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Blog 11: The role of AI in Climate change


Most of the global community accepts the validity of the climate change science. Current predictions suggest an average increase in temperature of between 2 and 5 degrees Celsius due to human activity. This is expected to cause significant disturbances to ocean currents, ocean acidity, sea level and weather extremes (floods/ drought/ storms/ fires). The impact of this rapid change on natural patterns that have been established for thousands of years is unknown. It is reasonable to envisage disastrous compounding effects. For example, severe bushfires destroy forest ecosystems and acid oceans destroy coral reefs.

I am constantly reminded that prediction the future over a timeframe as short as 80 years is difficult. It is likely that outcomes predicted from current data and understandings will be significantly affected by emergent or currently unknown factors.

In this blog we explore how artificial intelligence, or more accurately advanced learning algorithms might play an important role in climate change.


To explore ways in which AI, or Advanced Learning Algorithms, might impact climate change.


Artificial intelligence is machine-based learning. Fundamental to learning is the study of data, seeking to find patterns or correlations that can be described by theories. Theories allow us to predict cause and effect. Machine based learning has an advantage over human learning from superior capability to quickly process vast amounts of data. Human based learning currently has the advantage of imagination. It is yet to be proven that machine learning will become capable of imagination.

Fundamentally, all intelligence is based upon algorithms. It seems likely that machine learning will always differ from human learning. Constraints on both are different. Like cats and dogs are different.

1. AI and Energy: What role can AI play in helping the transition to more efficient renewable energy in the world? Already AI is being used to improve the efficiency of energy use in home and across grids. PWC estimated it will provide a positive contribution of 4% to carbon emissions by 2030.

I think this is a gross under estimation of the likely impact. The holy grail of clean energy is fusion. This is how solar energy is generated. Already projects have proven the concept of fusion power generation. The critical enabler for commercial scale fusion power generation is the ability to control the unstable reaction. The critical issue is adjusting the magnetic field to sustain the reaction and experts are turning to AI as the solution. If it works, some are predicting commercial scale fusion power as soon as 2040. This would be an emissions game changer.

2. AI and Transport: The future of AI in transportation is autonomous vehicles, efficient traffic management systems, and the elimination of outdated, inefficient static hardware systems. Autonomous vehicles will help reduce traffic, increase safety, and make vehicular transportation more accessible for all. Uber is just the tip of the iceberg, once we have efficient low altitude options picking up cargo and flying it to its destination, constraints imposed by roads disappear. Private vehicles are estimated to be productively used 16% of the time. If ride share flying vehicles replace road transport, a commute could be cut from 40 minutes to 10 minutes and move more people in one trip. American airlines are already planning this to be a service for getting passengers to and from their homes. The complexity of flying vehicle traffic management is greatly reduced if controlled by a central traffic control system with autonomous control of all flying vehicles. The impact of this change on city transport and emissions could be large.

3. AI and Satellite imagery: A five fold increase in the number of satellites orbiting earth combined with advances in AI is going to provide a step change in understanding the global ecosystem and the activities and events occurring in real time. The precision of GPS tracking will be measured in centimetres rather than metres. The speed of communication will be faster; AI will be essential to making sense of the petabytes of data. This will allow more automation of transport, greater understanding of environmental impacts, greater policing of compliance to global laws and greater potential for military space applications. Improved accuracy of long-range weather forecasting will enable better preparation for severe weather cycles and better crop performance.

4. AI and Communications: Facebook et al already use algorithms to better match information to different customer profiles. Everything from deciding Amazon best seller catalogue to pushing biased media to suit a particular person’s personal profile uses algorithms. The concept of fake news has extended to realistic fake video footage. Online help services driven by AI are commonplace. How far can this go? It is likely that AI will be capable of accentuating belief biases in people by modifying content to suit the purpose of the algorithms. How will we know what is the purpose of any given algorithm? AI can speed up information flow, screen out unwanted information and even augment reality. I think the use of AI capable of creating new algorithms in online communication systems has dangerous long-term implications.

5. AI and genetic engineering: AI is being used in genetic engineering to speed up understanding of genomic sequences. It is expected AI will be able to guide gene editing soon to produce desirable genetic characteristics. The implications of this in creating everything from climate resistant coral to designer people may have profound implications to climate change sensitivity of organisms.

6. AI and Government: The question today for many is whether democracy can survive AI. The reality is that technologies like AI cannot be put back in the box. The days of communications being controlled by central organisations is over. AI can help streamline and even eliminate many inefficient government processes. It may be our greatest hope in overcoming misrepresentation of data to suit country based political purposes. AI may be the best way to provide unbiased global assessment on climate. It may provide the tools to support the impartial global governance desperately needed with climate change.

7. AI and emergent variables: The development of AI itself represents one of the greatest divergent factors of this generation. The convergence of incredible analytical capability with mammoth amounts of data must lead to new and accelerated rates of learning. Humanity will almost certainly defer to AI to answer many questions. Many, like chess champion Kasparov, believe that augmentation of machine intelligence and human intelligence offers the greatest potential for advancement. Machines almost certainly will not develop so called emotional intelligence in the same way as people do. Relationships, influence, and creative thinking are important characteristics that humans are wired for. AI can be designed with the ability to create new algorithms, and this may create a completely new way of thinking, perhaps devoid of emotional overlays. Intelligence without emotional and human bias might be an interesting dynamic in global affairs. Imagine if there was an advanced intelligence decision making entity that always sought best solutions for everyone without bias. Climate change absolutely needs this. The question is can humanity achieve global governance in an orderly fashion on its own?


AI, or Advanced Learning Algorithms (ALA’s) without doubt have an important role to play in climate change. It is likely to evolve into one of the most important advances in learning, it has the potential to transform our world. Human intelligence in the future will definitely be augmented with machine learning and most likely will defer to it in a significant way.


The human mind isn’t a computer; it cannot progress in an orderly fashion down a list of candidate moves and rank them by a score down to the hundredth of a pawn the way a chess machine does. Even the most disciplined human mind wanders in the heat of competition. This is both a weakness and a strength of human cognition. Sometimes these undisciplined wanderings only weaken your analysis. Other times they lead to inspiration, to beautiful or paradoxical moves that were not on your initial list of candidates.” ― Garry Kasparov

If we can make computers more intelligent–and I want to be careful of AI hype–and understand the world and the environment better, it can make life so much better for many of us. Just as the Industrial Revolution freed up a lot of humanity from physical drudgery, I think AI has the potential to free up humanity from a lot of the mental drudgery.

Andrew Ng, Google Brain Founder

The human brain—that original source of intelligence—provides important inspiration here. Our brains are incredibly efficient relative to today’s deep learning methods. They weigh a few pounds and require about 20 watts of energy, barely enough to power a dim lightbulb. Yet they represent the most powerful form of intelligence in the known universe.

Geoff Hinton

I fear that AI may replace humans altogether. If people design computer viruses, someone will design AI that improves and replicates itself. This will be a new form of life that outperforms humans.

Stephen Hawking

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