Determining a Framework for the Generation and Evaluation of Ambient Intelligent Agent System Designs

Milica Pavlovic, Sotirios Kotsopoulos, Yihyun Lim, Scott Penman, Sara Colombo, Federico Casalegno

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    7 Citations (Scopus)

    Abstract

    The design and realization of Ambient Intelligence (AmI) systems using Artificially Intelligent (AI) agents is a rising field of research. However, the absence of clearly defined working criteria, supporting the generation and evaluation of AmI agent system designs, is a conspicuous obstacle to their advancement. The contribution of this paper is that we determine and test a framework for the generation and evaluation of AmI system designs, based on user experience and business criteria. Specifically, the process of designing a personal lighting AI agent, in collaboration with a leading lighting design company, is used as a case study to determine and test a framework for the generation and evaluation of AmI system designs based on feasibility and acceptability. First, we use storytelling videos to describe and communicate the user values and design scenarios to the stakeholders. Second, we generate design proposals for a lighting AmI agent based on five distinct systemic factors, namely: (a) the context of interaction; (b) the required system data; (c) the required sensing input; (d) the required user input; and (e) the desired system output. Finally third we determine an evaluation framework that is based on three distinct levels of in-built system intelligence, from lower to higher. The three levels reflect the feasibility and acceptability of the system. Feasibility is what a specific company is capable of producing, and in what timeframe. Acceptability is the potential of familiarity and trust that the users can feel while interacting with the AI agent.

    Original languageEnglish
    Title of host publicationProceedings of the Future Technologies Conference, FTC 2019 Volume 1
    EditorsKohei Arai, Rahul Bhatia, Supriya Kapoor
    PublisherSpringer
    Pages318-333
    Number of pages16
    ISBN (Print)9783030325190
    DOIs
    Publication statusPublished - 2020
    Event4th Future Technologies Conference, FTC 2019 - San Francisco, United States
    Duration: 24 Oct 201925 Oct 2019

    Publication series

    NameAdvances in Intelligent Systems and Computing
    Volume1069
    ISSN (Print)2194-5357
    ISSN (Electronic)2194-5365

    Conference

    Conference4th Future Technologies Conference, FTC 2019
    Country/TerritoryUnited States
    CitySan Francisco
    Period24/10/1925/10/19

    Bibliographical note

    Funding Information:
    Acknowledgments. This research is a result of collaboration between the MIT Design Lab and Signify. Doctoral research of the author Milica Pavlovic has been funded by TIM S.p.A., Services Innovation Department, Joint Open Lab Digital Life, Milan, Italy.

    Funding Information:
    This research is a result of collaboration between the MIT Design Lab and Signify. Doctoral research of the author Milica Pavlovic has been funded by TIM S.p.A., Services Innovation Department, Joint Open Lab Digital Life, Milan, Italy.

    Publisher Copyright:
    © 2020, Springer Nature Switzerland AG.

    Funding

    Acknowledgments. This research is a result of collaboration between the MIT Design Lab and Signify. Doctoral research of the author Milica Pavlovic has been funded by TIM S.p.A., Services Innovation Department, Joint Open Lab Digital Life, Milan, Italy. This research is a result of collaboration between the MIT Design Lab and Signify. Doctoral research of the author Milica Pavlovic has been funded by TIM S.p.A., Services Innovation Department, Joint Open Lab Digital Life, Milan, Italy.

    Keywords

    • Ambient Intelligence
    • Design vision
    • Evaluation framework
    • Generation framework
    • User Experience

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