Generative AI and its potential environmental impact

Generative AI is a type of artificial intelligence that is able to generate new content based on existing data. This technology offers the potential to transform a wide range of industries, from creating realistic video game environments to generating personalized medical treatments. As with most new technologies, there are environmental impacts to consider. We will discuss them in this blogpost – and illustrate some ways to mitigate them. Read on to find out more about generative AI and its potential environmental impact.

What are potential environmental impacts of generative AI?

One of the most significant potential environmental impacts is the energy consumption of generative AI. It requires enormous computational power to process the large amount of data, which is needed to generate new information. In January 2023, ChatGPT had roughly 590 million visits. With approximately 5 questions per user, this amounted to the same energy consumption as 175,000 people consume in the same period of time. While this enormous figure only takes into account the electricity of the actual usage, another couple of thousands of megawatt have been used to train ChatGPT. The development of ever more powerful components needed to generate content increases electricity consumption significantly To date, this electricity is still mainly generated from non-renewable energies. Hence, generative AI is right now contributing to climate change and enhancing environmental damage.

Another potential environmental impact is the increase in e-waste. Many devices are being exchanged due to outdated hardware. As a result, the demand for new devices, which in turn require new resources for production, is increasing tremendously. If hardware is not properly disposed of, large areas of the environment are or will be polluted. Bosch wants to take its share in climate protection and is already recycling many electrical parts, as you can read here.

Generative AI also has high (negative) potential to contribute to the decimation of natural resources. The infrastructure and production of generative AI applications requires the use of rare minerals and metals, which are either highly intricate in production or often mined in critical social and working environments.

How can we mitigate these effects?

Yet, the potential environmental damages of generative AI are not inevitable. Companies and organizations can take actions to reduce the environmental impact – and so can every one of us! For example, we can invest in energy-efficient hardware and infrastructure. Further possible mitigation effects for companies are to power their data centers with renewable energy, and to increase resource and energy efficiency through circularity.   if you want to learn more about how Bosch uses sustainable innovations for an increased efficiency.

Generative AI can actually help reduce the consumption of natural resources by making processes leaner and by minimizing waste. For instance, generative AI algorithms can be used to optimize buildings, infrastructure, and the design of products. AI can also support in reducing the amount of material needed. On the next level, significant reductions in raw material consumption and energy usage can be achieved. Furthermore, generative AI can be used to optimize the use of resources such as water and energy in manufacturing and production processes. By analyzing data and identifying areas where resources are used inefficiently, the algorithms can suggest concrete changes to improve efficiency and reduce waste. Click here to learn more about transparency for energy data. As a pioneer in the industry, Bosch and its more than 400 locations have been CO₂ neutral since 2020. Do you also want to achieve this magical step? if you think you are ready for the climate journey with Bosch.

Generative AI and its potential environmental impact

Generative AI has the potential to transform many industries. However, it is paramount to consider its potential environmental impact before implementing it into processes. As with any technology, it is up to companies, organizations, and individuals to take responsibility and to minimize the resulting impacts on our environment. By taking proactive steps to reduce energy consumption, e-waste, and resource depletion, we can make sure that generative AI will become a net positive for both our society and our planet.