmental impact and take proactive measures to minimize harm. With more accurate data and increased awareness, it is possible to find sustainable solutions that allow AI to thrive without compromising the environment.
Editor Notes:
AI’s rapid growth has undoubtedly brought numerous benefits and advancements. However, it is crucial to address the environmental impact and energy consumption associated with this technology. The work of individuals like Alex de Vries sheds light on this issue and encourages us to consider the long-term consequences of AI. By balancing innovation, sustainability, and ethical considerations, we can harness the power of AI responsibly.
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