You can’t manage what you can’t measure – climate and data innovation needs to be powered in tandem: Google, Deloitte

Public-private partnerships to enable continued cross-border data sharing are critical to unlocking the potential to harness existing data for climate action, according to a report.

Google Breakfast Briefing UCFS 2023
Ben King, managing director, Google Singapore, APAC (middle), in conversation with Yvonne Zhang, sustainability and climate change leader, risk advisory, Deloitte (left) and Jessica Cheam, founder and managing director, Eco-Business (right), about the latest findings from a commissioned Deloitte report at Unlocking capital for sustainability 2023. Image: Eco-Business

It is estimated that at least 2.5 quintillion bytes (or 2.5 billion gigabytes) of data is produced each day. This figure is only set to increase as technological innovations allow governments, organisations and individuals new ways to gather data.

Yet, only 12 per cent of city data is being used for policymaking, reflecting the long way to go for governments to leverage the potential of this exponentially growing data for climate action.

“We have the technology, we have the data and we have the information to solve climate change. It’s just putting it to use and figuring out the ‘how,’” said Ben King, managing director, Google Singapore, APAC, on a panel discussion about some of the findings from a commissioned Deloitte report, which will be launched in full at the COP28 climate summit in November.

Yvonne Zhang, sustainability and climate director, Deloitte Southeast Asia, emphasised the importance of equitable access to data and innovative technologies, noting that they are key for enabling climate action.

Both King and Zhang were speaking at this year’s Unlocking capital for sustainability event, an annual sustainable finance forum organised by Eco-Business. 

“Data is plentiful. The question is how do we let that trickle down to a level where resources, information and change can happen from the ground up,” said Zhang, emphasising the need for data governance policies to be interoperable, strategic partnerships, and for insights, as well as existing and upcoming technologies, to be meaningfully used.

Cross-border data sharing challenges

Since 2017, Google has been working on Data Commons, an open-source platform that aims to improve the accessibility and utility of the world’s publicly available data. There is, however, currently more data on the platform for the United States, India and OECD countries than for Africa, South America and parts of Asia.

“Data localisation and privacy concerns from the user standpoint are two of the biggest barriers related to cross-border data sharing in APAC,” said King, who called on Asian governments to adopt international data sharing standards and invest more in data security technologies.

While there is a voluntary framework on digital data governance for Asean, member countries have adopted different cross-border data regimes.

For example, the Philippines and Singapore allow all data, including personal data, to flow freely across borders with minimal regulatory requirements, while Indonesia and Vietnam adopt a stricter regulatory approach that completely or partially prohibits data from being shared outside their borders, citing public and national security concerns. Malaysia and Thailand allow for cross-border data flows under certain conditions.

While harmonising data policies and making them interoperable across different jurisdictions will allow for data to flow more freely, this will require increased collaboration between policymakers and industry, noted Zhang, who also works with standards bodies like the International Organisation for Standardisation (ISO), International Sustainability Standards Board (ISSB) and Global Reporting Initiative (GRI).

Zhang also pointed out that some sustainability-related data, for instance on nature and human behaviour, are “analogue”, meaning that these data are gathered through physical observations, which need a different method to produce and interpret.

“Some of the models of cooperation and dialogue require a longer time because analogue processes go through a more organic pace of change, not the kind of explosive moves we see in the digital space,” said Zhang, noting that in contrast to analogue data, digital data is an enabler of rapid scalability.

Despite the regulatory fragmentation in Asia’s markets, businesses across a range of sectors have continued to innovate by adopting low-cost technological solutions.

For instance, Aruna, an Indonesian start-up, uses location data from Google Earth Engine and Google Cloud to help fishermen verify that they are fishing within permitted areas. The location data also allows the company to report on the sustainability of their catches more accurately to regulators and global certification bodies.

Decarbonising digital technology solutions 

While digital technologies have enormous potential to be drivers of decarbonisation, it is important to ensure that on a net basis, they do not produce more emissions.

According to the International Energy Agency (IEA), data centres and data transmission networks – which are largely responsible for storing, managing and distributing vast amounts of data online – accounted for around 330 million tonnes (Mt) of CO2 equivalent in 2020 or 0.6 per cent of greenhouse gas emissions globally.

However, since data centre providers continue to prioritise energy efficiency and are transitioning to clean energy, emissions have grown modestly in the last decade despite increased demand for processing power. Google, for example, says its data centres are more than 1.5 times as energy efficient as a typical enterprise data centre. Major tech companies including Amazon, Google and Microsoft have also committed to net zero goals and are investing heavily in renewable energy projects.

Towards the end of the panel, King responded to concerns surrounding how demand for artificial intelligence-powered (AI)-powered products may lead to increased energy consumption.

“The reality is that as AI and machine learning really starts to take hold, the computing power required is significant and there are concerns raised as a result of that,” said King.

“Forecasting this is very challenging. But what we’re seeing is that as these computing loads increase, the power to drive it has been less than our original forecast. We’re also excited to see how solutions that might come on the back of AI can drive down the power consumption required.”

Like this content? Join our growing community.

Your support helps to strengthen independent journalism, which is critically needed to guide business and policy development for positive impact. Unlock unlimited access to our content and members-only perks.

Most popular

Featured Events

Publish your event
leaf background pattern

Transforming Innovation for Sustainability Join the Ecosystem →