Information and communication technologies (ICTs) must be designed and used for humane ends. The rapid adoption of Artificial Intelligence (AI) has raised the critical question of whether we can ensure AI's alignment with human values to guide its design and use. We perform a selective literature review with the specific search terms of the papers published in the top information systems (basket of 8 journals and 5 AI journals in IS) from 2000-2020 to answer this question. The findings indicate that IS research has contributed insufficiently to a deeper understanding of human values and AI value alignment principles. Moreover, the mainstream IS research on AI is mostly dominated from its technical and managerial aspects. Thus, the future research agendas are proposed accordingly. The paper provides some food for thoughts in studying human values and AI alignment within the context of IS research.

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The need for a systematic approach to work with artificial intelligence (AI) is current and rapidly
growing. It is important that Information Systems researchers get ahead of public sentiment and be able to provide proactive commentary about the current state-of-the-art, as well as solutions for future systems. One critical question is how can we ensure value alignment between AI and human values through AI operations from design to use? For the purposes of this discussion, we adopt the
phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we firstly analyze the AI phenomenon from selected resources from the top IS research outlets (basket of 8 journals and 5 AI journals in IS). Secondly, we briefly present what are material values and technological mediation and reflect on the AI value alignment principle through the lenses of these theories. Supported by these new understandings and reflections, we propose to build a common principle of human values to understand the AI value alignment principle through phenomenological theories. The paper contributes unique aspect of material values that are not addressed in the current AI research.@en