Frontier Institute Comment: HJ 48 Study of Facial Recognition

Frontier Institute Comment: HJ 48 Study of Facial Recognition

The following is a formal comment provided by The Frontier Institute in regard to the HJ 48 Study of Facial Recognition Technology

Facial Recognition Tech (FRT) is increasingly being used as a tool to make Montana government  more efficient – assisting law enforcement investigations and rooting out identity fraud.  However, this powerful technology can be abused, threatening the privacy and security of  Montanans without proper public knowledge and oversight. 

Frontier Institute identifies two main concerns with the current system regulating the use of  FRT by governments in Montana:  

  1. No uniform standard for the use of FRT by law enforcement 

After a series of public information requests, Frontier Institute understands that the Montana  Analysis and Technical Information Center (MATIC)1 – the state’s fusion center2 – has an  internal policy3 governing the use of FRT. While MATIC does not have direct access to a FRT  system, it is authorized to submit search requests to external entities with FRT system access.  Under the policy, FRT searches are authorized only for specific use cases, with investigations  conditioned on “reasonable suspicion” of a crime.  

However, the MATIC policy applies only to FRT searches they facilitate. Recent media reports  revealed that local Montana law enforcement agencies directly ran potentially hundreds of FRT  searches using a separate system.4 

The existence of internal policies governing local law enforcement use of FRT is unknown to the  public, leaving open questions about the adequacy of internal policy to protect against abuse.  

Recommendation #1 

The Legislature should consider adopting a transparent, uniform standard for FRT use by law  enforcement in Montana. The uniform standard should establish the necessary legal conditions  for investigations or searches which utilize FRT (reasonable suspicion, probable cause etc.)

  1. No uniform standard for accessing civilian FRT databases 

FRT is already used for identity verification in non-criminal contexts, such as Unemployment  Insurance (UI) and the Department of Motor Vehicles (DMV). 

The DMV has maintained that they do not allow any external access to their FRT system.  However, the Montana’s driver’s license database is shared with national law enforcement  databases, such as the National Law Enforcement Telecommunication System (NLETS)5. NLETS  intends6 to develop FRT search capabilities, which may in the future subject law-abiding driver’s  license holders to law enforcement FRT searches. 

The use of third-party FRT applications also opens significant concerns for law enforcement  “backdoors” into civilian FRT databases. For example, Montana’s UI Program utilizes the vendor  ID.ME for FRT identity verification. ID.ME product terms state that user information can be  shared in response to government requests7. This vendor policy could mean that, despite the  existence of any internal UI FRT system use policy, law enforcement may be able to access FRT  searches of the UI database via requests to the vendor.  

These examples pose concerns about the security and privacy of law-abiding citizens who apply  for government benefits or receive a driver’s license in Montana.  

Recommendation #2 

The legislature should consider adopting a transparent, uniform standard for FRT system access  in non-criminal contexts. The uniform standard should establish authorized law enforcement  uses of civilian FRT databases and extend those same conditions to any FRT vendors. Photos  collected in FRT databases in a non-criminal context should not be automatically linked or  shared with any external law enforcement database.  

Frontier Institute encourages the committee to scrutinize government use of FRT in Montana  and evaluate the necessity of adopting a transparent, uniform standard for its use.

 

1 https://dojmt.gov/enforcement/investigations-bureau/
2https://www.dhs.gov/national-network-fusion-centers-fact-sheet
3https://files.frontierinstitute.org/wp-content/uploads/2021/11/MATIC-FR-Policy-2.pdf
4https://www.buzzfeednews.com/article/ryanmac/facial-recognition-local-police-clearview-ai-table
5https://www.nlets.org/resources/maps/initiatives/key
6https://www.nlets.org/sites/default/files/2021-05/baa_fact-sheet.pdf 
7https://www.id.me/privacy

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