4 Ways AI Could Improve the State of the Earth

  1. Smart Agriculture and New Food Systems

    If the agricultural industry were to integrate AI technology into their farms and fields, it could eventually allow for the early detection of several devastating crop diseases and issues, provide timed nutrition to livestock, and generally to optimise agricultural inputs and returns based on supply and demand. With the utilization of AI technology, it could potentially increase the efficiency and productivity of the agriculture industry by a large margin, creating a very positive impact on the environment by lowering the use of water, fertilisers and pesticides which cause damage to important ecosystems, and increase resilience to climate extremes.

  2. AI “smart” cities

    Artificial Intelligence in large, populated cities would definitely help to augment urban sustainability. With AI technology, cities would be able to simulate and automate the generation of zoning laws, building ordinances and floodplains, combined with both augmented and virtual reality. In addition, “smart” cities would easily have the accessibility to collect daily city-wide data on energy usage, water consumption, traffic flows, and unpredictable weather reports, essentially keeping the urban population and government up to date on various important issues to keep their town running smoothly.

  3. A “digital” Earth

    A real-time, digital geospatial dashboard for the planet would enable AI technology to be able to monitor, model and manage environmental systems at a scale and speed never possible before. From tackling significantly detrimental issues like illegal deforestation, forest fires, water droughts, fishing and poaching, to air pollution, natural disaster response and smart agriculture, international and national government agencies like NASA would be quickly able to aid in helping global crises and source them almost immediately. The impact this could have on the environment or the entire Earth in general would be extremely unprecedented. 

  4. Reinforcement learning for Earth sciences breakthroughs

    Reinforcement learning – a technique which in of itself requires no input data, substantially less computing power, and in which the AI practically learns from itself – could soon transform to enable its application to real-world problems in the natural and Earth sciences. In cooperating with Earth scientists to identify the systems anywhere from climate science, materials science, and biology, in which these areas can be codified to apply reinforcement learning for scientific progress can almost be considered is vital. For example, in the realm of materials science, AI could be used to search for a room temperature superconductor – a hypothetical substance that allows for incredibly efficient energy systems.

Meher Bhatia