Restricting Data Sharing and Collection of Facial Recognition Data by the Consent of the User: A Systems Analysis

Mass Data Collection through Facial Recognition Technology poses a threat to the personal privacy of millions, with big data companies selling and analyzing user data points without appropriate consent and having unrestricted access to said data. Personal privacy should be a right that requires protection in our interconnected society that is becoming ever more reliant on technology. We believe that as this technology progresses without proper restriction, its implementation will effectively eliminate personal privacy, effectively placing a constraint on user autonomy. This is due in part to the vagueness of current policies centered around privacy. If this does not change, personal privacy could be eliminated. FRT has many features, some of which are controversial and impede its effectiveness. Through a systems analysis approach that examines the integration of the social and technical dimensions of these privacy problems, our preliminary research examines several approaches that will be most effective in addressing this complex problem while supporting FRT development. By proposing the following solutions, we hope to prevent personal privacy infringement via FRT: Propose and pass policy similar to the Commercial Facial Recognition Privacy Act, improve data encryption for databases with sensitive personal information (such as Facial Recognition data), and change the way privacy policy is delivered to the consumer by setting maximum length standards on the policy that is written and using less legal jargon to promote the reading and understanding of these privacy policies and what they require of the user. Based on analysis of these proposed solutions, we believe that there will be an increase in security and the feeling of personal privacy across the board.