The new surveillance state

Are we transitioning into a Surveillance State?  An unprecedented level of digital transformation is occurring across all aspects of society.  Moreover, we are at increased risk of becoming a Predictive State, as evidenced by technology exploitation in China.  Following are ten sets of facts to consider.

  • Chicago has deployed 35,000 government-operated closed-circuit cameras, which approximates 128 cameras per square mile.  In comparison, the city of London has 627,000 cameras, and Beijing is approaching 3 million public surveillance cameras.  By 2022, China is projected to have one public CCTV camera for every two people.  An analysis of 120 cities showed little correlation between the number of public CCTV cameras and crime or safety.
  • Nearly half of all adults in the United States have pre-identified photos in databases used for law-enforcement facial recognition searches, working in tandem with the proliferation of public surveillance cameras.
  • Apple, Samsung, and Huawei smartphones, which represent 53% global market share in Q319, all exploit facial, fingerprint, and/or iris-recognition biometrics.  That's a lot of sensitive data for three companies to possess.
  • The global biometrics authentication market (which captures unique human identifiers, such as facial recognition, voice recognition, signature recognition, DNA matching, and vein pattern recognition) is projected to grow from $12B to $50B, from 2016 to 2024.    
  • Public acceptance of the use of biometrics with smartphones is accelerating new use cases for biometric authentication, ranging from law enforcement/public security to border control to population voter registration, and includes new commercial applications across myriad industries.
  • India's Aadhaar project is the world's largest biometric identification system use case, covering 1.246 billion people — all of whom are given unique 12-digit identification numbers pegged to a facial photograph, ten fingerprints, and two iris scans.  This project was initiated for public subsidy and unemployment applications but now includes payment processing.  Aadhaar is proof that this technology scales, and it provides a blueprint for other countries.
  • Digital transformation is rendering health care privacy (HIPAA) regulation obsolete, relative to ensuring patient privacy.  This week, Congress demanded an update from Google and Ascension, asking what data exactly are stored with Google, which employees have access to patient data, and to what extent patients were informed about the companies' agreement.
  • Voice interaction devices (that can record all conversations) are becoming mainstream in homes.  Early this year, Amazon revealed it had sold a total of 100 million Alexa devices.
  • Uber reportedly has a new policy of audio-recording as an effort to enhance passenger safety, but users will have the ability to "opt out." 
  • The market for wearable, connected devices, with biometric authentication capability, is projected to exceed 400 million devices in 2024.  These devices will be especially leveraged for collection of PII in health care, as evidenced by Google's recent $2.1B acquisition of Fitbit.

As the repositories of sensitive data and PII explode, machine learning/artificial intelligence (ML/AI) is being exploited to analyze and predict behavior.  According to a new report by International Data Corporation, ML/AI spending will grow from $37.5 billion to $97.9 billion in 2023.  Per David Schubmehl, research director, Cognitive/Artificial Intelligence Systems, "[t]he use of artificial intelligence and machine learning (ML) is occurring in a wide range of solutions and applications from ERP and manufacturing software to content management, collaboration, and user productivity."  With quantum computing becoming mainstream over the next decade, the ability to analyze and predict outcomes will scale by orders of magnitude.

China is a world leader in the exploitation of individuals' data with ML/AI.  Its cutting-edge Social Score Credit System, that takes in a broad range of behaviors both financial and social, all underwritten by an invisible web of Big Data, is a portent of the Predictive State.

To protect individual liberty, we need to pass national privacy legislation that mandates that individuals own data about themselves, states that consent is required to share that data, and specifies data security best practices for compliance.

Are we transitioning into a Surveillance State?  An unprecedented level of digital transformation is occurring across all aspects of society.  Moreover, we are at increased risk of becoming a Predictive State, as evidenced by technology exploitation in China.  Following are ten sets of facts to consider.

  • Chicago has deployed 35,000 government-operated closed-circuit cameras, which approximates 128 cameras per square mile.  In comparison, the city of London has 627,000 cameras, and Beijing is approaching 3 million public surveillance cameras.  By 2022, China is projected to have one public CCTV camera for every two people.  An analysis of 120 cities showed little correlation between the number of public CCTV cameras and crime or safety.
  • Nearly half of all adults in the United States have pre-identified photos in databases used for law-enforcement facial recognition searches, working in tandem with the proliferation of public surveillance cameras.
  • Apple, Samsung, and Huawei smartphones, which represent 53% global market share in Q319, all exploit facial, fingerprint, and/or iris-recognition biometrics.  That's a lot of sensitive data for three companies to possess.
  • The global biometrics authentication market (which captures unique human identifiers, such as facial recognition, voice recognition, signature recognition, DNA matching, and vein pattern recognition) is projected to grow from $12B to $50B, from 2016 to 2024.    
  • Public acceptance of the use of biometrics with smartphones is accelerating new use cases for biometric authentication, ranging from law enforcement/public security to border control to population voter registration, and includes new commercial applications across myriad industries.
  • India's Aadhaar project is the world's largest biometric identification system use case, covering 1.246 billion people — all of whom are given unique 12-digit identification numbers pegged to a facial photograph, ten fingerprints, and two iris scans.  This project was initiated for public subsidy and unemployment applications but now includes payment processing.  Aadhaar is proof that this technology scales, and it provides a blueprint for other countries.
  • Digital transformation is rendering health care privacy (HIPAA) regulation obsolete, relative to ensuring patient privacy.  This week, Congress demanded an update from Google and Ascension, asking what data exactly are stored with Google, which employees have access to patient data, and to what extent patients were informed about the companies' agreement.
  • Voice interaction devices (that can record all conversations) are becoming mainstream in homes.  Early this year, Amazon revealed it had sold a total of 100 million Alexa devices.
  • Uber reportedly has a new policy of audio-recording as an effort to enhance passenger safety, but users will have the ability to "opt out." 
  • The market for wearable, connected devices, with biometric authentication capability, is projected to exceed 400 million devices in 2024.  These devices will be especially leveraged for collection of PII in health care, as evidenced by Google's recent $2.1B acquisition of Fitbit.

As the repositories of sensitive data and PII explode, machine learning/artificial intelligence (ML/AI) is being exploited to analyze and predict behavior.  According to a new report by International Data Corporation, ML/AI spending will grow from $37.5 billion to $97.9 billion in 2023.  Per David Schubmehl, research director, Cognitive/Artificial Intelligence Systems, "[t]he use of artificial intelligence and machine learning (ML) is occurring in a wide range of solutions and applications from ERP and manufacturing software to content management, collaboration, and user productivity."  With quantum computing becoming mainstream over the next decade, the ability to analyze and predict outcomes will scale by orders of magnitude.

China is a world leader in the exploitation of individuals' data with ML/AI.  Its cutting-edge Social Score Credit System, that takes in a broad range of behaviors both financial and social, all underwritten by an invisible web of Big Data, is a portent of the Predictive State.

To protect individual liberty, we need to pass national privacy legislation that mandates that individuals own data about themselves, states that consent is required to share that data, and specifies data security best practices for compliance.