Students and faculty express concerns on AI and energy use – Western Herald

Report on the Environmental Impact of Artificial Intelligence in the Context of Sustainable Development Goals

1.0 Event Summary

On November 10, the Lee Honors College at Western Michigan University (WMU) hosted a presentation titled “The Hidden Costs of AI.” The event featured two speakers who addressed the significant environmental and energy consumption challenges posed by the rapid expansion of artificial intelligence (AI) technologies. The discussion highlighted the direct conflict between current AI development trajectories and the achievement of several United Nations Sustainable Development Goals (SDGs).

• Dr. Paul Pancella: A WMU faculty member with a doctorate in nuclear physics and a contributor to the university’s climate action plan.
• Olivia Gries: A WMU masters student in social work and an intern at the Michigan League of Conservation Voters.

2.0 Key Findings: Energy Consumption and Climate Impact

Dr. Pancella’s presentation focused on the massive electrical power requirements of AI, which present a direct challenge to global sustainability targets, particularly those related to energy and climate.

2.1 Conflict with SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action)

The report identified that the escalating energy demand of AI infrastructure undermines progress towards ensuring sustainable energy for all and combating climate change. Key statistics presented include:

1. AI-powered search engines require approximately ten times the electricity of conventional search engines.
2. It is projected that within five years, AI data centers could account for as much as 5% of the total electrical consumption in the United States.

This level of consumption, if met by non-renewable energy sources, will significantly increase greenhouse gas emissions, thereby hindering efforts under SDG 13 (Climate Action) and straining energy grids in the pursuit of SDG 7 (Affordable and Clean Energy).

3.0 Implications for Sustainable Innovation and Responsible Consumption

The discussion extended to the broader implications for sustainable development, emphasizing the need for responsible practices in both the production and consumption of AI technologies.

3.1 Challenges to SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production)

While AI represents a significant technological innovation, its current implementation model raises concerns about the sustainability of the infrastructure required to support it, a key component of SDG 9. Speaker Olivia Gries advocated for greater awareness among consumers, particularly students, regarding the environmental footprint of their digital activities. This aligns with the principles of SDG 12 (Responsible Consumption and Production), which calls for a fundamental shift in how goods and services are consumed.

• Gries voiced opposition to the university’s implementation of the “Buster Bot” AI assistant, citing it as an example of institutional consumption without due consideration for environmental impact.
• A call to action was made for students to reconsider their use of tools like ChatGPT, framing the use of such services as a consumption choice with tangible environmental consequences.

4.0 Conclusion and Audience Reception

The event served as an educational platform to inform attendees about the hidden environmental costs of AI. An assessment from a student attendee, Leo Jackson, indicated that while the presentation was informative, there is a need for more detailed analysis on the topic. The session underscored the critical need to integrate sustainability principles into the design, deployment, and use of AI technologies to ensure that technological advancement does not come at the expense of achieving the Sustainable Development Goals.

Analysis of the Article in Relation to Sustainable Development Goals

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article highlights issues related to several Sustainable Development Goals (SDGs) through its discussion on the environmental impact of Artificial Intelligence (AI). The primary connections are:

• SDG 7: Affordable and Clean Energy: The article’s central theme is the “massive electrical power use” of AI, directly addressing energy consumption and efficiency.
• SDG 9: Industry, Innovation, and Infrastructure: AI is a key component of modern innovation and digital infrastructure. The article examines the negative environmental externalities of this technology, linking it to the need for sustainable industrial and technological development.
• SDG 11: Sustainable Cities and Communities: The discussion takes place at Western Michigan University (WMU) and references the university’s “climate action plan” and efforts to “advance campus sustainability,” which relates to making settlements and communities like a university campus more sustainable.
• SDG 12: Responsible Consumption and Production: The article features a call for students to “take note of the environmental impact of heavy AI use” and advocates against the use of certain AI tools, promoting conscious and responsible consumption of digital services.
• SDG 13: Climate Action: The core issue discussed is the “serious environmental damage” and “hidden environmental toll” of AI, which contributes to climate change through high energy consumption. The mention of a “climate action plan” and the educational nature of the event directly relate to climate action.

2. What specific targets under those SDGs can be identified based on the article’s content?

Based on the article’s content, the following specific SDG targets can be identified:

1. Target 7.3: By 2030, double the global rate of improvement in energy efficiency.
   • Explanation: The article directly addresses energy inefficiency by stating that “AI search engines require ten times the electricity of a normal search engine.” This highlights a move away from, rather than towards, greater energy efficiency for this specific task, making this target highly relevant.
2. Target 9.4: By 2030, upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies and industrial processes.
   • Explanation: The article critiques AI, a key modern technology, for its significant environmental damage and high energy requirements. This implicitly calls for the development and adoption of more sustainable and resource-efficient AI technologies, aligning with the goal of this target.
3. Target 11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management.
   • Explanation: The article mentions that a speaker “works to advance campus sustainability and helped develop the university’s climate action plan.” A university campus functions as a small community, and its climate action plan is a direct effort to reduce its environmental impact, which is the focus of this target.
4. Target 12.8: By 2030, ensure that people everywhere have the relevant information and awareness for sustainable development and lifestyles in harmony with nature.
   • Explanation: The event hosted by the Lee Honors College, titled “a talk on the hidden environmental toll of artificial intelligence,” is an explicit effort to educate and raise awareness among students about the environmental consequences of their technology use, directly contributing to this target.
5. Target 13.3: Improve education, awareness-raising and human and institutional capacity on climate change mitigation, adaptation, impact reduction and early warning.
   • Explanation: The entire event described in the article serves as an educational initiative to inform the WMU community about the climate and environmental impacts of AI. This directly aligns with the goal of improving education and awareness on climate change issues.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article mentions or implies several quantitative and qualitative indicators that can be used to measure progress:

• Indicator: Projected electricity consumption of AI.
  • Details: The article states, “it is estimated that in the next five years AI will grow to be the root of roughly five percent of the United States’ overall electrical consumption.”
  • Relevance: This quantifiable data point can be used to track energy consumption (related to Target 7.3) and the overall environmental footprint of the technology sector (related to Target 9.4).
• Indicator: Comparative energy efficiency of technologies.
  • Details: The article provides the specific comparison that “AI search engines require ten times the electricity of a normal search engine.”
  • Relevance: This metric directly measures the energy efficiency of a new technology compared to an existing one, which is central to assessing progress towards Target 7.3.
• Indicator: Implementation of institutional climate action plans.
  • Details: The article mentions the existence of the “university’s climate action plan.”
  • Relevance: The development and implementation of such plans at institutional levels (like universities, which are part of communities) is a qualitative indicator of progress towards Target 11.6 (reducing the environmental impact of communities) and Target 13.3 (building institutional capacity for climate action).
• Indicator: Number and scope of educational and awareness-raising events.
  • Details: The article is about an event hosted by the Lee Honors College to “highlight the environmental damage and high energy requirements of AI.”
  • Relevance: The hosting of such events is a direct measure of efforts to improve education and awareness, which is the core of Target 12.8 and Target 13.3.

4. Summary Table of SDGs, Targets, and Indicators

Source: westernherald.com