Ball-AR: Fostering Playful Co-Located Interaction Through Environment-centric Physical Activity with AR

We present Ball-AR, an augmented reality (AR) game where two players in the same physical space attempt to hit each other with virtual dodgeballs overlaid on the physical world. Researchers have studied AR's potential for fostering co-located interaction and physical activity; however, they have not investigated the impacts of physical activity and physical environment on user experiences and interaction. We created an AR dodgeball game centered around encouraging physical activity and harnessing the physical environment. We then evaluated the game with five dyads to analyze the impacts of these design choices on the quality of gameplay and interaction between players. We found that physical activity and the shared physical space created memorable experiences and interactions among participants, although participants desired a more augmented and immersive experience

Diagnosing and Debiasing Corpus-Based Political Bias and Insults in GPT2

The training of large language models (LLMs) on extensive, unfiltered corpora sourced from the internet is a common and advantageous practice. Consequently, LLMs have learned and inadvertently reproduced various types of biases, including violent, offensive, and toxic language. However, recent research shows that generative pretrained transformer (GPT) language models can recognize their own biases and detect toxicity in generated content, a process referred to as self-diagnosis. In response, researchers have developed a decoding algorithm that allows LLMs to self-debias, or reduce their likelihood of generating harmful text. This study investigates the efficacy of the diagnosing-debiasing approach in mitigating two additional types of biases: insults and political bias. These biases are often used interchangeably in discourse, despite exhibiting potentially dissimilar semantic and syntactic properties. We aim to contribute to the ongoing effort of investigating the ethical and social implications of human-AI interaction.Comment: 9 page