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AI has the capacity to harness and manipulate significant data identifying patterns and connections that humans struggle to do. The data analytics enabled by AI provides unique opportunities to investigate key environmental and sustainability issues for our World. This section will allow you to better understand some of the key benefits associated with AI and the environment, alongside introducing you to the concept of the circular economy and investigating how AI is benefiting humanity.
AI and the benefit for the environment
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It is widely recognised that humans are not managing the global environment as they should and that there are dire consequences to this mismanagement for the future. Manmade problems such as increasing population, urbanization and industrialisation are changing the conditions essential to life on Earth. The ability of AI to manage large amounts of data concurrently and to identify correlations in that data could prove to be a turning point for global sustainability.
The global environment is not in good shape, natural disasters are occurring at an alarming rates including earthquakes, bush fires and soaring heat in some areas of the globe. This is unsustainable in the long term.
According to the WEF report ‘Harnessing Artificial Intelligence for the Earth’ (2018) the Earth is losing its biodiversity at mass extinction levels. One in five species on Earth faces eradication and scientists estimate this will rise to 50% by the end of the century unless change occurs. The chemistry of the ocean is changing at an alarmin rate as it absorbs greenhouse gases with catastrophic impact. By 2030 the Earth may fall 40% short of fresh water to support global economy and 92% of the Earths residents live in areas which fail to conform to the WHO clean air guidelines.
The 4th industrial revolution offers a unique opportunity to overcome these challenges. Underpinned by the digital economy and based on rapid advances in AI, Internet, robots, biotechnology and quantum computing among others there are immediate and urgent focuses that need to be addressed in the management of our global economy and sustainability. AI is the most dynamic game changer in the global economy, its ability to sense its environment, think, learn and act in responses to what they sense, and their programmed objectives makes AI a game changer. AI needs to work to transform traditional approaches to managing problems such as climate change, growing and delivery of food, water security and protecting biodiversity. To do this AI systems need to be developed in a way that ensures they remain ‘friendly’ incorporating the health of the natural environment as a key fundamental design element.
AI has proved its capacity to deliver though the use and maximisation of big data, processing power, connected global infrastructure, open-source software and data, improved algorithms and accelerating returns. The convergence of all these factors has enabled AI to move from a research-based approach (in vitro) to integrating with everyday life (in vivo). This in turn has enabled many organisations to pioneer and utilise AI advances and applications, even start ups.
The future will only continue to further develop AI capacity, delivering better and more detailed results facilitating more effective decision making. This can have a significantly positive impact on the global environment, addressing key issues such as farming, crop rotation, water purity, air pollution etc. WEF have highlighted a number of priority action areas for addressing the Earth’s key challenge areas detailed in this diagram below:
Source: https://www3.weforum.org/docs/Harnessing_Artificial_Intelligence_for_the_Earth_report_2018.pdf
For AI to work most effectively synergies need to be created between the problem, technology and the solution. WEF (2018) identify five key game changers to support this:
- Transformational impact: solutions have the ability to completely disrupt current thinking and create transformational impact and change
- Adoption parallel: level of adoption is a critical success factor regrading population size
- Centrality of AI to the solution: AI must be posed as the central cog in the solution
- Systems impact: shifting perception across human systems
- Realizable enabling environment: Supported by both social and political dynamics
The greatest potential for transformation of human systems will include a cross sectoral integrated approach where boundaries are not geographical or political but environmental. Some key advances have been seen in developments such as autonomous and connected vehicles; distributed energy grids; smart agriculture; weather forecasting and climate modelling; community disaster response data and analytics platforms; decentralized water; AI designed intelligent, connected and liveable cities (SMART cities); Oceans data platform and developing the Earths bank of codes.
Looking forward it is anticipated AI will continue to drive significant benefits facilitating a more sustainable life system on Earth supported by future developments in areas such as: real time digital dashboard of the Earth; autonomous farming; quantum and distributed computing to scale computational power and reinforced learning for natural science breakthroughs. While it is true AI will be game changer for the environment and bring about many solutions to the key challenges currently being faced, it is also important to be cognisant of the potential adverse reactions which may occur. These may fall into key areas such as performance; security; control; ethical; economic and societal risks. To avoid such risks AI solutions, need to be developed in an integrated manner enabling a responsible and accountable approach with industry led collaboration across a range of disciplines.
Circular economy
Since the industrial revolution and beyond the global economy has operated a linear economy model in which products are consumed or used once and then discarded. This economic model will not support long term sustainability of the Earth and needs to be realigned to a circular model, where reuse of materials is at the core of design, thereby encouraging a circular motion of goods and services.
The linear economy relies on using finite resources and then discarding them, this cannot continue the Earth does not have the capacity to cope with current or future predicted levels of waste, and hence immediate action needs to be taken to rethink on a global scale.
1.3 billion tons of landfill are generated in waste each year, with a projected increase to 2.2 billion tons by 2025. Each year it is expected a total of 2.1 billion tons of waste is dumped (including landfill).
AI can be used to accelerate the path to a global circular economy through focuses on designing out waste and pollution, increasing effectiveness of and optimising circular economy business models and streamlining the infrastructure required to keep products and materials in use. Merging both AI with the circular economy has the opportunity to accelerate a shift towards a regenerative system fit for the future.
The circular economy relies on design enabling future reuse and redesign. Designers working with AI can develop better designs, due to the speed with which an AI algorithm can analyse large amounts of data and then subsequently suggest amendments. When AI is incorporated into design it acts to slice though complexity and suggest design models which best fit the circular design criteria, it works to accelerate the design process through the capacity to analyse large amounts of data simultaneously and can come up with novel designs which acts to challenge and push human thinking.
There are a number of ways in which AI can act the influence the future of the circular economy such as dynamic pricing (lowering food process closer to the expiry date); creating effective connections (through matching algorithms to connect people with the things they want) and by supporting predictive maintenance to reduce faults. AI can work to aid the identification of products which can be reused, resold, repaired or recycled to maximise value preservation. It can be used to support automated disassembly based on the condition of the product. Sorting of post-consumer mixed material streams using AI visual recognition techniques will also act to influence the changes required to drive a circular economy.
AI can support reuse business models and asset utilization through pricing and demand prediction, predictive maintenance and smart inventory management, all critical components of an effective circular economy.
The potential value unlocked by AI through designing out waste in a circular economy for food is $127 billion pa by 2030.
AI and the benefit for humanity
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AI enables businesses, governments and communities to create a high performing eco system that can serve the entire planet. Its impact on humanity continues to be significant.
AI is having a significant impact on human lives in resolving some of the world’s most complex challenges and issues. Energy is a critical resource to sustain life.
AI has revolutionized the energy market in recent years through use of meteorological data and sensors to optimize, anticipate and regulate energy consumption in a variety of industries. People with disabilities have been allowed to live more independent fulfilled lives through the assistance of AI and voice assistant technologies, along with smart devices.
The development of new drugs has been supported by AI through analysing vast quantities of data to find the most promising compounds. Reporting of sexual harassment has been made easier through the use emails, chats and social media being monitored by AI systems for inappropriate material. The fight against human trafficking has been assisted by AI supported technologies and computer vision algorithms to collect photos from various websites and categorize images, alerting police prior to the crime occurring. National defence has been supported by AI used to sift through huge layers of data and video to identify patterns and correlations providing a level of intelligence unknown before now.
AI has immense potential to benefit society and human lives for the present and future, already AI integration and deployments have aided more effective decision making, business models and risk mitigation. System performance utilising AI in banking sectors, national security, health care, transportation and criminal justice have made significant economic and social benefits and continue to do so.
The opportunity for AI to revolutionize human wellbeing is a realistic aim however key challenges such as development bottlenecks and application risks must be overcome before the full benefits can be realised and true scalability can be achieved. AI has already proved to be an effective tool in tackling key human development challenges for example object detection software and satellite imagery aided rescuers in Houston as they navigated the aftermath of a Hurricane Harvey. Poaching in Africa has been significantly reduced by through the use of algorithms in wildlife parks. Denmark uses voice recognition in emergency calls to identify if callers are experiencing a cardiac arrest and AI has already been used to detect early signs of diabetes from heart rate sensor data.
The 2030 Agenda for Sustainable development adopted by United Nations member states in 2015 provides a shared blueprint for peace and prosperity for people and plant and has at its heart 17 sustainable development goals (SDGs). It is expected that AI will accelerate advances in each of the United Nations sustainable development goals over the forthcoming years. However, to reach the level of scalability that is required to create real change AI development obstacles and the reassurance that AI technologies will do more good than harm needs to be addressed. Mitigation of risk is a critical success factor.
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Source: https://www.youtube.com/watch?v=Bpuoj1Op1kY
Data accessibility is a hurdle which needs to be overcome, often sensitive or commercial data, which is privately owned will not be shared, limiting the scope of use on a global scale. The dearth of data scientists remains a key issue for future development, one suggestion has been for larger organisations to take on pro bono approach allowing their data scientists to work on beneficial causes supporting humanity. Human prejudice in AI programming needs to be addressed to element unconscious biases in development phases. Stakeholders from private and public sectors must work together collaboratively increasing the availability of data that serve the public good. Already satellite companies participate in an in international agreement that commits them to providing open access during emergencies.
AI presents unimaginable opportunities for developing human well being and social and economic development however there continues to remain significant obstacles facilitating true scalability to impact global change.