One of the most well-respected and widely used tools in the study of general intelligence is the Raven's Progressive Matrices test, a nonverbal task wherein subjects must induce the rules that govern the patterns in an arrangement of shapes and figures. This thesis describes the first neurally based, biologically plausible model that can dynamically generate the rules needed to solve Raven's matrices. We demonstrate the success and generality of the rules generated by the model, as well as interesting insights the model provides into the causes of individual differences, at both a low (neural capacity) and high (subject strategy) level. Throughout this discussion we place our research within the broader context of intelligence research, seeking to understand how the investigation and modelling of Raven's Progressive Matrices can contribute to our understanding of general intelligence.

One of the most well-respected and widely used tools in the study of general intelligence is the Raven's Progressive Matrices test, a nonverbal task wherein subjects must induce the rules that govern the patterns in an arrangement of shapes and figures. This thesis describes the first neurally based, biologically plausible model that can dynamically generate the rules needed to solve Raven's matrices. We demonstrate the success and generality of the rules generated by the model, as well as interesting insights the model provides into the causes of individual differences, at both a low (neural capacity) and high (subject strategy) level. Throughout this discussion we place our research within the broader context of intelligence research, seeking to understand how the investigation and modelling of Raven's Progressive Matrices can contribute to our understanding of general intelligence.

Whether the hand you write with has any impact or says anything about you has been debated for hundreds of years. The most cited in the media today is an association between left-handedness and creativity. However, handedness has also been associated with intelligence, with a small advantage for those being right-handed, according to a systematic review. The present study compared intelligence, measured by the Wiener Matrizen Test, across groups who self-reported writing always with the right, always with the left, or sometimes with the left and sometimes with the right hand (ambidextrous), in a sample of 8,399 Swedish adults. The right-handed group had higher intelligence than both left-handed and ambidextrous groups, with an effect size for the right-left difference of 0.18 for males and 0.08 for females. Although of little consequence for any individual, such effects may have practical consequences at the group level, and should therefore be taken into account when comparing groups across demographic categories. Left-handedness is, for example, 23% more common among males than among females. / Huruvida den hand du skriver med har någon betydelse eller säger något om dig har debatterats i hundratals år. Mest citerat i media idag är en association mellan vänsterhänthet och kreativitet. Hänthet har också associerats med intelligens, med en liten fördel för högerhänta, enligt en systematisk litteraturgenomgång. Föreliggande studie jämförde intelligens, mätt med Wiener Matrizen Test, över grupper som själv-rapporterat att alltid skriva med höger, alltid med vänster, eller ibland med höger och ibland med vänster hand (ambidexter), i ett sampel med 8.399 vuxna svenskar. Gruppen med högerhänta hade högre intelligens än både vänsterhänta och ambidextra, med en effektstorlek för skillnaden mellan höger och vänster på 0,18 för mänoch 0,08 för kvinnor. Även om sådana effekter har liten betydelse för individen kan de ha praktiska konsekvenser på gruppnivå, och bör därför beaktas när man jämför grupper med olika demografiska kategorier. Vänsterhänthet är till exempel 23% vanligare bland män än bland kvinnor.

The objective of this research is to elucidate motivation and emotion processing inan AGI (Artificial General Intelligence) system NARS (Non-Axiomatic Reasoning System). Under the basic assumption that an artificial general intelligence system should work with insufficient resources and knowledge, the emotion module can help direct the selection of internal tasks, and allow the autonomous allocation of internal resources and rapid response with urgency, so that the inference capability of AGI system can be improved. The psychological and AI theories related to emotion are extensively reviewed,including the source of emotion, the appraisal process in emotional experience, the cognitive processing and coping process, and the necessity of emotion for Artificial General Intelligence design. This dissertation describes the conceptual design, realization process and application process of emotion in NARS. The process of internal resource allocation triggeredby different emotions based on NARS reasoning framework is proposed, and the design can be applied to any scene. The similarity and difference between human emotion and artificial intelligence emotion are discussed. At the same time, the advantages and disadvantages of the design and its theory are also discussed. A recent implementation of the NARS model, will be discussed with examples. and the emotion model has been tested preliminarily in a new version of OpenNARS. New Temporal Induction model, Anticipation model, Goal processing model, and Emotion model which is implemented in the new system will also be discussed in detail. The dissertation concludes with suggestions and ideas that are put forward forthe role of emotion in future human-computer interaction. / Computer and Information Science

Recent adaptationist accounts of human mental and physical health have reinvigorated the debate over the evolution of human intelligence. In the tradition of strong inference the current study was developed to determine which hypothesis; Rushton’s (2000) differential K theory, or Miller’s (2000a) fitness indicator model (F), better accounts for general intelligence ('g') in an undergraduate university population (N = 194). Due to the lengthy administration time of the test materials a newly developed 18-item short form of the Ravens Advanced Progressive Matrices (APM-18; Sefcek, Miller, & Figueredo, 2007) was used. There was a significant positive relationship between K and F (r = .31, p < .001), however no significant relationships were found between 'g' and either K or F (for each, r = -.06, p ≥ .05). While contrary to both hypotheses, these results may be explained in relation to antagonistic pleiotropy and a potential failure to derive within species comparisons directly from between species comparisons.

This study examines the impact of Artificial Intelligence on the Labour Market within the next decade. Methods and limitations in the technology and their correlation to work, as well as the possible developments likely to be seen in the coming decade, is presented. It also looks at whether Artificial General Intelligence (a system that meet human performance in all fields) could be invented in the next ten years. So far, methods like machine-, deep- and reinforcement learning has resulted in systems that sometimes exceed human performance but are narrow in skill and proficiency. Meaning that AGI is very unlikely to be achieved before 2030. AI is estimated to replace work in the production-, service-, care- and welfare-, transport-, and warehouse sector. The conclusion, however, is that transformation will happen in a pace such that society will be able manage it without the changes causing mass-unemployment.

In this study, the potential for artificially intelligent sapient life to be integrated into a Lutheran theological anthropology is investigated. The investigation is done via the means of a reconstruction and reactualisation of Lutheran anthropology, applied to the hypothetical scenario of artificial general intelligences having been created. The study takes its roots in questions of how intelligent life made by human artifice would interact with the Lutheran narrative-relational imago Dei paradigm, and what room there is within the Lutheran framework to integrate such intelligent life. In the study, the analysis will be threefold; with the first chapter dedicated to presenting the basis within Lutheran theology within which the rest of the study is conducted, the second chapter to identifying core points of conflict that may arise were artificial life to be introduced, and the third to finding preliminary solutions to these. Although the study is and must be hypothetical-speculative in nature, the conclusion is reached that there seems to be some manner of room for artificial intelligences to be integrated into a Lutheran way of understanding the imago Dei paradigm, albeit with some lingering issues that can quite hardly be solved entirely until the real dawn of artificial intelligence. Although some reservations remain, it therefore points towards the possibility of future artificial intelligences being Humanity’s theological equals, and leaves it to future studies to reach a more elaborate understanding of what that means and implies in practice, both ethical and dogmatic.

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