No abstract

Recent years have seen many breakthroughs in natural language processing (NLP), transitioning it from a mostly theoretical field to one with many real-world applications. Noting the rising number of applications of other machine learning and AI techniques with pervasive societal impact, we anticipate the rising importance of developing NLP technologies for social good. Inspired by theories in moral philosophy and global priorities research, we aim to promote a guideline for social good in the context of NLP. We lay the foundations via the moral philosophy definition of social good, propose a framework to evaluate the direct and indirect real-world impact of NLP tasks, and adopt the methodology of global priorities research to identify priority causes for NLP research. Finally, we use our theoretical framework to provide some practical guidelines for future NLP research for social good. 1

Using haptic interfaces to assist the training of skills within the curriculum of undergraduate dentists provides a unique opportunity to advance rendering algorithms and engineering of haptic devices. In this paper we use the dental context to explore a rendering technique called smoothed particle hydrodynamics (SPH) as a potential method to train students on appropriate techniques for insertion of filling material into a previously prepared (virtual) dental cavity. The paper also considers how problems of haptic rendering might be implemented on a Graphical Processing Unit (GPU) that operates in the haptics control loop. The filling simulation used 3000 particles to represent the cavity boundary (approx. 1400 particles), tool (approx. 42 particles) and filling material (approx. 1600 particles), running at an average of 447Hz. Novel smoothing function in SPH was developed and its flexibility is presented.

Recent years have seen many breakthroughs in natural language processing (NLP), transitioning it from a mostly theoretical field to one with many real-world applications. Noting the rising number of applications of other machine learning and AI techniques with pervasive societal impact, we anticipate the rising importance of developing NLP technologies for social good. Inspired by theories in moral philosophy and global priorities research, we aim to promote a guideline for social good in the context of NLP. We lay the foundations via the moral philosophy definition of social good, propose a framework to evaluate the direct and indirect real-world impact of NLP tasks, and adopt the methodology of global priorities research to identify priority causes for NLP research. Finally, we use our theoretical framework to provide some practical guidelines for future NLP research for social good. 1