Numerous projects, normally run by younger people, are exploring robot use by older people. But are older any different from younger people in the way they want to interact with robots? Understanding older compared to younger people’s preferences will give researchers more insight into good design. We compared views on multi-modal human–robot interfaces, of older people living independently, with students and university staff. We showed 96 participants aged under 65 and 18 aged 65 + , six videos presenting different scenarios, including interfaces both working properly and failing, for an older man interacting with a robot by speech and touch screen tablet. Participants were asked about the interfaces they might use and why, using self-completed questionnaires with mainly open-ended questions. People over 65 were more like people under 21 than those aged 22–64 (78%, 67%, 47% respectively) in preferring speech over tablet for robot–human interaction. But reasons for doing so may differ, for example, hearing and eyesight impairment versus speaking while hands full. Older participants were more likely (83% vs. 55%) to want a robot in the house than those under 65. Older people were as familiar with tablets and smart speakers as younger people, but less likely to use smart phones. Some younger people suggested interacting with robot via their smart phone, and while not at home. Answers to similar questions about preferences for robot interaction varied according to position in the questionnaire. User-centred design of human–robot interfaces should include open questions to understand people’s preferences, should account for question wording and order in interpreting user preferences, and should include people of all age ranges to better understand interface use. Older people’s technology needs have differences and similarities to the younger people who are likely carrying out the research. Our sample of older people were more like people under 21 than those aged in between for preference of robot–human interaction, and more willing to have a robot in the home than younger people. Differences may come from a more home based lifestyle and difficulties with vision, hearing, or dexterity rather than lack of interest in technology.
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Government Office for Science (2017) Future of an ageing population. Foresight report looking at the challenges and opportunities of an ageing society 2016. https://www.gov.uk/government/publications/future-of-an-ageing-population. Accessed 5 Oct 2017
Broekens J, Heerink M, Rosendal H (2009) Assistive social robots in elderly care: a review. Gerontechnology. https://doi.org/10.4017/gt.2009.08.02.002.00
Frennert S (2016) Older people meet robots: Three case studies on the domestication of robots in everyday life. Doctoral dissertation, Lund University, Lund, Sweden
Lu DV, Smart WD (2011) Human–robot interactions as theatre. In: RO-MAN-11, pp 473–478. https://doi.org/10.1109/roman.2011.6005241
Pantic M, Cowie R, D’Errico F, Heylen DKJ, Mehu M, Pelachaud C et al (2011) Social signal processing: the research agenda. In: Moeslund T, Hilton A, Krüger V, Sigal L (eds) Visual analysis of humans. Springer, London. https://doi.org/10.1007/978-0-85729-997-0_26
Breazeal C (2003) Emotion and sociable humanoid robots. Int J Hum Comput Stud 59:119–155
Dautenhahn K (2007) Socially intelligent robots: dimensions of human–robot interaction. Philos Trans R Soc Lond B Biol Sci 362:679–704
Brick T, Scheutz M (2007) Incremental natural language processing for HRI. In: 2nd ACM/IEEE international conference on human–robot interaction (HRI), Arlington, VA, pp 263–270
Bastianelli E, Castellucci G, Croce D, Basili R, Nardiet D (2014) Effective and robust natural language understanding for human robot interaction. Front Artif Intell Appl. https://doi.org/10.3233/978-1-61499-419-0-57
Salichs MA, Barber R, Khamis AM, Malfaz M, Gorostiza JF, Pacheco R, Rivas R, Corrales A, Delgado E, Garcia D (2006) Maggie: a robotic platform for human-robot social interaction. In: 2006 IEEE conference on robotics, automation and mechatronics, Bangkok, pp 1–7. https://doi.org/10.1109/RAMECH.2006.252754
SoftBank Robotics (2017) Who is pepper? https://www.ald.softbankrobotics.com/en/robots/pepper. Accessed 5 Oct 2017
HOBBIT Project Website (2017) HOBBIT—the mutual care robot. http://hobbit.acin.tuwien.ac.at/. Accessed 5 Oct 2017
MARIO Project (2017) http://www.mario-project.eu/portal/. Accessed 5 Oct 2017
Enrich me—Our approach (2017) http://www.enrichme.eu/wordpress/about/our-approach/. Accessed 5 Oct 2017
Robot-Era (2017) http://www.robot-era.eu/robotera/index.php. Accessed 5 Oct 2017
Fischinger D, Einramhof P, Papoutsakis K, Wohlkinger W, Mayer P, Panek P et al (2016) Hobbit, a care robot supporting independent living at home: first prototype and lessons learned. Robot Auton Syst 75:60–78
Frennert S, Östlund B (2014) Seven matters of concern of social robots and older people. Int J Social Robot 6(2):299–310
Dorsten AM, Sifford KS, Bharucha A, Mecca LP, Wactlar H (2009) Ethical perspectives on emerging assistive technologies: insights from focus groups with stakeholders in long-term care facilities. J Empir Res Hum Res Ethics 4(1):25–36. https://doi.org/10.1525/jer.2009.4.1.25
Pino M, Boulay M, Jouen F, Rigaud AS (2015) “Are we ready for robots that care for us?” Attitudes and opinions of older adults towards socially assistive robots. Front Aging Neurosci. https://doi.org/10.3389/fnagi.2015.00141
Wu YH, Fassert C, Rigaud AS (2012) Designing robots for the elderly: appearance issue and beyond. Arch Gerontol Geriatr 54(1):121–126. https://doi.org/10.1016/j.archger.2011.02.003
Heerink MB, Krose V, Evers B, Wielinga B (2010) Assessing acceptance of assistive social agent technology by older adults: the almere model. Int J Social Robot 2(4):361–375. https://doi.org/10.1007/s12369-010-0068-5
Heerink M, Krose B, Evers V, Wielinga B (2009) Measuring acceptance of an assistive social robot: a suggested toolkit. In: The 18th IEEE international symposium on robot and human interactive communication, vol. 1 and 2. https://doi.org/10.1109/roman.2009.5326320
Wallen F (2017) Comparing voice and touch interactions for smartphone radio and podcast application. https://kth.diva-portal.org/smash/get/diva2:1119305/FULLTEXT01.pdf. Accessed 5 Oct 2017
Multiple-actOrs Virtual Empathic CARgiver for the Elder (MoveCare). https://cordis.europa.eu/project/rcn/206414/factsheet/en. Accessed 17 July 2019
Broadbent E, Kuo IH, Lee YI, Rabindran J, Kerse N, Stafford R et al (2010) Attitudes and reactions to a healthcare robot. Telemed J E Health. https://doi.org/10.1089/tmj.2009.0171
Minae KM, Jung MF, Knepper RA (2016) Human expectations of social robots. In: Proceeding HRI’16 the eleventh ACM/IEEE international conference on human robot interaction, pp 463–464. ISBN: 978-1-4673-8370-7
DiNuevo A, Broz F, Wang N, Belpaeme T, Cangelosi A, Jones R et al (2017) The multi-modal interface of robot-era multi-robot services tailored for the elderly. Intell Serv Robot. https://doi.org/10.1007/s1137
Arras KO, Cerqui D (2005) Do we want to share our lives and bodies with robots? A 2000-people survey. Technical report 0605-001. Autonomous Systems Lab Swiss Federal Institute of Technology, EPFL. www2.informatik.uni-freiburg.de/~arras/papers/arrasTR05.pdf. Accessed 10 Feb 2018
Office for National Statistics (2016) Internet access—households and individuals: 2016. 5. Mobile or smartphones are the most popular devices used by adults to access the internet. https://www.ons.gov.uk/peoplepopulationandcommunity/householdcharacteristics/homeinternetandsocialmediausage/bulletins/internetaccesshouseholdsandindividuals/2016#mobile-or-smartphones-are-the-most-popular-devices-used-by-adults-to-access-the-internet. Accessed 12 Feb 2018
Brink MD, Schreckenberg D, Vienneau D, Cajochen C, Wunderli JM, Probst-Hensch N et al (2016) Effects of scale, question location, order of response alternatives, and season on self-reported noise annoyance using ICBEN scales: a field experiment. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph13111163
Lee S, McClain C, Webster N, Han S (2016) Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated health, and subjective life expectancy in survey instruments. Qual Life Res 25(10):2497–2510. https://doi.org/10.1007/s11136-016-1304-8
Siminski P (2008) Order effects in batteries of questions. Qual Quant 42(4):477–490. https://doi.org/10.1007/s11135-006-9054-2
Re DE, O’Connor JJM, Bennett PJ, Feinberg DR (2012) Preferences for very low and very high voice pitch in humans. PLoS ONE. https://doi.org/10.1371/journal.pone.0032719
Pichora-Fuller MK, Singh G (2006) Effects of age on auditory and cognitive processing: implications for hearing aid fitting and audiologic rehabilitation. Trends Amplif. https://doi.org/10.1177/108471380601000103
Liu H, Wang EQ, Chen Z, Liu P, Larson CR, Huang D (2010) Effect of tonal native language on voice fundamental frequency responses to pitch feedback perturbations during sustained vocalizations. J Acoust Soc Am 128:3739–3746
Tay B, Jung BY, Park T (2014) When stereotypes meet robots: the double-edge sword of robot gender and personality in human-robot interaction. Comput Hum Behav 38:75–84. https://doi.org/10.1016/j.chb.2014.05.014
Wainer J, Feil-seifer DJ, Shell DA, Mataric MJ (2006) The role of physical embodiment in human–robot interaction. Robot Hum Interact Commun. https://doi.org/10.1109/ROMAN.2006.314404
Dautenhahn K, Ogden B, Quick T (2002) From embodied to socially embedded agents—implications for interaction-aware robots. Cognit Syst Res 1:2. https://doi.org/10.1016/s1389-0417(02)00050-5
We thank Deborah Hubbard and residents at Wesley Court Plymouth, students and staff at the University of Plymouth who took part, and all collaborators on the MoveCare project for their comments on this project.
This study was partly funded by EU funding for the MoveCare Project https://cordis.europa.eu/project/rcn/206414/factsheet/en. University of Plymouth were funded by the MoveCare Project. Funding was provided by Horizon 2020 (Grant No. 732158).
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Biswas, M., Romeo, M., Cangelosi, A. et al. Are older people any different from younger people in the way they want to interact with robots? Scenario based survey. J Multimodal User Interfaces 14, 61–72 (2020). https://doi.org/10.1007/s12193-019-00306-x