The goal is not to have intelligent robots that

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interactions. The goal is not to have intelligent robots that portray emotions, but rather to have them be able to understand emotion. This way they can respond in appropriate ways. Culture can also be modeled in software. “As the development of virtual agents focuses increasingly more on the social aspects of human interaction, it becomes crucial to address the notion of culture and how it affects human behavior” (Degens, Paiva, Prada, Hofstede, Beulens, Aylett, 2016). Degens, Paiva, Prada, Hofstede, Beulens, and Aylett propose the social importance dynamics framework. This type of understanding of culture is important to design a system with agents that accommodate to the local culture in a natural way. The Synectic IVA project has an aggressive development and testing timeline. Crowdsourcing bootstrapping (CB) is a way to rapidly build AI. The Crowdsourcing bootstrap framework is a good method for this type of project. It enables the IVA to accumulate large amounts of foundational knowledge quickly. “The CB framework uses crowdsourcing for large scale data collection” (Borish, Lok, 2016). Crowdsourcing usually involves providing a web interface that allows users to provide direct input towards a problem, or to provide sample data through the participation in surveys or other data collection tools. A challenge with crowdsourcing is getting enough people motivated to spend the time to record the data. Crowd design frameworks tend involve either linear competition or iterative improvements as reward systems for the “crowd”. “Linear competitions might be single or multistage and reward workers with staged payments or a winner-take-all prize” (Wu, Corney, Grant, 2015). Iterative improvements are often the situation where workers are the “crowd” and receive monetary
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AI as Complement to Cloud CRM 7 reward for improving upon the existing system. For the Synectic IVA project, iterative improvements could be a valuable testing method during the crowdsourcing phase. Video game developers also focus on tools that allow for rapid AI development. This is because “video game AI is often specifically designed for each game” (Safadi, Fonteneau, Ernst, 2015). This challenge caused the developers to make a system that enabled them to use the same AI across multiple game types by what they term “detachment”. The focus is “creating AI that operates solely on concepts” (Safadi, Fonteneau, Ernst, 2015). This conceptual design of the framework allows an AI to be broken into small chunks that can be implemented quickly to meet changing requirements. “Agile or adaptive enterprise architecture (EA) capability is a key strategic capability that plays an important role in describing the structure, behavior, social, technology, and facility elements of an adaptive enterprise” (Gill 2013; ISO/IEC 42010 2007). If new business arrive that require AI, the conceptual AI foundation can be reused in altered environments.
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Christopher Reinemann
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