"Phantom Friend" or "Just a Box with Information": Personification and Ontological Categorization of Smart Speaker-based Voice Assistants by Older Adults
Open accessAbstract
As voice-based conversational agents such as Amazon Alexa and Google Assistant move into our homes, researchers have studied the corresponding privacy implications, embeddedness in these complex social environments, and use by specific user groups. Yet it is unknown how users categorize these devices: are they thought of as just another object, like a toaster? As a social companion? Though past work hints to human-like attributes that are ported onto these devices, the anthropomorphization of voice assistants has not been studied in depth. Through a study deploying Amazon Echo Dot Devices in the homes of older adults, we provide a preliminary assessment of how individuals 1) perceive having social interactions with the voice agent, and 2) ontologically categorize the voice assistants. Our discussion contributes to an understanding of how well-developed theories of anthropomorphism apply to voice assistants, such as how the socioemotional context of the user (e.g., loneliness) drives increased anthropomorphism. We conclude with recommendations for designing voice assistants with the ontological category in mind, as well as implications for the design of technologies for social companionship for older adults.
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Claims the paper makes
5 of 40 cited sources checked · 2 supported · 1 flagged · accuracy not yet measured
- Findingcitation
The natural language conversation and responsiveness of voice assistants are what make them social.
“Like work on robots [28], we find that the natural language conversation and the responsiveness of these devices is what make them social.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [28] 28. Raya A Jones. 2017. What makes a robot 'social'? Social Studies of Science 47, 4: 556-579. https://doi.org/10.1177/0306312717704722 source
In “Pinpointing robot sociality” (page unavailable), Jones distinguishes observable conversation from the dialogicality of a social act and says conversational turn-taking cannot create that quality. The paper treats conversational responsiveness as a feature of robot design, not as sufficient to make a robot social; it also excludes disembodied AIs from its working definition of social robots (“The HRI context,” page unavailable). (LLM, conf=0.85)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
- Findingown data
On the first pass open-coding the transcripts, attributions of the device as human-like appeared throughout the data.
“On our first pass opencoding the transcripts, we found attributions of the device as human-like appearing throughout the data.”
Quote in the paperSubstantial claim - Findingown data
There were instances when users' perceptions of Alexa did not clearly classify into 'human-like' or 'object-like'.
“There were instances when users' perceptions of Alexa did not clearly classify into “human-like” or “object-like””
Quote in the paperSubstantial claim - Findingown data
Most participants in the study-all but P3 and P6-used polite terms such as 'please' and 'thank you' when using Alexa.
“We found that most participants in our study -all but P3 and P6 -used polite terms, such as “please” and “thank you” when using Alexa.”
Quote in the paperNot a substantial claim - Findingown data
All participants in the study referred to Alexa as 'she' or 'her' multiple times during interviews.
“Like this previous work, all participants in our study referred to Alexa as “she” or “her” multiple times during interviews.”
Quote in the paperNot a substantial claim
- Findingown data
Participants sometimes used object pronouns (e.g., 'it') when attributing human-like behavior to the device.
“Conversely, participants sometimes used object pronouns (e.g., “it”) when they were attributing human-like behavior to the device”
Quote in the paperSubstantial claim - Findingown data
One of the factors resulting in anthropomorphism of the voice assistant was a desire for social contact and affiliation.
“Our findings indicate that one of the factors resulting in anthropomorphism of the voice assistant was a desire for social contact and affiliation.”
Quote in the paperSubstantial claim - Findingown data
When participants felt the device was not responding to them specifically, they perceived it as more like an object.
“Conversely, when participants felt as though the device was not responding to them specifically, they perceived the device to be more like an object.”
Quote in the paperSubstantial claim - Findingown data
About half of the participants mentioned greeting Alexa at morning or at night.
“In addition to the polite behavior described above, about half of the participants mentioned greeting Alexa at morning or at night.”
Quote in the paperNot a substantial claim - Findingown data
Movement between categories occurs based on factors specific to the characteristics of the voice assistant (such as nature of interaction) or the user (desire for social contact or affiliation), along with the location and moment of interaction.
“Movement occurs based on factors specific to the characteristics of the voice assistant (such as nature of interaction) or the user (desire for social contact or affiliation), along with the location and moment of interaction.”
Quote in the paperSubstantial claim - Findingown data
Participants in this study personify and objectify voice assistants, sometimes within the same sentence.
“Our findings indicate that participants in this study personify and objectify voice assistants, sometimes within the same sentence.”
Quote in the paperSubstantial claim - Findingown data
Most participants described the presence of Alexa in terms of having someone in their homes.
“Most participants described the presence of Alexa in terms of having someone in their homes.”
Quote in the paperSubstantial claim - Findingown data
Participants in the study fluidly move between categorizing the voice assistant as 'humanlike' and 'object-like' rather than straightforwardly categorizing it as one or the other.
“Our findings indicate that instead of straightforwardly categorizing the voice assistant as”
Quote in the paperSubstantial claim - Findingown data
Older adults who are more in need of social contact may be more likely to personify a technology and at times seek social connection through it.
“Our work indicates that someone who is more in need of social contact may be more likely to personify a technology and at times seek social connection through it.”
Quote in the paperSubstantial claim - Findingown data
In addition to physical proximity, moments of interaction move perceptions of the device from one ontological category to another.
“In addition to physical proximity affecting whether the device is particularly human-like or object-like, moments of interaction also move perceptions of the device from one category to another.”
Quote in the paperSubstantial claim - Findingown data
P4 and other participants (P2, P3) expressed personification of the device when discussing the lack of social interaction in the house.
“P4, and other participants (P2, P3) expressed personification of the device when discussing the lack of social interaction in the house.”
Quote in the paperSubstantial claim - Findingown data
Not all participants desire the female voice trait for the voice assistant.
“Further, we found that not all participants desire the female voice trait for the voice assistant.”
Quote in the paperSubstantial claim - Findingown data
Over the course of the study, participants' perceptions of where Alexa fit in terms of ontological categorization shifted.
“Over the course of the study, participants' perceptions of where Alexa fit in terms of ontological categorization shifted.”
Quote in the paperSubstantial claim - Findingown data
Participants who described the desire for contact said that talking to Alexa alleviated their loneliness at home, more in regards to moments of loneliness rather than a global feeling of loneliness.
“Those participants that described the desire for contact actually said that talking to Alexa alleviated their loneliness at home -more in regards to moments of loneliness, rather than a global feeling of loneliness.”
Quote in the paperSubstantial claim - Findingcitation
People's perception of Alexa does not continuously exist in an 'in-between' category, but rather fluidly moves between human and object-like perceptions.
“At the same time, we also find that people's perception of Alexa does not continuously exist in an 'inbetween' category (suggested by Kahn et al. [30]), but rather, fluidly move between human and object like perceptions.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [30] 30. Peter H. Kahn Jr., Aimee L. Reichert, Heather E. Gary, Takayuki Kanda, Hiroshi Ishiguro, Solace Shen, Jolina H. Ruckert, and Brian Gill. 2011. The New Ontological Category Hypothesis in Human-robot Interaction. In Proceedings of the 6th International Conference on Human-robot Interaction (HRI '11), 159-160. https://doi.org/10.1145/1957656.1957710 source
- Findingnone given
Individuals seem to arrive at categorizations over time and with sustained use of the voice assistant.
“Individuals seem to arrive at categorizations over time and with sustained use of the voice assistant.”
Quote in the paperSubstantial claim - Findingown data
For P7, Alexa was more like a phone than someone in the room when the device did not seem accessible.
“For P7, Alexa was more like a phone than someone in the room at times when the device did not seem to be accessible.”
Quote in the paperNot a substantial claim - Findingown data
Instances of companionship through the embodied voice assistant surfaced in the analysis.
“Instances of companionship through the embodied voice assistant surfaced in our analysis”
Quote in the paperSubstantial claim - Findingown data
The physical location of the device and its embeddedness in the home environment matters.
“We find that the physical location of the device and its embeddedness in the home environment matters.”
Quote in the paperSubstantial claim - Findingown data
Having an interface that used natural ways of conversing led participants to perceive Alexa as a friend.
“Participants described how having an interface that used natural ways of conversing led to them to perceive Alexa as a friend.”
Quote in the paperSubstantial claim - Findingown data
The physical location of Alexa affects perceptions of it as human-like or object-like.
“The physical location of Alexa also affects these perceptions.”
Quote in the paperSubstantial claim - Findingown data
Some participants mentioned that Alexa lacked responsiveness at times, leading them to see it as object-like.
“Some participants mentioned that Alexa lacked responsiveness at times, leading them to see it as object-like.”
Quote in the paperSubstantial claim - Findingown data
Having someone to say goodnight in the home, in the context of going to bed, was important to participants.
“Here, having someone to say goodnight in the home, in the context of going to bed, was important -location and context is a topic we return to below.”
Quote in the paperNot a substantial claim - Findingown data
One participant described not using the voice assistant from the adjacent kitchen, although physically the kitchen was within the hearing range of the voice assistant.
“For example, one participant described not using the voice assistant from the adjacent kitchen, although physically, the kitchen was within the hearing range of the voice assistant.”
Quote in the paperSubstantial claim - Findingown data
Even if designers purposefully create personas to cultivate a particular desired user experience, the same voice assistant persona will be perceived differently by different users.
“Our findings reveal that even if designers purposefully create personas to cultivate a particular desired user experience, the same voice assistant persona will be perceived differently by different users.”
Quote in the paperSubstantial claim - Findingown data
People desiring companionship were more likely to value the device as a companion.
“But these forms of conversation were not viewed as equally important by all, with people desiring companionship more likely to value the device as a companion.”
Quote in the paperSubstantial claim - Findingnone given
All these participants lived alone.
“It is important to note that all these participants lived alone.”
Quote in the paperSubstantial claim - Findingown data
Participants sometimes made disclaimers indicating their recognition of uneasy categorization when referring to the device as a person.
“Participants sometimes made disclaimers indicating their recognition of this uneasy categorization, such as,”
Quote in the paperSubstantial claim - Findingown data
P6 voiced discomfort about categorizing Alexa as a person.
“P6 voiced a similar discomfort:”
Quote in the paperNot a substantial claim - Interpretationown data
The link between using 'she' or 'her' and the personification of the voice assistant is not as clear as past literature indicates.
“However, the usage examples described above suggests that the link between using “she” or “her” and the personification of the voice assistant is not as clear as past literature indicates.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [46] 46. Yuting Liao, Jessica Vitak, Priya Kumar, Michael Zimmer, and Katherine Kritikos. 2019. Understanding the Role of Privacy and Trust in Intelligent Personal Assistant Adoption. In Information in Contemporary Society (Lecture Notes in Computer Science), 102-113. source
- cites [57] 57. Alisha Pradhan, Kanika Mehta, and Leah Findlater. 2018. "Accessibility Came by Accident": Use of Voice-Controlled Intelligent Personal Assistants by People with Disabilities. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18), 459:1-459:13. https://doi.org/10.1145/3173574.3174033 source
- Interpretationown data
The use of personal pronouns 'she' or 'her' by participants did not necessarily indicate anthropomorphism.
“However, these references did not necessarily indicate anthropomorphism.”
Quote in the paperSubstantial claim - Premisecitation
Users have often personified voice assistants in smart speakers such as Alexa and have attributed the agent to be a 'companion' or 'friend'.
“Collectively, this background work highlights that users have often personified voice assistants in smart speakers such as Alexa and have attributed the agent to be a “companion” or “friend”.”
Quote in the paperSubstantial claim0 of 4 sources checked- cites [46] 46. Yuting Liao, Jessica Vitak, Priya Kumar, Michael Zimmer, and Katherine Kritikos. 2019. Understanding the Role of Privacy and Trust in Intelligent Personal Assistant Adoption. In Information in Contemporary Society (Lecture Notes in Computer Science), 102-113. source
- cites [56] 56. François Portet, Michel Vacher, Caroline Golanski, Camille Roux, and Brigitte Meillon. 2013. Design and evaluation of a smart home voice interface for the elderly: acceptability and objection aspects. Personal and Ubiquitous Computing 17, 1: 127-144. https://doi.org/10.1007/s00779-011-0470-5 source
- cites [57] 57. Alisha Pradhan, Kanika Mehta, and Leah Findlater. 2018. "Accessibility Came by Accident": Use of Voice-Controlled Intelligent Personal Assistants by People with Disabilities. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18), 459:1-459:13. https://doi.org/10.1145/3173574.3174033 source
- cites [62] 62. Anara Sandygulova and Gregory MP O'Hare. 2018. Age-related Differences in Children's Associations and Preferences for a Robot's Gender. In Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction - HRI '18, 235-236. https://doi.org/10.1145/3173386.3177077 source
- Interpretationown data
Users might not binarily classify voice assistants as humanlike or object-like.
“This suggests that users might not binarily classify voice assistants as humanlike or object-like”
Quote in the paperSubstantial claim - Interpretationown data
Thinking about Alexa as its own category of being resembles Kahn et al.'s hypothesis of how people see robots as 'in-between' human and object.
“Thinking about Alexa as its own category of being resembles Kahn et al.'s hypothesis of how people see robots as “in-between” human and object [30].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [30] 30. Peter H. Kahn Jr., Aimee L. Reichert, Heather E. Gary, Takayuki Kanda, Hiroshi Ishiguro, Solace Shen, Jolina H. Ruckert, and Brian Gill. 2011. The New Ontological Category Hypothesis in Human-robot Interaction. In Proceedings of the 6th International Conference on Human-robot Interaction (HRI '11), 159-160. https://doi.org/10.1145/1957656.1957710 source
- Premisecitation
Forced adoption is an approach sometimes taken with new technologies such as smart speakers and smart sensors.
“forced adoption is an approach that is sometimes taken with new technologies such as smart speakers [54] and smart sensors [42].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [54] 54. Martin Porcheron, Joel E. Fischer, Moira McGregor, Barry Brown, Ewa Luger, Heloisa Candello, and Kenton O'Hara. 2017. Talking with Conversational Agents in Collaborative Action. In Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing -CSCW '17 Companion, 431-436. https://doi.org/10.1145/3022198.3022666 source
- cites [42] 42. Amanda Lazar, Mark Diaz, Robin Brewer, Chelsea Kim, and Anne Marie Piper. 2017. Going Gray, Failure to Hire, and the Ick Factor: Analyzing How Older Bloggers Talk About Ageism. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17), 655-668. https://doi.org/10.1145/2998181.2998275 source
- Study design and conductown data
This study was not an entirely naturalistic deployment because users were given devices and training.
“This study was not an entirely naturalistic deployment -users were given the devices and some training to use the basic device and third-party skills, and received a printed reference guide and the option to contact the researchers for technical support.”
Quote in the paperSubstantial claim - Interpretationnone given
Individuals apply self-knowledge and accessible anthropocentric knowledge to the nonhuman voice agent, leading to anthropomorphizing behavior.
“Individuals apply this self-knowledge and accessible anthropocentric knowledge to the nonhuman voice agent, leading to anthropomorphizing behavior.”
Quote in the paperNot a substantial claim - Premisecitation
Individuals may be more likely to personify agents when they feel lonely.
“Thus, individuals may be more likely to personify agents when they feel lonely.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [17] 17. Nicholas Epley, Adam Waytz, and John T. Cacioppo. 2007. On seeing human: a three-factor theory of anthropomorphism. Psychological Review 114, 4: 864-886. https://doi.org/10.1037/0033-295X.114.4.864 source
- Interpretationreasoning
Conversational voice assistants in the home might have the potential to provide social interaction, a goal pursued in past work on older adults largely through social robots.
“This implies that conversational voice assistants in the home might have the potential to provide social interaction, a goal pursued in past work on older adults largely through social robots [35,60].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [35] 35. C. D. Kidd, W. Taggart, and S. Turkle. 2006. A sociable robot to encourage social interaction among the elderly. In Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., 3972-3976. https://doi.org/10.1109/ROBOT.2006.1642311 source
- cites [60] 60. Simon Robinson, Jennifer Pearson, Shashank Ahire, Rini Ahirwar, Bhakti Bhikne, Nimish Maravi, and Matt Jones. 2018. Revisiting "Hole in the Wall" Computing: Private Smart Speakers and Public Slum Settings. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18), 498:1-498:11. https://doi.org/10.1145/3173574.3174072 source
- Interpretationown data
The voice assistant technology has potential for supporting social interactions.
“indicating the potential of this technology for supporting social interactions.”
Quote in the paperSubstantial claim - Interpretationcitation
The ways in which one personifies a device are deeply linked to the specifics of one's life: the experiences that have built up over the lifetime in which the anthropocentric knowledge is based, and the specific living conditions that lead one to have more or less desire for social contact.
“These theories help us understand that the ways in which one personifies a device are deeply linked to the specifics of one's life: the experiences that have built up over the lifetime in which the anthropocentric knowledge is based, and the specific living conditions that lead one to have more or less desire for social contact.”
Quote in the paperSubstantial claim - Study design and conductown data
Working with a population who does not have prior exposure to voice interaction allows a truly 'forced adoption' study, where changes over time become an important part of the findings.
“in our study, working with a population who does not have prior exposure to voice interaction allows us to do a truly “forced adoption” study, where we see some changes over time that become an important part of our findings.”
Quote in the paperSubstantial claim - Interpretationreasoning
The simultaneous presence of all three of Epley et al.'s factors is not necessary for anthropomorphization of the voice assistant.
“We also see how the simultaneous presence of all three of Epley et al.'s factors is not necessary for anthropomorphization of the voice assistant.”
Quote in the paperSubstantial claim - Study design and conductreasoning
Forced adoption allows the study to see initial perceptions of the device, which is difficult when contacting users who already had experience with devices.
“This approach allows us to see initial perceptions of the device, something difficult to study when contacting users who already had experience with devices.”
Quote in the paperSubstantial claim
- Classified as probably not a substantial claim. 23
- May combine two claims. 12
- The quote only partly states this claim. 2
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationYounger, mid-aged and older adults have similar attitudes towards comfort and social impacts of robots.
“Researchers have also studied how people from different age groups perceive robots, finding that younger, mid-aged and older adults have similar attitudes towards comfort and social impacts of robots [3].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [3] 3. Uba Backonja, Amanda K. Hall, Ian Painter, Laura Kneale, Amanda Lazar, Maya Cakmak, Hilaire J. Thompson, and George Demiris. 2018. Comfort and Attitudes Towards Robots Among Young, Middle-Aged, and Older Adults: A Cross-Sectional Study. Journal of Nursing Scholarship 50, 6: 623-633. https://doi.org/10.1111/jnu.12430 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSome studies indicate older adults' preference for using robots for household purposes more than for companionship.
“Specific to older adults, some studies in HCI and HRI indicate older adults' preference for using robots for household purposes more than for companionship [5,13]”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [5] 5. J. M. Beer, C. Smarr, T. L. Chen, A. Prakash, T. L. Mitzner, C. C. Kemp, and W. A. Rogers. 2012. The domesticated robot: Design guidelines for assisting older adults to age in place. In 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 335-342. https://doi.org/10.1145/2157689.2157806 source
The Results (Assistance Preference Checklist Data; page unavailable) report that older adults preferred robot assistance for many household tasks, particularly cleaning. The study compared robot versus human assistance for home-based tasks; it did not compare household uses of robots with companionship, so the claimed relative preference is unsupported. (LLM, conf=0.86)
Experimental — accuracy not yet measured - cites [13] 13. K. Dautenhahn, S. Woods, C. Kaouri, M. L. Walters, and and I. Werry. 2005. What is a robot companion -friend, assistant or butler? In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 1192-1197. https://doi.org/10.1109/IROS.2005.1545189 source
In “Acceptance of robot companions” (page unavailable), 96.4% of participants wanted a robot that could do household jobs, while none of the study’s older participants wanted one as a friend. But the study’s limitations (page unavailable) state that no participant was older than 55, so its findings do not establish this preference for older adults generally. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationIn HRI literature, there is some evidence suggesting technology in the form of social robots can reduce loneliness for older adults.
“In HRI literature although there is some evidence suggesting technology in form of social robots can reduce loneliness for older adults (e.g., [4,31])”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites [4] 4. Marian R. Banks, Lisa M. Willoughby, and William A. Banks. 2008. Animal-Assisted Therapy and Loneliness in Nursing Homes: Use of Robotic versus Living Dogs. Journal of the American Medical Directors Association 9, 3: 173- 177. https://doi.org/10.1016/j.jamda.2007.11.007 source
- cites [31] 31. Masao Kanamori, Mizue Suzuki, and Misao Tanaka. 2002. Maintenance and improvement of quality of life among elderly patients using a pet-type robot. Nihon Ronen Igakkai Zasshi. Japanese Journal of Geriatrics 39, 2: 214-218. source
May combine two claims.
Findingown dataParticipants in the study saw Alexa as human-like and object-like, and moved between these categorizations.
“Unlike that past work, though, participants in our study also saw Alexa as human-like and object-like, and moved between these categorizations.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing), S4 (based).
Findingnone givenParticipants used greetings such as 'good morning' and polite expressions like 'thank you' with Alexa by the third week.
“such as”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataParticipants' ontological categorizations shifted over time, with some moving from human-like to object-like and others from object-like to human-like.
“These examples show how the human-like vs. machine-like categorization changed over time.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataAlexa was seen as providing social interaction when it was responsive and engaging in small talk, but reverted to an object when it did not provide these forms of interaction.
“Just as Alexa was seen as providing social interaction when it was responsive and engaging in small talk, it reverted to an object when it did not provide these forms of interaction.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataParticipants personified the agent when supporting human-like conversations or providing social support, but also dehumanized it due to lack of responsiveness or personal touch.
“For example, participants personified the agent when supporting human-like conversations or providing social support, but also dehumanized it due to lack of responsiveness or personal touch.”
Quote in the paperSubstantial claimThe quote only partly states this claim.
Findingown dataParticipants repeatedly referred to Alexa in human-like terms, including as a person, a friend, a phantom friend, somebody talking back, and having company.
“Similar to past work [57], we found that Alexa was repeatedly referred to in human-like terms.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [57] 57. Alisha Pradhan, Kanika Mehta, and Leah Findlater. 2018. "Accessibility Came by Accident": Use of Voice-Controlled Intelligent Personal Assistants by People with Disabilities. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18), 459:1-459:13. https://doi.org/10.1145/3173574.3174033 source
May combine two claims.
Findingown dataWhen participants felt the device's presence (perceived ubiquitousness), they thought of it as human-like, and this presence was tied to their home.
“When participants felt the device's presence (i.e., perceived ubiquitousness), they thought of it as human-like.”
- Also stated in: § 3.2.3 Changes over the Longer Term, Location and from Moment to Moment. · plain
“This presence was tied to a location: their home.”
Quote in the paperSubstantial claim- Also stated in: § 3.2.3 Changes over the Longer Term, Location and from Moment to Moment. · plain
May combine two claims.
Findingown dataIn our study, some attached more value and deeper feelings to the assistant, while others considered the interactions as mostly inconsequential.
“In our study, some attached more value and deeper feelings to the assistant, while others considered the interactions as mostly inconsequential.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataP5 refused to categorize Alexa at all, instead designating a new category: 'I think of it as that's Alexa'.
“Aligning with the complex categorizations of other participants, P5 refused to categorize Alexa at all, instead designating a new category:”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductcitationThe study does not intend to obtain generalizable results because it is in-depth qualitative work with a small sample size.
“Like other in-depth qualitative work with a small sample size, we do not intend to obtain generalizable results [32,47].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [32] 32. Evangelos Karapanos, Jean-Bernard Martens, and Marc Hassenzahl. 2010. On the Retrospective Assessment of Users' Experiences over Time: Memory or Actuality? In CHI '10 Extended Abstracts on Human Factors in Computing Systems (CHI EA '10), 4075-4080. https://doi.org/10.1145/1753846.1754105 source
- cites [47] 47. Irene Lopatovska and Harriet Williams. 2018. Personification of the Amazon Alexa: BFF or a Mindless Companion. In Proceedings of the 2018 Conference on Human Information Interaction&Retrieval -CHIIR '18, 265-268. https://doi.org/10.1145/3176349.3176868 source
Classified as probably not a substantial claim.
PremisecitationEpley et al.'s three-factor theory of anthropomorphism explains anthropomorphizing behavior through elicited agent knowledge, effectance motivation, and sociality.
“Epley et al. [17] enlist three factors-“elicited agent knowledge or anthropocentric knowledge”, “effectance motivation”, and “sociality”-to explain anthropomorphizing behavior”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [17] 17. Nicholas Epley, Adam Waytz, and John T. Cacioppo. 2007. On seeing human: a three-factor theory of anthropomorphism. Psychological Review 114, 4: 864-886. https://doi.org/10.1037/0033-295X.114.4.864 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataThe nature of primary commands was coded as 'polite', 'rude' or 'neutral' by two research team members, achieving a Cohen's Kappa of 0.91.
“The nature of each these primary commands was coded as “polite”, “rude” or “neutral” using a using a multi-step process by two research team members [24], achieving a Cohen's Kappa of 0.91.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [24] 24. Daniel J. Hruschka, Deborah Schwartz, Daphne Cobb St.John, Erin Picone-Decaro, Richard A. Jenkins, and James W. Carey. 2004. Reliability in Coding Open-Ended Data: Lessons Learned from HIV Behavioral Research. Field Methods 16, 3: 307-331. https://doi.org/10.1177/1525822X04266540 source
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationPolite behavior such as saying thank you is learned over time until it becomes natural.
“The quote above indicates that polite behavior such as saying thank you is learned over time until it becomes natural -resonating with past work [46].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [46] 46. Yuting Liao, Jessica Vitak, Priya Kumar, Michael Zimmer, and Katherine Kritikos. 2019. Understanding the Role of Privacy and Trust in Intelligent Personal Assistant Adoption. In Information in Contemporary Society (Lecture Notes in Computer Science), 102-113. source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningDaily diary calls may have resulted in increased usage of Alexa due to reminders about its presence.
“These calls provided us with daily interaction data that helped us to probe for indepth explanations during weekly in-person interviews, but may also have resulted in an increased usage of Alexa due to reminders about its presence.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataThe population studied has specific characteristics: all over 65, no experience with voice assistants, and did not use smartphones, computers or tablets regularly.
“Finally, the population with whom we engaged, though diverse in some ways, has a specific set of characteristics -they are all over 65, had no experience with voice assistants, and did not use smartphones, computers or tablets regularly.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationOlder adults' 'social communications' include both physical and digital spaces.
“Hope et al. [22] identified that older adults' “social communications” include both physical and digital spaces (e.g., printing out a typed letter and sending it through physical mail), which is lacking in the current day social media technologies.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [22] 22. Alexis Hope, Ted Schwaba, and Anne Marie Piper. 2014. Understanding digital and material social communications for older adults. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems -CHI '14, 3903-3912. https://doi.org/10.1145/2556288.2557133 source
Classified as probably not a substantial claim. May combine two claims.
Study design and conductcitationOur analysis primarily draws upon linguistic theory, that everyday language used to label objects can reveal ontologies, also corroborated with several instances of self-reported participants' mental states, thus drawing on the mentalistic theory as well.
“In this work, our analysis primarily draws upon linguistic theory, that everyday language used to label objects can reveal ontologies [18], also corroborated with several instances of self-reported participants' mental states (e.g., the feeling of not being alone in the house), thus drawing on the mentalistic theory as well.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [18] 18. Brian Epstein. 2018. Social Ontology. In The Stanford Encyclopedia of Philosophy (Summer 2018), Edward N. Zalta (ed.). Metaphysics Research Lab, Stanford University.
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Classified as probably not a substantial claim.
PremisecitationEpley's framework claims that self-knowledge or knowledge about human characteristics serves as the readily available induction base for reasoning about nonhuman objects, contributing to easily available anthropocentric knowledge.
“Epley's framework, which has not yet been applied to conversational voice assistants, claims that self-knowledge or knowledge about human characteristics in general would serve as the readily available (or accessible) induction base for reasoning of nonhuman objects, thus contributing to easily available anthropocentric knowledge.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [17] 17. Nicholas Epley, Adam Waytz, and John T. Cacioppo. 2007. On seeing human: a three-factor theory of anthropomorphism. Psychological Review 114, 4: 864-886. https://doi.org/10.1037/0033-295X.114.4.864 source
May combine two claims.
InterpretationreasoningThe perception of Alexa as human-like emerged when it was filling a social need for P4, and it might return to object-like when she no longer needed it.
“This suggests that the perception of Alexa as human-like emerged when it was filling a social need for her -and it might return to object-like when she no longer needed it.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based).
Premisenone givenThere has been a significant body of research on anthropomorphization that has not yet been applied to voice assistants.
“At the same time, there has been a significant body of research on anthropomorphization that has not yet been applied to this domain.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductcitationOur understanding of the relationship between anthropomorphism, embodiment and voice assistants is based on a specific sample, as is common with qualitative work on smart speakers.
“Our understanding of the relationship between anthropomorphism, embodiment and voice assistants, although grounded in past work, is based on a specific sample as is common with qualitative work on smart speakers (e.g., children [16], people with disabilities [56] or multi-user family based households [54]).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [16] 16. Stefania Druga, Randi Williams, Cynthia Breazeal, and Mitchel Resnick. 2017. "Hey Google is It OK if I Eat You?": Initial Explorations in Child-Agent Interaction. In Proceedings of the 2017 Conference on Interaction Design and Children (IDC '17), 595-600. https://doi.org/10.1145/3078072.3084330 source
- cites [56] 56. François Portet, Michel Vacher, Caroline Golanski, Camille Roux, and Brigitte Meillon. 2013. Design and evaluation of a smart home voice interface for the elderly: acceptability and objection aspects. Personal and Ubiquitous Computing 17, 1: 127-144. https://doi.org/10.1007/s00779-011-0470-5 source
- cites [54] 54. Martin Porcheron, Joel E. Fischer, Moira McGregor, Barry Brown, Ewa Luger, Heloisa Candello, and Kenton O'Hara. 2017. Talking with Conversational Agents in Collaborative Action. In Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing -CSCW '17 Companion, 431-436. https://doi.org/10.1145/3022198.3022666 source
Classified as probably not a substantial claim.
PremisecitationIn HRI literature, there are a number of concerns including deception, infantilization, and privacy regarding social robots.
“there are also a number of concerns including deception, infantilization, and privacy [63,70].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [63] 63. Alex Sciuto, Arnita Saini, Jodi Forlizzi, and Jason I. Hong. 2018. "Hey Alexa, What's Up?": A Mixed-Methods Studies of In-Home Conversational Agent Usage. In Proceedings of the 2018 Designing Interactive Systems Conference (DIS '18), 857-868. https://doi.org/10.1145/3196709.3196772 source
- cites [70] 70. Alexandra Vtyurina and Adam Fourney. 2018. Exploring the Role of Conversational Cues in Guided Task Support with Virtual Assistants. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18), 208:1-208:7. https://doi.org/10.1145/3173574.3173782 source
Classified as probably not a substantial claim.
InterpretationreasoningMany of the study's findings are interpreted with broader significance beyond older adults.
“And while some of our discussion specifically addresses use of voice assistants for older adults, many of our findings are interpreted with broader significance.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe usage logs provided actual interactions to complement participants' perceptions of these interactions.
“The usage logs provided us with the actual interactions to complement participants' perceptions of these interactions.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPast theories relate to and shed light on the behaviors of the population studied.
“Given the ways that past theories [17,30] relate to and shed light on the behaviors of the population we study, our beliefs on the commonalities are confirmed.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [17] 17. Nicholas Epley, Adam Waytz, and John T. Cacioppo. 2007. On seeing human: a three-factor theory of anthropomorphism. Psychological Review 114, 4: 864-886. https://doi.org/10.1037/0033-295X.114.4.864 source
- cites [30] 30. Peter H. Kahn Jr., Aimee L. Reichert, Heather E. Gary, Takayuki Kanda, Hiroshi Ishiguro, Solace Shen, Jolina H. Ruckert, and Brian Gill. 2011. The New Ontological Category Hypothesis in Human-robot Interaction. In Proceedings of the 6th International Conference on Human-robot Interaction (HRI '11), 159-160. https://doi.org/10.1145/1957656.1957710 source
Classified as probably not a substantial claim.
PremisecitationHumans anthropomorphize non-humans based on their anthropocentric knowledge.
“Humans anthropomorphize non-humans based on their anthropocentric knowledge.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [17] 17. Nicholas Epley, Adam Waytz, and John T. Cacioppo. 2007. On seeing human: a three-factor theory of anthropomorphism. Psychological Review 114, 4: 864-886. https://doi.org/10.1037/0033-295X.114.4.864 source
Probably not a substantial claim: may not pass S2 (checkable).
PremisecitationSocial motivation describes the desire for social contact or connection and social approval from other agents.
“Social motivation describes the desire for social contact or connection and social approval from other agents.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [17] 17. Nicholas Epley, Adam Waytz, and John T. Cacioppo. 2007. On seeing human: a three-factor theory of anthropomorphism. Psychological Review 114, 4: 864-886. https://doi.org/10.1037/0033-295X.114.4.864 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationInterfaces that merge digital and physical space may be more appealing to some older people.
“Although social media and social networking sites can foster social connections in general, studies have found that interfaces that merge digital and physical space may be more appealing to some older people [22,23].”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [22] 22. Alexis Hope, Ted Schwaba, and Anne Marie Piper. 2014. Understanding digital and material social communications for older adults. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems -CHI '14, 3903-3912. https://doi.org/10.1145/2556288.2557133 source
- cites [23] 23. Dominik Hornung, Claudia Müller, Irina Shklovski, Timo Jakobi, and Volker Wulf. 2017. Navigating Relationships and Boundaries: Concerns around ICT-uptake for Elderly People. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems -CHI '17, 7057-7069. https://doi.org/10.1145/3025453.3025859 source
May combine two claims.
Interpretationown dataWe extend Kahn et al.'s theory to apply to voice assistants, identifying factors that influence shifts between ontological categorizations: voice assistant capabilities (e.g., responsiveness), desire for personalization and companionship, sustained use over time, and location and moment of interaction.
“Thus, we extend Kahn et al.'s theory to apply to voice assistants, identifying factors that influence shifts between ontological categorizations: the voice assistant capabilities (e.g., responsiveness), desire for personalization and companionship, sustained use over time, and location and moment of interaction with the voice assistant.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductown dataUsage logs were analyzed to understand users' actual interactions in addition to their perceptions of these interactions.
“To understand a particular phenomenon -how “politeness” appears in conversations with Alexa -we analyzed the usage logs, as we wanted to understand users' actual interactions in addition to their perceptions of these interactions.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationPast work has found that technology-mediated social interaction can be a form of at times unwelcome additional work for older adults as they feel that they must put in effort, be social and gracious while using such systems.
“Past work has found that technology-mediated social interaction can be a form of at times unwelcome additional work for older adults as they feel that they must put in effort, be social and gracious while using such systems [43].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [43] 43. Amanda Lazar, Christian Koehler, Joshua Tanenbaum, and David H. Nguyen. 2015. Why we use and abandon smart devices. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '15, 635-646. https://doi.org/10.1145/2750858.2804288 source
The paper relies on this without support.
Smart speakers have unique qualities compared to smartphone-based voice assistants: they support verbal conversational interaction with no visual output, are always-on and always listening, and are placed in the home environment.
“Compared to smartphone-based voice assistants (e.g., Siri), smart speakers have unique qualities.They support verbal conversational interaction, most often with no visual output.Smart speakers are also “always-on” and “always listening”, and are placed in the social, collaborative, semi-private home environment.”
The paper relies on this without support.
The socioemotional context of the user (e.g., loneliness) drives increased anthropomorphism.
“Our discussion contributes to an understanding of how well-developed theories of anthropomorphism apply to voice assistants, such as how the socioemotional context of the user (e.g., loneliness) drives increased anthropomorphism.”
The paper relies on this without support.
Older adults experience 'moments of loneliness'.
“As we investigate the opportunity for voice assistants to alleviate”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Older adults' VA use resembles general use by all populations, such as listening to music, searching for general and health information, engaging in casual conversations, checking the date, time, or weather, and setting reminders.
“Research ston VA use suggests that older adults' VA use resembles general use by all populations [1] such as listening to music, searching for general and health information, engaging in casual conversations, checking the date, time, or weather, and setting reminders [10,11,23,25,32].”
From Studying Exploration & Long-Term Use of Voice Assistants by Older Adults (2023) · cites this paper as [23]
The Limitations section says the authors see commonalities between their older participants and other users, which supports the broad idea of resemblance. But their findings concern a small, specifically selected group, and they explicitly say the results are not generalizable; the paper does not establish that older adults’ voice-assistant use resembles use by all populations. The activity examples are attached to separate citations in the citing sentence. (LLM, conf=0.82)
Experimental — accuracy not yet measuredPast research reports that older adults use voice assistants for checking the date, time, or weather; playing music; and searching for general information, similar to younger adults.
“Past research reports that older adults use voice assistants for checking the date, time, or weather; playing music; and searching for general information [11,23,32], similar to how younger adults use voice assistants [1].”
From Studying Exploration & Long-Term Use of Voice Assistants by Older Adults (2023) · cites this paper as [23]
Section 3.1.2 describes an older participant thanking Alexa after receiving information, supporting the information-seeking part. Section 3.2 says participants were taught to play music and ask questions, but training does not establish that they used those features; the passages found also do not establish that participants checked the date, time, or weather. The comparison with younger adults is attached to a different citation and is not assessed here. Page numbers were not available in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measuredRegularly updated flyers in a one-page format that could be kept close to the device were more effective than a one-time flyer researchers have used in the past.
“Regularly updated flyers in a one-page format that could be kept close to the device were more effective than a onetime flyer researchers have used in the past [23].”
From Studying Exploration & Long-Term Use of Voice Assistants by Older Adults (2023) · cites this paper as [23]
The Limitations section (3.4; page not available) says participants received a printed reference guide, supporting the claim that the researchers used printed guidance. It does not describe a one-page flyer, say it was kept near the device, or compare its effectiveness with regularly updated flyers. (LLM, conf=0.82)
Experimental — accuracy not yet measuredCurrent commercial voice assistant capabilities are far more limited than older adults' desires for conversational interactions.
“Despite older adults' desires to have conversational interactions with VAs, current commercial VA capabilities are far more limited [48].”
From Situated Understanding of Errors in Older Adults' Interactions with Voice Assistants: A Month-Long, In-Home Study (2026) · cites this paper as [48]
Section 4.4 reports that some older participants desired social contact through Alexa. Section 3.2.1 reports that Alexa sometimes failed to respond conversationally, particularly in its chat feature. The paper does not establish the broader claim that current commercial voice assistants’ capabilities are far more limited than older adults’ conversational desires; it also reports that brief exchanges with Alexa met some participants’ social needs. The indexed passages provide no page number. (LLM, conf=0.83)
Experimental — accuracy not yet measuredOlder adults prefer and initially attempt a more conversational interaction style.
“older adults prefer and initially attempt a more conversational interaction style [48].”
From Situated Understanding of Errors in Older Adults' Interactions with Voice Assistants: A Month-Long, In-Home Study (2026) · cites this paper as [48]
Section 3.2.1 reports that participants engaged in human-like small talk with Alexa and that natural conversation helped some perceive it as a friend. But section 3.2.3 says some participants initially viewed Alexa as object-like and only later became comfortable conversing with it. The paper therefore does not support a general claim that older adults prefer and initially attempt a conversational style. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Older adults tend to anthropomorphize the device as a companion within their home environment.
“An important aspect of older adults and their usage of CAs is their tendency to anthropomorphize the device as a companion within their home environment [6,35].”
From A Collaborative Approach to Support Medication Management in Older Adults with Mild Cognitive Impairment Using Conversational Assistants (CAs) (2022) · cites this paper as [35]
Existing research has explored how older adults have used and perceived existing features of voice-only VAs.
“Existing research has explored how older adults have used and perceived existing features of voice-only VAs [16, 43, 57, 58, 72], but the potential merits and setbacks of the secondary touchscreen modality are underexplored.”
From Screen or No Screen? Lessons Learnt from a Real-World Deployment Study of Using Voice Assistants With and Without Touchscreen for Older Adults (2023) · cites this paper as [57]
Most prior works only focused on general uses of VAs for older adults, rather than healthcare applications.
“Additionally, most prior works (e.g., [57, 72]) only focused on general uses (e.g., music) of VAs for older adults, rather than healthcare applications, which are indispensable use cases [15, 16].”
From Screen or No Screen? Lessons Learnt from a Real-World Deployment Study of Using Voice Assistants With and Without Touchscreen for Older Adults (2023) · cites this paper as [57]
Despite knowing these limitations, users expressed conversational and companionship as a benefit.
“Despite knowing these limitations, users expressed conversational and companionship as a benefit [11], based on having casual conversations [23] in a question-and-answer format [11].”
From Studying Exploration & Long-Term Use of Voice Assistants by Older Adults (2023) · cites this paper as [23]
Various studies demonstrated that smart speakers are used by older adults daily for physical, mental, and social health.
“For instance, various studies demonstrated that smart speakers are used by older adults daily [10] for physical [22,23], mental [7,32], and social health [8,31].”
From Smart Speakers for Health and Well-Being of Older Adults: A Mixed-Methods Review (2025) · cites this paper as [32]
There is a comparatively significant body of work studying how VUIs could provide companionship to older adults.
“However, there is a comparatively signifcant body of work (e.g., [57,87]) studying how VUIs could provide companionship to older adults.”
From OK Google, Let's Learn: Using Voice User Interfaces for Informal Self-Regulated Learning of Health Topics among Younger and Older Adults (2023) · cites this paper as [87]
A significant research gap remains in comprehensive error analysis of older adults' long-term interactions with voice assistants at home.
“While researchers have investigated older adults' long-term interactions with VAs at home-focusing on their adoption of the technology, its benefits and challenges, and their perceptions of the experience [28, 48, 49, 51]-a significant research gap remains in the area of comprehensive error analysis.”
From Situated Understanding of Errors in Older Adults' Interactions with Voice Assistants: A Month-Long, In-Home Study (2026) · cites this paper as [48]
Older adults tend to favor polite interactions, both in their own communications to VAs and when receiving their responses.
“this could stem from the fact that older adults tend to favor polite interactions, both in their own communications to VAs [48] and when receiving their responses [23].”
From Situated Understanding of Errors in Older Adults' Interactions with Voice Assistants: A Month-Long, In-Home Study (2026) · cites this paper as [48]
Structured command names limited older adults' ability to discover new skills.
“Further, such structured command names limited older adults' ability to discover new skills [23].”
From Studying Exploration & Long-Term Use of Voice Assistants by Older Adults (2023) · cites this paper as [23]
The Methods section describes training older participants to use third-party skills, and Data Analysis (§3.3, page unavailable) describes how the researchers analyzed voice commands. Neither passage addresses whether structured command names limited participants’ discovery of new skills. Searches for “discover new skills,” “command names,” and related terms found no passage making that point. (LLM, conf=0.74)
Experimental — accuracy not yet measuredOlder adults may face difficulty discovering and remembering commands associated with VA skills.
“Older adults may face difficulty discovering and remembering commands associated with VA skills [23,31].”
From Studying Exploration & Long-Term Use of Voice Assistants by Older Adults (2023) · cites this paper as [23]
The Data collection and device setup section says participants were trained to use third-party skills, and the Limitations section says they received a printed reference guide. Neither section reports difficulty discovering or remembering skill commands. Searches for those difficulties found no passage in our copy that addresses them. (LLM, conf=0.70)
Experimental — accuracy not yet measuredOlder adults often employ trial-and-error approaches to mitigate challenges with VAs.
“To mitigate these challenges, older adults often employ trial-and-error approaches [6,11], often giving up after rephrasing their commands several times and receiving no response from the system [23].”
From Studying Exploration & Long-Term Use of Voice Assistants by Older Adults (2023) · cites this paper as [23]
Section 3.2.1 reports that some older participants found Alexa unresponsive, but it does not say they used trial-and-error to overcome that difficulty. Searches for trial-and-error, rephrasing, and repeated commands found no passage supporting that approach. The separate claim about giving up is attributed to [23], not this source. (LLM, conf=0.72)
Experimental — accuracy not yet measuredOlder adults may face challenges in discovering commands related to unknown or new skills and remembering the language used to initiate complex commands.
“For example, older adults may face challenges in discovering commands related to unknown or new skills, [23,28] and remembering the language used to initiate complex commands (e.g.reminders) [23].”
From Studying Exploration & Long-Term Use of Voice Assistants by Older Adults (2023) · cites this paper as [23]
Section 3.2 says participants were trained to use reminders and third-party skills, while Section 3.4 notes that they received a reference guide and technical support (page numbers unavailable). Neither passage says they struggled to discover commands for new skills or remember the wording for complex commands. Searches for skill discovery, command phrasing, and reminders found no passage addressing those difficulties. (LLM, conf=0.72)
Experimental — accuracy not yet measuredVUIs are comparatively more accessible to older adults and people with disabilities due to their speech-based nature.
“Due to the speech-based nature of VUIs, they are comparatively more accessible to older adults [87,88,107] and people with disabilities [102].”
From OK Google, Let's Learn: Using Voice User Interfaces for Informal Self-Regulated Learning of Health Topics among Younger and Older Adults (2023) · cites this paper as [87]
Sections 2.3 and 3.1 describe a study of older adults using voice assistants, but do not say that speech-based interfaces are more accessible to them than other interfaces. A search for accessibility, ease of use, and speech found no passage establishing that comparison. The separate claim about people with disabilities is cited to [102], not this source. (LLM, conf=0.74)
Experimental — accuracy not yet measuredOlder adults ontologically categorized VUIs as a person as well as an object (or something in between).
“This finding is also supported by Pradhan et al. [62], who found older adults ontologically cat-egorized VUIs as a person as well as an object (or something in between).”
From Examining Humanness as a Metaphor to Design Voice User Interfaces (2024) · cites this paper as [62]
Users perceived VUIs to be human, non-human, or something in between.
“Although users perceived VUIs to be human, non-human, or something in between [14, 62]”
From Examining Humanness as a Metaphor to Design Voice User Interfaces (2024) · cites this paper as [62]
Older adults view voice user interfaces as social companions that can reduce loneliness.
“they perceive VUIs as social companions [29,43], capable of alleviating loneliness.”
From Using Experience-Based Participatory Approach to Design Interactive Voice User Interfaces for Delivering Physical Activity Programs with Older Adults (2023) · cites this paper as [43]
In a longitudinal study with seven older adults, Pradhan et al. found that older adults anthropomorphized agents using he or she pronouns and described them as friends.
“Further, in a longitudinal study with seven older adults, Pradhan et al. [43] found that older adults anthropomorphized older adults (as per the CASA paradigm [37]) using he or she pronouns and described them as friends.”
From Using Experience-Based Participatory Approach to Design Interactive Voice User Interfaces for Delivering Physical Activity Programs with Older Adults (2023) · cites this paper as [43]
Older adults are often unfamiliar with how to initiate a conversation with voice user interfaces and what to do during a conversational breakdown.
“Additionally, older adults are often unfamiliar with how to initiate a conversation with VUIs [38,51] and what to do during a conversational breakdown.”
From “A Painless Way to Learn:” Designing an Interactive Storytelling Voice User Interface to Engage Older Adults in Informal Health Information Learning (2023) · cites this paper as [51]
VUIs are often anthropomorphized, with users projecting traits such as intelligence, likeability, and trust onto them.
“Due to voice acting as an input modality, VUIs are often anthropomorphized [21,51]-with users projecting traits like intelligence, likeability, and trust onto them.”
From “A Painless Way to Learn:” Designing an Interactive Storytelling Voice User Interface to Engage Older Adults in Informal Health Information Learning (2023) · cites this paper as [51]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Citation [46] identifies a different study
MinorThe text attributes a finding to Lopatovska and Williams at [46], but reference 46 lists Liao and colleagues. Lopatovska and Williams are listed as reference 47, so the citation points to the wrong source.
“Lopatovska and Williams [46] attribute participants' use of the word "she" to anthropomorphizing the voice assistant Alexa.”
“46. Yuting Liao, Jessica Vitak, Priya Kumar, Michael Zimmer, and Katherine Kritikos. 2019. Understanding the Role of Privacy and Trust in Intelligent Personal Assistant Adoption.”
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Alexa, what do we know about conversational commerce? Insights from a systematic literature review.
Lim, W. M., Kumar, S., Verma, S., & Chaturvedi, R. (2022) · Psychology & Marketing · doi:10.1002/mar.21654 · Cited by 293 · see citing works
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“…(Druga et al., 2017; Garg & Sengupta, 2020), low-income populations (Robinson et al., 2018), privacy concerns (Lau et al., 2018; Liao et al., 2019), conversational aspects (Purington et al., 2017; Vtyurina & Fourney, 2018), and personification (Lopatovska & Williams, 2018; Pradhan et al., 2019).”
BackgroundJo, E., Epstein, D. A., Jung, H., & Kim, Y.-H. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581503 · Cited by 174 · see citing works
Why Do People Use Artificial Intelligence (AI)-Enabled Voice Assistants?
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An Empirical Study of Older Adult’s Voice Assistant Use for Health Information Seeking
Brewer, R., Pierce, C., Upadhyay, P., & Park, L. (2022) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3484507 · Cited by 89 · see citing works
“(2019) study older adults’ language expectations with voice assistants and show how they “personify and objectify” the devices [47] and that many use voice assistants for health-related information seeking [48].”
BackgroundInfluentialDignity, Autonomy, and Style of Company
Coghlan, S., Waycott, J., Lazar, A., & Neves, B. B. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449178 · Cited by 82 · see citing works
“notes that the CSCW community is increasingly interested in ‘understanding social interactions mediated by robots’ [70].”
BackgroundSelf-citationUnderstanding Older Adults' Participation in Design Workshops
Pradhan, A., Jelen, B., Siek, K. A., Chan, J., & Lazar, A. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376299 · Cited by 75 · see citing works
“Emerging research [40,62,73] and popular press articles [11,35,67,86] Attending to the final design ideas of participants also reveal values associated with technology, an area of interest in HCI in general [15] and specifically with older adults [45].”
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“…2021 Prospective n = 12 77–95 years 4 months Google Home O’Brien, 2020 Retrospective n = 125 consumer reviews, 2015–2018 Not reported N/A Amazon Echo Pradhan, 2019 Prospective n = 7 65–83 years 3 weeks Echo Dot Scherr, 2020 Prospective n = 11 68–83 years ≥12 months Echo Show Chambers and Beaney…”
BackgroundNallam, P., Bhandari, S., Sanders, J., & Martin-Hammond, A. (2020) · Gerontology and Geriatric Medicine · doi:10.1177/2333721420985975 · Cited by 63 · see citing works
“There has been growing interest in using intelligent voice assistants (IVAs), such as Amazon Echo and Google Home, to support older adults (Buinhas et al., 2019; Pradhan et al., 2019; Reis et al., 2018; Sanders & Martin-Hammond, 2019; Sayago et al., 2019; Trajkova & Martin-Hammond, 2020) at home for health-related and…”
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“[67] explored the anthropomorphism aspects,”
BackgroundUnderstanding Older Adults’ Perceptions and Challenges in Using AI-enabled Everyday Technologies
Shandilya, E., & Fan, M. (2022) · International Symposium of Chinese CHI (Chinese CHI) · doi:10.1145/3565698.3565774 · Cited by 84 · see citing works
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“…2010; de Graaf, 2016; Seibt, 2017; Oranç & Küntay, 2020; Levillain & Zibetti, 2017; Mel-son et al., 2009; Bernstein & Crowley, 2008; Gaudiello et al., 2015; Jipson et al., 2016; Kim et al., 2019)), and also in the particular context of DVAs (e.g., (Fester-ling & Siraj, 2020; Pradhan et al., 2019)).”
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“Third, AIPA also provides friendly conversations to users and serves as a sec-retary close to humans (O'Leary, 2019; Pradhan et al., 2019).”
BackgroundExploring the Determinants of Users’ Continuance Usage Intention of Smart Voice Assistants
Pal, D., Babakerkhell, M. D., & Zhang, X. (2021) · IEEE Access · doi:10.1109/access.2021.3132399 · Cited by 62 · see citing works
“For example, one study in [35] related to the use of voice-assistants by elderly people show that these devices can provide socioemotional support to the users by providing them with an engaging experience that”
BackgroundEmerging Roles and Relationships Among Humans and Interactive AI Systems
Lindgren, H. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2435693 · Cited by 73 · see citing works
“As described by Pradhan et al. (2019), the shift can be due to a shift of activity purpose between satisfying emotional needs through a digital companion, and non-companion purposes.”
InfluentialXygkou, A., Ang, C. S., Siriaraya, P., Kopecki, J. P., Covaci, A., Kanjo, E., & She, W. J. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642538 · Cited by 61 · see citing works
“Interestingly, studies in this domain have also highlighted how the perception of voice assistants as being either human-like or object-like tends to be dynamic and is often infuenced by factors such as the interaction style and the user’s desire for social companionship [44].”
BackgroundStudying Exploration & Long-Term Use of Voice Assistants by Older Adults
Upadhyay, P., Heung, S., Azenkot, S., & Brewer, R. N. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580925 · Cited by 51 · see citing works
“However, these interactions could be susceptible to a novelty effect, which may wear off over time, as suggested by [23].”
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“All the articles detail the total number of people engaged, except for 31% (5/16) of the articles [26,31,32,34,35].”
InfluentialMao, W., Sun, W. M., Wang, M., & Qiu, L. (2020) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3432195 · Cited by 47 · see citing works
Hey Google, Do You Have a Personality? Designing Personality and Personas for Conversational Agents
Pradhan, A., & Lazar, A. (2021) · Proceedings of the 3rd Conference on Conversational User Interfaces · doi:10.1145/3469595.3469607 · Cited by 50 · see citing works
“, ascribe human-like properties, characteristics, or mental states to nonhuman agents [8]) and perceive them as human-like to even associate social roles of friend or a partner with the agent [19, 22, 23].”
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Melville, N. P., Robert, L., & Xiao, X. (2022) · Information Systems Journal · doi:10.1111/isj.12422 · Cited by 51 · see citing works
“For example, human-like machine voices d that are prespecified by agents p may be perceived more as trusted friend or collaborator than tablet or sound speaker in repeated enactments with repeated impacts e (Pradhan et al. 2019).”
BackgroundFesterling, J., & Siraj, I. (2020) · Human Development · doi:10.1159/000508499 · Cited by 48 · see citing works
“Although Pradhan et al. (2019) provide a consistent conclusion of their discussion in favour of anthropomorphism, it should be emphasised that the theoretical claim of NOCH differs systematically from the argument of anthropomorphism: as pointed out earlier, the attribution of humanoid qualities to…”
BackgroundShao, C., & Kwon, K. H. (2021) · Human Behavior and Emerging Technologies · doi:10.1002/hbe2.293 · Cited by 49 · see citing works
The Impact of Everyday AI-Based Smart Speaker Use on the Well-Being of Older Adults Living Alone
Park, S., & Kim, B. (2022) · Technology in Society · doi:10.1016/j.techsoc.2022.102133 · Cited by 46 · see citing works
Liu, N., Pu, Q., Shi, Y., Zhang, S., & Qiu, L. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2074667 · Cited by 46 · see citing works
“IVAs have demonstrated the capability to provide customized services, assistance, and support for older adults (Pradhan et al., 2019; Thakur & Han, 2019; Trajkova & Martin-Hammond, 2020).”
BackgroundGao, Y., Jin, Y., Chauhan, J., Choi, S., Li, J., & Jin, Z. (2021) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3448113 · Cited by 45 · see citing works
Mathur, N., Dhodapkar, K., Zubatiy, T., Li, J., Jones, B., & Mynatt, E. (2022) · Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3517428.3544830 · Cited by 45 · see citing works
Brewer, R. N. (2022) · CHI Conference on Human Factors in Computing Systems Extended Abstracts · doi:10.1145/3491101.3519642 · Cited by 43 · see citing works
“and help to provide companionship or connect with others [55, 67].”
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Damholdt, M. F., Quick, O. S., Seibt, J., Vestergaard, C., & Hansen, M. (2023) · International Journal of Social Robotics · doi:10.1007/s12369-023-01014-z · Cited by 46 · see citing works
“[52] 2015 USA Qualitative lab study 20 20.”
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“…participants’ conceptualization of LLM-based chatbots as a “potential friends” or “entities without a personality,” using similar language to the “object-like” versus “human-like” language used by older adults’ to describe categorization of smart-speakers in prior work (Pradhan et al., 2019).”
InfluentialMetaphors in Voice User Interfaces: A Slippery Fish
Desai, S., & Twidale, M. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3609326 · Cited by 42 · see citing works
Designing Conversational AI for Aging: A Systematic Review of Older Adults' Perceptions and Needs
Huang, Y.-H., Zhou, Q., & Piper, A. M. (2025) · International Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713578 · Cited by 54 · see citing works
Cambre, J., Reig, S., Kravitz, Q., & Kulkarni, C. (2020) · Conference on Designing Interactive Systems · doi:10.1145/3357236.3395479 · Cited by 30 · see citing works
“Further still, different populations raise different design needs and usability challenges, such as older adults [42], children [5,29] and settings where multiple people interact simultaneously with an assistant [41].”
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Cambre, J., Williams, A. C., Razi, A., Bicking, I., Wallin, A., Tsai, J., Kulkarni, C., & Kaye, J. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445409 · Cited by 39 · see citing works
“On the one hand, this tendency to anthropomorphize can have positive effects, such as by leading to a sense of attachment or companionship with the assistant [56, 59].”
BackgroundKoban, K., & Banks, J. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.108098 · Cited by 38 · see citing works
Chung, J., Bleich, M., Wheeler, D. C., Winship, J. M., McDowell, B., Baker, D., & Parsons, P. (2021) · Gerontology and Geriatric Medicine · doi:10.1177/23337214211005869 · Cited by 35 · see citing works
“For example, older adults who are socially isolated may see virtual assistants as a social companion and interact with the assistant to feel their desire for social connectedness (Pradhan et al., 2019).”
Desai, S., & Chin, J. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581507 · Cited by 38 · see citing works
Embracing Companion Technologies
Niess, J., & Woźniak, P. W. (2020) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3419249.3420134 · Cited by 36 · see citing works
“The inquiry into the ontology of everyday artefacts was also addressed by more recent work in HCI [37].”
Automation, wellbeing and Digital Voice Assistants: Older people and Google devices
Duque, M., Pink, S., Strengers, Y., Martin, R., & Nicholls, L. (2021) · Convergence The International Journal of Research into New Media Technologies · doi:10.1177/13548565211038537 · Cited by 39 · see citing works
“These dynamics were moreover gendered with personal pronouns and polite manners (Pradhan et al., 2019).”
BackgroundMethodResultInfluentialA Systematic Review of Ethical Concerns with Voice Assistants
Seymour, W., Zhan, X., Coté, M., & Such, J. M. (2023) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3600211.3604679 · Cited by 41 · see citing works
Do, H. J., Kong, H., Lee, J., & Bailey, B. P. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555112 · Cited by 31 · see citing works
Wienrich, C., Carolus, A., Markus, A., Augustin, Y., Pfister, J., & Andreas Hotho, A. (2023) · Computers · doi:10.3390/computers12040077 · Cited by 31 · see citing works
“The primary category captured the extent to which users personify the IVA [69].”
BackgroundTechnology-Mediated Enrichment in Aged Care: Survey and Interview Study
Waycott, J., Zhao, W., Kelly, R. M., & Robertson, E. (2022) · JMIR Aging · doi:10.2196/31162 · Cited by 33 · see citing works
“This is in contrast to some of the recent research on the use of voice assistants and robot devices that suggests they can provide a sense of companionship [40].”
Adaimi, R., Yong, H., & Thomaz, E. (2021) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3448090 · Cited by 29 · see citing works
“Other researchers have studied the use of voice assistants by focusing on particular sub-populations, such as multi-user households [33], children and parents [12, 15], people with disabilities [36], older adults [35], and under-served users in low-income regions [38].”
BackgroundDifferences in Interactions with a Conversational Agent
Oh, Y. H., Chung, K., & Ju, D. Y. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17093189 · Cited by 30 · see citing works
“These studies indicate that CAs are perceived not only as typical electronic machines but also as companions [13,20,29,30].”
BackgroundInfluentialChin, J., Desai, S., Lin, S. (.-H., & Mejia, S. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637365 · Cited by 27 · see citing works
“[55] found that users do not have a fixed mental model to describe VAs.”
BackgroundChen, C., Lifset, E. T., Han, Y., Roy, A., Hogarth, M., Moore, A. A., Farcas, E., & Weibel, N. (2023) · The 25th International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3597638.3608378 · Cited by 25 · see citing works
“, [57, 72]) only focused on general uses (e.”
BackgroundDesai, S., Lundy, M., & Chin, J. (2023) · Proceedings of the 5th International Conference on Conversational User Interfaces · doi:10.1145/3571884.3597141 · Cited by 25 · see citing works
User-centered AI-based voice-assistants for safe mobility of older people in urban context
Anthony, B. (2024) · AI & Society · doi:10.1007/s00146-024-01865-8 · Cited by 25 · see citing works
“In addition, evidence from Pradhan et al. (2019) stated that not all users desire a female voice trait for their voice-assistants.”
InfluentialKoushik, V., & Kane, S. K. (2022) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2022.102862 · Cited by 24 · see citing works
CareJournal: A Voice-Based Conversational Agent for Supporting Care Communications
Rudnik, J., Raghuraj, S., Li, M., & Brewer, R. N. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642163 · Cited by 26 · see citing works
“We used prototype evaluation interviews to gain contextual insight into care partners’ communication practices [50, 51], their interaction with conversational agents [109], and their reactions to computer-mediated care communication [64].”
Yan, C., Johnson, K., & Jones, V. K. (2024) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph21010100 · Cited by 26 · see citing works
“Our sample size ( n = 15) and study duration are consistent with previous studies on voice-activated virtual home assistants among adults 65 or older (average sample size = 16, sample size range: 7–19; study duration range: 3 weeks–12 months) [27,29,40,41].”
ResultSmall Group Interactions with Voice-User Interfaces
Ostrowski, A. K., Zygouras, V., Park, H. W., & Breazeal, C. (2021) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3434073.3444655 · Cited by 28 · see citing works
“will expand the limited capability of the functionalities VUIs can provide today and make them become supportive partners, motivating allies, and collaborative companions [34, 58, 65, 69, 83].”
BackgroundCOVID-19 and the secret virtual assistants: the social weapons for a state of emergency
Sheerman, L., Marston, H. R., Musselwhite, C., & Morgan, D. (2020) · Emerald Open Research · doi:10.35241/emeraldopenres.13571.1 · Cited by 23 · see citing works
“Indeed, VAs provide users with a sense of presence and older adults are reporting the adoption of VAs as a personal friend (Pradhan et al., 2019).”
BackgroundVoice Controlled Devices and Older Adults – A Systematic Literature Review
Jakob, D. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-05581-2_14 · Cited by 26 · see citing works
Soubutts, E., Ayobi, A., Eardley, R., McNaney, R., Cater, K., & O'Kane, A. A. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555193 · Cited by 23 · see citing works
“Voice assistants (VAs) are devices which allow their users to converse, ask questions, and obtain information simply by speaking to the device [61].”
Sengupta, K., Sarcar, S., Pradhan, A., McNaney, R., Sayago, S., Chattopadhyay, D., & Joshi, A. (2020) · Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3334480.3381057 · Cited by 23 · see citing works
Self-citationExamining Humanness as a Metaphor to Design Voice User Interfaces
Desai, S., Dubiel, M., & Leiva, L. A. (2024) · ACM Conversational User Interfaces 2024 · doi:10.1145/3640794.3665535 · Cited by 21 · see citing works
“Moreover, users fluctuated between human and non-human metaphors seamlessly without cognitive dissonance.”
BackgroundGÜLTEKİN, M., & ŞAHİN, M. (2024) · Cyberpsychology Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2024-1-6 · Cited by 20 · see citing works
Kuoppamäki, S., Jaberibraheem, R., Hellstrand, M., & McMillan, D. (2023) · International Journal of Social Robotics · doi:10.1007/s12369-023-01055-4 · Cited by 20 · see citing works
“We aimed to understand issues influencing the acceptability of conversational agents for our participants in order to develop an interaction paradigm that could be perceived as purposeful among this age group [5, 6, 16–18].”
BackgroundStrengers, Y., Duque, M., Mortimer, M., Pink, S., Martin, R., Nicholls, L., Horan, B., Eugene, A., & Thomson, S. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533502 · Cited by 20 · see citing works
“Some studies have highlighted how older people relate to and anthropomorphize voice assistants, which can provide companionship for older adults [59], as we have discussed elsewhere [14].”
BackgroundFridolin: participatory design and evaluation of a nutrition chatbot for older adults
Weber, P. P., Mahmood, F., Ahmadi, M., von Jan, V., Ludwig, T. G., & Wieching, R. (2023) · i-com · doi:10.1515/icom-2022-0042 · Cited by 21 · see citing works
Is Alexa like a computer? A search engine? A friend? A silly child? Yes.
Desai, S., & Twidale, M. (2022) · Proceedings of the 4th Conference on Conversational User Interfaces · doi:10.1145/3543829.3544535 · Cited by 20 · see citing works
Arakawa, R., Lehman, J. F., & Goel, M. (2024) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3699759 · Cited by 22 · see citing works
Age-Related Differences in Preferences for Using Voice Assistants
Gollasch, D., & Weber, G. (2021) · Mensch und Computer (MuC) · doi:10.1145/3473856.3473889 · Cited by 20 · see citing works
“(15) Integrate security questions as checks to prevent accidental irreversibly actions – [33] age 60+ (16) Make suggestions proactively – [6] general usability issues of voice assistants (17) Offer help and support proactively – [26] age 65-83, mean: 71.”
Background"This machine is for the aides": Tailoring Voice Assistant Design to Home Health Care Work
Bartle, V., Albright, L., & Dell, N. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581118 · Cited by 18 · see citing works
“IVAs have also shown potential for inhome health applications [55, 61, 80, 83], including self-managing health conditions [22], supporting independent living [21], and providing emotional support[24, 49, 52].”
BackgroundManiar, N., Chan, S., Zulfikar, W. D., Ren, S., Xu, C., & Maes, P. (2025) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3708359.3712151 · Cited by 23 · see citing works
Speaking with My Screen Reader: Using Audio Fictions to Explore Conversational Access to Interfaces
Phutane, M., Jung, C., Chen, N., & Azenkot, S. (2023) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3597638.3608404 · Cited by 18 · see citing works
“[102] Researchers investigated metaphorical perceptions of CAs and investigated whether users viewed them as mere “object-like” tools, or “human-like” friends [81, 83, 103].”
BackgroundInfluentialDigital ethnography of home use of digital personal assistants
Paay, J., Kjeldskov, J., Hansen, K. M., Jørgensen, T. B., & Overgaard, K. L. (2020) · Behaviour and Information Technology · doi:10.1080/0144929x.2020.1834620 · Cited by 19 · see citing works
“…Findlater 2018) and older adults (Pradhan, Findla-ter, and Lazar 2019), personi fi cation of digital personal assistants (Lopatovska and Williams 2018; Pradhan, Findlater, and Lazar 2019; Purington et al. 2017), racial and socioeconomic impacts on DPA use (Garg and Sen-gupta 2019), privacy issues…”
BackgroundMethodInfluentialSin, J., Chen, D., Threatt, J. G., Gorham, A., & Munteanu, C. (2022) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3543829.3543841 · Cited by 19 · see citing works
“However, conversational VUIs may better match older adults’ needs and expectations, as has suggested in existing literature [19].”
BackgroundCybersex with human- and machine-cued partners: Gratifications, shortcomings, and tensions.
Banks, J., & Ouytsel, J. V. (2020) · Technology Mind and Behavior · doi:10.1037/tmb0000008 · Cited by 17 · see citing works
“…cueing is multimodal, comprising visual (e.g., expressions and gazes; cf. Chesher & Andreallo, 2020), verbal (textual conveyances or vocalizations; Pradhan et al., 2019), and behavioral (e.g., social context awareness cues; Fraune et al., 2020) properties that denote a “living/nonliving,”…”
BackgroundLiu, C., Su, M., Xiang, Y., Huang, Y., Yang, Y., Kang Zhang, A., & Fan, M. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714228 · Cited by 17 · see citing works
“In this context, voice agents utilize artificial intelligence to offer an intuitive and accessible conversational way for older adults to interact with technology, providing assistance and companionship [42, 66, 77, 99].”
Voice Assistants for Mental Health Services: Designing Dialogues with Homebound Older Adults
Wong, N., Jeong, S., Reddy, M. C., Stamatis, C. A., Lattie, E. G., & Jacobs, M. L. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3661536 · Cited by 22 · see citing works
Phinnemore, R., Reza, M., Lewis, B., Mahadevan, K., Wang, B. K., Annett, M., & Wigdor, D. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581346 · Cited by 18 · see citing works
“As voice assistants can be designed with anthropomorphic characteristics such as genders and personas [2, 54] and given that voice assistants play human-like behavioural roles (i.”
BackgroundAnthony, B. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2344145 · Cited by 19 · see citing works
ShamAIn: Designing Superior Conversational AI Inspired by Shamanism
Cho, H., Seo, J. A., Lee, J., Kim, C.-M., & Nam, T.-J. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714297 · Cited by 19 · see citing works
“For instance, CAI has proven efective as a caregiver for older adults [77, 106], a tour guide [17], a mental health counselor [53, 104], an educational mentor [71, 94], a friend [10], and even a romantic partner [4].”
Zhang, R., Duan, W., Flathmann, C., McNeese, N. J., Knijnenburg, B. P., & Freeman, G. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3686976 · Cited by 18 · see citing works
Minder, B., Wolf, P., Baldauf, M., & Verma, S. (2023) · Humanities and Social Sciences Communications · doi:10.1057/s41599-023-01615-z · Cited by 18 · see citing works
“Two papers from both CS and SS contributed to the theory of anthropomorphism in the VA context (Lopatovska and Oropeza, 2018; Pradhan et al., 2019).”
BackgroundRingfort-Felner, R., Laschke, M., Neuhaus, R., Theofanou-Fülbier, D., & Hassenzahl, M. (2022) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3546155.3546699 · Cited by 15 · see citing works
“Recent work has already begun to broaden the roles IPAs can take in such a relationship, for example, as a friend [52, 59, 67], companion [43, 57], coach [71], or tutor [27], depending on the specific requirements of different situations, such as commuting to work.”
BackgroundInfluentialSchuß, M., Rollwagen, A., & Riener, A. (2022) · Multimodal Technologies and Interaction · doi:10.3390/mti6120109 · Cited by 17 · see citing works
Garg, R., Cui, H., & Kapadia, Y. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479495 · Cited by 15 · see citing works
“, [3, 9, 31, 50, 65, 67, 79]) have assessed the use of smart speakers by various groups of users (e.”
BackgroundChang, F., Sheng, L., & Gu, Z. (2024) · JMIR mHealth and uHealth · doi:10.2196/47472 · Cited by 14 · see citing works
“Other studies have assessed the feasibility and usability of smart speakers for promoting active aging [19,20], investigated older adults’first impressions of smart speakers [19,21], and identified influential factors regarding older adults’attitudes toward smart speakers [22].”
BackgroundThe Use of Smart Home Speakers by the Elderly: Exploratory Analyses and Potential for Big Data
Purao, S., Hao, H., & Meng, C. (2021) · Big Data Research · doi:10.1016/j.bdr.2021.100224 · Cited by 15 · see citing works
Zaga, C., & Lupetti, M. L. (2022) · doi:10.3990/1.9789036553599 · Cited by 14 · see citing works
Using Voice-Activated Technologies to Enhance Well-Being of Older Adults in Long-Term Care Homes
Grigorovich, A., Marcotte, A.-A., Colobong, R., Szabo, M., MacNeill, C., Blais, D., Giffin, G., Clahane, K., Goldman, I. P., Harris, B., et al. (2024) · Innovation in Aging · doi:10.1093/geroni/igae102 · Cited by 13 · see citing works
“Recent research on voice-activated ICTs suggests that these may be even more beneficial for older adults with disabilities or complex health issues given their accessibility features, relatively simple user interface, and built-in virtual assistant (Nimrod & Ivan, 2022; Pradhan et al., 2019).”
Ethical aspects of voice assistants: a critical discourse analysis of Indonesian media texts
Arifin, A. A., & Lennerfors, T. T. (2021) · Journal of Information Communication and Ethics in Society · doi:10.1108/jices-12-2020-0118 · Cited by 13 · see citing works
A Taxonomy of Embodiment in the AI Era
Hellström, T., Kaiser, N., & Bensch, S. (2024) · Electronics · doi:10.3390/electronics13224441 · Cited by 14 · see citing works
Desai, S., Hu, X., Lundy, M., & Chin, J. (2023) · International Conference on Human-Agent Interaction · doi:10.1145/3623809.3623827 · Cited by 13 · see citing works
Habscheid, S., Hector, T., Hrncal, C., & Waldecker, D. (2021) · Journal für Medienlinguistik · doi:10.21248/jfml.2021.44 · Cited by 13 · see citing works
“Die Aufzeichnungen erwiesen sich auch bei einer Untersuchung zur Personifizierung und ontologischen Kategorisierung von IPA-Dialogen als nützlich, wurden aber auch hier zusätzlich zu Interviews herangezogen (vgl. Pradhan et al. 2019).”
BackgroundExperience of the Use of AI Conversational Agents Among Low-Income Older Adults Living Alone
Kim, K. M., & Kim, S. H. (2024) · SAGE Open · doi:10.1177/21582440241301022 · Cited by 13 · see citing works
“Personification involves treating conversational agents as if they were human (Pradhan et al., 2019).”
InfluentialJang, Y.-B. (2020) · Archives of Design Research · doi:10.15187/adr.2020.08.33.3.127 · Cited by 15 · see citing works
“As noted in Pradhan et al. (2019), “personification” and “anthropomorphism” are interchangeably used from time to time.”
BackgroundLong-Term Interaction with Relational SIAs
Kory-Westlund, J. M., Park, H. W., Grover, I., & Breazeal, C. (2022) · ACM eBooks · doi:10.1145/3563659.3563667 · Cited by 12 · see citing works
Ahire, S., Rohs, M., & Simon, B. (2022) · Annual Symposium on Human-Computer Interaction for Work (CHIWORK) · doi:10.1145/3533406.3533420 · Cited by 11 · see citing works
Framing Effects on Judgments of Social Robots’ (Im)Moral Behaviors
Banks, J., & Koban, K. (2021) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.627233 · Cited by 11 · see citing works
“…context and self-relevance may drive more speci fi c frames, as when eldercare professionals frame robots as threats to their roles (Frennert et al., 2021), while older adults themselves tend to hold relative-humanness frames for AI, emphasizing companionship potentials (Pradhan et al., 2019).”
Background
- Authors
- Pradhan, A., Findlater, L., & Lazar, A.
- Affiliations
- University of Maryland, College Park (US)
- University of Washington (US)
- Venue
- Proceedings of the ACM on Human-Computer Interaction
- Published
- 2019-11-07
- Volume
- 3
- Issue
- CSCW
- Pages
- 1-21
- ISSN
- 2573-0142 (ISSN-L)
- OpenAlex
- W3084929246
- Cited by
- 223
- References
- 65
- Citations by year
- 2026: 25 · 2025: 45 · 2024: 35 · 2023: 28 · 2022: 42 · 2021: 30 · 2020: 17 · 2019: 1
- FWCI
- 28.27
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the ACM on Human-Computer Interaction (publishedVersion)
- Funders
- Mozilla Foundation
- National Science Foundation (#1816145)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- voice assistants, anthropomorphism, older adults, social companionship, loneliness, human-AI interaction
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