Anthropomorphization in the context of human cooperation with intelligent machines

Intelligent machines have a profound impact on individuals and society. We show how human-machine cooperation plays an important role in the transformation that is taking place and should therefore be a key focus of machine behaviour. In this context, we discuss algorithm aversion and the human reluctance to cooperate with (intelligent) machines. There is a transparency-efficiency trade-off regarding human-machine cooperation as misguiding humans into believing that their cooperation partner was human increases efficiency. We argue that the human tendency to anthropomorphize machines can be used to avoid the ethical difficulties that would arise from a lack of transparency. Influencing human interaction with a machine through humanoid features is the anthropomorphization nudge. We argue that machines should bear humanoid features only if there is a legitimate reason for this. The question when humanoid features are used should be made on a use-case basis. We finally present a study proposal to test the ability of humans to distinguish machines into different categories depending on whether they are endowed with humanoid features

Towards a Virtual Collaborator in Online Collaboration from an Organizations’ Perspective

In this empiric study, we present the specifications of virtual collaboration in times of the Covid-19 pandemic in an organization that worked mostly co-located beforehand, and requirements for a virtual collaborator (VC) resulting from those specifications. Related work shows that a VCs can support virtual teams in achieving their goals and promote creative work. We extend this with insights from practice by observing creative and collaborative workshops in the automotive industry and conducting interviews with facilitators and participants of these workshops. Subsequently, we identify the challenges that participants face in virtual collaboration, and derive design guidelines for a VC to address them. Main problems arise due to the virtual interaction lacking nonverbal communication and in the preparation phase that requires more planning and effort. A VC could help by influencing group cohesion and build networks between the participants, influencing the virtual working environment as well as contributing to the contents

Responding to human full-body gestures embedded in motion data streams.

 This research created a neural-network enabled artificially intelligent performing agent that was able to learn to dance and recognise movement through a rehearsal and performance process with a human dancer. The agent exhibited emergent dance behaviour and successfully engaged in a live, semi-improvised dance performance with the human dancer

Gender in 21st century SF cinema : 50 titles

This e-book has been written by the 8 students enrolled in the course 'Gender Studies: New Sexualities/New Textualities' (Spring 2018-19) of the MA in English Studies (UAB). The teacher, Sara Martín, is also the e-book's editor and a contributor. In this e-book you will find an analysis of the gender issues in 50 SF produced between 2001-2018. All the films use English as their only or main language. The purpose of the e-book is to raise awareness about the need for more diversity in gender representation but also to call attention about the limited presence of women in general and of LGTBI+ persons in the ranks of the directors, screen playwrights, and producers in current cinema, not only SF but also all the other genres

Evolving Models From Observed Human Performance

To create a realistic environment, many simulations require simulated agents with human behavior patterns. Manually creating such agents with realistic behavior is often a tedious and time-consuming task. This dissertation describes a new approach that automatically builds human behavior models for simulated agents by observing human performance. The research described in this dissertation synergistically combines Context-Based Reasoning, a paradigm especially developed to model tactical human performance within simulated agents, with Genetic Programming, a machine learning algorithm to construct the behavior knowledge in accordance to the paradigm. This synergistic combination of well-documented AI methodologies has resulted in a new algorithm that effectively and automatically builds simulated agents with human behavior. This algorithm was tested extensively with five different simulated agents created by observing the performance of five humans driving an automobile simulator. The agents show not only the ability/capability to automatically learn and generalize the behavior of the human observed, but they also capture some of the personal behavior patterns observed among the five humans. Furthermore, the agents exhibited a performance that was at least as good as agents developed manually by a knowledgeable engineer

Ethics of Infinite Improbability and the Logic of Jokes : A look at the philosophical inquiry in Douglas Adams’ Hitchhiker-series

Master's thesis English EN500 - University of Agder 201