In this book, the author traces research into one of the most scientifically denied features of dreaming consciousness - the thinking abilities of non-lucid dreamers. Contrary to explanations provided by cognitive neuroscientists, notably that deactivation of the dorsolateral prefrontal cortex indicates that non-lucid dreamers are incapable of self-generated thought (including executive skills and metacognitive monitoring), the phenomenological findings presented here reveal the wide range of dreamers' sophisticated thought processes. Granted, these thought processes come to existence if and when dreamers find (...) themselves in specific condition during which they realize that they might want to attempt to change their current experience. (shrink)

From the neurophysiological perspective, thinking in dreaming and the quality of dream thought have been considered hallucinatory, bizarre, illogical, improbable, or even impossible. This empirical phenomenological research concentrates on testing whether dream thought can be defined as rational in the sense of an intervening mental process between sensory perception and the creation of meaning, leading to a conclusion or to taking action. From 10 individual dream journals of male participants aged 22–59 years and female participants aged 25–49 years, we delimited (...) four dreams per journal and randomly selected five thought units from each dream for scoring. The units provided a base for testing a hypothesis that the thought processes of dream construction are rational. The results support the hypothesis and demonstrate that eight fundamental rational thought processes can be applied to the dreaming process. (shrink)

Purpose The purpose of this study is to examine public perceptions and attitudes toward using artificial intelligence (AI) in the US criminal justice system. Design/methodology/approach The authors took a quantitative approach and administered an online survey using the Amazon Mechanical Turk platform. The instrument was developed by integrating prior literature to create multiple scales for measuring public perceptions and attitudes. Findings The findings suggest that despite the various attempts, there are still significant perceptions of sociodemographic bias in the criminal justice (...) system and technology alone cannot alleviate them. However, AI can assist judges in making fairer and more objective decisions by using triangulation – offering additional data points to offset individual biases. Social implications Other scholars can build upon the findings and extend the work to shed more light on some problems of growing concern for society – bias and inequality in criminal sentencing. AI can be a valuable tool to assist judges in the decision-making process by offering diverse viewpoints. Furthermore, the authors bridge the gap between the fields of technology and criminal justice and demonstrate how the two can be successfully integrated for the benefit of society. Originality/value To the best of the authors’ knowledge, this is among the first studies to examine a complex societal problem like the introduction of technology in a high-stakes environment – the US criminal justice system. Understanding how AI is perceived by society is necessary to develop more transparent and unbiased algorithms for assisting judges in making fair and equitable sentencing decisions. In addition, the authors developed and validated a new scale that can be used to further examine this novel approach to criminal sentencing in the future. (shrink)