Designing Artificial Intelligence Equipped Social Decentralized Autonomous Organizations for Tackling Sextortion Cases Version 0.7

With the rapid diffusion of social networks in combination with mobile phones, a new social threat of sextortion has emerged, in which vulnerable young women are essentially blackmailed with their explicit shared multimedia content. The phenomenon of sextortion is now widely studied by psychologists, sociologists, criminologists, etc. The findings have been translated into scattered help from NGOs, specialized law enforcement units, and therapists, who usually do not coordinate their efforts among each other. This paper addresses the gap of lacking coordination systems to effectively and efficiently use modern information technologies that align the efforts of scattered and non-aligned sextortion help organizations. Consequently, this paper not only investigates the goals, incentives, and disincentives for a system design and development that not only governs effectively and efficiently diverse cases of sextortion victims, but also leverages artificial intelligence in a targeted manner. It explores how AI and, in particular, autonomous cognitive entities can improve victim profiles analysis, streamline support mechanisms, and provide intelligent insight into sextortion cases. Furthermore, the paper conceptually studies the extent to which such efforts can be monetized in a sustainable way. Following a novel design methodology for the design of trusted blockchain decentralized applications, the paper presents a set of conceptual requirements and system models based on which it is possible to deduce a best-practice technology stack for rapid implementation deployment

Design elements of conflict : A design study of a gamified smartphone application for employee onboarding

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Emerging Technology Adoption and Use : Consolidated Assignments from Spring 2020

Digitalization changes the world. Information systems, software applications and other technologies are in a central role in this change. They enable new work practices and processes, new business models and opportunities, initiate changes in how technologies are used, perceived and interpreted, and ultimately force individuals, organizations, and even societies at large to respond to those changes. Individuals, organizations, and societies have to somehow transform and adjust their old ways of doing things. Yet, not only technologies drive digital transformation. Increasing amounts of data that is produced by numerous sensors, applications, and systems account for the transformation as well. Such data is gathered and collected, merged together, and analyzed by different methods and tools; by using artificial intelligence, data analytics, or data science. The sense-making of such versatile data is of importance because not only can it be used to improve decision-making at workplaces but also, it can be utilized for the benefit of individuals and societies, in organizational and non-work settings. These views, transformation and smartness, pose several questions for information system (IS) research. In general, we might ask what actually is the smartness of individuals, organizations, or a society. We can even ask whether stakeholders possess the required abilities, skills and competences to enable and support the change. These, and other related questions arise due to fast evolving landscape of information technology, and information and technology. The nuanced understanding of Smart Transformation in IS has become even more critical due to governmental and organizational programs that foster smartness. This report summarizes research reports of students attending “Emerging Technology Adoption and Use” course in Tampere University. During the course, we focused on three emerging technologies. Extended Reality Blockchain Artificial Intelligence Each group collaborated on finding a common topic of interest. They focused on the adoption and/or use of a particular emerging technology in a setting of their own choosing. As you are about to see, the findings of each group emphasize different perspectives. These range from the negative effects of technology use to the opportunities and delights of information systems

How ChatGPT is changing digital marketing activities: The Aleluya’s Case.

openIn recent years, several terms related to artificial intelligence have come to the forefront of everyday conversations, leaving us both delighted and confused about its scope. Initially, this paper shows that AI is not something that was born sporadically in recent years, on the contrary it is something that has been worked on for more than half a decade and has had major milestones in its history. One of those milestones is ChatGPT, an AI-powered chatbot capable of generating human-like text responses in a conversational manner. This new technology holds great promise in almost every industry, and this paper focuses on evidencing the different scenarios in which ChatGPT can transform companies' marketing activities, making them more efficient, innovative and user-friendly. But it also considers its implications and challenges. Finally, a case study is shown in the Colombian startup Aleluya, in which an experiment was carried out implementing ChatGPT in their marketing activities in order to generate an appropriation of this new technology and to see in practice its advantages and disadvantages

Exploring the role of experience API in supporting new trends in Educational Technology: A literature review

Despite its growth in the area of educational technology, Experience API (xAPI) continues to be under-used as a solution across the different platforms in institutions and organizations. There is a lack of any detailed summary in the literature about the potential and the limitation of using xAPI in conjunction with learning platforms and technologies. This thesis examines the role of xAPI in promoting, shaping and supporting learning in organizational contexts. This discussion is developed by using cases reported in the literature and new cases from contemporary educational technologies. The thesis illustrates the role the standard plays within current major trends in digital learning and within the context of a broader ecosystem of learning platforms and technologies. It provides a useful and thorough account of xAPI and its potential to an audience of individuals responsible for implementing xAPI within organizations. xAPI provides to some extent a promise of improved impact to Performance Evaluation and Evaluating training Effectiveness. However, xAPI lacks concrete cases and examples to support its utilization in the fields of Learning Analytics, Performance Management, Predictive Learning and Workforce Planning. Keywords: Experience API (xAPI), Learning Management Systems, Learning Record Store, Learning Analytics, Microlearning, Evaluation Effectiveness, Predictive Learning, Adaptive Learning, Workforce Planning

Ohjelmointitehtävien klusterointi tarkistuksen ja tutkimisen tehostamiseksi

Programming courses often receive large quantities of program code submissions to exercises which, due to their large number, are graded and students provided feedback automatically. Teachers might never review these submissions therefore losing a valuable source of insight into student programming patterns. This thesis researches how these submissions could be reviewed efficiently using a software system, and a prototype, CodeClusters, was developed as an additional contribution of this thesis. CodeClusters' design goals are to allow the exploration of the submissions and specifically finding higher-level patterns that could be used to provide feedback to students. Its main features are full-text search and n-grams similarity detection model that can be used to cluster the submissions. Design science research is applied to evaluate CodeClusters' design and to guide the next iteration of the artifact and qualitative analysis, namely thematic synthesis, to evaluate the problem context as well as the ideas of using software for reviewing and providing clustered feedback. The used study method was interviews conducted with teachers who had experience teaching programming courses. Teachers were intrigued by the ability to review submitted student code and to provide more tailored feedback to students. The system, while still a prototype, is considered worthwhile to experiment on programming courses. A tool for analyzing and exploring submissions seems important to enable teachers to better understand how students have solved the exercises. Providing additional feedback can be beneficial to students, yet the feedback should be valuable and the students incentivized to read it