It Is Your Turn: Collaborative Ideation With a Co-Creative Robot through Sketch

Lin, Yuyu; Guo, Jiahao; Chen, Yang; Yao, Cheng; Ying, Fangtian

doi:10.1145/3313831.3376258

Cited by 70 publications

(23 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A study conducted by Santhanam et al [ 68 ] investigated the effects of cognitive biases when evaluating the outputs of conversational agents. Lin et al [ 69 ] investigated the better approach for collaborative ideation from a physical robot and a virtual agent. Pfau et al [ 70 ] investigated the appropriateness of using bots in games when real players drop due to various reasons.…”

Section: Classifying Hcml Researchmentioning

confidence: 99%

“…Given that the majority in those sectors are not AI experts developing AI systems for them requires us to investigate the human aspect of such systems. Our analysis shows that application domains have specifically targeted gaming [63,70,165,174,211], interactive technologies [69,112,113,118,130,131,[133][134][135]137,140,144,152,153,155,212,213], medicine [49,57,67,110,114,180,192,193,203,214,215], psychiatry [98], music [65,83,85,102,153], sports [126], dating [60], video production [84], assistive technologies [2,80,86,88,89,…”

Section: Application Domainsmentioning

confidence: 99%

See 1 more Smart Citation

A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning

Kaluarachchi

Reis

Nanayakkara

2021

Sensors

View full text Add to dashboard Cite

After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or Machine Learning (ML) field is undergoing rapid growth concerning research and real-world application development. Deep Learning has generated complexities in algorithms, and researchers and users have raised concerns regarding the usability and adoptability of Deep Learning systems. These concerns, coupled with the increasing human-AI interactions, have created the emerging field that is Human-Centered Machine Learning (HCML). We present this review paper as an overview and analysis of existing work in HCML related to DL. Firstly, we collaborated with field domain experts to develop a working definition for HCML. Secondly, through a systematic literature review, we analyze and classify 162 publications that fall within HCML. Our classification is based on aspects including contribution type, application area, and focused human categories. Finally, we analyze the topology of the HCML landscape by identifying research gaps, highlighting conflicting interpretations, addressing current challenges, and presenting future HCML research opportunities.

show abstract

Section: Classifying Hcml Researchmentioning

confidence: 99%

Section: Application Domainsmentioning

confidence: 99%

A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning

Kaluarachchi

Reis

Nanayakkara

2021

Sensors

View full text Add to dashboard Cite

show abstract

“…In their study, the robot's and the human's creativity share the same definition of being unexpected, novel product creation. Meanwhile, in the study of co-creativity (Lin et al, 2020), the focus is on facilitating the robot's creativity by getting feedback from the user while collaborating to draw a figure. The main point is to lead the robot to more creative outcomes (Hu et al, 2021), since the robot mostly creates ideas during collaboration.…”

Section: Creativity In Roboticsmentioning

confidence: 99%

“…The majority of the examples we saw in robotics use interaction patterns to support users' creativity. Robots adopt the role of either a supportive agent that facilitates the user's creativity (Elgarf et al, 2021;Alves-Oliveira et al, 2019) or a creative peer that is collaborating with the user on a creative task (Law et al, 2019;Lin et al, 2020;Hu et al, 2021). In that sense, all of the examples put creative thinking of the user as an aim of the robot.…”

Section: Introductionmentioning

confidence: 99%

Exploring Behavioral Creativity of a Proactive Robot

Buyukgoz

Pandey²,

Chamoux

et al. 2021

Front. Robot. AI

View full text Add to dashboard Cite

Creativity, in one sense, can be seen as an effort or action to bring novelty. Following this, we explore how a robot can be creative by bringing novelty in a human–robot interaction (HRI) scenario. Studies suggest that proactivity is closely linked with creativity. Proactivity can be defined as acting or interacting by anticipating future needs or actions. This study aims to explore the effect of proactive behavior and the relation of such behaviors to the two aspects of creativity: 1) the perceived creativity observed by the user in the robot’s proactive behavior and 2) creativity of the user by assessing how creativity in HRI can be shaped or influenced by proactivity. We do so by conducting an experimental study, where the robot tries to support the user on the completion of the task regardless of the end result being novel or not and does so by exhibiting anticipatory proactive behaviors. In our study, the robot instantiates a set of verbal communications as proactive robot behavior. To our knowledge, the study is among the first to establish and investigate the relationship between creativity and proactivity in the HRI context, based on user studies. The initial results have indicated a relationship between observed proactivity, creativity, and task achievement. It also provides valuable pointers for further investigation in this domain.

show abstract

“…Tools for assisting creativity are becoming more commonplace. New systems utilizing artificial intelligence (AI) methods to empower the tools themselves to be creative are stepping in different fields, including robots for playing music ( Hoffman and Weinberg, 2010 ; Weinberg et al, 2020 ) and singing ( Miranda, 2008 ), sketching ( Lin et al, 2020 ) and even fostering creativity in children ( Ali et al, 2019 ). These co-creative robots represent technological progress in machine engineering, artificial intelligence as well as human-machine interaction.…”

Section: Introductionmentioning

confidence: 99%

Embodiment in 18th Century Depictions of Human-Machine Co-Creativity

2021

View full text Add to dashboard Cite

Artificial intelligence has a rich history in literature; fiction has shaped how we view artificial agents and their capacities in the real world. This paper looks at embodied examples of human-machine co-creation from the literature of the Long 18th Century (1,650–1,850), examining how older depictions of creative machines could inform and inspire modern day research. The works are analyzed from the perspective of design fiction with special focus on the embodiment of the systems and the creativity exhibited by them. We find that the chosen examples highlight the importance of recognizing the environment as a major factor in human-machine co-creative processes and that some of the works seem to precede current examples of artificial systems reaching into our everyday lives. The examples present embodied interaction in a positive, creativity-oriented way, but also highlight ethical risks of human-machine co-creativity. Modern day perceptions of artificial systems and creativity can be limited to some extent by the technologies available; fictitious examples from centuries past allow us to examine such limitations using a Design Fiction approach. We conclude by deriving four guidelines for future research from our fictional examples: 1) explore unlikely embodiments; 2) think of situations, not systems; 3) be aware of the disjunction between action and appearance; and 4) consider the system as a situated moral agent.

show abstract

It Is Your Turn: Collaborative Ideation With a Co-Creative Robot through Sketch

Cited by 70 publications

References 44 publications

A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning

A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning

Exploring Behavioral Creativity of a Proactive Robot

Embodiment in 18th Century Depictions of Human-Machine Co-Creativity

Contact Info

Product

Resources

About