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Can HAL help us save the planet?

Or … how can AI help us to meet Science-Based Targets?

As a teenager, I remember being captivated by the iconic movie ‘2001: A Space Odyssey’ directed by Stanley Kubrick. The HAL 9000 computer, which controlled things on the Discovery One spacecraft, showed us what could happen when AI takes control away from us. But this is science-fiction. Science fact is more mundane and, apparently less threatening.

AI is already in use across many sectors. Amazon, Netflix and Spotify for example, use AI to make suggestions on what we’d like to buy, watch or listen to. And as you’d expect, there are different views on the impact of AI. Some people believe that AI will create more jobs than it eliminates, but others think the opposite.

Unless you’ve been living in a cave, you’ll know (excuse the bad pun) that climate change is a hot topic. This year, yet more global temperature records have been broken.

According to accepted scientific, peer-reviewed evidence, if the rise in global temperatures goes unchecked, it will cause havoc to our planet.

That’s why the 2016 Paris Agreement on climate change was such an important event. 195 countries pledged to take action to keep the rise in global temperature below 2 degrees.

The way to do this is to manage Greenhouse Gas (GHG) Emissions. And that’s what the Science-Based Targets Initiative ( SBTi ) was set up to facilitate. By August 31st 2018, 469 companies have made a commitment to take action. 126 have had SBTi targets approved as being aligned with climate science.

There are 3 kinds of GHG emission, Scope 1 and 2 are seen as being ‘internal’ to an organisation’s operations whilst Scope 3 are the emissions largely produced by trading partners along the supply or value chain. These typically represent the most significant concentration of emissions. They are also the most difficult to control, because thousands or tens of thousands of organisations are usually involved.

According to statistics from sciencebasedtargets.org, the most common cause of targets being rejected is because Scope 3 emissions were not correctly screened

Understanding the emissions from each organisation is undoubtedly a mammoth challenge but it’s far from insurmountable. Getting the data by a conventional assessment questionnaire is not possible, that’s an obvious limitation which is because it would likely take too long and cost far too much to assess each organisation individually.

But, this should not deter committed organisations from getting to grips with their value chain emissions because, in many instances, suppliers actually want to participate and contribute to innovative climate reduction programmes.

 So what’s to be done?

One approach that is proving highly feasible is to use Artificial Intelligence (AI) to get the data in a cost-effective and timely way.

In business, AI is used to solve problems, analyse data and make smarter decisions. This is especially true where there is a lot of data and many variables to consider. AI is an algorithm that solves a problem. It’s very useful in taking a sample or ‘base’ data and running a set of calculations to look for trends and patterns.

For example, if we input accurate data on organisations of a certain size and activity (e.g. Mining, Retail etc), the model can make predictions about Scope 3 emissions for other organisations with that same profile.

Whilst this may not be 100% correct for every organisation, it will probably be close enough from a statistical perspective. So, it may be tempting to think that AI is the answer to getting the Scope 3 data you need. But that’s not the whole picture. AI is an excellent solution, but it needs accurate, reliable source data, to work its magic. It does have the capacity to transform the way GHG (and other ESG) data is modelled and accelerate both the development and implementation of low-carbon initiatives across the value chain.

This is a ground-breaking way of working and the benefits are significant. Results can be achieved in less time, with greater accuracy and a far lower cost than by using a traditional survey approach. And that must be worth looking at in more detail.

Ecodesk provides a science-based target solution that combines proven environmental survey process with AI to identify and manage the impact of GHG emissions across the value chain. More information is available here.

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