Cleantech needs more AI talent to help save the world

The International Energy Agency recently confirmed dread-worthy news that carbon emissions hit a record high in 2017. Scientists working in the cleantech space around the world are busy trying to find ways to slow — or eliminate — the upward trajectory of carbon emissions and other harmful environmental developments. Some are already turning to artificial intelligence to solve the world’s energy efficiency challenges. However, any real progress in the global race to stem climate change’s environmental impact will require the best people and technology the world has to offer.

Data-driven technologies, like AI, can solve some big problems related to climate change. For instance, there is a huge public-private sector push in Canada underway to combine information and resources to tackle key areas including natural resources, food production, and the environmental impacts of mining, energy production, and power generation. Canada is not alone in looking to AI for answers. In fact, AI has become at least part of the answer to global issues from eliminating workplace biases to feeding communities in recent years.

Survival depends on noble tech talent

Across North America, clean energy providers already benefit from increased access to consumer data and connections to machine learning technology that heats homes, trades electricity, boosts wind power production, and keeps pipelines safe. One of the first things Ontario did when it launched a “green bank” last year was to give away 100,000 smart thermostats in an effort to change consumption habits in favor of sustainability.

However, there is a different kind of energy crisis looming in the region: talent. Successful deployment of AI for cleantech in North America, and globally, relies on a constant stream of people from diverse backgrounds and with specific expertise to flourish.

Personally, I think that developing technology for cleantech is more rewarding — and, frankly, more important — than for consumer or enterprise IT purposes because it directly involves world-saving work. The cleantech industry needs a noble crop of people to develop algorithm-driven systems that pull data from diverse, trusted sources and ensure the integrity of that information as it’s applied to industry-specific work. The main difficulty resides in understanding how to attract and retain talent that could find potentially higher paying or more luxurious work elsewhere in the technology community.

Achieving a diverse, AI-savvy talent pipeline within industries — from mining to energy to agriculture — will advance efforts to minimize global footprints and maximize local benefits. The world needs our best and brightest people working on scalable solutions for energy efficiency, food distribution, and natural resource conservation.

The AI-driven future of global sustainability

Applying AI systems to cleantech pursuits introduces efficiencies that help the industry produce more by using fewer resources. Agricultural organizations can tap AI systems to grow and process more food using less energy, water, and fertilizer. Mining companies can extract more minerals and metals from the ground more securely while using less fuel and producing less waste. But AI’s impact gets even more compelling when you look at the energy sector.

AI helps utilities and companies monitor the integrity of pipelines, speeds up the development of nuclear fusion power, and makes it possible for intelligent infrastructure to interact with power grids. AI is helping alternative energy companies efficiently draw consumer-ready energy out of solar and wind farms. Data analyzed by AI-driven systems also helps providers predict when power plant equipment needs maintenance so they can repair issues before system failures occur.

Global companies like General Electric are using AI to boost different forms of energy production and pull from tech-driven data reports to anticipate performance and maintenance needs around the world. Here in North America, companies like Canvass Analytics and Rockwell Automation are applying AI to connect industrial plant operations to the Internet of Things and improve system efficiencies across cleantech industries. Meanwhile, algorithm-driven technologies, like The MineSense System and Goldspot‘s machine learning platform, are starting to change how mining, mineral exploration, and natural resources companies secure and adjust operations that affect the environment. Big data-driven smart devices, like the thermostats from Ecobee and Nest, are starting to transform consumers’ relationship with energy, especially as Canada makes the transition to a low-carbon economy.

Homegrown AI workers can change the world

North America — thanks in part to Canada’s connected AI research community and the U.S.’ geographically expanding technology industry — offers the quality of life, infrastructure, and talent necessary to fuel industries tapping emerging technologies like AI to make a global impact. I am hopeful that the same will be true for cleantech, an industry that needs a diverse, eager, and noble community to solve complex problems with global relevance.

Specifically, we need to grow, and sustain, a community of dedicated AI developers who create and innovate upon AI-driven systems that transform critical cleantech industries, energy consumption habits, and people’s lives around the world. Our future might depend on it.

Jane Kearns is a senior advisor for cleantech at Toronto-based MaRS Discovery District. Kearns is also the cofounder of the CanadaCleantech Alliance and a board director at the Water Technology Acceleration Project (WaterTAP).