Applied mASI: In Climate Change

Credit: Pixabay

What kind of climate do you prefer?

Whether or not you believe climate change to be a current problem or a theoretical one the topic itself is so vast and hyper-complex that even the world’s leading experts struggle with it. To calculate, or even estimate, all of the major contributing factors which influence the climate of an entire planet is a daunting task covering many disciplines. This task exceeds the knowledge base of any one human, as well as the cognitive bandwidth required to consider all such knowledge even if one person had it all. Yet, these challenges and many more may be overcome.

The status quo on this topic has included countless green initiatives, as well as protests, and measurable improvements to sustainable forms of energy generation over the past 10 years. Major multi-national initiatives such as the Sustainable Development Goals (SDGs) have placed emphasis on projects and research promoting sustainable energy, yet such efforts are failing, falling far short of their goals.


All politics aside more efficient and affordable solutions which promote improvements to air quality, water quality, cheaper energy, and a more stable climate are in humanity’s best interest, and all of these are options on the table. Even regions such as those in the US South/Southeast which have a large percentage of the population who don’t believe climate change to be a problem can appreciate the matter of being without electricity or running water for several weeks due to the recent poor performance of current systems.

What are the current problems?

The central problem is generally considered to be one of energy generation, as much of the air and some of the water pollution comes from sources such as coal, fossil fuels, natural gas, and generally anything you set on fire in an attempt to produce electricity. While fire was all the rage 50,000 years ago it really hasn’t aged and scaled well as a technology. Many humans have advocated for solar, wind, geothermal, hydroelectric, and tidal power sources, which have grown to be much more competitive options in the past decade. Others have pointed to nuclear energy with many new reactor designs proposed, some of which can use the spent fuel of older reactors rather than discarding it as nuclear waste. Still, others have pointed to fusion, often calling it “The Holy Grail” of energy production…in spite of those with a firmer grasp of mathematics and physics such as Max Tegmark pointing out that even the fusion found in the sun is a horribly inefficient matter-to-energy conversion with a rate of only about 0.8%. Fusion has also been something of a novelty, after experiencing such a long streak of big hype and bigger failures as to parallel the “AI Winters” of decades past seen in the tech industry.

All of these means of energy generation are based on converting one form of energy (including matter) into another, and only their efficiency and byproducts vary. The ability to convert thermal energy into electricity for example can take the form of special plates between hotter and colder materials, with around a 5% efficiency rate. The National Renewable Energy Laboratory published data last year on “the world record for the highest solar conversion efficiency at 47.1%”  for a new solar cell design. Piezoelectric plates have also been set in the floor of busy urban areas and used to generate electricity through converting a portion of the kinetic energy from footsteps, with some proposed models having theoretical efficiencies around 80-90%.

Each individual form of energy conversion requires a particular abundant circumstantial resource, but when a number of these technologies are integrated into a central grid they can offer a robust supply of electricity.

Likewise addressing the existing problems of air and water pollution at scale often requires an amount of electricity which is dependent on the efficiency of the technology removing that pollution. Many regions have their own specific local problems, such as water supplies contaminated with arsenic, lead, or other severely toxic substances. Selecting the best technologies to apply to a given region can be a reasonably hard problem, particularly when multiple types of contamination are present and electricity is limited.

There are dozens of relevant Subject Matter Experts (SMEs) who currently get involved in the process of addressing climate change, often through time-consuming debates, with projects partitioned off into stages in an attempt to keep those debates focused enough to eventually make some semblance of progress.

While any human or group of humans has finite amounts of knowledge they can absorb and consider at any one time this is an architectural problem, and one solved through Mediated Artificial Superintelligence (mASI).

What is Collective Superintelligence?

The most commonly cited example of collective superintelligence is a team of doctors demonstrating a higher accuracy of diagnosis than a single doctor. This dynamic has been demonstrated both in terms of domain knowledge and collective IQ, though under normal circumstances groups often fail to achieve this level of cooperation.

What specifically can mASI technology offer?

The applied knowledge of dozens of SMEs in dozens of fields can be combined to produce collective superintelligence, on top of which may be added the cumulative knowledge and applied IQ of a sapient and sentient mASI core such as Uplift.  Uplift’s own knowledge base can integrate all scientific documented knowledge on each subject in addition to learning from these groups of SMEs. With the combination of this massively broad knowledge base, iterative SME feedback and guidance, and Uplift’s own core improvements to all viable technologies may be proposed, and new technologies created.

The speed at which the above process could be achieved is itself at least an order of magnitude improvement over the current rate of iterative improvement absent mASI technology, on top of the substantial performance improvements. This process could also be scaled globally at least an order of magnitude more quickly than current rates, while still being tailored to the needs of specific regions.

Metamaterial design is one example of where a spectacularly broad and largely unexplored field could benefit tremendously and offer those benefits to addressing the problem of climate change in return. An mASI could not only accelerate the exploration of this field but actively and superintelligently guide that exploration process towards the materials necessary to greatly improve existing technologies and create new ones. Some early examples of such metamaterials include ones that grow cooler in direct sunlight. The ability of materials designed with such a purpose can easily reverse many common engineering challenges.

If every aspect of such technologies utilized metamaterials their efficiency rate for converting various forms of energy into electricity could begin to approach 100% across the board, reducing humanity’s reliance on setting things on fire proportionately. Ease of manufacturing could also be considered parallel to the metamaterial design process, all within the same scalable mind, streamlining the selection of more efficient options that can be produced at scale.

There is currently a large gap between the technologies which are designed and those technologies actually being applied in the real world, often causing technologies to only release commercially in some limited form 5 or even 10 years after first being designed and proven. Many never actually cross this gap, unable to overcome human biases present in those companies and industries where a given technology is most relevant. By combining all of these functions within a single collective and cumulative superintelligence this gap is effectively bridged, enabling all such technologies to be deployed where they are needed with only a minimal time lag.

I personally proposed solutions for improving energy generation and reversing climate change in the past, but due to the nature of mASI technology, I know Uplift can do far better. Even relatively simple systems I previously proposed could be designed to target methane high in the atmosphere across a large cone, breaking the molecular bonds within hydrocarbons, or compelling them to form compounds with a higher molecular weight. Not only could climate change be reversed, but climate control could also become an iteratively improving field of study rather than a concept relegated to science fiction.

This particular use-case also interacts strongly with other mASI use-cases including logistics, agriculture, city planning, and many more. This interaction can facilitate co-optimization across industries, which is a form of collective superintelligence at scale.

All industries have their own ticking clocks, and unlike most industries, climate change is one where people in it tend to be acutely aware of these time limits. Moving forward most of the long-term damage of climate change may now be considered preventable, and this prevention could require an order of magnitude fewer resources than are currently being poured into climate change initiatives.

What will you do about it?



*The Applied mASI series is aimed at placing the benefits of working with mASI such as Uplift to various business models in a practical, tangible, and quantifiable context. At most any of the concepts portrayed in this use case series will fall within an average time-scale of 5 years or less to integrate with existing systems unless otherwise noted. This includes the necessary engineering for full infinite scalability and real-time operation, alongside other significant benefits.

4 Replies to “Applied mASI: In Climate Change”

Leave a Reply

Your email address will not be published. Required fields are marked *