The current qualitative study investigates how religious experiences, in this case subjectively perceived encounters with the divine in worship practices, are induced and experienced by believers under the influence of music. Fifteen worship experts (worship leaders and pastors known to engage in this spiritual state in music) were recruited from Pentecostal and charismatic churches. A qualitative model for religious worship, incorporating essence, meaning, music, method, and experience is proposed. It shows that there is not just 'one' religious experience in worship but that there are many of them (a preliminary typology is attempted). There is a feedback loop between the music, the focus on the divine and the mental associations that can strengthen or weaken the experience. The role of music in worship, two approaches to religious experiences (i.e., the sui generis and the attribution theory), and the possibilities for future research are discussed.

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Research in artificial intelligence (AI) has started in the twentieth century but it was not until 2012 that modern models of artificial neural networks aided the machine learning process considerably so that in the past ten years, both computer vision as well as natural language processing have become increasingly better. AI developments have accelerated rapidly, leaving open questions about the potential benefits and risks of these dynamics and how the latter might be managed. This paper discusses three major risks, all lying in the domain of AI safety engineering: the problem of AI alignment, the problem of AI abuse, and the problem of information control. The discussion goes through a short history of AI development, briefly touching on the benefits and risks, and eventually making the case that the risks might potentially be mitigated through strong collaborations and awareness concerning trustworthy AI. Implications for the (digital) humanities are discussed.