Sec. 2. Findings

328 words·~1 min read·/bill/118/hr/7197/ih/section-2

A research copy — for the controlling text, always check the official state or federal source. Not legal advice.

Congress finds the following: Multiple estimates indicate that the amount of computational power being used for artificial intelligence applications has increased rapidly over the last decade. A 2022 estimate suggested that the number of computational operations being used to create each of the largest artificial intelligence models is currently doubling every 10 months. Accelerating use of artificial intelligence has the potential to greatly increase energy consumption due to the power utilization of computer hardware required for training and operating artificial intelligence models, despite ongoing efficiency gains in both artificial intelligence models and hardware.

Rapid growth in data center infrastructure, including cooling systems and backup power equipment, supporting artificial intelligence and other computing-intensive technologies contributes to pollution, water consumption, and land-use changes. Resource and energy-intensive manufacturing processes are required for the hardware that runs artificial intelligence and other computing-intensive technologies, leading to significant environmental impacts. Yearly increases in electronic waste (known as e-waste ) pose increasing environmental and health risks, and will likely be exacerbated by outdated and discarded hardware used for artificial intelligence and other computing-intensive technologies.

Many applications of artificial intelligence can have direct and indirect positive environmental impacts. Positive environmental impacts may include optimizing systems for energy efficiency, developing renewable energy, advancing planetary systems research, enabling discovery of new materials, and automatically monitoring environmental changes. However, artificial intelligence applications may also have direct and indirect negative environmental impacts, including rebound effects, behavioral impacts, and accelerating high-pollution activities.

Estimates of the current and future environmental impacts of artificial intelligence are currently uncertain. Negative environmental effects may have a disparate impact across different regions and communities. Various options exist to reduce the negative environmental impacts of artificial intelligence, including using more efficient models, hardware, and data centers, using renewable energy, and examining the impacts of artificial intelligence applications. Promoting transparency and environmental protection measures may help mitigate negative environmental impacts of the rapid growth in artificial intelligence use, while promoting artificial intelligence uses with net positive environmental impacts.