Publications

@article{difede_enhancing_2022,

title = {Enhancing exposure therapy for posttraumatic stress disorder (PTSD): a randomized clinical trial of virtual reality and imaginal exposure with a cognitive enhancer},

author = {JoAnn Difede and Barbara O. Rothbaum and Albert A. Rizzo and Katarzyna Wyka and Lisa Spielman and Christopher Reist and Michael J. Roy and Tanja Jovanovic and Seth D. Norrholm and Judith Cukor and Megan Olden and Charles E. Glatt and Francis S. Lee},

url = {https://www.nature.com/articles/s41398-022-02066-x},

doi = {10.1038/s41398-022-02066-x},

issn = {2158-3188},

year  = {2022},

date = {2022-12-01},

urldate = {2022-09-13},

journal = {Transl Psychiatry},

volume = {12},

number = {1},

pages = {299},

abstract = {Abstract Posttraumatic stress disorder (PTSD) is a significant public health issue. Yet, there are limited treatment options and no data to suggest which treatment will work for whom. We tested the efficacy of virtual reality exposure (VRE) or prolonged imaginal exposure (PE), augmented with D-cycloserine (DCS) for combat-related PTSD. As an exploratory aim, we examined whether brain-derived neurotrophic factor (BDNF) and fatty acid amide hydrolase (FAAH) moderated treatment response. Military personnel with PTSD ( n = 192) were recruited into a multisite double-blind randomized controlled trial to receive nine weeks of VRE or PE, with DCS or placebo. Primary outcome was the improvement in symptom severity. Randomization was stratified by comorbid depression (MDD) and site. Participants in both VRE and PE showed similar meaningful clinical improvement with no difference between the treatment groups. A significant interaction ( p = 0.45) suggested VRE was more effective for depressed participants (CAPS difference M = 3.51 [95% CI 1.17–5.86]},

keywords = {DTIC, MedVR, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{pauw_avatar_2022,

title = {The avatar will see you now: Support from a virtual human provides socio-emotional benefits},

author = {Lisanne S. Pauw and Disa A. Sauter and Gerben A. Kleef and Gale M. Lucas and Jonathan Gratch and Agneta H. Fischer},

url = {https://linkinghub.elsevier.com/retrieve/pii/S074756322200190X},

doi = {10.1016/j.chb.2022.107368},

issn = {07475632},

year  = {2022},

date = {2022-11-01},

urldate = {2022-09-28},

journal = {Computers in Human Behavior},

volume = {136},

pages = {107368},

keywords = {DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{gratch_power_2022,

title = {The power to harm: AI assistants pave the way to unethical behavior},

author = {Jonathan Gratch and Nathanael J. Fast},

url = {https://linkinghub.elsevier.com/retrieve/pii/S2352250X22001014},

doi = {10.1016/j.copsyc.2022.101382},

issn = {2352250X},

year  = {2022},

date = {2022-10-01},

urldate = {2022-09-28},

journal = {Current Opinion in Psychology},

volume = {47},

pages = {101382},

keywords = {AI, DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{adami_impact_2022,

title = {Impact of VR-Based Training on Human–Robot Interaction for Remote Operating Construction Robots},

author = {Pooya Adami and Patrick B. Rodrigues and Peter J. Woods and Burcin Becerik-Gerber and Lucio Soibelman and Yasemin Copur-Gencturk and Gale Lucas},

url = {https://ascelibrary.org/doi/10.1061/%28ASCE%29CP.1943-5487.0001016},

doi = {10.1061/(ASCE)CP.1943-5487.0001016},

issn = {0887-3801, 1943-5487},

year  = {2022},

date = {2022-05-01},

urldate = {2022-09-23},

journal = {J. Comput. Civ. Eng.},

volume = {36},

number = {3},

pages = {04022006},

keywords = {DTIC, UARC, Virtual Humans, VR},

pubstate = {published},

tppubtype = {article}

}

@article{fujiwara_synchrony_2022,

title = {Synchrony facilitates altruistic decision making for non-human avatars},

author = {Ken Fujiwara and Rens Hoegen and Jonathan Gratch and Norah E. Dunbar},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0747563221004027},

doi = {10.1016/j.chb.2021.107079},

issn = {07475632},

year  = {2022},

date = {2022-03-01},

urldate = {2022-09-28},

journal = {Computers in Human Behavior},

volume = {128},

pages = {107079},

keywords = {DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{de_visser_designing_2022,

title = {Designing Man’s New Best Friend: Enhancing Human-Robot Dog Interaction through Dog-Like Framing and Appearance},

author = {Ewart J. Visser and Yigit Topoglu and Shawn Joshi and Frank Krueger and Elizabeth Phillips and Jonathan Gratch and Chad C. Tossell and Hasan Ayaz},

url = {https://www.mdpi.com/1424-8220/22/3/1287},

doi = {10.3390/s22031287},

issn = {1424-8220},

year  = {2022},

date = {2022-02-01},

urldate = {2022-09-28},

journal = {Sensors},

volume = {22},

number = {3},

pages = {1287},

abstract = {To understand how to improve interactions with dog-like robots, we evaluated the importance of “dog-like” framing and physical appearance on interaction, hypothesizing multiple interactive benefits of each. We assessed whether framing Aibo as a puppy (i.e., in need of development) versus simply a robot would result in more positive responses and interactions. We also predicted that adding fur to Aibo would make it appear more dog-like, likable, and interactive. Twenty-nine participants engaged with Aibo in a 2 × 2 (framing × appearance) design by issuing commands to the robot. Aibo and participant behaviors were monitored per second, and evaluated via an analysis of commands issued, an analysis of command blocks (i.e., chains of commands), and using a T-pattern analysis of participant behavior. Participants were more likely to issue the “Come Here” command than other types of commands. When framed as a puppy, participants used Aibo’s dog name more often, praised it more, and exhibited more unique, interactive, and complex behavior with Aibo. Participants exhibited the most smiling and laughing behaviors with Aibo framed as a puppy without fur. Across conditions, after interacting with Aibo, participants felt Aibo was more trustworthy, intelligent, warm, and connected than at their initial meeting. This study shows the benefits of introducing a socially robotic agent with a particular frame and importance on realism (i.e., introducing the robot dog as a puppy) for more interactive engagement.},

keywords = {DTIC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{schuller_intelligent_2021,

title = {Intelligent Signal Processing for Affective Computing [From the Guest Editors]},

author = {Bjorn W. Schuller and Rosalind Picard and Elisabeth Andre and Jonathan Gratch and Jianhua Tao},

url = {https://ieeexplore.ieee.org/document/9591500/},

doi = {10.1109/MSP.2021.3096415},

issn = {1053-5888, 1558-0792},

year  = {2021},

date = {2021-11-01},

urldate = {2022-09-29},

journal = {IEEE Signal Process. Mag.},

volume = {38},

number = {6},

pages = {9--11},

keywords = {Emotions, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{horstmann_i_2021,

title = {I Just Wanna Blame Somebody, Not Something! Reactions to a Computer Agent Giving Negative Feedback Based on the Instructions of a Person},

author = {Aike C. Horstmann and Jonathan Gratch and Nicole C. Krämer},

url = {https://linkinghub.elsevier.com/retrieve/pii/S1071581921001014},

doi = {10.1016/j.ijhcs.2021.102683},

issn = {10715819},

year  = {2021},

date = {2021-06-01},

urldate = {2021-06-18},

journal = {International Journal of Human-Computer Studies},

pages = {102683},

abstract = {Previous research focused on differences between interacting with a person-controlled avatar and a computer-controlled virtual agent. This study however examines an aspiring form of technology called agent representative which constitutes a mix of the former two interaction partner types since it is a computer agent which was previously instructed by a person to take over a task on the person’s behalf. In an experimental lab study with a 2 x 3 between-subjects-design (N = 195), people believed to study together either with an agent representative, avatar, or virtual agent. The interaction partner was described to either possess high or low expertise, while always giving negative feedback regarding the participant’s performance. Results show small but interesting differences regarding the type of agency. People attributed the most agency and blame to the person(s) behind the software and reported the most negative affect when interacting with an avatar, which was less the case for a person’s agent representative and the least for a virtual agent. Level of expertise had no significant effect and other evaluation measures were not affected.},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{de_melo_heuristic_2021,

title = {Heuristic thinking and altruism toward machines in people impacted by COVID-19},

author = {Celso M. Melo and Jonathan Gratch and Frank Krueger},

url = {https://linkinghub.elsevier.com/retrieve/pii/S2589004221001966},

doi = {10.1016/j.isci.2021.102228},

issn = {25890042},

year  = {2021},

date = {2021-03-01},

urldate = {2021-04-14},

journal = {iScience},

volume = {24},

number = {3},

pages = {102228},

abstract = {Autonomous machines are poised to become pervasive, but most treat machines differently: we are willing to violate social norms and less likely to display altruism toward machines. Here, we report an unexpected effect that those impacted by COVID-19—as measured by a post-traumatic stress disorder scale—show a sharp reduction in this difference. Participants engaged in the dictator game with humans and machines and, consistent with prior research on disasters, those impacted by COVID-19 displayed more altruism to other humans. Unexpectedly, participants impacted by COVID-19 displayed equal altruism toward human and machine partners. A mediation analysis suggests that altruism toward machines was explained by an increase in heuristic thinking—reinforcing prior theory that heuristic thinking encourages people to treat machines like people—and faith in technology—perhaps reflecting long-term consequences on how we act with machines. These findings give insight, but also raise concerns, for the design of technology.},

keywords = {UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{mell_expert-model_2021,

title = {An expert-model and machine learning hybrid approach to predicting human-agent negotiation outcomes in varied data},

author = {Johnathan Mell and Markus Beissinger and Jonathan Gratch},

url = {http://link.springer.com/10.1007/s12193-021-00368-w},

doi = {10.1007/s12193-021-00368-w},

issn = {1783-7677, 1783-8738},

year  = {2021},

date = {2021-03-01},

urldate = {2021-04-15},

journal = {J Multimodal User Interfaces},

abstract = {We present the results of a machine-learning approach to the analysis of several human-agent negotiation studies. By combining expert knowledge of negotiating behavior compiled over a series of empirical studies with neural networks, we show that a hybrid approach to parameter selection yields promise for designing more effective and socially intelligent agents. Specifically, we show that a deep feedforward neural network using a theory-driven three-parameter model can be effective in predicting negotiation outcomes. Furthermore, it outperforms other expert-designed models that use more parameters, as well as those using other techniques (such as linear regression models or boosted decision trees). In a follow-up study, we show that the most successful models change as the dataset size increases and the prediction targets change, and show that boosted decision trees may not be suitable for the negotiation domain. We anticipate these results will have impact for those seeking to combine extensive domain knowledge with more automated approaches in human-computer negotiation. Further, we show that this approach can be a stepping stone from purely exploratory research to targeted human-behavioral experimentation. Through our approach, areas of social artificial intelligence that have historically benefited from expert knowledge and traditional AI approaches can be combined with more recent proven-effective machine learning algorithms.},

keywords = {DTIC, Machine Learning, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{lee_comparing_2021,

title = {Comparing mind perception in strategic exchanges: human-agent negotiation, dictator and ultimatum games},

author = {Minha Lee and Gale Lucas and Jonathan Gratch},

url = {http://link.springer.com/10.1007/s12193-020-00356-6},

doi = {10.1007/s12193-020-00356-6},

issn = {1783-7677, 1783-8738},

year  = {2021},

date = {2021-01-01},

urldate = {2021-04-15},

journal = {J Multimodal User Interfaces},

abstract = {Recent research shows that how we respond to other social actors depends on what sort of mind we ascribe to them. In a comparative manner, we observed how perceived minds of agents shape people’s behavior in the dictator game, ultimatum game, and negotiation against artificial agents. To do so, we varied agents’ minds on two dimensions of the mind perception theory: agency (cognitive aptitude) and patiency (affective aptitude) via descriptions and dialogs. In our first study, agents with emotional capacity garnered more allocations in the dictator game, but in the ultimatum game, agents’ described agency and affective capacity, both led to greater offers. In the second study on negotiation, agents ascribed with low-agency traits earned more points than those with high-agency traits, though the negotiation tactic was the same for all agents. Although patiency did not impact game points, participants sent more happy and surprise emojis and emotionally valenced messages to agents that demonstrated emotional capacity during negotiations. Further, our exploratory analyses indicate that people related only to agents with perceived affective aptitude across all games. Both perceived agency and affective capacity contributed to moral standing after dictator and ultimatum games. But after negotiations, only agents with perceived affective capacity were granted moral standing. Manipulating mind dimensions of machines has differing effects on how people react to them in dictator and ultimatum games, compared to a more complex economic exchange like negotiation. We discuss these results, which show that agents are perceived not only as social actors, but as intentional actors through negotiations, in contrast with simple economic games.},

keywords = {UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{gratch_promise_2021,

title = {The Promise and Peril of Automated Negotiators},

author = {Jonathan Gratch},

url = {https://onlinelibrary.wiley.com/doi/10.1111/nejo.12348},

doi = {10.1111/nejo.12348},

issn = {0748-4526, 1571-9979},

year  = {2021},

date = {2021-01-01},

urldate = {2021-04-14},

journal = {Negotiation Journal},

volume = {37},

number = {1},

pages = {13--34},

keywords = {ARO-Coop, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{gratch_field_2021,

title = {The field of Affective Computing: An interdisciplinary perspective},

author = {Jonathan Gratch},

url = {https://people.ict.usc.edu/~gratch/CSCI534/Readings/Gratch%20-%20The%20field%20of%20affective%20computing.pdf},

year  = {2021},

date = {2021-01-01},

journal = {Transactions of the Japanese Society for Artificial Intelligence},

volume = {36},

number = {1},

pages = {13},

keywords = {Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{de_melo_risk_2021,

title = {Risk of Injury in Moral Dilemmas With Autonomous Vehicles},

author = {Celso M. Melo and Stacy Marsella and Jonathan Gratch},

url = {https://www.frontiersin.org/articles/10.3389/frobt.2020.572529/full},

doi = {10.3389/frobt.2020.572529},

issn = {2296-9144},

year  = {2021},

date = {2021-01-01},

urldate = {2021-04-14},

journal = {Front. Robot. AI},

volume = {7},

pages = {572529},

abstract = {As autonomous machines, such as automated vehicles (AVs) and robots, become pervasive in society, they will inevitably face moral dilemmas where they must make decisions that risk injuring humans. However, prior research has framed these dilemmas in starkly simple terms, i.e., framing decisions as life and death and neglecting the influence of risk of injury to the involved parties on the outcome. Here, we focus on this gap and present experimental work that systematically studies the effect of risk of injury on the decisions people make in these dilemmas. In four experiments, participants were asked to program their AVs to either save five pedestrians, which we refer to as the utilitarian choice, or save the driver, which we refer to as the nonutilitarian choice. The results indicate that most participants made the utilitarian choice but that this choice was moderated in important ways by perceived risk to the driver and risk to the pedestrians. As a second contribution, we demonstrate the value of formulating AV moral dilemmas in a game-theoretic framework that considers the possible influence of others’ behavior. In the fourth experiment, we show that participants were more (less) likely to make the utilitarian choice, the more utilitarian (nonutilitarian) other drivers behaved; furthermore, unlike the game-theoretic prediction that decision-makers inevitably converge to nonutilitarianism, we found significant evidence of utilitarianism. We discuss theoretical implications for our understanding of human decision-making in moral dilemmas and practical guidelines for the design of autonomous machines that solve these dilemmas while, at the same time, being likely to be adopted in practice.},

keywords = {Autonomous Vehicles, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{zhu_building_2020,

title = {Building preparedness in response to active shooter incidents: Results of focus group interviews},

author = {Runhe Zhu and Gale M. Lucas and Burcin Becerik-Gerber and Erroll G. Southers},

url = {https://linkinghub.elsevier.com/retrieve/pii/S221242091931427X},

doi = {10.1016/j.ijdrr.2020.101617},

issn = {22124209},

year  = {2020},

date = {2020-09-01},

journal = {International Journal of Disaster Risk Reduction},

volume = {48},

pages = {101617},

abstract = {Active shooter incidents present an increasing threat to the American society. Many of these incidents occur in building environments, therefore, it is important to consider design and security elements in buildings to decrease the risk of active shooter incidents. This study aims to assess current security countermeasures and identify varying considerations associated with implementing these countermeasures. Fifteen participants, with expertise and experience in a diverse collection of operational and organizational backgrounds, including se­ curity, engineering, law enforcement, emergency management and policy making, participated in three focus group interviews. The participants identified a list of countermeasures that have been used for active shooter incidents. Important determinants for the effectiveness of countermeasures include their influence on occupants’ behavior during active shooter incidents, and occupants’ and administrators’ awareness of how to use them effectively. The nature of incidents (e.g., internal vs. external threats), building type (e.g., office buildings vs. school buildings), and occupants (e.g., students of different ages) were also recognized to affect the selection of appropriate countermeasures. The nexus between emergency preparedness and normal operations, and the importance of tradeoffs such as the ones between cost, aesthetics, maintenance needs and the influence on oc­ cupants’ daily activities were also discussed. To ensure the effectiveness of countermeasures and improve safety, the participants highlighted the importance of both training and practice, for occupants and administrators (e.g., first responder teams). The interview results suggested that further study of the relationship between security countermeasures and occupants’ and administrators’ responses, as well as efficient training approaches are needed.},

keywords = {ARO-Coop, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{hartholt_multi-platform_2020,

title = {Multi-Platform Expansion of the Virtual Human Toolkit: Ubiquitous Conversational Agents},

author = {Arno Hartholt and Ed Fast and Adam Reilly and Wendy Whitcup and Matt Liewer and Sharon Mozgai},

url = {https://www.worldscientific.com/doi/abs/10.1142/S1793351X20400127},

doi = {10.1142/S1793351X20400127},

issn = {1793-351X, 1793-7108},

year  = {2020},

date = {2020-09-01},

journal = {International Journal of Semantic Computing},

volume = {14},

number = {03},

pages = {315--332},

abstract = {We present an extension of the Virtual Human Toolkit to include a range of computing platforms, including mobile, web, Virtual Reality (VR) and Augmented Reality (AR). The Toolkit uses a mix of in-house and commodity technologies to support audio-visual sensing, speech recognition, natural language processing, nonverbal behavior generation and realization, text-to-speech generation and rendering. It has been extended to support computing platforms beyond Windows by leveraging microservices. The resulting framework maintains the modularity of the underlying architecture, allows re-use of both logic and content through cloud services, and is extensible by porting lightweight clients. We present the current state of the framework, discuss how we model and animate our characters, and offer lessons learned through several use cases, including expressive character animation in seated VR, shared space and navigation in room-scale VR, autonomous AI in mobile AR, and real-time user performance feedback leveraging mobile sensors in headset AR.},

keywords = {UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{nye_feasibility_2020,

title = {Feasibility and usability of MentorPal, a framework for rapid development of virtual mentors},

author = {Benjamin D. Nye and Dan M. Davis and Sanad Z. Rizvi and Kayla Carr and William Swartout and Raj Thacker and Kenneth Shaw},

url = {https://www.tandfonline.com/doi/full/10.1080/15391523.2020.1771640},

doi = {10.1080/15391523.2020.1771640},

issn = {1539-1523, 1945-0818},

year  = {2020},

date = {2020-07-01},

journal = {Journal of Research on Technology in Education},

pages = {1--23},

abstract = {One-on-one mentoring is an effective method to help novices with career development. However, traditional mentoring scales poorly. To address this problem, MentorPal emulates conversations with a panel of virtual mentors based on recordings of real STEM professionals. Students freely ask questions as they might in a career fair, while machine learning algorithms attempt to provide the best answers. MentorPal has developed strategies for the rapid development of new virtual mentors, where training data will be sparse. In a usability study, 31 high school students self-reported a) increased career knowledge and confidence, b) positive ease-of-use, and that c) mentors were helpful (87%) but often did not cover their preferred career (29%). Results demonstrate the feasibility of scalable virtual mentoring, but efficacy studies are needed to evaluate the impact of virtual mentors, particularly for groups with limited STEM opportunities.},

keywords = {Learning Sciences, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{brixey_choco_2020,

title = {ChoCo: a multimodal corpus of the Choctaw language},

author = {Jacqueline Brixey and Ron Artstein},

url = {http://link.springer.com/10.1007/s10579-020-09494-5},

doi = {10.1007/s10579-020-09494-5},

issn = {1574-020X, 1574-0218},

year  = {2020},

date = {2020-07-01},

journal = {Language Resources and Evaluation},

abstract = {This article presents a general use corpus for Choctaw, an American indigenous language (ISO 639-2: cho, endonym: Chahta). The corpus contains audio, video, and text resources, with many texts also translated in English. The Oklahoma Choctaw and the Mississippi Choctaw variants of the language are represented in the corpus. The data set provides documentation support for this threatened language, and allows researchers and language teachers access to a diverse collection of resources.},

keywords = {ARO-Coop, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}