| 1. |
- Gutsche, Linda, et al.
(författare)
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The value of knowledge : joining reward and epistemic certainty optimisation for anxiety-sensitive planning
- 2024
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Ingår i: Autonomous agents and multiagent systems. - : Springer. - 9783031562549 - 9783031562556 ; , s. 30-42
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Bokkapitel (refereegranskat)abstract
- Anxiety is one of the most basic emotional states and also the most common disorder. AI agents however are typically focused on maximising performance, concentrating on expected values and disregarding the degree of exposure to uncertainty. This paper introduces a formalism derived from Partially Observable Markov Decision Processes (POMDPs) to give the first model based on cognitive psychology of the anxiety induced by epistemic uncertainty (i.e. the lack of precision of knowledge about the current state of the world). An algorithm to generate policies balancing reward maximisation and anxiety reduction is given. It is then used on a classical example to demonstrate how this can lead in some cases to a dramatic reduction of epistemic uncertainty for nearly no cost and thus a more human-friendly reward optimisation. The empirical validation shows results reminiscent of behaviours that cognitive psychology identifies as coping mechanisms to anxiety.
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| 2. |
- Horned, Arvid, et al.
(författare)
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From threatening pasts to hopeful futures : a review of agent-based models of anxiety
- 2023
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Ingår i: Advances in social simulation. - : Springer Nature. - 9783031349195 - 9783031349225 - 9783031349201 ; , s. 139-152
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Konferensbidrag (refereegranskat)abstract
- Despite being understated, anxiety is a critical factor affecting all levels of society, directly impacting individual decisions and with well-identified ramifications on social play, social constructs, and collective outcomes, as well as being a significant direct social toll tied to yearly trillion-USD social cost. Through a systematic literature review of social simulation research featuring models of anxiety, this paper frames the state of the art on anxiety modelling, and identifies trends and patterns in bibliographic indicators, aspects of anxiety that are modelled, how they are modelled, and their purpose and integration within agent based models. Based on these findings, this paper proposes a way forward as to structure the field as to enable the social simulation community as a whole to cover this critical aspect.
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| 3. |
- Horned, Arvid, et al.
(författare)
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Models of anxiety for agent deliberation : the benefits of anxiety-sensitive agents blue sky ideas track
- 2023
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Ingår i: Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023). - : International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). ; , s. 1761-1767
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Konferensbidrag (refereegranskat)abstract
- Anxiety is one of the most critical sources of harm to psychological wellbeing, tied to an array of issues, from discomfort and maladaptive coping to severe pathological disorders -making of anxiety one of the largest economic and social healthcare expenses. AI systems are not neutral to the exposure of individuals and societies to anxiety, and the current emphasis on performance-optimization of current AI systems arguably sets a pathway for a systemic rise of anxiety. As a response to this trend, towards further increasing the human-centeredness of existing applications, this paper is dedicated to depicting the landscape of open challenges, high-impact applications, and promising solutions for designing anxiety-sensitive agents. This paper first circumvents the key components of anxiety through a summary of the extensive psychology literature on anxiety; then shows the feasibility of building agent-based models by putting forward an example of a logical model of anxiety; and last, examines current research fields through the lens of anxiety, highlighting categories of prospective applications and techniques which stand to benefit from anxiety-sensitive agents.
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| 4. |
- Javed, Rana Tallal, et al.
(författare)
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Get out of the BAG! Silos in AI ethics education : unsupervised topic modeling analysis of global AI curricula (extended abstract)
- 2023
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Ingår i: Proceedings of the thirty-second international joint conference on artificial intelligence. - : International Joint Conferences on Artificial Intelligence. - 9781956792034 ; , s. 6905-6909
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Konferensbidrag (refereegranskat)abstract
- This study explores the topics and trends of teaching AI ethics in higher education, using Latent Dirichlet Allocation as the analysis tool. The analyses included 166 courses from 105 universities around the world. Building on the uncovered patterns, we distil a model of current pedagogical practice, the BAG model (Build, Assess, and Govern), that combines cognitive levels, course content, and disciplines. The study critically assesses the implications of this teaching paradigm and challenges practitioners to reflect on their practices and move beyond stereotypes and biases.
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| 5. |
- Javed, Rana Tallal, et al.
(författare)
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Get out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula
- 2022
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Ingår i: Journal of Artificial Intelligence Research. - : AI Access Foundation. - 1076-9757 .- 1943-5037. ; 73, s. 933-965
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Tidskriftsartikel (refereegranskat)abstract
- The domain of Artificial Intelligence (AI) ethics is not new, with discussions going back at least 40 years. Teaching the principles and requirements of ethical AI to students is considered an essential part of this domain, with an increasing number of technical AI courses taught at several higher-education institutions around the globe including content related to ethics. By using Latent Dirichlet Allocation (LDA), a generative probabilistic topic model, this study uncovers topics in teaching ethics in AI courses and their trends related to where the courses are taught, by whom, and at what level of cognitive complexity and specificity according to Bloom’s taxonomy. In this exploratory study based on unsupervised machine learning, we analyzed a total of 166 courses: 116 from North American universities, 11 from Asia, 36 from Europe, and 10 from other regions. Based on this analysis, we were able to synthesize a model of teaching approaches, which we call BAG (Build, Assess, and Govern), that combines specific cognitive levels, course content topics, and disciplines affiliated with the department(s) in charge of the course. We critically assess the implications of this teaching paradigm and provide suggestions about how to move away from these practices. We challenge teaching practitioners and program coordinators to reflect on their usual procedures so that they may expand their methodology beyond the confines of stereotypical thought and traditional biases regarding what disciplines should teach and how.
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| 6. |
- Jensen, Maarten, et al.
(författare)
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Dynamic context-sensitive deliberation
- 2024
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Ingår i: Multi-Agent-Based simulation XXIV. - : Springer Nature. - 9783031610332 - 9783031610349 ; , s. 112-126
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Bokkapitel (refereegranskat)abstract
- Truly realistic models for policy making require multiple aspects of life, realistic social behaviour and the ability to simulate millions of agents. Current state of the art Agent-based models only achieve two of these requirements. Models that prioritise realistic social behaviour are not easily scalable because the complex deliberation takes into account all information available at each time step for each agent. Our framework uses context to considerably narrow down the information that has to be considered. A key property of the framework is that it can dynamically slide between fast deliberation and complex deliberation. Context is expanded based on necessity. We introduce the elements of the framework, describe the architecture and show a proof-of-concept implementation. We give first steps towards validation using this implementation.
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| 7. |
- Jensen, Maarten, et al.
(författare)
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Towards Efficient Context-Sensitive Deliberation
- 2022
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Ingår i: Advances in Social Simulation. - Cham : Springer Science+Business Media B.V.. - 9783030928421 - 9783030928438 ; , s. 409-421
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Konferensbidrag (refereegranskat)abstract
- We propose a context-sensitive deliberation framework where the decision context does not deliver an action straight away, but where rather the decision context and agent characteristics influence the type of deliberation and type of information evaluated which will affect the final decision. The framework is based on the Contextual Action Framework for Computational Agents (CAFCA). Our framework also tailors the deliberation type used to the decision context the agent finds itself in, starting from the least cognitive taxing deliberation types unless the context requires more complex deliberation types. As a proof-of-concept the paper shows how context and information relevance can be used to conceptually expand the deliberation system of an agent.
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| 8. |
- Kreulen, Kurt, et al.
(författare)
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How culture influences individual behavior during a pandemic : a social simulation of the COVID-19 crisis
- 2022
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Ingår i: JASSS. - : University of Surrey. - 1460-7425. ; 25:3
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Tidskriftsartikel (refereegranskat)abstract
- Since its first appearance in Wuhan (China), countries have been employing, to varying degrees of success, a series of non-pharmaceutical interventions aimed at limiting the spread of SARS-CoV-2 within their populations. In this article, we build on scientific work that demonstrates that culture is part of the explanation for the observed variability between countries in their ability to effectively control the transmission of SARS-CoV-2. We present a theoretical framework of how culture influences decision-making at the level of the individual. This conceptualization is formalized in an agent-based model that simulates how cultural factors can combine to produce differences across populations in terms of the behavioral responses of individuals to the COVID-19 crisis. We illustrate that, within our simulated environment, the culturally-dependent willingness of people to comply with public health related measures might constitute an important determinant of differences in infection dynamics across populations. Our model generates the highest rates of non-compliance within cultures marked as individualist, progressive and egalitarian. Our model illustrates the potential role of culture as a population-level predictor of infections associated with COVID-19. In doing so, the model, and theoretical framework on which it is based, may inform future studies aimed at incorporating the effect of culture on individual decision-making processes during a pandemic within social simulation models.
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| 9. |
- Lorig, Fabian, et al.
(författare)
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Agent-based social simulation for policy making
- 2023
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Ingår i: Human-centered artificial intelligence. - : Springer Nature. - 9783031243486 ; , s. 391-414, s. 391-414
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Konferensbidrag (refereegranskat)abstract
- In agent-based social simulations (ABSS), an artificial population of intelligent agents that imitate human behavior is used to investigate complex phenomena within social systems. This is particularly useful for decision makers, where ABSS can provide a sandpit for investigating the effects of policies prior to their implementation. During the Covid-19 pandemic, for instance, sophisticated models of human behavior enable the investigation of the effects different interventions can have and even allow for analyzing why a certain situation occurred or why a specific behavior can be observed. In contrast to other applications of simulation, the use for policy making significantly alters the process of model building and assessment, and requires the modelers to follow different paradigms. In this chapter, we report on a tutorial that was organized as part of the ACAI 2021 summer school on AI in Berlin, with the goal of introducing agent-based social simulation as a method for facilitating policy making. The tutorial pursued six Intended Learning Outcomes (ILOs), which are accomplished by three sessions, each of which consists of both a conceptual and a practical part. We observed that the PhD students participating in this tutorial came from a variety of different disciplines, where ABSS is mostly applied as a research method. Thus, they do often not have the possibility to discuss their approaches with ABSS experts. Tutorials like this one provide them with a valuable platform to discuss their approaches, to get feedback on their models and architectures, and to get impulses for further research.
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| 10. |
- Vanhée, Loïs, Dr., et al.
(författare)
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Anxiety-sensitive planning : from formal foundations to algorithms and applications
- 2022
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Ingår i: Proceedings of the thirty-second international conference on automated planning and scheduling. - : Association for the Advancement of Artificial Intelligence. - 9781577358749 ; , s. 730-740
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Konferensbidrag (refereegranskat)abstract
- Anxiety is the most prominent source of stress, harmful behaviours, and psychological disorders. AI systems, usually built for maximizing performance, increase the worldwide exposition to anxiety. This foundational paper introduces Anxiety-Aware Markov Decision Processes (AA-MDPs), the first formalism rooted in fundamental psychology research for modelling the anxiety tied to policies. In addition, this paper formalizes models and practical polynomial algorithms for generating anxiety-sensitive policies. Empirical validation demonstrates that AA-MDPs policies replicate the influence of anxiety on human decision-making observed by fundamental psychology research. Last, this paper demonstrates that AA-MDPs are directly applicable for social good, through a real-world use case (Anxiety-Sensitive Itinerary Planning), the immediate applicability for augmenting any formerly-defined MDP model with anxiety-awareness, and direct tracks developing future high-impact models.
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