AI and Cognitive Assistants in Collaboration

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    My Virtual Colleague: A State-of-the-Art Analysis of Conversational Agents for the Workplace
    ( 2020-01-07) Feng, Shengjia ; Buxmann, Peter
    Conversational interfaces at the workplace are not a new idea, but it is only the recent technological advancements that turned what was once a vision into near-future reality. Improved reliability and accuracy enable conversational systems to be used in higher stake environments, such as the workplace. In this work, we perform a literature review on concepts proposed to incorporate Conversational Agents (CA) into the workplace. We found 29 workplace CAs designed for workers that contribute to eight different application domains. Based on the studies of these CAs, we compiled a list of aspects to be considered when designing such CAs and identified starting points for further research.
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    Studying with the Help of Digital Tutors: Design Aspects of Conversational Agents that Influence the Learning Process
    ( 2020-01-07) Wellnhammer, Natalie ; Dolata, Mateusz ; Steigler, Susanne ; Schwabe, Gerhard
    Conversational agents such as Apple’s Siri or Amazon’s Alexa are becoming more and more prevalent. Almost every smart device comes equipped with such an agent. While on the one hand they can make menial everyday tasks a lot easier for people, there are also more sophisticated use cases in which conversational agents can be helpful. One of these use cases is tutoring in higher education. Several systems to support both formal and informal learning have been developed. There have been many studies about single characteristics of pedagogical conversational agents and how these influence learning outcomes. But what is still missing, is an overview and guideline for atomic design decisions that need to be taken into account when creating such a system. Based on a review of articles on pedagogical conversational agents, this paper provides an extension of existing classifications of characteristics as to include more fine-grained design aspects.
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    Factors Influencing Approval of Wikipedia Bots
    ( 2020-01-07) Dalgali, Ayse ; Crowston, Kevin
    Before a Wikipedia bot is allowed to edit, the operator of the bot must get approval. The Bot Approvals Group (BAG), a committee of Wikipedia bot developers, users and editors, discusses each bot request to reach consensus regarding approval or denial. We examine factors related to approval of a bot by analyzing 100 bots’ project pages. The results suggest that usefulness, value-based decision making and the bot’s status (e.g., automatic or manual) are related to approval. This study may contribute to understanding decision making regarding the human-automation boundary and may lead to developing more efficient bots.
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    Cluster Analysis of Musical Attributes for Top Trending Songs
    ( 2020-01-07) Al-Beitawi , Zayd ; Salehan, Mohammad ; Zhang, Sonya
    Music streaming services like Spotify have changed the way consumers listen to music. Understanding what attributes make certain songs trendy can help services to create a better customer experience as well as more effective marketing efforts. We performed cluster analysis on Top 100 Trending Spotify Song of 2017, with ten attributes, including danceability, energy, loudness, speechiness, acousticness, instrumentalness, Liveness, valence, tempo, and duration. The results show that music structures with high danceability and low instrumentalness increase the popularity of a song and lead them to chart-topping success.
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    Introduction to the Minitrack on AI and Cognitive Assistants in Collaboration
    ( 2020-01-07) Ebel, Philipp ; Bittner, Eva ; Oeste-Reiß, Sarah ; Söllner, Matthias