# Essential Features in a Theory of Context for Enabling Artificial General Intelligence
## Supporting Ecosystems and Social Factors  
A range of supporting ecosystems, both in industry and through governmental bodies such as national funding agencies, are currently geared toward supporting some of the areas we covered in Section 3, and a few consider context as a central concept in the future development of AI. Before describing some of these programs, we note the importance of ecosystems and social factors for enabling research in context-rich AI, both theoretically and empirically. In an economy with heavy competition for resources, it is difficult to really interest in a field unless there are incentives and supporting infrastructures in place. The fact that funding opportunities for developing more context-rich AI already exist (with some having been launched very recently) is an encouraging finding, suggesting that context-rich AI will get the attention it deserves. We focus primarily on supporting ecosystems in the United States, although similar findings apply both in China, where AI research has accelerated immensely over the last few years, and also the European Union. In the United States, the National Science Foundation (NSF), has instituted multiple programs where context-rich AI is going to play a key role, although the development of such an AI is not the \"direct\" aim of the effort. One example is the relatively recent call for \"AI Institutes\", a joint government effort [99] between NSF, the U.S. Department of Agriculture (USDA) National Institute of Food and Agriculture (NIFA), the U.S. Department of Homeland Security (DHS) Science and Technology Directorate (S&T), and the U.S. Department of Transportation (DOT) Federal Highway Administration (FHWA). It also involves significant industry participation from the likes of Amazon and Google (among others). Simply put, these institutes are meant to facilitate \"new and sustained research in AI to drive science and technology progress\". Teams comprising one or more organizations can submit proposals to one of eight themes. One of these themes is \"human-AI interaction and collaboration\". In both Sections 2 and 3, we argued that, for seamless human-AI interaction and collaboration to occur, an AI must necessarily (although not sufficiently) be context-rich. Some other themes also have relevance to context-rich AI, including _AI-Augmented Learning_[100]. While this is the most direct and well-funded example of context-rich AI enablement (with an anticipated funding of USD 128 to 160 million over eight institute selections), in recent years, other similar but smaller-scale multi-disciplinary AI programs have also been announced. The relevance of context-rich AI to military applications and the United States Departments of Defense (DoD) cannot be underestimated. Multiple DARPA programs have been instituted in the last few years that involve context, either directly or indirectly. Many of these programs are described as \"third-wave AI\" programs [101] that combine (and improve upon) the best of first-wave AI (logical, rule-based and/or expert systems) and second-wave AI (machine learning and other 'inductive' architectures). We mentioned the DARPA XAI program earlier [76], but another one is the DARPA Machine Common Sense (MCS) program [102] that directly funds research and development in commonsense AI, which must be context-rich and context-aware to achieve its full potential. Yet another example is the DARPA Science of Artificial Intelligence and Learning for Open-world Novelty (SAIL-ON) program [89], which attempts to build AI systems that can 'act appropriately and effectively in novel situations' that occur in open worlds, of which the real world is an example. Context and novelty go hand-in-hand, since an event is typically novel with respect to its context. For example, if someone starts shouting in the middle of an examination, that would (generally) be considered more novel than if someone started shouting in a political rally or a protest.