Biometrics as a global industry is evolving rapidly. With each passing day, more news sprouts up about countries adopting biometric identification technology to secure borders, establish free and fair elections, or tighten airport security. Countries like India have embarked on massive identity campaigns to develop documentation that helps facilitate more equitable social benefit distribution and eliminate government waste and corruption. Governments all over the planet are increasingly evaluating and choosing to adopt biometric identification technology to boost security, eliminate fraud, and establish societal parity by ensuring that entitlements reach those for whom they were intended.
However, using biometrics for identification and authentication reaches far beyond tightening security and eliminating fraud and waste. As biometric deployments spill over into the commercial sector, companies are starting to leverage the technology’s power to encourage employee accountability, lower liabilities, increase efficiencies, and strengthen compliance. Biometric used in business vs. government deployments has fundamentally transformed the dimension of using the technology for security only to using it for convenience in addition to security and other concerns.
In order to achieve success in the new commercial landscape, biometric technology vendors who were once solely accustomed to government specs dictating the parameters and scope of a biometric identification project where end users (most often citizens) had no choice on what biometric modalities to use had to become experts at “human factor engineering” – that is, biometric tech vendors had to more closely study the intersection of people, technology, policy, and work across multiple domains using an interdisciplinary approach that drew from cognitive psychology, organizational psychology, human performance, industrial engineering, and economic theory to design and implement biometric systems that are acceptable and successful in a commercial environment.
18. Human Factor Engineering
• Age of the • Intuitive design
users • User feedback
• Working class • Footprint
• Culture
Demography Ergonomics
Weather Cost
• Cold • Biometric
• Dry module can’t be
• Wet more expensive
then system