{"id":961,"date":"2019-09-12T12:07:01","date_gmt":"2019-09-12T12:07:01","guid":{"rendered":"http:\/\/horizon.peachpuff-wolverine-566518.hostingersite.com\/?p=961"},"modified":"2019-09-12T12:07:01","modified_gmt":"2019-09-12T12:07:01","slug":"ai-can-help-us-fight-climate-change-but-it-has-an-energy-problem-too","status":"publish","type":"post","link":"https:\/\/scienceblog.com\/horizon\/961\/ai-can-help-us-fight-climate-change-but-it-has-an-energy-problem-too\/","title":{"rendered":"AI can help us fight climate change. But it has an energy problem, too"},"content":{"rendered":"

by Annette Ekin<\/p>\n

Artificial intelligence (AI) technology can help us fight climate change \u2013 but it also comes at a cost to the planet. To truly benefit from the technology\u2019s climate solutions, we also need a better understanding of AI\u2019s growing carbon footprint<\/strong>, say researchers.\u00a0\u00a0<\/strong><\/h3>\n
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AI is changing the way we work, live and solve challenges. It can improve healthcare, protect\u00a0elephants<\/a> from poachers, and work out how broadband should be distributed.<\/p>\n

But it could be most valuable as a range of applications helping humanity fight our biggest threat – climate change. AI can strengthen\u00a0climate predictions<\/a>, enable smarter decision-making for decarbonising industries from building to transport, and work out how to allocate renewable energy.<\/p>\n

AI\u2019s relevance as a climate change fighting tool comes at a time when there are increasing ethical concerns linked largely to a data-hungry form of the technology called machine learning, where computer systems analyse patterns in existing data to make predictions and decisions. Machine learning applications have raised concerns about creeping public surveillance,\u00a0intentional misuse<\/a>, privacy, transparency and data bias that can lead to discrimination and inequality.<\/p>\n

It is part of a wider ethics debate in the EU about how to use AI for the benefit of human beings, the challenges that the technology poses and how best to tackle them.<\/p>\n

\u2018We have to realise that AI is, in fact, a piece of software that we people design,\u2019 said Virginia Dignum, a professor in social and ethical artificial intelligence at Ume\u00e5 University in Sweden. We must be responsible for how we use AI, she says. \u2018(It is) not some kind of magic that comes from outer space and happens to us. No. We make AI happen.\u2019<\/p>\n

Perhaps surprisingly, one issue that is only beginning to be discussed is the environmental footprint of AI.<\/p>\n

Netflix<\/strong><\/p>\n

The algorithms that tells us, for example, what to watch on Netflix tonight have an environmental impact, according to Prof. Dignum. \u2018AI uses a lot of energy,\u2019 said the computer scientist, who is part of a\u00a052-person expert group<\/a>\u00a0advising the European Commission on trustworthy and \u2018human-centric\u2019 AI.<\/p>\n

The storage, and particularly the processing, of data to train algorithms \u2013 the \u2018recipes\u2019 computers use to make calculations \u2013 in data centres or in the cloud across different centres with rows of machines doing computations consume energy, she says.<\/p>\n

For one algorithm to train itself on whether an image shows a cat, for instance, it needs to process millions of cat images. The ecosystem for information and communications technology, of which data centres are a part, are comparable to\u00a0aviation in terms of fuel emissions.\u00a0<\/a><\/p>\n

\u2018It\u2019s a use of energy that we don\u2019t really think about,\u2019 said Prof. Dignum. \u2018We have data farms, especially in the northern countries of Europe and in Canada, which are huge. Some of those things use as much energy as a small city.\u2019<\/p>\n

She draws on a University of Massachusetts, US,\u00a0study<\/a>\u00a0which found that\u00a0training a large AI model to handle human language can lead to emissions of nearly 300,000 kilograms of carbon dioxide equivalent<\/a>, about five times the emissions of the average car in the US, including its manufacture.<\/p>\n

Swedish researcher Anders Andrae has forecast that data centres could account for\u00a010% of total electricity use by 2025<\/a>.<\/p>\n

Although AI has been around for about half a century, the question of environmental impact \u2013 and other ethical issues – is only arising now because the techniques developed over decades can now be used in combination with\u00a0an explosion in data and strong computational power, Prof. Dignum explains. \u2018It\u2019s time to start thinking about doing AI in a more environmentally friendly way,\u2019 she said.<\/p>\n

AI might be part of the problem, but it also has the potential to help us find solutions for climate change.<\/p>\n

Professor Felix Creutzig, who leads a working group called Land Use, Infrastructures and Transport at Mercator Research Institute on Global Commons and Climate Change in Berlin, Germany, investigates ways to tackle climate change using data science. He is part of a group of international researchers advocating for more\u00a0collaborative climate change solutions using machine learning<\/a>.<\/p>\n

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It\u2019s time to start thinking about doing AI in a more environmentally friendly way.<\/p>\n

Prof. Virginia Dignum, Ume\u00e5 University, Sweden<\/p>\n<\/blockquote>\n<\/div>\n

Vast opportunities<\/strong><\/p>\n

Prof. Creutzig sees\u00a0vast AI opportunities<\/a>\u00a0to ramp up the applications for targeted climate change solutions at the street scale, or even building level, that can be applied in cities. Urban spaces are of particular concern, as they\u2019ll be home to more than\u00a0two-thirds of the world\u2019s population<\/a>\u00a0by 2050 and are incredibly resource-intensive.<\/p>\n

\u2018It\u2019s cool to work with technologies and to invest in low-carbon technologies, but to achieve anything close to the\u00a02 degree or 1.5 degree target<\/a>\u00a0(for limiting global warming) we must reduce energy demands drastically and can achieve that by improved spatial configurations,\u2019 he said.<\/p>\n

Improving spatial use can help address issues such as urban heat islands, a phenomenon where urban environs built of steel and cement store heat and warm cities. \u2018That\u2019s a key problem of our future,\u2019 he said.<\/p>\n

Greening cities or using wind channel architecture to create ventilation are ways to help cities deal with extreme heat that can be guided by AI.<\/p>\n

Prof. Creutzig is employing a method called stacked architecture, which uses machine learning with traditional mechanical modelling to, for instance, obtain insights into how buildings behave when it comes to temperature or energy demand, to find the best design for low energy use and high quality of life. These can then inform urban planning and policymakers.<\/p>\n

Precisely because AI has so much potential, he also thinks its use should be combined with regulation, such as on not storing unnecessary data or constraining its use, so that it is targeted, efficient and doesn\u2019t cause a new problem. However, he says that there\u2019s currently not enough research into machine learning\u2019s environmental impact. \u2018There\u2019s a lot to explore,\u2019 he said.<\/p>\n

\u2018Basically it (AI) is a fuel of application \u2026 it can lead to a new energy use,\u2019 said Prof. Creutzig. \u2018And this would be the opposite of what we want to have. The main example I’m thinking about is smart mobility and autonomous driving because these are really driven by AI or will be modelled by AI.\u2019<\/p>\n

For Andrea Renda, head of global governance and digital economy expert at the\u00a0Centre for European Policy Studies<\/a>\u00a0in Brussels, Belgium, and also a member of the\u00a0expert group<\/a>\u00a0advising the European Commission, AI needs to be developed and deployed so it can meet society\u2019s needs and protect the environment by saving more energy than it expends.<\/p>\n

\u2018All of these (data-intensive techniques) are extremely dangerous for the environment unless you can use those techniques in a way that, while using a lot more energy, save a lot more energy because they provide for more efficient solutions,\u2019 said Prof. Renda.<\/p>\n

Both Prof. Renda and Prof. Dignum agree that basic research into AI forms that are less data hungry than machine learning,\u00a0such as automated reasoning, should be an EU priority. This would mean less use of personal data and energy consumption.<\/p>\n

Prof. Dignum has been working with \u2018synthetic data\u2019, which is not based on real examples. It could be used to generate, for example, images of broken bones not based on sensitive patient data in order to train an algorithm on what to spot in an X-ray. This data can then be discarded so that it\u2019s not stored.<\/p>\n

Some researchers in the US have also proposed that AI research should include reporting on\u00a0computational costs<\/a>\u00a0of training algorithms\u00a0to enhance transparency.<\/p>\n

To make sure AI is used to help, and not hinder, our society, Prof. Renda says it\u2019s time to merge the two big debates of today. \u2018One is on digital technology and the other one is on sustainable development, and in particular the environment. If we use the former to save the latter, I think we will have made the best possible use of the resources that we have,\u2019 he said. \u2018Otherwise we’re just wasting time.\u2019<\/p>\n

On 25 September, Prof. Dignum will be participating in a session called\u00a0<\/em>Human-centered Artificial Intelligence<\/a>\u00a0at the EU\u2019s Research & Innovation days to help shape the scope of EU research and policy on AI from 2021-2027.<\/em><\/p>\n

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Originally published on Horizon<\/a>.\u00a0<\/em><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

by Annette Ekin Artificial intelligence (AI) technology can help us fight climate change \u2013 but it also comes at a cost to the planet. To truly benefit from the technology\u2019s climate solutions, we also need a better understanding of AI\u2019s growing carbon footprint, say researchers.\u00a0\u00a0 AI is changing the way we work, live and solve … Read more<\/a><\/p>\n","protected":false},"author":298,"featured_media":962,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"generate_page_header":"","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[11,16],"tags":[47,126,79,24],"class_list":["post-961","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-earth-energy-environment","category-technology","tag-artificial-intelligence","tag-climate-change","tag-research","tag-science"],"yoast_head":"\nAI can help us fight climate change. 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