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Megatrends, emerging issues and outlooks


more efficient use of resources during production processes and improved consumer awareness, leading to better informed choices. Many software applications are already being incorporated into personal electronics to scan, share information, and provide a user with targeted choices.


From the environmental management point of view, AI offers opportunities for more timely and robust environmental management decision support tools. This includes assessing real-time


data from numerous monitoring stations,


processing large data sets and providing timely information for policy-makers and users. For example AI can be combined with ecological models to predict changes in species distribution and migration due to climate change, or changes in invasive species distribution. Similarly, information from satellites and sensors connected with additional information from local sensors (such as sensors carried by drones) can be used to optimize agricultural processes, including automated tractors and sprayers, and allow tracking food from production to consumption. While the listed examples are still focused to solve specific problems, it is expected that the next step is for researchers and computer scientists to advance AI so that computers can learn general knowledge that can be used to enable them to work in new situations, or respond better to the user’s contexts and mood and also to automate many tasks, greatly improving personal efficiency and productivity (Policy Horizons 2012).


4.2.6 Transport systems


Although autonomous and semi-autonomous cars are still under development, it is also important from an environmental perspective to understand that there could be significant changes to existing transport systems. This not only includes individual personal transportation but also public transportation, as well as providing services in hospitals, warehouses and factories. Advancement of such “driverless” cars strongly depends on the advancement of AI to compute and interpret large amounts of information to facilitate smooth and more efficient service delivery. This could mean a considerable opportunity for North American people and businesses.


For example older people who might have been forced to give up cars may continue to be able to “drive”. This could result in an aging North American demographic continuing with automobile use and all of its environmental consequences. On the other hand, driverless-car technology may also promote the lower environmental consequences and the more efficient use of current roadways and, for example, reduce the need for parking: one gets out of a car and it goes directly to find the next passenger (The Economist 2015a). The smartphone-based apps that can quickly “call” for a car (in the future, no doubt a driverless car) are also likely to lead to long-term changes in patterns of car ownership and use.


Growth in telework and other changes that reduce use of central offices, and continuing growth in online shopping are all leading to changes in transport needs. Another potential major change in transport systems is drone delivery of packages. Major barriers today are probably more regulatory than technological, and within ten years this form of delivery may be quite common (The Economist 2015b). Any major changes in transport systems of course will have implications for conventional pollutants and greenhouse gas emissions, as well as for sustainable lifestyles.


These emerging technologies provide many opportunities and challenges for users and policy-makers to improve quality of life, environmental management and overall sustainability of the region. Many of these challenges as well as opportunities are explored in a series of scenarios Box 4.2.2. Large-scale


technologies means that they become the part of our every- day lives in less than a decade. This growth of coupled technologies, big data and AI to manage more and more of our technologies (transport, appliances, mobile devices, etc.) and lives is generally referred to as the “Internet of Things” (Wired 2016). This “Internet of Things” creates opportunities and challenges for policy-makers to anticipate and respond in a timely manner to the potential consequences to the environment, as well as to the social challenges posed, such as privacy issues, changes in employment types and structures, changes in educational needs, and others.


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availability of these emerging


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