Navigating Sustainable AI – How to Minimize Your AI Carbon Footprint

Companies need to consider the AI carbon footprint as part of investing in this new technology.

One might argue that Artificial Intelligence (AI) came of age in 2023. The launch of ChatGPT as a generative AI tool put this technology at the top of many new strategies. The longer term impact will be felt for many years to come. AI has revolutionized industries, but its environmental impact has begun to raise concerns. The MIT Technology Review reported that training just one AI model can emit more than 626,00 pounds of carbon dioxide equivalent – which is nearly five times the lifetime emissions of an average American car (source). Real Estate and Title companies, driven by their commitment to sustainability, need to start adopting tailored strategies to minimize their AI carbon footprint.

Understanding the Environmental Impact

AI’s impact on the environment stems from energy-intensive processes, data center proliferation, electronic waste, and resource-intensive hardware production. Today’s rush to incorporate AI into everything has the potential to exacerbate potential environmental issues. Here are three factors that can have a big impact on an AI carbon footprint.

1. Energy Consumption Optimization

AI models, especially deep learning algorithms, demand substantial computational power. This leads to high energy consumption. The process of training these models involves massive data sets and extensive computations, significantly increasing carbon emissions. This is the case with Real Estate, Title, and other industry operations.

AI models can be optimized by employing techniques like pruning unnecessary parameters and layers. This approach significantly reduces the energy footprint during training and inference. Companies can adopt model compression methods to ensure efficiency without compromising accuracy.

For example, Real Estate valuation models could be streamlined by only focusing on essential features to reduce the computational load. The resulting impact is less energy consumption.

2. Efficient Data Center Practices

The storage and processing requirements of AI systems is now driving an influx of data centers. These centers, crucial for AI operations, consume massive amounts of energy, contributing to the environmental toll of AI.

A transition to energy-efficient data centers powered by renewable energy sources could help reduce this burden. Real Estate, Title, and other organizations should evaluate cloud service providers based on their commitment to sustainability. Adopting a hybrid cloud strategy allows organizations to dynamically allocate resources, optimizing efficiency and reducing carbon emissions.

For example, utilizing cloud services with a strong focus on sustainability, Real Estate databases and Title processing systems can operate seamlessly, minimizing the need for on-premises data centers.

3. Collaborative Resource Sharing Strategies:

Collaboration among Real Estate and Title companies in AI projects can lead to resource optimization. Pooling computational resources and data storage capabilities not only reduces redundancy but also creates a shared infrastructure that is more energy-efficient. Establishing industry-wide standards for data sharing can foster a collaborative ecosystem, promoting environmental sustainability.

For example, Real Estate companies in a region can collaborate on shared AI initiatives, consolidating resources for property valuation models and reducing the overall environmental impact.

4. Resource-Intensive Hardware Production

The production of hardware components crucial for AI operations, such as Graphics Processing Units (GPUs) and semiconductors, contributes significantly to environmental degradation. The extraction and processing of rare earth metals required for these components often results in deforestation, habitat destruction, and pollution. Real Estate and Title companies can address this issue by actively seeking out manufacturers committed to sustainable sourcing and production practices. Investing in recycled or upcycled hardware components can further reduce the environmental impact of AI infrastructure.

For example, Title companies could contribute to reducing the AI carbon footprint by sourcing GPUs from manufacturers utilizing sustainable practices.

5. Biased Algorithms and Environmental Consequences

The development and deployment of biased algorithms in AI systems can lead to suboptimal resource allocation, potentially exacerbating environmental issues. For instance, biased algorithms in property valuation models might perpetuate inequalities in housing markets. Real Estate and Title companies need to prioritize fairness and transparency in their AI systems to avoid unintended environmental consequences. Ethical AI practices, ongoing audits, and diverse data sets can help mitigate biases, ensuring that AI applications contribute positively to environmental sustainability.

For example, Real Estate companies can implement fair lending practices by continually auditing AI algorithms. This review would look for biases, ensuring equitable valuation processes and reducing the risk of perpetuating environmental injustices.

Understanding the multifaceted nature of AI’s environmental impact empowers Real Estate and Title companies to adopt targeted strategies. Addressing energy consumption, data center practices, collaborative strategies, hardware production, and algorithmic biases collectively creates a roadmap towards reducing the AI carbon footprint across these industries. By actively engaging with these challenges, organizations can contribute to a more environmentally conscious and ethically-driven future.

Working with a Systems Integrator as a Sustainability Partner

Collaborating with a systems integrator familiar with AI technology is a strategic move. These experts can apply their knowledge to deliver best-in-class AI solutions. This move can also further reduce your AI carbon footprint and emissions in AI projects.

Read this case study for an example of how a Title industry analytics company differentiated itself by providing a faster, more reliable service. By adopting an Axis Smart Data Extraction solution, this company achieved cost savings of 40%.

Here are a few examples of how working with an experienced systems integrator can help further your AI project – while helping to reduce your AI carbon footprint.

  1. Optimize Workflows – Systems integrators can streamline AI workflows, ensuring efficient use of resources. This includes optimizing data storage, processing, and model deployment, reducing unnecessary energy consumption.
  2. Utilize Environmentally-Friendly Hardware – Integrators can recommend and implement eco-friendly AI hardware, utilizing components that minimize environmental impact. This approach contributes to a more sustainable AI infrastructure within Real Estate and Title companies.
  3. Apply Continuous Monitoring and Improvement – Systems integrators play a crucial role in continuously monitoring AI systems. By identifying inefficiencies and implementing improvements, they contribute to long-term sustainability goals, reducing the carbon footprint over time.

Bernard Marr made some great points in this article that was published in Forbes, Green Intelligence: Why Data And AI Must Become More Sustainable. One of his points was to follow Google’s “4M” best practices, which can significantly reduce energy and carbon emissions for anyone using Google Cloud services. These include selecting efficient machine learning model architectures, using processors and systems optimized for ML training, computing in the cloud rather than on-premises, and map optimization to choose locations with the cleanest energy. Watch this video to learn more:

In conclusion, the environmental impact of AI is a multifaceted challenge that requires a proactive and collaborative approach. Real Estate and Title companies can lead by example, adopting strategies to minimize their AI carbon footprint. By optimizing models, adopting energy-efficient practices, and collaborating with knowledgeable systems integrators, these companies can contribute to a more sustainable future while embracing the benefits of AI technology.