How can AI help to achieve sustainability?

sustainability kestävä kehitys digitalisaatio digitalization AI

Digitalization and artificial intelligence (AI) are shaping and transforming an increasing range of sectors and companies today. Yet there is no single definition on AI, but it can be described to have capabilities to automatically extract knowledge, recognize patterns from data and have logical reasonings for decision making. Benefits from AI could be derived by the possibility of analyzing large-scale interconnected databases to develop joint actions aimed at preserving the three P’s: people, planet, and profit.

Systems which leverage machines to process and analyze substantial amounts of data have changed how we work and act, are used by sectors from banking to energy and real estate & construction, for example. AI is expected to affect productivity, sustainability reporting, and several other areas, both in the short and long term.

AI may act as an enabler for the sustainability targets of companies and cities. For example, AI can support low-carbon systems by supporting the creation of circular economies and smart cities that efficiently use their resources. This could mean that AI can help to integrate variable renewables by enabling smart grids that partially match electrical demand to times when the solar and/or wind power is available. Furthermore, AI is expected to support low-carbon energy systems with high integration of renewable energy and energy efficiency, which are all needed to address climate change. Another use case is in 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.

AI can support the understanding of climate change and the modeling of its possible impacts. AI can help us predict what will happen and how we can prepare ourselves or how we can tackle or even prevent harmful events. AI can strengthen and enable smarter decision making to decarbonize cities and industries.

On the other hand, there are increasing ethical concerns linked largely to a data-hungry form of the technology of machine learning, where computer systems analyze patterns in existing data to make predictions and decisions. Machine learning applications have raised concerns about creeping public surveillance, intentional misuse, privacy, transparency, and data bias that can lead to discrimination and inequality. We need to stay alert on the existing biases in the data used to train AI algorithms that may result in exacerbation of those biases. So, people still needed to validate the information and results that are produced by AI.

Another downside is that use of AI creates an increasingly large carbon footprint as the storage and processing of data needed for example to fully train a large algorithm can consume massive amounts of energy. We cannot forget the need for rare earth metals on computers and other devices. We need to work on making digitalization and AI more sustainable, energy and material efficient yet considering also social aspects in chains of custody.

Despite many challenges, we still have massive opportunity in our hands. It’s time to merge the two big debates of today: One is on digitalization and AI technology and the other one is on sustainable development. If we use digitalization to make sustainability happen in a larger scale and new level. I think we will have made the best possible use of the resources that we have.

Mia Andelin
Chief Sustainability Officer
Sweco Finland

Mia joins the AI in AEC Conference Panel discussion AI for sustainability: Can AI help achieve environmental sustainability? on the 23rd March 2023