Public Perceptions of Biometric Devices: The Effect of Misinformation on Acceptance and Use

Introduction The term biometrics relates to the measurement (metric) of characteristics of a living (bio) thing in order to identify it. The techniques of using physical characteristics for identification can be traced to the ancient Egyptians who used the biometric of height (Roberts, 2003). Today the most widely recognized biometric is the fingerprint, which has been in use for over a century. At its inception, fingerprinting required the manual processing of matching between 20 and 7 minutiae points on the whorls, arches, and loops of a fingerprint (Short, 2002). By the mid-1970s, the process had been automated in the US by the Federal Bureau of Investigation into the Automated Fingerprint Identification Systems (AFIS) now used throughout the world (Roberts, 2003). Enabled by the accelerated changes in technological power, other biometrics came to be used, such as hand geometry, iris and retina scanning, voice, and handwriting verification (Harris & Yen, 2002). Today biometric devices are used in diverse organizational settings ranging from cafeterias for school children (Graziano, 2003) to white-collar employees at the Mitsubishi Motors North America plant (Maher, 2003) to doctors at the University of Arizona Medical Center (Worthen, 2002). The reasons for these implementations are also various. The school cafeteria utilizes the system to track student expenses so that parents only pay for the lunches actually eaten, rather than a lump sum for a full semester. The five hundred Mitsubishi Motors white-collar employees use biometrics to clock in when they arrive at their desks in order to monitor their productivity and time on the job. The doctors have their fingerprints scanned instead of using passwords for logging onto their computer systems, thereby increasing security and saving time in the process. The savings for using biometrics in organizational settings to eliminate passwords and their associated calls to the help desk have been estimated at $50 to $100 per call (Hulme, 2003). When comparing this to the one time cost of current fingerprint scanners of under $100 each (Louwers & VanDenburgh, 2003), the organization's return on investment seems self-evident. Given the advantages of using a biometric system for monitoring employees and increasing security of information as well as access to buildings, it is not surprising that the industry is expected to grow from $93.4 million in 2001 (Hulme, 2003) to $4 billion in 2007 (Roberts, 2003). However, even with the wide adaptability of the technology to various organizational functions, the acceptance of biometrics has been slow. Reasons cited for hesitancy to use biometric devices include lack of confidence in the reliability, difficulties integrating with other systems, and getting people to change their work patterns (Hulme, 2003). However, the most often cited obstacle is user apprehension (Calderon & Subbaiah, 2003; Fratto, 2003; Roberts, 2003) Thus, despite these advantages, it has been reported that public perceptions of biometrics can hinder their acceptance. In order to address these perceptions, it is first necessary to identify them. This paper presents the findings from a survey of 300 respondents regarding their familiarity with and acceptance of biometric devices. It begins with a brief discussion of commonly used biometric devices, presents the survey methodology and results, and concludes with suggestions for alleviating misconceptions through education. Common Types of Biometric Devices The most common biometric devices used today include: fingerprint scans, iris scans, retina scans, voice recognition, and handwriting recognition. Each will be discussed briefly below. In every case, the initial process for using biometric devices is to enroll the participants in the system by taking several samples of the biometric to be used in order to create a biometric template. The template consists of binary numbers, making it impossible to re-create the biometric sample from the template. …