Artificial intelligence has a double-edged sword when it comes to climate change and the environment.
Artificial intelligence is being used by scientists to
detect, adapt, and react to ecological concerns.
Civilization is becoming exposed to new environmental
hazards and vulnerabilities as a result of the same technologies.
Much has been written on the importance of information
technology in green economy solutions.
Data from natural and urban ecosystems is collected and
analyzed using intelligent sensing systems and environmental information
systems.
Machine learning is being applied in the development of
sustainable infrastructure, citizen detection of environmental perturbations
and deterioration, contamination detection and remediation, and the redefining
of consumption habits and resource recycling.
Planet hacking is a term used to describe such operations.
Precision farming is one example of planet hacking.
Artificial intelligence is used in precision farming to
diagnose plant illnesses and pests, as well as detect soil nutrition issues.
Agricultural yields are increased while water, fertilizer,
and chemical pesticides are used more efficiently thanks to sensor technology
directed by AI.
Controlled farming approaches offer more environmentally
friendly land management and (perhaps) biodiversity conservation.
Another example is IBM Research's collaboration with the
Chinese government to minimize pollution in the nation via the Green Horizons
program.
Green Horizons is a ten-year effort that began in July 2014
with the goal of improving air quality, promoting renewable energy integration,
and promoting industrial energy efficiency.
To provide air quality reports and track pollution back to
its source, IBM is using cognitive computing, decision support technologies,
and sophisticated sensors.
Green Horizons has grown to include global initiatives such
as collaborations with Delhi, India, to link traffic congestion patterns with
air pollution; Johannesburg, South Africa, to fulfill air quality objectives;
and British wind farms, to estimate turbine performance and electricity output.
According to the National Renewable Energy Laboratory at the
University of Maryland, AI-enabled automobiles and trucks are predicted to save
a significant amount of gasoline, maybe in the region of 15% less use.
Smart cars eliminate inefficient combustion caused by stop-and-go and speed-up and slow-down driving behavior, resulting in increased fuel efficiency (Brown et al.2014).
Intelligent driver input is merely the first step toward a
more environmentally friendly automobile.
According to the Society of Automotive Engineers and the
National Renewable Energy Laboratory, linked automobiles equipped with
vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication
might save up to 30% on gasoline (Gonder et al.
2012).
Smart trucks and robotic taxis will be grouped together to
conserve fuel and minimize carbon emissions.
Environmental robots (ecobots) are projected to make
significant advancements in risk monitoring, management, and mitigation.
At nuclear power plants, service robots are in use.
Two iRobot PackBots were sent to Japan's Fukushima nuclear
power plant to measure radioactivity.
Treebot is a dexterous tree-climbing robot that is meant to
monitor arboreal environments that are too difficult for people to access.
The Guardian, a robot created by the same person who
invented the Roomba, is being developed to hunt down and remove invasive
lionfish that endanger coral reefs.
A similar service is being provided by the COTSbot, which
employs visual recognition technology to wipe away crown-of-thorn starfish.
Artificial intelligence is assisting in the discovery of a
wide range of human civilization's effects on the natural environment.
Cornell University's highly multidisciplinary Institute for
Computer Sustainability brings together professional scientists and citizens to
apply new computing techniques to large-scale environmental, social, and
economic issues.
Birders are partnering with the Cornell Lab of Ornithology
to submit millions of observations of bird species throughout North America, to
provide just one example.
An app named eBird is used to record the observations.
To monitor migratory patterns and anticipate bird population
levels across time and space, computational sustainability approaches are
applied.
Wildbook, iNaturalist, Cicada Hunt, and iBats are some of
the other crowdsourced nature observation apps.
Several applications are linked to open-access databases and
big data initiatives, such as the Global Biodiversity Information Facility,
which will include 1.4 billion searchable entries by 2020.
By modeling future climate change, artificial intelligence is also being utilized to assist human populations understand and begin dealing with environmental issues.
A multidisciplinary team from the Montreal Institute for
Learning Algorithms, Microsoft Research, and ConscientAI Labs is using street
view imagery of extreme weather events and generative adversarial networks—in
which two neural networks are pitted against one another—to create realistic
images depicting the effects of bushfires and sea level rise on actual
neighborhoods.
Human behavior and lifestyle changes may be influenced by
emotional reactions to photos.
Virtual reality simulations of contaminated ocean ecosystems
are being developed by Stanford's Virtual Human Interaction Lab in order to
increase human empathy and modify behavior in coastal communities.
Information technology and artificial intelligence, on the other hand, play a role in the climate catastrophe.
The pollution created by the production of electronic
equipment and software is one of the most pressing concerns.
These are often seen as clean industries, however they often
use harsh chemicals and hazardous materials.
With twenty-three active Superfund sites, California's
Silicon Valley is one of the most contaminated areas in the country.
Many of these hazardous waste dumps were developed by
computer component makers.
Trichloroethylene, a solvent used in semiconductor cleaning,
is one of the most common soil pollutants.
Information technology uses a lot of energy and contributes
a lot of greenhouse gas emissions.
Solar-powered data centers and battery storage are
increasingly being used to power cloud computing data centers.
In recent years, a number of cloud computing facilities have been developed around the Arctic Circle to take use of the inherent cooling capabilities of the cold air and ocean.
The so-called Node Pole, situated in Sweden's northernmost
county, is a favored location for such building.
In 2020, a data center project in Reykjavik, Iceland, will
run entirely on renewable geo thermal and hydroelectric energy.
Recycling is also a huge concern, since life cycle
engineering is just now starting to address the challenges of producing
environmentally friendly computers.
Toxic electronic trash is difficult to dispose of in the
United States, thus a considerable portion of all e-waste is sent to Asia and
Africa.
Every year, some 50 million tons of e-waste are produced throughout
the globe (United Nations 2019).
Jack Ma of the international e-commerce company Alibaba
claimed at the World Economic Forum annual gathering in Davos, Switzerland,
that artificial intelligence and big data were making the world unstable and
endangering human life.
Artificial intelligence research's carbon impact is just now
being quantified with any accuracy.
While Microsoft and Pricewaterhouse Coopers reported that
artificial intelligence could reduce carbon dioxide emissions by 2.4 gigatonnes
by 2030 (the combined emissions of Japan, Canada, and Australia), researchers
at the University of Massachusetts, Amherst discovered that training a model
for natural language processing can emit the equivalent of 626,000 pounds of
greenhouse gases.
This is over five times the carbon emissions produced by a
typical automobile throughout the course of its lifespan, including original
production.
Artificial intelligence has a massive influence on energy usage and carbon emissions right now, especially when models are tweaked via a technique called neural architecture search (Strubell et al. 2019).
It's unclear if next-generation technologies like quantum
artificial intelligence, chipset designs, and unique machine intelligence
processors (such as neuromorphic circuits) would lessen AI's environmental
effect.
Artificial intelligence is also being utilized to extract additional oil and gas from beneath, but more effectively.
Oilfield services are becoming more automated, and
businesses like Google and Microsoft are opening offices and divisions to cater
to them.
Since the 1990s, Total S.A., a French multinational oil
firm, has used artificial intelligence to enhance production and understand
subsurface data.
Total partnered up with Google Cloud Advanced Solutions Lab
professionals in 2018 to use modern machine learning techniques to technical
data analysis difficulties in the exploration and production of fossil fuels.
Every geoscience engineer at the oil company will have
access to an AI intelligent assistant, according to Google.
With artificial intelligence, Google is also assisting
Anadarko Petroleum (bought by Occidental Petroleum in 2019) in analyzing
seismic data to discover oil deposits, enhance production, and improve
efficiency.
Working in the emerging subject of evolutionary robotics, computer scientists Joel Lehman and Risto Miikkulainen claim that in the case of a future extinction catastrophe, superintelligent robots and artificial life may swiftly breed and push out humans.
In other words, robots may enter the continuing war between
plants and animals.
To investigate evolvability in artificial and biological
populations, Lehman and Miikkulainen created computer models to replicate
extinction events.
The study is mostly theoretical, but it may assist engineers
comprehend how extinction events could impact their work; how the rules of
variation apply to evolutionary algorithms, artificial neural networks, and
virtual organisms; and how coevolution and evolvability function in ecosystems.
As a result of such conjecture, Emerj Artificial
Intelligence Research's Daniel Faggella notably questioned if the
"environment matter[s] after the Singularity" (Faggella 2019).
Ian McDonald's River of Gods (2004) is a notable science
fiction novel about climate change and artificial intelligence.
The book's events take place in 2047 in the Indian
subcontinent.
A.I.Artificial Intelligence (2001) by Steven Spielberg is set in a twenty-second-century planet plagued by global warming and rising sea levels.
Humanoid robots are seen as important to the economy since
they do not deplete limited resources.
Transcendence, a 2014 science fiction film starring Johnny
Depp as an artificial intelligence researcher, portrays the cataclysmic danger
of sentient computers as well as its unclear environmental effects.
~ Jai Krishna Ponnappan
You may also want to read more about Artificial Intelligence here.
See also:
Chatbots and Loebner Prize; Gender and AI; Mobile Recommendation Assistants; Natural Language Processing and Speech Understanding.
Further Reading
Bort, Julie. 2017. “The 43 Most Powerful Female Engineers of 2017.” Business Insider. https://www.businessinsider.com/most-powerful-female-engineers-of-2017-2017-2.
Chan, Sharon Pian. 2011. “Tech-Savvy Dreamer Runs Microsoft’s Social-Media Lab.” Seattle Times. https://www.seattletimes.com/business/tech-savvy-dreamer-runs-microsofts-social-media-lab.
Cheng, Lili. 2018. “Why You Shouldn’t Be Afraid of Artificial Intelligence.” Time. http://time.com/5087385/why-you-shouldnt-be-afraid-of-artificial-intelligence.
Cheng, Lili, Shelly Farnham, and Linda Stone. 2002. “Lessons Learned: Building and Deploying Shared Virtual Environments.” In The Social Life of Avatars: Computer Supported Cooperative Work, edited by Ralph Schroeder, 90–111. London: Springer.
Davis, Jeffrey. 2018. “In Chatbots She Trusts: An Interview with Microsoft AI Leader Lili Cheng.” Workflow. https://workflow.servicenow.com/customer-experience/lili-chang-ai-chatbot-interview.
