Improvisation for technically-oriented peoples

Teaching “soft” skills to technical people is just as important as learning “hard” skills. Improvisation techniques can also be used in teaching technical concepts such as cybersecurity, agile development, database design, programming concepts, and most importantly how to better one’s communication skills. In an age where rapid changes have become the norm, improvisation techniques can be used to help navigate the new challenges of the next generation careers, global interaction, and technologies. These techniques can easily be incorporated in other methodologies such as creative problem-solving and design thinking. There are clearly defined and flexible rules for improvising, which make it easier for technical persons to learn and use in their daily life and career.Enseñar las habilidades “blandas” a las personas técnicas es tan importante como aprender las habilidades “duras”. Las técnicas de improvisación también se pueden usar en la enseñanza de conceptos técnicos como la ciberseguridad, el desarrollo ágil, el diseño de bases de datos, los conceptos de programación y, lo más importante, cómo mejorar las habilidades de comunicación. En una era en la que los cambios rápidos se han convertido en la norma, las técnicas de improvisación pueden usarse para ayudar a navegar los nuevos desafíos de las carreras de la próxima generación, la interacción global y las tecnologías. Estas técnicas pueden incorporarse fácilmente en otras metodologías, como la resolución creativa de problemas y el pensamiento de diseño. Existen reglas claramente definidas y flexibles para la improvisación que facilitan que las personas técnicas aprendan y usen en su vida diaria y carrer

Event Representations for Automated Story Generation with Deep Neural Nets

Automated story generation is the problem of automatically selecting a sequence of events, actions, or words that can be told as a story. We seek to develop a system that can generate stories by learning everything it needs to know from textual story corpora. To date, recurrent neural networks that learn language models at character, word, or sentence levels have had little success generating coherent stories. We explore the question of event representations that provide a mid-level of abstraction between words and sentences in order to retain the semantic information of the original data while minimizing event sparsity. We present a technique for preprocessing textual story data into event sequences. We then present a technique for automated story generation whereby we decompose the problem into the generation of successive events (event2event) and the generation of natural language sentences from events (event2sentence). We give empirical results comparing different event representations and their effects on event successor generation and the translation of events to natural language.Comment: Submitted to AAAI'1

Social Bots: Human-Like by Means of Human Control?

Social bots are currently regarded an influential but also somewhat mysterious factor in public discourse and opinion making. They are considered to be capable of massively distributing propaganda in social and online media and their application is even suspected to be partly responsible for recent election results. Astonishingly, the term `Social Bot' is not well defined and different scientific disciplines use divergent definitions. This work starts with a balanced definition attempt, before providing an overview of how social bots actually work (taking the example of Twitter) and what their current technical limitations are. Despite recent research progress in Deep Learning and Big Data, there are many activities bots cannot handle well. We then discuss how bot capabilities can be extended and controlled by integrating humans into the process and reason that this is currently the most promising way to go in order to realize effective interactions with other humans.Comment: 36 pages, 13 figure

Euphonia:reflecting on the design of an AI-powered voice-controlled narrative game

This paper reflects on the design process for a work-in-progress AI-powered voice-controlled narrative game created by Innovation for Games and Media Enterprise (InGAME). This paper describes the steps which led to the final design decisions, and how the background research, research questions and initial prototyping may be traced through to the work-in-progress game. The design process is then reviewed for its suitability as a practice-based research and development workflow, before finally suggesting next steps the project will take