B̶i̶o̶s̶p̶h̶e̶r̶e̶ Technosphere?

Source: Deep Learning on Medium

Exigency and Applicability of Cognitive technology to embrace technological development without sacrificing the natural world and maintaining sustainability.

Image Courtesy: Nature and technology are usually viewed as interdependent rather than in opposition.

The Anthropogenic impact on the environment is undeniable. Our ever-growing demand for natural resources is leading to land-use changes, loss of biodiversity, pollution, Holocene extinction, environmental degradation and defaunation. The technological evolution has led us to a world full of skyscrapers, aeroplanes, cheap food and factory-made everything to live long and comfortable lives. On the contrary, it wrecked the environment and left us dependent on resources and systems that are inherently unsustainable. The climatic changes continue to disrupt weather patterns, temperatures and water availability which are, directly or indirectly, impacting on the human and natural ecosystems.

The 21st century will question everything we think we know about nature and technology. The environment is a hot topic, literally. As global temperatures have warmed since 1850, the discussion on what to do about it has heated up even more.

GIF courtesy: Are global temperatures “spiralling out of control”?

Due to the emerging technological breakthroughs and swift advances in our ability to read, write, and edit DNA, we are gaining a much deeper understanding of how life works. The more we learn, the more we’ll be able to use biology as a tool to treat diseases as well as improve agricultural yields.

Simultaneously, our machines are becoming more biological. They can think and communicate with one another. They are ushering in an era of technologies that are faster, more adaptable, more efficient, and making the world more digitally connected, as they can sense and react to the world around them. And thanks to the ubiquity of wireless networks, our gadgets can now connect into new kinds of ecosystems that turn our cities and homes into smart and responsive environments.

The line between biology and technology is beginning to blur.

Video Courtesy: Technosphere: The Earth is forming highways and aeroplanes and cities, instead of forming streams, mountains and forests.Thanks to Us!

The good news is that there is more information available than ever before about the environment. Growing global attention is leading to increasing regulations, deeper research and deployment of advanced sensing, mapping technologies and better monitoring which assists us in better understanding and prevention of damage and stressors on Earth’s land, air, and water. However, connecting the dots for better insights and solutions which can be harnessed with intelligent algorithms is the need of the hour.

Cognitive technology, enabled by artificial intelligence, or AI, is uniquely adapted to helping with the challenges, from finding patterns and interconnections within macro datasets to providing local, personalized diagnosis and predictions that learn and improve over time.AI techniques may also help correct biases in models, extract the most relevant data to avoid data degradation, predict extreme events and be used for impacts modelling. The more meaningful data there is, the smarter the artificial intelligence gets, and the larger the synergy effects from economic benefits and sustainable impacts become. Therefore, thinking about the environment pays off twofold.

According to a recent survey by Intel and the research firm Concentrix, 74% of business decision-makers working in environmental sustainability agree artificial intelligence (AI) will help solve long-standing environmental challenges; 64% agree the Internet of Things (IoT) will help solve these challenges. In the face of this dire reality, the potential of technology to safeguard our environment is a rare source of optimism.

Image Courtesy: The potential of AI to clean up the environment is boundless

Game-Changers AI applications that can address environmental challenges :

Autonomous and connected electric vehicles

AI-guided autonomous vehicles will enable a transition to mobility-on-demand in the near future. Substantial greenhouse gas reductions for urban transport can be unlocked through route and traffic optimisation, eco-driving algorithms, programmed platooning of cars to traffic, and autonomous ride-sharing services. AI-enabled traffic lights will do their part too, adjusting to the flow of traffic to minimize driving time. The first phase of such a system is currently in place in some intersections in Pittsburgh, where it’s already reduced travel time by 25 % and idling by more than 40 %. Electric AV fleets will be essential in delivering real gains.

Distributed energy grids

AI can enhance the predictability of demand and supply for renewables across a distributed grid, improve energy storage, efficiency and load management, assist in the integration and reliability of renewables and enable dynamic pricing and trading, creating market incentives. AI techniques will contribute to renewable energy integration which will translate into a new, improved and modernized electrical grid. These new methods and products will allow the distribution system to integrate high penetration levels of renewable energy, lowered carbon footprints and more consumer choices.

Smart agriculture and food systems

AI-augmented agriculture involves automated data collection, decision-making and corrective actions via robotics to allow early detection of crop diseases and issues, to provide timed nutrition to livestock, and generally to optimise agricultural inputs and returns based on supply and demand. This promises to increase the resource efficiency of the agriculture industry, enhanced yields, lowering the use of water, fertilisers and pesticides which cause damage to important ecosystems and increase resilience to climate extremes.

Next-generation weather and climate prediction

“Climate Informatics”, a new blossoming field in AI that fundamentally transforms weather forecasting and improves our understanding of the effects of climate change. This field traditionally requires high performance energy-intensive computing, but deep-learning networks can allow computers to run much faster and incorporate more complexity of the ‘real-world’ system such as atmospheric and ocean dynamics and ocean and atmospheric chemistry, into the calculations. This sharpens the exactness in weather and climate modelling, making simulations more useful for decision-makers.

Image Courtesy: Priority action areas for addressing Earth challenge areas

Smart disaster response

AI can analyse simulations and real-time data of weather events and disasters in a region to seek out vulnerabilities and enhance disaster preparation, provide early warning, and prioritise response through coordination of emergency information capabilities. Deep reinforcement learning may one day be integrated into disaster simulations to determine optimal response strategies.

AI-designed intelligent, connected and livable cities

AI could be used to simulate and automate the generation of zoning laws, building ordinances and floodplains, combined with augmented and virtual reality. Real-time city-wide data on energy, water consumption and availability, traffic flows, and the weather could create an “urban dashboard” to optimise urban sustainability. In China, IBM’s Green Horizon project is using an AI system that can forecast air pollution, track pollution sources and produce potential strategies to deal with it. It can determine if, for example, it would be more effective to restrict the number of drivers or close certain power plants in order to reduce pollution in a particular area. AI would simulate the climatic conditions at the urban scale and explore different strategies to test how well they ease heat waves. For example, if a city wanted to plant new trees, machine learning models could determine the best places to plant them to get optimal tree cover and reduce heat from the pavement.

A transparent digital Earth

We can tackle environmental problems from illegal deforestation, water extraction, fishing and poaching to air pollution, natural disaster response and smart agriculture by designing a real-time, open API, AI-infused digital geospatial dashboard would enable the monitoring, modelling and management of environmental systems.

Moreover, a nascent AI technique which learns from itself that could soon evolve to enable its application to real-world problems in the natural sciences thereby can be codified to apply reinforcement learning for scientific progress and discovery is vital.

A true conservationist is a man who knows that the world is not given by his fathers, but borrowed from his children.

Let’s look forward to a brighter and greener future! 🌎

The advancement of artificial intelligence, it is now possible to tackle some of the world’s biggest problems with emerging technologies in this maturing industry. AI is shaping up to be the key that governments, organizations, and individuals can tap to work towards a cleaner and eco-friendly planet. It’s time to put AI to work for the planet. We’re only at the beginning, when we think about the ways that Cognitive technology is going to help us protect and conserve our natural resources, really the sky is the limit.

Image Courtesy: A good Anthropocene demands that humans use their growing social, economic, and technological powers to make life better for people, stabilize the climate, and protect the natural world.