Advertisement

Age-Related Accessibility Biases in Pass-Face Recognition

  • Ray Adams
  • Gisela Susanne Bahr
  • Ejder Sevgen Raif
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6766)

Abstract

Accessibility and security are often depicted as conflicting aspirations. Accessible systems may be less secure and secure systems may be less accessible. The search is on for greater security for logging onto systems, whilst achieving acceptably high levels of accessibility. Pass-faces are based on the twin axioms of greater accessibility and security. A new user of a pass face system is asked to select “n” faces from an array of faces, where n is at least two and usually more. The user is required to memorize those faces and to recognize them again when represented to you as part of larger display. It has been suggested that this approach is less susceptible to poaching than are alphanumeric methods. There has been a considerable volume of work to evaluate the usage of pass face systems, but little work on the psychology of pass faces. Equally, pass face systems have received little attention from researchers in accessibility. In the present study, two previously unrelated themes were investigated in two experiments. First, are pass face systems acceptably usable? Second, how do pass face systems rely on the reliability of human face recognition memory? In two experiments, two types of pass face system consisting of (a) older faces; over 50 years of age and (b) younger faces; under 30 years of age were created. It turns out that younger participants are often better at recognizing younger faces than older faces in the context of pass face security, whilst older participants are sometimes better at recognizing older faces than younger faces in the context of pass face security. Thus an experiment that used only younger faces would falsely conclude that younger participants were better at face recognition memory than older participants in general. These results were checked and confirmed by literatures reviews of pass face security and human recognition memory for faces. These results show that universal access cannot be applied on a one-size-fits-all basis. They also suggest that the security-related disciplines of HCI and psychology would benefit from greater interaction between them.

Keywords

Recognition Memory Practice Session Famous People Face Recogni Background Item 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bahr, G.S., Ford, R.: Why Pop-Ups Don’t Work And How To Make Them Effective: Pop-Up Prompted Eye Movements, User Affect And Decision Making. Computers in Human Behavior 27, 776–783 (2011)CrossRefGoogle Scholar
  2. 2.
    Barrington, L., Yoder-Wise, P.: Executive control function: a clinically practical assessment. Journal of Gerontological Nursing 32(2), 28–34 (2006)CrossRefGoogle Scholar
  3. 3.
    Elias, J.W., Treland, J.: Executive function in Parkinson’s disease and subcortical disorders. Seminars in Clinical Neuropsychiatry 4(1), 34–40 (1999)Google Scholar
  4. 4.
    Levitt, T., Fugelsang, J., Crossley, M.: Processing speed, attentional capacity, and age-related memory change. Experimental Aging Research 32, 263–295 (2006)CrossRefGoogle Scholar
  5. 5.
    Park, D.: Consumer Fraud and the Aging Mind. Scientific Testimony Presented to the Senate Special Committee on Aging (July 27, 2005), www.centerforhealthyminds.org/downloads/park%20testimony.pdf (accessed July 2007)
  6. 6.
    Perfect, T.J., Moon, H.C.: The own-age effect in face recognition. In: Duncan, J., Phillips, L., McLeod, P. (eds.) Measuring the Mind, pp. 317–337. Oxford University Press, Oxford (2005)Google Scholar
  7. 7.
    Royall, D.R.: Précis of executive dyscontrol as a cause of problem behavior in dementia. Experimental Aging Research 20, 73–94 (1994)CrossRefGoogle Scholar
  8. 8.
    Skurnik, I., Yoon, C., Park, D.C., Schwarz, N.: How warnings about false claims become recommendations: Paradoxical effects of warnings on beliefs of older consumers. Journal of Consumer Research 31, 713–724 (2005)CrossRefGoogle Scholar
  9. 9.
    Stableford, S., Mettger, W.: Plain Language: A Strategic Response to the Health Literacy Challenge. Journal of Public Health Policy 28, 71–93 (2007)CrossRefGoogle Scholar
  10. 10.
    U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Quick Guide to Health Literacy, www.health.gov/communication/literacy/quickguide (accessed July 2007)

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ray Adams
    • 1
  • Gisela Susanne Bahr
    • 2
  • Ejder Sevgen Raif
    • 3
  1. 1.Collaborative International Research Centre for Universal Access (CIRCUA), School of Engineering & Information SciencesMiddlesex UniversityLondonUK
  2. 2.Florida Institute of TechnologyMelbourneUSA
  3. 3.Collaborative International Research Centre for Universal Access (CIRCUA)UK

Personalised recommendations