Design implications for designing with a collaborative AI

Janin Koch

Design implications for designing with a collaborative AI

Janin Koch^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

22 Citations (Scopus)

Abstract

This paper proposes a framework for a collaborative designing system from an interaction design perspective. Using the agent-based model from the mixed-initiative interaction framework as a starting point, an ideal interaction scenario in a web design context is described and implications for designing collaborative systems are presented. Previous work on machine learning and artificial intelligence for interaction design has already looked at recognition of designers' intent and combinatorial problem-solving in design. This paper, in contrast, focuses on the interaction design perspective of designing such a system, and introduces a framework that highlights requirements in this context. The framework uses the notion of task model and world model from agent-based models as a frame, and the resulting implications call for a stronger involvement of designers in the process.

Original language	English
Title of host publication	SS-17-01: Artificial Intelligene for the Social Good; SS-17-02: Computational Construction Grammar and Natural Language Understanding; SS-17-03: Computational Context: Why It's Important, What It Means, and Can It Be Computed?; SS-17-04: Designing the User Experience of Machine Learning Systems; SS-17-05: Interactive Multisensory Object Perception for Embodied Agents; SS-17-06: Learning from Observation of Humans; SS-17-07: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence; SS-17-08: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing
Publisher	AAAI Press
Pages	415-418
Number of pages	4
Volume	SS-17-01 - SS-17-08
ISBN (Electronic)	9781577357797
Publication status	Published - 2017
MoE publication type	A4 Conference publication
Event	AAAI Spring Symposium - Stanford, United States Duration: 27 Mar 2017 → 29 Mar 2017

Conference

Conference	AAAI Spring Symposium
Country/Territory	United States
City	Stanford
Period	27/03/2017 → 29/03/2017

Access to Document

https://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15382/14577

Cite this

Koch, J. (2017). Design implications for designing with a collaborative AI. In SS-17-01: Artificial Intelligene for the Social Good; SS-17-02: Computational Construction Grammar and Natural Language Understanding; SS-17-03: Computational Context: Why It's Important, What It Means, and Can It Be Computed?; SS-17-04: Designing the User Experience of Machine Learning Systems; SS-17-05: Interactive Multisensory Object Perception for Embodied Agents; SS-17-06: Learning from Observation of Humans; SS-17-07: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence; SS-17-08: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing (Vol. SS-17-01 - SS-17-08, pp. 415-418). AAAI Press. https://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15382/14577

Koch, Janin. / Design implications for designing with a collaborative AI. SS-17-01: Artificial Intelligene for the Social Good; SS-17-02: Computational Construction Grammar and Natural Language Understanding; SS-17-03: Computational Context: Why It's Important, What It Means, and Can It Be Computed?; SS-17-04: Designing the User Experience of Machine Learning Systems; SS-17-05: Interactive Multisensory Object Perception for Embodied Agents; SS-17-06: Learning from Observation of Humans; SS-17-07: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence; SS-17-08: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing. Vol. SS-17-01 - SS-17-08 AAAI Press, 2017. pp. 415-418

@inproceedings{90f7d65995184beba41422035ac6781b,

title = "Design implications for designing with a collaborative AI",

abstract = "This paper proposes a framework for a collaborative designing system from an interaction design perspective. Using the agent-based model from the mixed-initiative interaction framework as a starting point, an ideal interaction scenario in a web design context is described and implications for designing collaborative systems are presented. Previous work on machine learning and artificial intelligence for interaction design has already looked at recognition of designers' intent and combinatorial problem-solving in design. This paper, in contrast, focuses on the interaction design perspective of designing such a system, and introduces a framework that highlights requirements in this context. The framework uses the notion of task model and world model from agent-based models as a frame, and the resulting implications call for a stronger involvement of designers in the process.",

author = "Janin Koch",

year = "2017",

language = "English",

volume = "SS-17-01 - SS-17-08",

pages = "415--418",

booktitle = "SS-17-01: Artificial Intelligene for the Social Good; SS-17-02: Computational Construction Grammar and Natural Language Understanding; SS-17-03: Computational Context: Why It's Important, What It Means, and Can It Be Computed?; SS-17-04: Designing the User Experience of Machine Learning Systems; SS-17-05: Interactive Multisensory Object Perception for Embodied Agents; SS-17-06: Learning from Observation of Humans; SS-17-07: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence; SS-17-08: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing",

publisher = "AAAI Press",

address = "United States",

note = "AAAI Spring Symposium ; Conference date: 27-03-2017 Through 29-03-2017",

}

Koch, J 2017, Design implications for designing with a collaborative AI. in SS-17-01: Artificial Intelligene for the Social Good; SS-17-02: Computational Construction Grammar and Natural Language Understanding; SS-17-03: Computational Context: Why It's Important, What It Means, and Can It Be Computed?; SS-17-04: Designing the User Experience of Machine Learning Systems; SS-17-05: Interactive Multisensory Object Perception for Embodied Agents; SS-17-06: Learning from Observation of Humans; SS-17-07: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence; SS-17-08: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing. vol. SS-17-01 - SS-17-08, AAAI Press, pp. 415-418, AAAI Spring Symposium, Stanford, California, United States, 27/03/2017. <https://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15382/14577>

Design implications for designing with a collaborative AI. / Koch, Janin.
SS-17-01: Artificial Intelligene for the Social Good; SS-17-02: Computational Construction Grammar and Natural Language Understanding; SS-17-03: Computational Context: Why It's Important, What It Means, and Can It Be Computed?; SS-17-04: Designing the User Experience of Machine Learning Systems; SS-17-05: Interactive Multisensory Object Perception for Embodied Agents; SS-17-06: Learning from Observation of Humans; SS-17-07: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence; SS-17-08: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing. Vol. SS-17-01 - SS-17-08 AAAI Press, 2017. p. 415-418.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

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AU - Koch, Janin

PY - 2017

Y1 - 2017

N2 - This paper proposes a framework for a collaborative designing system from an interaction design perspective. Using the agent-based model from the mixed-initiative interaction framework as a starting point, an ideal interaction scenario in a web design context is described and implications for designing collaborative systems are presented. Previous work on machine learning and artificial intelligence for interaction design has already looked at recognition of designers' intent and combinatorial problem-solving in design. This paper, in contrast, focuses on the interaction design perspective of designing such a system, and introduces a framework that highlights requirements in this context. The framework uses the notion of task model and world model from agent-based models as a frame, and the resulting implications call for a stronger involvement of designers in the process.

AB - This paper proposes a framework for a collaborative designing system from an interaction design perspective. Using the agent-based model from the mixed-initiative interaction framework as a starting point, an ideal interaction scenario in a web design context is described and implications for designing collaborative systems are presented. Previous work on machine learning and artificial intelligence for interaction design has already looked at recognition of designers' intent and combinatorial problem-solving in design. This paper, in contrast, focuses on the interaction design perspective of designing such a system, and introduces a framework that highlights requirements in this context. The framework uses the notion of task model and world model from agent-based models as a frame, and the resulting implications call for a stronger involvement of designers in the process.

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M3 - Conference article in proceedings

AN - SCOPUS:85028695131

VL - SS-17-01 - SS-17-08

SP - 415

EP - 418

BT - SS-17-01: Artificial Intelligene for the Social Good; SS-17-02: Computational Construction Grammar and Natural Language Understanding; SS-17-03: Computational Context: Why It's Important, What It Means, and Can It Be Computed?; SS-17-04: Designing the User Experience of Machine Learning Systems; SS-17-05: Interactive Multisensory Object Perception for Embodied Agents; SS-17-06: Learning from Observation of Humans; SS-17-07: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence; SS-17-08: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing

PB - AAAI Press

T2 - AAAI Spring Symposium

Y2 - 27 March 2017 through 29 March 2017

ER -

Koch J. Design implications for designing with a collaborative AI. In SS-17-01: Artificial Intelligene for the Social Good; SS-17-02: Computational Construction Grammar and Natural Language Understanding; SS-17-03: Computational Context: Why It's Important, What It Means, and Can It Be Computed?; SS-17-04: Designing the User Experience of Machine Learning Systems; SS-17-05: Interactive Multisensory Object Perception for Embodied Agents; SS-17-06: Learning from Observation of Humans; SS-17-07: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence; SS-17-08: Wellbeing AI: From Machine Learning to Subjectivity Oriented Computing. Vol. SS-17-01 - SS-17-08. AAAI Press. 2017. p. 415-418

Design implications for designing with a collaborative AI

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