AI can tackle the climate emergency – if developed responsibly

Our planet is altering at a dangerous pace attributable to climate change. And at the identical time, we appear to be entering a period of unprecedented technological transformation. Advances in robotics, artificial intelligence (AI) and internet-connected devices are creating increasingly complex intelligent technological systems.

As pressures on the planet and its climate increase, so does the hope that these novel technologies will give you the chance to assist us detect, adapt and reply to the growing environmental crisis. There are loads of examples of how artificial intelligence could do that.

But for that to occur, the individuals who make and regulate this technology have to rethink some simplistic assumptions about how AI will shape the long run of our planet. It’s time to begin a serious discussion about the right way to put AI to make use of for each people and planet.

One of the good uses of artificial intelligence is in understanding patterns in large amounts of knowledge. It will help us to improve our models of the climate and understand how we’re affecting the planet. Combining AI with local knowledge about agriculture can help farmers produce more food by making higher decisions about what techniques to make use of for a farm’s soil and weather conditions.

Using AI to analyse data from social media and microsensors placed around cities could help us higher understand how people use them, revolutionising urban planning and helping mega-cities prepare for a turbulent climate future. AI could even help design products that will be more easily recycled by more quickly narrowing down competing designs to fulfill sustainability criteria.

With such potential, it’s no wonder major tech firms, governments and other organisations world wide have gotten increasingly all in favour of using AI for sustainability. For example, the Indian government’s thinktank NITI Aayog has partnered with Microsoft to develop AI applications for small-scale farming. And China has launched a seven-year pilot program to develop automated farming technologies similar to unmanned mix harvesters or robotic tractors.

If developed in a responsible way, this sort of AI could help create a prosperous future for all without adding to climate and environmental destruction. But that won’t occur until the important thing players revise their simplistic assumptions about AI.

A key issue is the inaccurate concept that the advantages of advances in data evaluation and automation will trickle down routinely to those that need it essentially the most. The digitalisation of agriculture is more likely to include high investment costs and a necessity for developed infrastructure (similar to rural web access) and education amongst its users.

This won’t be an issue for giant corporations and wealthy landowners, but could leave behind many farmers, particularly small ones in emerging economies. We’ve already seen tensions developing between farmers within the US and huge technology firms who need to use farmers’ data to create more priceless agricultural services and products.

What’s more, complex ecosystems underpinning food production don’t all the time profit from increased efficiency and optimisation of agriculture. In fact, more intensive farming could mean many environments lose their resilience to the stresses and shocks that result from environmental change.

AI bias

Studies of AI in predictive policing, healthcare, facial recognition, and credit rankings have shown the technology can result in serious unintended consequences similar to racial and gender discrimination, attributable to various types of algorithmic bias.

This indicates that current AI technology doesn’t necessarily make the perfect decisions about the right way to reply to a situation. Instead, it could find yourself replicating the identical form of processes that characterised past human decisions, complete with their biases.

The environment is facing a potentially very different set of circumstances to the past attributable to the changing climate. So applying our current predictive models based on historical data would make its forecasts and proposals unfit for a brand new and turbulent ecological context.

Another significant problem for lots of these technologies is that they’re vulnerable to cyber-attacks. Malicious software can disrupt data collection and evaluation or remotely control irrigation or nutrient delivery systems with the aim of destroying crop production. And the event of AI to be used in cyber-attacks could make it harder to detect attacks and keep malicious software out.

The state of our planet and the potential risks and opportunities embedded in AI have until now been discussed individually. This must change. Technology giants, governments and civil society have to work with sustainability scientists to develop strong principles that guide the event of AI towards sustainability for all.

AI must be responsible, not only in order that we understand the way it makes its decisions and does so without discriminating, but additionally in order that it doesn’t make environmental issues worse. No matter how intelligent technology becomes, its impact on people and the planet will all the time be our responsibility.