Report on Lancaster Chamber Annual Dinner: Artificial Intelligence and Sustainable Development

Introduction

On June 18, the Lancaster Chamber held its annual dinner featuring keynote speaker Zack Kass, who addressed the integration and future applications of artificial intelligence (AI). The discussion highlighted several important points, particularly the need for community reinvestment and the environmental implications of AI technologies.

Key Discussion Points

Community Reinvestment and Sustainable Development

Kass emphasized the importance of reinvesting in local communities, aligning with several Sustainable Development Goals (SDGs), including:

• SDG 11: Sustainable Cities and Communities
• SDG 8: Decent Work and Economic Growth
• SDG 9: Industry, Innovation, and Infrastructure

However, some context was missing regarding how these reinvestments could be balanced with environmental sustainability.

Environmental Impact of Artificial Intelligence

When questioned about AI’s environmental footprint, Kass deflected responsibility by comparing AI companies to almond farmers, suggesting that AI developers should not be singled out for climate accountability. This response overlooks critical environmental concerns, including:

1. Energy consumption: The International Energy Agency forecasts that data centers will consume 945 terawatt-hours by 2030, exceeding the total energy use of Japan, which raises concerns related to SDG 7: Affordable and Clean Energy.
2. Water usage: Data centers require substantial fresh water for cooling, impacting SDG 6: Clean Water and Sanitation.

This deflection fails to address the essential question of how to integrate AI into businesses while safeguarding the environment for future generations, a core principle of SDG 13: Climate Action.

Urgency of Climate Action and Equitable AI Integration

Kass suggested that technology could resolve the environmental challenges humanity faces. However, the reality is that many communities are already experiencing the severe effects of climate change, such as the record high temperatures observed in Lancaster County this summer. This situation underscores the urgency of:

• SDG 13: Climate Action – mitigating ongoing climate disasters.
• SDG 10: Reduced Inequalities – ensuring equitable access and benefits from AI technologies.
• SDG 16: Peace, Justice, and Strong Institutions – fostering inclusive decision-making regarding technology deployment.

The challenge remains: how to introduce AI responsibly and equitably, ensuring that future generations inherit resilient and thriving communities.

Conclusion

The Lancaster Chamber’s annual dinner highlighted the intersection of artificial intelligence and sustainable development. While AI presents opportunities for innovation and economic growth, it also poses significant environmental challenges that must be addressed in alignment with the United Nations Sustainable Development Goals. Effective reinvestment in communities, responsible energy and water use, and equitable technology integration are essential to achieving a sustainable future.

Report prepared by Lucas Shumaker, Marietta

1. Sustainable Development Goals (SDGs) Addressed or Connected

1. SDG 7: Affordable and Clean Energy – The article discusses the significant energy consumption of data centers powering AI technologies, highlighting the need for sustainable energy use.
2. SDG 9: Industry, Innovation and Infrastructure – The integration and future applications of artificial intelligence relate to fostering innovation and building resilient infrastructure.
3. SDG 11: Sustainable Cities and Communities – The article emphasizes reinvesting in communities and building sustainable futures for generations to come.
4. SDG 13: Climate Action – The environmental impact of AI, climate disasters, and the need to address climate issues are central themes in the article.
5. SDG 6: Clean Water and Sanitation – The article mentions the large amounts of fresh water required for cooling data centers.

2. Specific Targets Under Those SDGs

1. SDG 7
   • Target 7.2: Increase substantially the share of renewable energy in the global energy mix.
   • Target 7.3: Double the global rate of improvement in energy efficiency.
2. SDG 9
   • Target 9.4: Upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies.
3. SDG 11
   • Target 11.3: Enhance inclusive and sustainable urbanization and capacity for participatory, integrated and sustainable human settlement planning and management.
4. SDG 13
   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters.
   • Target 13.3: Improve education, awareness-raising and human and institutional capacity on climate change mitigation, adaptation, impact reduction and early warning.
5. SDG 6
   • Target 6.4: Substantially increase water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater.

3. Indicators Mentioned or Implied to Measure Progress

1. Energy Consumption of Data Centers – The article cites International Energy Agency models predicting data centers will use 945 terawatt-hours by 2030, implying the use of energy consumption metrics to measure progress towards SDG 7 targets.
2. Water Usage for Cooling Systems – The mention of large amounts of fresh water required for cooling data centers relates to indicators measuring water withdrawal and efficiency under SDG 6.
3. Frequency and Impact of Climate Disasters – References to continuous climate disasters and high temperatures imply indicators related to climate resilience and disaster risk reduction under SDG 13.
4. Community Reinvestment and Equity – The article’s focus on equitable introduction of AI and reinvestment in communities suggests indicators measuring inclusive urban development and social equity under SDG 11.

4. Table: SDGs, Targets and Indicators

Source: lancasteronline.com