Ethical Implications of Biometrics Face Recognition Systems
Biometrics Face Recognition system are used to identify people who have been born with their own unique identity that can never be changed or similar to others but is somehow identical. That is where the magic of technology begins, using unique traits from human faces, software develops more advancements in the tech world.
Machine Learning is the key tool used by data scientists to biometrically differentiate people who are identical. Each has its own features, expressions, and characteristics which can be mathematically extracted known as “face vectors” while scanning faces using face-matching algorithms.
What is Biometrics Face Recognition System?
Face Recognition Systems consists of multiple machine learning algorithms that use face verification software to verify the face that has been scanned in front of the camera by using a selfie factor. The software scans the retina or iris, expressions like the distance between eyes and their color, shape of the nose, mouth, shape of jaws, and cheekbones.
Once the face matches the dataset the concerned image will be verified. This whole process basically requires seconds to finish up the verification in the backend. The feature of this technology quickly accesses the same individual and denies the fake ones on an immediate basis saves more time and involves less processing than any other recognition system.
Top Ethical Questions that Haunt Biometrics Face Recognition Systems
There are multiple aspects that raise many questions to haunt Facial Recognition Technology:
1. Privacy Invasion
Invading someone’s privacy generates many concerns related to security issues because it gathers and stores a large amount of personal data without the knowledge of individuals. There have also been worries that the data stored by software companies use without consent to identify criminals using secure liveness check face recognition systems.
Racial biases, surveillance and a mass amount of data can be stored to violate freedom of speech or by using deep fake technologies to misuse or mislead people’s identity in order to defame them.
2. Racial and Gender Bias
Facial Recognition Systems is said to have biased results using face matching algorithms that detect more white males than black males. This has been huge since its inception and cannot be overcome till now as some organization uses these software for their own benefits and never adjust such people who are hardworking yet incompetent.
This biasness can lead to false detection indirectly not allowing people to enter their circumstances to discriminate against them and make diverse decisions against them hypothetically.
3. Misuse of Personal Information
Misusing some saved personal information of users, some companies interpret that all the information belongs to them and they can breach this information whenever required. This resulted in trust issues in people regarding whether their stored information is safe or not. Whenever there comes an emerging case of any emergency they oversee all information to the concerned companies for the purpose of verification who then detects and verifies the identity of users.
Here the biggest concern arises that people do not allow companies to take over their personal information or presume for a second that all the information belongs to them.
4. Lack of Accountability
Some companies use third-party software to save the data of their customers and are not concerned about privacy. The data shared by users using facial scans are not stored properly in the dataset. Hence, the data remains open to many deepfake webs that violate privacy and hack all the information resulting in threats or asking for their desired information.
People are then more concerned about whether to share their personal information online or not. Thus, inequitable scenarios build more concerns in secure facial recognition technology.
5. Security Concerns
Biometric face recognition is now a question of security and privacy that involves storage, concerns, and processing of sensitive information that increases the vulnerability to cyber attacks, data breaches, hacking, and identity theft.
Errors can be prevented in machine learning but AI solved and access each data internally for a safer experience but sometimes negative consequences make all disruption.
6. Human Error Leading to False Detection
Human errors can cause many disabilities by capturing improper images or falsely saving training data, mixing training data with testing data, inadequate verification software, and without validating identities.
Using strict protocols, formal caliber software, and responsible identity names can help to deliver the required results but unfortunately, people unwillingly do not want to accept the requirement of face recognition API in today’s real world.
Why is Facial Recognition API Worth Considering?
Facial Recognition API considers a quick and efficient way to detect the identity of a person with very useful and various scenarios such as access control, restricted areas, security screening, and identity verification. It is less intrusive as compared to other passwords, and identification methods since it uses physical identities for authentication.
Without a face scan, others cannot breach it because it will not recognize the detected face, this considers the fact that it is the most efficient way to secure privacy.
Facia’s Commitment to Comply all Ethical Implications With Best Practices
Facia emerges as the leader of all Biometrics face recognition security systems and can be marked as the best software with 100% guaranteed data protection. It strives to build the facial recognition liveness check in providing ultimate security considering the laws and their enforcement. This includes adhering to establishing businesses, appropriate methodologies, and continuous efforts to make better and more efficient results in meantime.
Facia face verification with AI-powered 3D liveness recognizes the importance of ethical practices and strives to maintain the employee’s data with foolproof security ensuring their well beings and their safety as a priority. We comply with the following practices to ensure the ethical implication of technology.
How We Proceed With Privacy?
1. Inform Consent
We ensure to have designed a framework for the business that protects users’ data to secure their privacy. We consistently inform each person about their data protection that cannot be breached at any cost and willingly provides each and every detail to the owner. If the user did not allow us to access their privacy we will not proceed further.
2. Ensure Transparency
Facia believes that clarity is very important at any stage while connecting with the user. The information should be easily accessible to the owner but highly protected from third parties. We ensure that maintaining good relationships with stakeholders or customers can improve relations. Lack of transparency can be categorized as eroding trust and leading to suspected illegal or unethical activities.
3. Conduct Regular Evaluation
Collecting and analyzing information according to the requirements to improve the effectiveness of the software, methods, programming decisions, etc. Evaluation basically provides systematic methods to ensure practices and interventions that appraise a brand to increase its awareness and determine how well goals are achieved.
4. Provide Adequate Security
Loss or theft of data by unauthorized access or hackers results in the failure of implementing policies designed by software. Facia assures to provide security measures using physical or technical derivates.
5. Ethical Framework
Facia allows its user to make individual decisions in preventive and corrective ways to ensure compliance with programs. We treat each individual fairly and cannot compromise on them. The best software is knowns for its work and document each and everything leading to the capabilities and strengths. Discrimination acts, unfair means, public information, data theft, spoof attacks, and risks of anything that damages a user’s identity are strictly observed by the Data Management Team.
3. Regular Engagement with Experts
We are bound to deliver the best results as an emerging software. It is fact that customers are and will always be the valuable asset of any company. Keeping that in mind, Facia is highly responsible for data handling and stores that information in secure datasets that cannot be breached by anyone even not by team members without consent. We use to engage with our experts on a regular basis to ensure that our software is up to the mark.
Security Commitments of Facia
The most important purpose of the face recognition security system is to protect people and their identities. Excellent features in security are basically a commitment to personal responsibility that requires honesty and integrity. Facia assures with a clear understanding that assets cannot be shared with anyone including third parties even for verification purposes.
We are highly responsible for building datasets with individual worth and dignity ethically to keep employees safe from harm. Data saved by our users are very critical information and hence cannot be breached by hackers.
Users when scanning their faces in front of the camera their facial characteristics, expressions, and features will be detected by biometrics face recognition using face matching algorithms in the form of mathematical digits known as “Face Vectors” which will be saved in the dataset.
Later, this dataset will be used to identify the user when they consider scanning again for their purposes like sign up/in, checks in/out, etc. Furthermore, the data is carefully handled by Data Management Team and they ensure that it cannot be correlated to identical users like twins.