Six ways AI is helping the environment today

Cat Mules

Could artificial intelligence drive us towards a more liveable future?

We should be careful making calls about the future of technology. In 1943, IBM’s founder is said to have predicted a world market “for maybe five computers” – to be disproven just 30 years later, when computer sales saw IBM the most profitable industrial company in history.

But with climate change the enduring issue of our time, the private sector is under greater pressure to respond. It seems only right to ask, could technology save the day?  Here are six ways AI is being used to make a difference.

The sharing economy

It’s a recent idea that is gaining rapid traction: peer-to-peer sharing of access to goods and services. Often facilitated by online community platforms, the sharing economy lessens environmental impact by empowering individuals to buy and use less.

AI helps these sharing economy giants gain traction by personalising the customer experience and streamlining business.

Iconic examples include Uber, who make it easier to get around without owning a car, and Netflix, who reduce the need to transport or create physical copies of movies. New Zealand’s TradeMe lets consumers push their underused goods by empowering anyone to become a retailer.

Electric cars

A decade ago, electric vehicles were rare commodities, with the only Tesla available being the Roadster at a hefty $109,000, and the Nissan LEAF only newly available in the US.

Today, even though shared vehicles are said to be the most sustainable mobility option, electric vehicles are fast catching up with evolving hybrid and plug-in powering ability. Tesla’s Model 3 is the world’s best-selling battery electric vehicle, and over 4.8 million battery electric cars are in use globally.

Elon Musk, CEO of both Tesla and private space exploration front-runner SpaceX, has been a powerful advocate for the environment from private enterprise. In 2018, he told 60 Minutes, “The whole point of Tesla is to accelerate the advent of electric vehicles and sustainable transport,” he said. “We’re trying to help the environment, we think it’s the most serious problem that humanity faces.”

Musk is also co-founder of OpenAI, a research organisation dedicated to ensuring AI is developed and used safely and effectively to minimise the future risks of robotics. Bernard Marr, of Enterprise Tech, believes that Tesla’s AI will process “thinking” algorithms for its Autopilot software, which currently enables Tesla vehicles to have some autonomous driving capability.

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The first Tesla Model 3 to roll off the production line, in a photo tweeted in 2017 by Tesla CEO Elon Musk. Photo: Twitter /@ElonMusk

Environmental monitoring

Environmental monitoring is being enabled by AI to track adherence to regulations, and to help businesses optimise their resource use.

Satellites and drones are essential to environmental monitoring and anticipating sites more prone to breaches to enable preventive action. Over the vast stretches of Africa, for example, poachers are finding it more difficult to get away with illegal hunting of animals.

The businesses uses of AI are broad and carve out new possibilities – both in terms of environmental protection and profit. In an article titled Energy Strategy for the C-Suite, Harvard Business Review authors explain that, “Monitoring and analyzing energy use can reveal operating issues that affect costs, performance, and quality,” noting possible businesses uses for AI such as alerting managers when actual consumption varies from prediction and using data to adjust prices and ensure profitability.

Renewable energy

Some of the most recognisable and important eco-friendly tech innovations of recent years have been in the clean energy sector. Renewable sources of energy, like solar, wind and hydroelectric power, are much more widespread, not to mention cheaper.

Challenges remain in renewable energy though, such as unpredictability of climate changes and minimal energy storage – areas in which AI is quickly filling the gaps.

Another example of AI-led renewable energy solutions is in storage, which plays a key role in balancing power supply and demand. Storage is predicted to be core to energy technologies of the future – with smart, centralised control centres interconnected with devices to collect a large amount of data. When coupled with AI, grid operators are given flexibility to cleverly adjust supply to match demand.

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Credit: Science in HD. 

Going digital to save the forests

Thanks to smartphones, computers and cloud storage, individuals and businesses are using much less paper.

With our ability to email the various bills, newsletters and other communications, we no longer need rely on printing, postage and physical storage. And now, with OCR and information extraction, we can fully automate previously paper-bound processing.

With more agile technology, enabled and inspired by the digital revolution, we can inspire a digital vision for the world of the future.

How does AI create a paperless world? The Forbes Digital Council writes there are two strategies: “One is to convert existing paper documents to digital. The other is not using paper in the first place.”

It appears some businesses are held up on their digitisation journey, and for that, the authors write, a planned approach will be key. They advise to “fully understand and map the investments and changes” and “define what applications, hardware, data centre changes, security improvements and workflow adjustments will be required”.

Smarter homes

The home is one of our biggest energy users – but AI-driven energy saving devices are helping us to significantly change that. Devices like smartphones, thermostats and motion-activated lighting are making it easier to only use power when we need it, saving on energy as well as money.

And with AI-driven energy saving devices at our fingertips, energy saving is more pervasive, connected with our other gadgets, and now used across both private homes and businesses.

 

So, in the face of environmental concerns, there are tools at our disposal. Evolutions with AI, driving much the potential of these tools, can support us in developing healthier and more sustainable futures – not just for business, but for the environment too.

Cat Mules

Umbrellar's Digital Journalist, coming from a background in tech reporting and research. Cat's inspired by the epic potential of tech and helping kiwi innovators share their success stories.

Data, AI, BI & ML

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Artificial Intelligence and Machine Learning are the terms of computer science. Artificial Intelligence : The word Artificial Intelligence comprises of two words “Artificial” and “Intelligence”. Artificial refers to something which is made by human or non natural thing and Intelligence means ability to understand or think. There is a misconception that Artificial Intelligence is a system, but it is not a system. AI is implemented in the system. There can be so many definition of AI, one definition can be “It is the study of how to train the computers so that computers can do things which at present human can do better.” Therefore it is an intelligence where we want to add all the capabilities to machine that human contain. Machine Learning : Machine Learning is the learning in which machine can learn by its own without being explicitly programmed. It is an application of AI that provide system the ability to automatically learn and improve from experience. Here we can generate a program by integrating input and output of that program. One of the simple definition of the Machine Learning is “Machine Learning is said to learn from experience E w.r.t some class of task T and a performance measure P if learners performance at the task in the class as measured by P improves with experiences.”

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