The health of the planet is one of the most important challenges facing humankind today. From climate change to unsafe levels of air and water pollution to coastal and agricultural land erosion, a number of serious challenges threaten human and ecosystem health. Ensuring the health and safety of our planet necessitates approaches that connect scientific, engineering, social, economic, and political aspects. New computational methods can play a critical role by providing data-driven models and solutions for cleaner air, usable water, resilient food, efficient transportation systems, better-preserved biodiversity, and sustainable sources of energy. The MIT Schwarzman College of Computing is committed to hiring multiple new faculty in computing for climate and the environment, as part of MIT's plan to recruit 20 climate-focused faculty under its climate action plan.

Recent technological advancements paved the way for Artificial Intelligence (AI) to be integrated into our daily lives. Innovations in the field have greatly disrupted the business landscape, changing consumer behavior, and redefining customer service. According to the 2019 report of the U.S. think-tank Centre for Data Innovation, AI is applied in 32% of Chinese businesses. Meanwhile, in the EU and U.S., AI application is at 18% and 22%, respectively. As businesses become more competitive, there is a proportionate increase in the demand for AI to help simplify complex tasks.

"Artificial intelligence will only be an adjunct to decision making and not replace human decision making. It will allow for more timely and fulsome engagement with a myriad of data and will present it in ways that will influence decision makers." Artificial intelligence (AI) presents an interesting set of opportunities and challenges for regulatory systems writ large. AI has a spectrum of possible outcomes. Some people think AI will become the computer that answers all the questions that could ever be asked or go beyond our ability as human beings to compute and choose.

Artificial Intelligence and Decision-Making Defence Policy, Technology AI will change decision-making in defence in multiple ways. Keith Dear argues that AI will change decision-making in the defence and security arena in four principal ways. First, by enabling'cognitive manoeuvre' the use of predictive analytics to enable much earlier intervention. Second, by forcing humans to take themselves'out of the loop' for decision-making by out-performing them in an increasing number of domains. Third, by providing advice that is correct, but difficult to explain.

Keith Dear argues that AI will change decision-making in the defence and security arena in four principal ways. First, by enabling'cognitive manoeuvre' the use of predictive analytics to enable much earlier intervention. Second, by forcing humans to take themselves'out of the loop' for decision-making by out-performing them in an increasing number of domains. Third, by providing advice that is correct, but difficult to explain. Fourth, in the short term, by driving unprecedented rigour into decision-making processes, forcing decision-makers to be much more explicit about the mental models on which they are basing decisions, to enable comparison with automated analytics.