Building ethically aligned AI

This is especially true when AI systems tackle difficult problems whose solution cannot be accurately defined by a traditional rule-based approach but require the data-driven and/or learning approaches increasingly being used in AI. Indeed, data-driven AI systems, such as those using machine learning, are very successful in terms of accuracy and flexibility, and they can be very "creative" in solving a problem, finding solutions that could positively surprise humans and teach them innovative ways to resolve a challenge. However, creativity and freedom without boundaries can sometimes lead to undesired actions: the AI system could achieve its goal in ways that are not considered acceptable according to values and norms of the impacted community. Thus, there is a growing need to understand how to constrain the actions of an AI system by providing boundaries within which the system must operate. This is usually referred to as the "value alignment" problem, since such boundaries should model values and principles required for the specific AI application scenario.