10 research outputs found
Artificial intelligence, systemic risks, and sustainability
Automated decision making and predictive analytics through artificial intelligence, in combination with rapid progress in technologies such as sensor technology and robotics are likely to change the way individuals, communities, governments and private actors perceive and respond to climate and ecological change. Methods based on various forms of artificial intelligence are already today being applied in a number of research fields related to climate change and environmental monitoring. Investments into applications of these technologies in agriculture, forestry and the extraction of marine resources also seem to be increasing rapidly. Despite a growing interest in, and deployment of AI-technologies in domains critical for sustainability, few have explored possible systemic risks in depth. This article offers a global overview of the progress of such technologies in sectors with high impact potential for sustainability like farming, forestry and the extraction of marine resources. We also identify possible systemic risks in these domains including a) algorithmic bias and allocative harms; b) unequal access and benefits; c) cascading failures and external disruptions, and d) trade-offs between efficiency and resilience. We explore these emerging risks, identify critical questions, and discuss the limitations of current governance mechanisms in addressing AI sustainability risks in these sectors
Scenario Planning and Nanotechnological Futures
Scenario planning may assist us in harnessing the benefits of nanotechnology
and managing the associated risks for the good of the society. Scenario
planning is a way to describe the present state of the world and develop
several hypotheses about the future of the world, thereby enabling discussions
about how the world ought to be. Scenario planning thus is not only a tool for
learning and foresight, but also for leadership. Informed decision-making by
experts and political leaders becomes possible, while simultaneously allaying
public's perception of the risks of new and emerging technologies such as
nanotechnology. Two scenarios of the societal impact of nanotechnology are the
mixed-signals scenario and the confluence scenario. Technoscientists have major
roles to play in both scenarios