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AI has a dirty secret: its carbon footprint

Opinion

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2 September 2019

Author: Camara Clarke

Image: Data Church by Vito Boeckx

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For technology brands serious about sustainability, it’s time to consider the environmental impact of incessant digital development

We’ve entered the artificial intelligence (AI) boom, with brands and businesses around the world exploring how AI can be used to improve their business, create more intelligent products, and intuitive experiences for consumers.

The unrelenting rate of AI development was revealed in a recent report from World Intellectual Property Organization (WIPO), which found that 50% of AI patents have been published since 2013. Francis Gurry, director general of WIPO, describes it as a ‘quantum leap… with what is happening right now in a very fast-moving field’.

Among these patents, WIPO cites a 175% annual increase in ‘deep learning’ patents – by far the fastest growing segment within the AI market. This is notable because deep learning was created to learn ‘human’ experiences without actual human input, instead using artificial neural networks. The networks repeatedly perform a task, ever so slightly adjusting the process to refine the outcome. Resulting use cases include language recognition software – for example, automated customer service – a growing field in which 85% of all customer service interactions are set to take place without a human by 2020 (source: Forbes).

Being privy to this surge in AI and its resulting processes can, at times, feel like we’re wandering through a sci-fi dream. With vast amounts of data, AI has capacity to massively increase efficiency and streamline our lives, however the energy use and environmental impact of these technologies has largely gone unchecked.

Data Church by Vito Boeckx
'Digital supply chains will soon come into focus as consumers become more expectant of companies to be transparent about their operations'

Natural language processing (NLP), a form of deep learning, analyses human language to create everything from more accurate predictive texting to refining search engine results. Yet, as the technology has developed, its processes have become increasingly energy intensive. A new study from the University of Massachusetts reveals that the process of training and optimising one large NLP model emitted more than 626,000lbs of carbon dioxide – nearly five times the lifetime emissions of the average American car, including those from its manufacturing. Of note, the most energy intensive part of the NLP modelling process is the optimisation – the part where the machine repeats and refines different tasks to alter the overall algorithm.

In environmental terms, such insights are alarming. Tech companies are being tasked to address this impact and take a more considerate approach to innovation. As Emma Strubell, lead researcher on the University of Massachusetts study, notes: ‘I’m not against energy use in the name of advancing science, but I think we could do better in terms of considering the trade-off between required energy and resulting model improvement’. She adds: ‘Large tech companies that use AI throughout their products are likely the largest contributors to this type of energy use.’

As a solution, Strubell highlights that big tech companies should not only source or create more renewable energy, they should provide ‘equitable access’ to their data for academic researchers, allowing them to independently train better algorithms that could then be used in turn to help others optimise their processing, all with less environmental impact.

This more moral mindset is becoming increasingly necessary for tech companies in an era when consumers are more aware of the ways in which the products, services and even their connectivity impacts planetary health. And with consumers expectant of companies to be transparent about their operations, digital supply chains will soon come into focus.

Looking to a future of brand experiences led by AI and intuitive solutions, companies must therefore take the steps to ensure their algorithms are sustainable, not only in their creation, but their refinement. In this way, there is an opportunity to openly demonstrate their positive contribution to optimising and safeguarding our world, while actively reducing the carbon footprint of innovation.

Camara Clarke is The Future Laboratory’s graduate trainee. For more on how tech companies are transforming themselves into climate-positive industry leaders, read our Sustainable Data Centres microtrend.

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