How Web3 and AI Applications Move the Sustainability Needle

Web3. Artificial Intelligence (AI). Sustainability . New technology can address old problems in unique ways that were not possible before. As a (slight) tech nerd, I'm always inspired to see innovative companies and individuals using new technologies like blockchain and AI for good.

In fact, the common narrative is that they harm it: Bitcoin critics are quick to mention the energy use required for cryptocurrency mining , and AI is known to be one of the most computing-heavy activities with a high need for energy given the huge data centers dedicated only to refining a predictive model. While these are semi-valid criticisms, they miss the bigger picture. These technologies play critical roles in how organizations operate more efficiently and can shift human behavior toward more sustainable patterns.

Web3 and the impact of sustainability

Blockchain is well known for its use in supply chains, and its use can actively help sustainability. As an example, the world's largest meatpacking group, JBS , recently developed a blockchain platform to track its livestock supply chain to combat deforestation (deforestation is done to provide more grazing space for animals, thereby resulting in a negative effect on biodiversity and air quality).

Walmart uses IBM blockchain-based Food Trust to track its products at every step of the supply chain, both to minimize operating costs and work toward sustainability goals by reducing energy loss and waste. This same tool is also used by Nestlé , Tyson Foods , Carrefour and Raw Seafoods, among others.

Applying blockchain development services to the problems facing supply chain managers has some advantages regarding sustainability:

Efficiency: Businesses can now complete financial transactions without third parties, reduce the time between order and payment processing, and further integrate the logistics flow. All this means less wasted material and energy.

Transparency: In today's complex supply chains , it has become difficult for customers and end users to verify the provenance and environmental footprint of a product. By ensuring records cannot be changed, blockchain makes supply chains more transparent, helping to accurately report sustainability practices. Sustainability starts with responsibility.

Multiple startups are focused on creating “carbon tokens” or blockchain-based tokens, which represent a stake in a sustainability project or digitized carbon credits that organizations can purchase to offset their emissions. A prominent example is Flowcarbon , a startup backed by private equity firm Andreessen Horowitz that is working on a carbon credit crypto token designed to make carbon credits more liquid, easier for consumers to understand, and with transparent prices.

Of course, these companies face some major problems. They are still tied to the DeFi ecosystem and can easily be used for speculation and greenwashing. The backlash against the idea of ​​carbon offsets versus actually reducing carbon emissions is growing, as demonstrated by a UN report released at the recent Cop27 climate conference . Startups that throw “blockchain” and “sustainability” in their pitches also tend to receive more venture capital funding during times of economic growth, but it’s important that these initiatives move the needle in measurable ways.

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Where AI comes in

AI is already a mature technology that is used across industries to automate processes, identify patterns, and outsource decisions. Yes, there are exciting new branches, such as generative AI , which creates original adaptations of text, images or sound you received as training data, but at its core, machine learning (ML) and AI models are already being used in all verticals in ways focused on sustainability. Some highlights from recent years:

• Self-driving cars reduce traffic congestion and air pollution

• Power grids are optimized with AI and less energy is lost

• AI helps organizations predict demand and this helps limit waste

• AI improves weather forecasts , helping communities cope with erratic weather conditions induced by climate change and prevent damage

• Computer vision-enabled drones tracking wildfires and ecosystem degradation in large natural areas

• Help organizations identify sources of energy and resource waste in their operations

  Web3, AI converge in the name of sustainability

  As we continue to think about responsible AI development, we must ensure clean data sources to train our models. AI will not reach its full potential by training on data sets riddled with AI-generated, falsified, or manipulated input. The immutability and transparency of Blockchain helps address this issue and provides an unprecedented level of “data integrity” and confirmation of data provenance. Especially on sensitive data like that generated on sustainability, we don't want black box models or centralized data pools training our core AI systems.

  In essence, both Web3 and AI further enable data and its capacity for positive change. As both develop, we will see more touchpoints between them, such as transferring AI-processed data to chains, applying AI to existing chain data, or performing AI directly on blockchain network nodes at the edge. These basic combinations of technology will increasingly see applications in sustainability.