Artificial Intelligence for Sustainability Innovation & Technology

AI:
The Good, the Bad, the Sketchy and the Lifesaving

You take the good, you take the bad, you take them both and there you have AI. The game-changing technology and its many applications and implications were examined throughout the week at SB’24 San Diego.

By Tom Idle and Hannah Zimmerman | Published 1 week ago | About a 13 minute read

Image: Amazon

With its already vast applications for increasing sustainability, artificial intelligence was naturally a hot topic throughout the week at SB’24 San Diego. But discussions also addressed its darker side — and, along with diving into its role in creating healthier products and helping save one of our most vital natural resources, a variety of experts explored how to rein in the technology’s environmental impacts and assuage the fears of reticent consumers.

A faster, more efficient path to safer chemicals

Image credit: cottonbro studio

As regulatory pressures mount around eliminating PFAS and other harmful substances, and consumers increasingly prioritize sustainability, companies are having to pay closer attention to the chemicals they use, and balance meeting regulatory requirements with maintaining product quality and performance. However, reformulating products to meet these demands presents significant challenges — particularly, when it comes to identifying at-risk ingredients and finding suitable replacements.

Identifying which ingredients pose risks to human health and the environment can be a complex task, especially given the vast number of chemicals used in industry. Manufacturers also face a race against time to stay ahead of evolving regulations, as reformulating products typically takes one to three years. Adding to the complexity is the fact that a replacement can often be as risky as the original and will be regulated in the future– forcing manufacturers to repeat the process.

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In response to these challenges, NobleAI — which demonstrated its product offering in the Innovation Expo at SB’24 San Diego — offers a risk-assessment and ingredient-replacement platform that helps companies quickly and efficiently navigate the complexities of product reformulation. The service is designed to identify and prioritize risks, find suitable ingredient replacements, and optimize formulations to reduce the time to market while ensuring compliance with regulatory demands.

NobleAI’s customizable risk-assessment tool leverages pre-trained models to evaluate factors including acute toxicity or carcinogenic potential, and uses curated toxicological and environmental data from sources including the US EPA and the National Cancer Institute for accurate risk assessments. This approach allows manufacturers to make science-based predictions about potential risks and avoid “regrettable substitutions” — in which a replacement ingredient later proves to be equally harmful.

The process begins when manufacturers plug product names, chemical recipes and CAS numbers into NobleAI’s risk-assessment tool — which breaks down formulations into graphs and charts that classify ingredients by their risk levels. The system allows users to click on individual ingredients to explore suitable alternatives, offering a detailed hazard map for the entire product portfolio.

Once risks are identified, NobleAI’s ingredient-replacement service steps in to find lower-risk substitutes. The AI-driven system optimizes for specific properties, ensuring that new formulations maintain the desired product performance while reducing health and environmental risks. Users are provided with a formulation comparison highlighting changes from the old to the new product, making the process transparent and efficient.

With AI’s help, manufacturers can now proactively predict future regulatory changes, accelerate their time to market and turn sustainability into a competitive advantage. By optimizing products for performance and environmental safety, manufacturers can meet their sustainability goals while maintaining the success of their existing product lines. This proactive approach positions sustainability as a priority, enabling companies to stay ahead in a rapidly changing market.

Could AI’s environmental drawbacks outweigh its benefits?

Image credit: OECD

The benefits of artificial intelligence (AI) for business are well documented: It can automate repetitive tasks such as data entry, customer service and inventory management — freeing up employees to focus on higher-value work. It can process vast amounts of data in real time — enabling companies to make more informed decisions, optimize supply chains or predict market trends. It can be used to personalize customer experiences, analyzing behavior and preferences to serve up tailored recommendations.

It can drive innovation, too — helping businesses develop new products, optimize existing processes and enter new markets.

What is less known, talked about or quantified is AI’s impact on the planet. As John Frey, Chief Technologist with Hewlett Packard Enterprise (HPE), pointed out during a Tuesday afternoon panel: “Sustainability professionals have little experience with enterprise technology,” and that needs to change if the negative impacts of tech are to be addressed.

Frey gave a potted history of AI — a technology that has been around for more than 60 years and is today found in everything from detecting credit card fraud to helping clinicians make more robust diagnoses. Generative AI, the most used technology, is where large-language models are used to serve up graphic or text-based information. But all this information comes with a cost, both in terms of the energy used to generate it and the water used in the process of cooling the data centers doing all the work.

Frey’s slideshow made for alarming reading. According to the latest Gartner Hype Cycle, by 2026, 75 percent of businesses will use generative AI to create synthetic data; in 2023, that figure was less than 5 percent. AI use is set to jump to 7.3 percent of global data center use next year — up from 2.3 percent this year. Worryingly, the required power to train AI models is doubling every 3-4 months. And the net new peak load for AI is expected to be 2,000MW by 2025 — with each new query typed into engines such as ChatGPT using 0.5Wh of power.

Then, there’s the water impact. Water is used in cooling, power generation and the chip-fabrication stage. Each question posed to a generative AI machine uses 16oz of water, and the whole process is driving double-digit growth in water use for model developers and hosts.

Companies including HPE have been working hard to help brands tackle these environmental impacts head on for many years — encouraging the adoption of a holistic approach that examines not just data and software efficiency but also equipment, energy and resource efficiency.

“Your company stores loads of data,” Frey said. “Only a third of it is ever used and most of it is not valuable after about a week. One option is to put constraints on the amount of power and equipment needed for your AI needs. Be the change.”

Kyle Ward, Interim Director for Decarbonization and Energy Transition at Anthesis Group, agreed and offered an alternative framework — known as the 4M framework — for brands looking to address their AI impacts.

“Use AI only when it is needed and select an efficient AI model architecture and process,” he said. “Also, be sure to incorporate sustainability standards into the development of digital services and products.”

Both speakers admitted that AI is an evolving topic, and not one that is easy to address. Frey urged brands to keep minimizing impact, even after those impacts have been reduced as much as possible. “Efficiency is the first fuel,” he said, pointing to emerging options such as reusing or selling the heat generated by data centers.

For all its good, AI has an emissions problem that — without action — could spiral out of control. The key takeaway from this session: It’s time to take it seriously.

Check out more highlights from throughout the week at SB’24 San Diego!

Clear communication, transparency can help alleviate consumer distrust of AI

Image credit: Amazon

Consumer hesitation and distrust toward AI and other emerging technologies are significant challenges in today’s tech-driven world. The root of these concerns often lies in the complex, confusing language used to describe innovations and a lack of transparency around their ethical implications.

A Wednesday afternoon panel discussed how brands can overcome these barriers by rethinking how they communicate about the technology with the public — using more accessible and human-centered language while addressing concerns about privacy, ethics and societal impacts.

Chris Konya — Co-Chief Strategy Officer at strategy and design consultancy SYLVAIN — offered insight into the power of language in shaping perceptions, using Amazon’s Alexa as an example. The name “Alexa” was chosen for its approachable and unique sound. However, introducing the device as a household name also led to the near extinction of "Alexa" as a baby name. And the now-common theme of AI assistants with female names such as Alexa, Siri and Cortana raises concerns about perpetuating gender biases in technology.

This highlights how language can empower or alienate consumers and make or break technology.

“Behind every word, there is a small bit of narrative — a small idea in our brains that comes and flows through society,” Konya said. “Those ideas shape the way that we think, the beliefs we have, and shape the things we do.”

Complex technical terms such as "Generative Pre-trained Transformer" (GPT) risk alienating everyday users — creating a sense of exclusion and fostering mistrust. Referencing the Sapir-Whorf hypothesis, language shapes thought; and without clear, inclusive language, people may struggle to fully understand or embrace AI. This leads to fear — as the technology feels unrelatable, intimidating and outside their control.

To address this, companies must simplify their language and make AI more accessible. Misha Kouzeh, founder of social impact consulting firm Tech Makes History, noted that 75 percent of consumers globally are concerned about the risks of AI.

“Sustainability and AI are both complex topics,” she said. “We need to think about how we distill these topics and talk to our consumers about what AI can do to drive humanity forward.”

Ethical concerns, particularly around privacy and data usage, contribute to the distrust. To counteract this, communication that is transparent and straightforward — as well as avoiding jargon and buzzwords — is crucial. For instance, IBM’s rebranding of AI as "augmented intelligence" helped soften the perception of AI as something overwhelming, making it feel more collaborative and less threatening.

This approach is critical in consumer-facing fields, such as self-driving vehicles or AI-driven financial tools. By emphasizing how these technologies augment human abilities rather than replace them, companies can help users feel more in control. Transparency about data usage and ethical standards is also key to fostering trust. Apple, for example, has built consumer confidence by prioritizing privacy in its AI-driven products.

Andrew McKechnie, Head of Marketing at carbon-utilization innovator Air Company, offered another perspective on this challenge. By using the power of design and experiences, as well as positioning its innovations within a broader narrative of sustainability, Air Company engages consumers and potential customers who might otherwise be hesitant to embrace climate tech.

“What we try to do is communicate that the technology exists in different life stages to our consumers and our b2b and enterprise customers,” he explained “We want them to understand that there is tech available today that can be a potential path to decarbonization.”

Ultimately, alleviating consumer hesitation and distrust of AI and other emerging technologies requires a shift in how companies communicate. By focusing on human-centered language, transparency and ethical clarity, brands can build trust and empower consumers to engage with the benefits of these innovations. Storytelling, rather than technical jargon, should be at the heart of this communication strategy — bridging the gap between complex technology and everyday user experience. Through thoughtful, inclusive communication, tech companies can drive greater acceptance and trust in the technologies shaping the future.

AI, the Colorado River and a water-positive movement

The Colorado River flows through the Grand Canyon | Image credit: David Ilécio

Global water scarcity is no longer just an environmental issue — it’s a pressing social problem and a business continuity challenge. How do companies with ambitious growth strategies secure the water they need to continue growing in a world where paying more for water will not work? At a certain point, having all the money in the world won’t matter.

This was the message given loud and clear by FIDO Tech founder and CEO Victoria Edwards during a Wednesday afternoon session about how her company is working to safeguard one of our most precious resources.

The numbers backing up her message were alarming, to say the least. By 2030, the World Bank projects water demand will outstrip supply by 40 percent. Since 2010, there has been a 500 percent increase in conflict because of restricted access to water.

Exacerbating the problem is leakage. Up to 60 percent of all water is lost through leaky pipes. In Chile, 70 percent of water is being lost; and of the remaining 30 percent available for communities to use, 65 percent is being used to mine lithium.

Edwards and her team have come up with a solution: an AI-assisted leak-detection technology that ‘listens’ to leaks and can pinpoint exactly where utilities need to dig to access and repair the leaky pipe.

“Leaks make a distinctive noise in the pipes, like an F Sharp. But they never show aboveground,” she said. “AI can tell where there’s a leak, how big it is and whether it makes commercial sense to dig and repair it.

“Yes, AI — particularly, generative AI — has an environmental impact; but it is part of the solution, too.”

Recognizing that most water utilities are under-resourced, and often faced with rigid operational practices and a workforce resistant to change, Edwards needed to find an alternative model to fund the much-needed leakage detection and repair. And as she explained, she got lucky: She found Microsoft, a company which had pledged to be water positive by 2020 and needed a transparent, auditable way of making a difference.

The two organizations decided to kickstart their partnership in London, working with Thames Water and creating a “catalytic community” actively looking for leaks across the enormous water network.

“We helped Thames save 4,730,348,247 gallons of water — fully audited by blockchain technology. Fully transparent,” Edwards stated.

Now, the team has taken its approach to the Colorado River basin — which supplies seven US states, supports 40 million people and a $1.4tn economy, and is one of the world’s most over-allocated rivers.

“After London, we knew we wanted to go further, bigger and faster — to expand and take on a big problem: the Colorado river basin. And we invited others to join us, including tech, other corporations — including Microsoft, PepsiCo & Meta — and utilities, to build something that has a lasting impact.”

That ‘something’ — known as Water United — goes beyond using AI to detect leaks. It is being used to help inform decision making by city planners, utilities and local communities. By understanding the impact of river water extraction, partners can decide on whether to build a new data center, for example.

“It’s about using the theory of connections and giving that to the local community to help them plan a water-resilient future,” Edwards explained. “All parties get what they need from the relationship. Businesses get continuity, tech is funded for the long term, utilities get a more resilient network.”

In closing, Edwards highlighted that in the one hour she had been talking, 1,875,000,000 cubic meters of water had been lost unnecessarily: “It’s unconscionable.”

Tom Idle

Content creator extraordinaire.

Tom is founder of storytelling strategy firm Narrative Matters — which helps organizations develop content that truly engages audiences around issues of global social, environmental and economic importance. He also provides strategic editorial insight and support to help organisations – from large corporates, to NGOs – build content strategies that focus on editorial that is accessible, shareable, intelligent and conversation-driving.

Hannah Zimmerman

Impact Manager, Purpose + Sustainability

Formerly working in the advertising world in Kansas City, Hannah Zimmerman has now married her past experience with her passion for sustainability. When she isn't chasing her four-year-old daughter or helping companies along on their sustainability journey through consulting, reporting, communications and certifications, she is working on her master's in Sustainability through Harvard.

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