Facia.ai
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About us Facia empowers businesses globally with with its cutting edge fastest liveness detection
Campus Ambassador Ensure countrywide security with centralised face recognition services
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ABOUT US
Facia is the world's most accurate liveness & deepfake detection solution.
Facial Recognition
Face Recognition Face biometric analysis enabling face matching and face identification.
Photo ID Matching Match photos with ID documents to verify face similarity.
(1:N) Face Search Find a probe image in a large database of images to get matches.
DeepFake
Deepfake Detection New Find if you're dealing with a real or AI-generated image/video.
Detect E-Meeting Deepfakes Instantly detect deepfakes during online video conferencing meetings.
Liveness
Liveness Detection Prevent identity fraud with our fastest active and passive liveness detection.
Single Image Liveness New Detect if an image was captured from a live person or is fabricated.
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Age Verification Estimate age fast and secure through facial features analysis.
Iris Recognition All-round hardware & software solutions for iris recognition applications.
Customer Onboarding New Seamlessly and comprehensively onboard your customers.
Read to learn all about Facia’s testing
Industries
Retail Access loyalty benefits instantly with facial recognition, no physical cards.
Governments Ensure countrywide security with centralised face recognition services
Dating Apps Secure dating platforms by allowing real & authentic profiles only.
Event Management Secure premises and manage entry with innovative event management solutions.
iGaming Estimate age and confirm your customers are legitimate.
KYC Onboarding Prevent identity spoofing with a frictionless authentication process.
Banking & Financial Prevent financial fraud and onboard new customers with ease.
Contact Liveness Experts To evaluate your integration options.
Use Cases
Account De-Duplication (1:N) Find & eliminate duplicate accounts with our face search.
Access Control Implement identity & access management using face authorization.
Attendance System Implement an automated attendance process with face-based check-ins.
Surveillance Solutions Monitor & identify vulnerable entities via 1:N face search.
Immigration Automation Say goodbye to long queues with facial recognition immigration technology.
Detect E-Meeting Deepfakes New Instantly detect deepfakes during online video conferencing meetings.
Pay with Face Authorize payments using face instead of leak-able pins and passwords.
Facial Recognition Ticketing Enter designated venues simply using your face as the authorized ticket.
Passwordless Authentication Authenticate yourself securely without ever having to remember a password again.
Meeting Deepfake Detection
Know if the person you’re talking to is real or not.
Learn
Blogs Our thought dumps on all things happening in facial biometrics.
News Stay updated with the latest insights in the facial biometrics industry
Whitepapers Detailed reports on the latest problems in facial biometrics, and solutions.
Knowledge Base Get to know the basic terms of facial biometrics industry.
Deepfake Laws Directory New Discover the legislative work being done to moderate deepfakes across the world.
Case Studies Read how we've enhanced security for businesses using face biometrics.
Press Release Most important updates about our activities, our people, and our solution.
FAQs Everything there is to know about Facia’s offerings, answered.
Implement
Mobile SDK Getting started with our Software Development Kits
Developers Guide Learn how to integrate our APIs and SDKs in your software.
On-Premises Deployment New Learn how to easily deploy our solutions locally, on your own system.
Most important updates about our activities, our people, and our solution.
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On 22nd January 2025, Senator Mike Cronk sponsored Alaska Senate Bill 33 (SB 33) in reaction to the increased threats of defamation and elections due to deepfakes and other artificial media. The bill seeks to create definitive legal paradigms of defamation cases involving artificial media and modulate the deployment of such media in electioneering communications.
SB 33 focuses its efforts on two issues: Defamation Claims: By defining and addressing defamation claims resulting from the application of synthetic media, the bill seeks to grant individuals legal recourse when injured by content.
Electioneering Communications: In an attempt to stop the spread of false or misleading information that has the potential to sway voters, it suggests regulations regarding the use of artificial intelligence in political campaigns.
Defamation Liability: Establishes norms for the responsibility of individuals or organizations for defamation by artificial media.
Disclosure Requirements: Demands open disclosure if synthetic media is used in election communications to inform the voter of the message’s authenticity.
Enforcement Mechanisms: Provides machinery for enforcement and sanctions in the event of a breach of the established norms.
As the bill is still pending, the specific penalties for non-compliance have not yet been released. SB 33 establishes enforcement provisions to induce compliance with its provisions. The bill is currently under consideration by the Senate State Affairs Committee with a hearing scheduled for April 29, 2025.
As SB 33 is still pending, there are no cases or reported precedents under said law.
For Political Campaigns: Campaigns must ensure that any synthetic media inserted in communications must include the required disclosure statement in order to comply with SB 33 mandates.
For Content Creators: The creators of synthetic media must be aware of the legal requirements and punishment of distributing false content.
For Voters: Voters must be informed of such legislation and be cautious of potentially deceptive media during elections.
With the advancement of synthetic media technology, SB 33 can be revised to address upcoming challenges to protect the reputations of individuals and electoral integrity. Regular discussions and assessments will indicate whether the legislative measures need to be implemented further.
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