AI-powered emotion recognition, typing with thoughts or eavesdropping virtual assistants: three non-fictional examples illustrate how AI may impact society. AI-related products and services... Show moreAI-powered emotion recognition, typing with thoughts or eavesdropping virtual assistants: three non-fictional examples illustrate how AI may impact society. AI-related products and services increasingly find their way into daily life. Are the EU's fundamental rights to privacy and data protection equipped to protect individuals effectively? In addressing this question, the dissertation concludes that no new legal framework is needed. Instead, adjustments are required. First, the extent of adjustments depends on the AI discipline. There is nothing like 'the AI'. AI covers various concepts, including the disciplines machine learning, natural language processing, computer vision, affective computing and automated reasoning. Second, the extent of adjustments depends on the type of legal problem: legal provisions are violated (type 1), cannot be enforced (type 2) or are not fit for purpose (type 3). Type 2 and 3 problems require either adjustments of current provisions or new judicial interpretations. Two instruments might be helpful for more effective legislation: rebuttable presumptions and reversal of proof. In some cases, the solution is technical, not legal. Research in AI should solve reasoning deficiencies in AI systems and their lack of common sense. Show less
In this thesis we have studied the influence of emotion on learning. We have used computational modelling techniques to do so, more specifically, the reinforcement learning paradigm. Emotion is... Show moreIn this thesis we have studied the influence of emotion on learning. We have used computational modelling techniques to do so, more specifically, the reinforcement learning paradigm. Emotion is modelled as artificial affect, a measure that denotes the positiveness versus negativeness of a situation to an artificial agent in a reinforcement learning setting. We have done a range of different experiments to study the effect of affect on learning, including the effect on learning if affect is used to control the exploration behaviour of the agent and the effect on learning when affect is communicated by a human (though real-time analysis of that human__s facial expressions) to a simulated robot. We conclude that affect is a useful concept to consider in adaptive agents that learn based on reinforcement learning and that in some cases affect can indeed help the learning process. Further, affective modelling in this way can help understand the psychological processes that underlie influences of affect on cognition. Finally, we have developed a formal notation for a specific type of emotion theory, i.e., cognitive appraisal theory. Show less
