Facial Recognition's Controversial Rise in Brazil

By Robert Wren Gordon, Published Nov 08, 2021, 09:37am EST

Brazilian media, academics, and NGOs are voicing alarm at facial recognition's growing popularity in the country, where its use has gone beyond public safety and concerns about its consequences for minority groups intensify.

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In this post, IPVM analyzes recent news reports and shares exclusive commentary from Brazilian academics and privacy advocates in a follow-up to UK/US Media Report on Facial Recognition Problems.

  • Background
  • Over 50% of Brazilians Black or Mixed-Race
  • Black Brazilian Man Detained due to False Positive
  • News Coverage Highlights 'Biased' Tech
  • CompSci Professors: Tech Not 'Biased'
  • Tech Deployed Not Mature Enough, Agree Interviewees
  • Brazilian Government Not Transparent
  • Weak Data Privacy Framework

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******** **** **** ** percent ** ********** ******** as *****, **** ** percent ******** *******, * **** **** locally ** ******** **** of ******** ** *********** Brazilians **** ***** *****-******* (ex-Barcelona) ****** **********(********), *** *******.

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Black ********* *** ********** *******

*** ********* ****** *** a ****** ********* *** ******* ** facial *********** ** *** Brazilian ***** ********* *** *****-***** *********** of ****** ****** (***** *** ******** ****, Dahua, *** ********* ****** recognition *********, ********* ** LAPIN) ******* ******* ** ** Afro-Brazilian *** ******** ** solely ** '****,' *** *** *********** monitored ****** *** ******* home **** ******** ***** ************** ***** ******** ** police *** ** * facial *********** ***** ********.

***** ****'* ******* ** one ** *** *** stories ** * ***** Brazilian *** ***** ******** due ** * ****** recognition ***** ********, ****** has * **** ******* of ***** ********* *** being ********** ******** *** to **** ** ***** locally **************** ******á******************** *** ****, ******* *** ****** of * ***** ** the ****** '*********' * suspect ** *** ***** of * ****** (*.*., human ***) ***** ***** (e.g., ****** ******,****á*****,***** ** *. *****,**,******* ****í,***).

** ********,*** ***** ** ****** Parks *** ****** ********, African ******** *** *** were *********** ******** ** the ** ***** ** facial *********** ***** *********, **** ******* ** leading ********* ***** (*.*.,*** ******,*****ã*,****É,***) *** **** ******** local ****** ******* ** favor ** ******* ****** use ** *** **********.

Recent **** ******* ***** ** **** ** ****** ***********

** ***** ** *** above, * ****** ***** of ******* *** ****** from ***** ************ ** *. *****(*), (*), (*),*** ********* ******,**** ** *****,****** *******,**** **** *****, ************* ** ****í***, *** ************* ** *ã* *****(*) **** ******* **, or ** ***** *****, the **** ** ***** Brazilians ***** ******** ** detained *** ** ****** recognition ***** *********, **** the********** ** *ã* ***** warning **** "****** *********** technology ** ****** ****** could ****** ****** *** misogyny."******* **************** ****, *** ********* ** IPVM ** ****** ** LAPIN, ****** **** *** university's *******, *******:

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***, ***** ******. ** various ******* ***********, ****** recognition ************ **** ******** and ********** ******* **** used ** **** ***** of ***-***** *******, *** elderly, ** *******. *** risk ** ***** ************** can ** **** ******* in ************ ***** *************** are *** *** **** as ***** **** *** the ******** ** *** technology, ** ** *** use **** *** ****** safety ********.

*****'* ***** ***** ** reminiscent ******** ******* ** ** parliamentarians, *** ********* ****** that "********** ******," *****, and "***** ******, ********, and *** *******" *** commonly ************* ** ****** recognition ********.

Academics: ********** *** ********** ******

**** ******** ******** ******. ******* ********,** ********* ********* ** computer ********* ********** ********** ** *****, *** **. ****** Vidal,** ********* ********* ** computer ********* ************* ** ****í***, *** **** ******.

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**** ********** ****** ******* facial *********** ***** ********** biased ******* ****** ** color, **** **. ******** (pictured) ****** **** ***** operator ***** ***** ** integral **** ** ***** detentions/arrests:

[I]t ** *********** **** ******** **** *** ******* ** **** *** ********** ** **** **** ******** ****** **** ***** **** **. [T]he technological bias is inherent to the method implemented and executed on a certain type of hardware (in this case, video surveillance cameras). Final errors in identifying suspects are very likely due to human operators, who discern the results of the technology. [emphasis added]

**. ******** ******* ****** that *** **** **** facial *********** ******** ***** to ** **** ******** on * "***** ****" is ********** ** ******** with ***** *******, ** operators, *** *** **** developers:

*** ******* ** ****** in ****** *********** ********** could ***** ** *** face ********* *****. *** let's ***** ***** **:if * ****** ********* ******* ** '*******' **** ******* **** * ******, ** ***** **** ****** ** **** ********** ********* *** ***** **** **** *** ***** ****, ***'* *** *****? In the identification module, the bias could also occur by only identifying the faces of black people. This is very unlikely to happen in a company that develops this type of technology. This, from a purely technological point of view. But, as I said before, perhaps the problem lies with whoever operates this technology, who, ultimately, must know how to properly retrieve the results of the face recognition system, analyze the results and issue an opinion—basically the work of a human expert. Therefore, I believe that the problem is much greater and involves historical, cultural, religious, political, social issues, etc. [emphasis added]

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**. ***** (********) ****** Dr. ********'* ******** ** his ********* ** ****:

* ******** **** *** statements ***** *** ***** of ********* ****** *** misogyny.

**. ***** ******* ***** the ********** ** *********** acceptable ********** ******:

[*]***** *********** ************ **** probabilistic **********, ***** ** call ***********, **** * data *** ****, *** the **** ****, ** incomplete **** (*.*., *** spatial ********** ***/** ****** image).As * ***** *********** ********* ** ************* *********, * ********** ** ***** ********** **** ** *****. With technology, there will always be an aggregate error, and what one must evaluate is whether this error is acceptable or not. [emphasis added]

**. ***** ******* *********** the **** ******* ** most ************-******* ******, * point **** ***** ** IPVM's ************** **'* ********** ****** Examined******:

*** **** ******** ** images, *** * *** this **** ******** **********, analyzed ** ******* ***/** used ** ****** *********** technologies, **** **** ******* with *** ******* ** capture, *******, ********, ***********, and *********, ***********.

Technology *** ****** ****** *** ****** ******?

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*** ********** *** ***** did, *******, ***** **** technology ********* ******** ** public ****** ****** *********** implementations ** ****** *** not ** ****** ****** for *** *********** ***, particularly ***** *** ******* of ************ ******* (* relevant ***** ** ******, where, ****** *** **, Canada, *** ******, ****** cameras ****** ***********). ********* to **. ********:

******* **** ** ***** surveillance ******* ********* ***** the ****** **** ****** in **** ** ****** identification ********.

*** *** ****, **. Vidal ********* ******** ********* for *** ***** ****** to ******* *** ******* of ***** ************ *** submit **** *** **** review, ****** ** ********* to ****** ***** ******** does ****, *** *** well:

[*]******** ********* ** *** work ** * *** to ******* ***** ******* on ****-******** ********* (*.*., prestigious ********** ********) **** ensure **** *** **** developed ** ********* *** methodologically *********.

[**** ** ****** **] an ************* **** ******** and ******** ** * model **** ****** *** peer-reviewed **********, ** ***** to ******* *** **** presented *** *** ***********. And ** ** ********** that **** **** ** data *********** ** ********, preserving ****** *** ************ property ** *** ********.

*** ***** ***** *** discussed ********** **'* ********** ****** Examined, ** *** ******* company ******** ** ******** data ** **** ** how ******* ****** (*.*., near ********, ********, ***.) impact *** ******** ** its ********.

*****, ***** ********* ***-**** ******** ****** *********** ** Brazil ** **** ****, simply ****** **** ******* technologies ** ****** *** "not ****** ******":

[*]*** *** *********** ** were **** ** ******* via *** ***** *** direct ********, *** ********** is *** ****** ****** to ** ******** ** a *** *********** *******.

Government *** ***********

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*** ********** ********** *** LAPIN ****** **** *** Brazilian **********'* ******* ** facial *********** *** **** fraught **** ************, **** local ****** *********** ******* to ******* ************** *** transparency, ***** ***** ********.

**. ***** ***** **** there *** ** *********** standards ** ***** ******* and * ******* ********* for ********** ***** *********:

[*]* *** ** *'* aware, ***** *** **** that ******** *** **********'* privacy, *** ******* ************ that ********* ********** *** this **********. * ****** example ** ****there ** ** ********** ** ******* *********** ****** *** **** **********, in order to fulfill the requirements for identification, with a degree of certainty, focused on minimizing a high amount of false positives. [emphasis added]

**. ***** ******* ***** that *********** ** *** publish ******** *********** ****:

[*]**** *** ** ***** details ** *** **** process ** **** ** the ********* ***********, ********* information ** *** *********** of *** ********* (** product) **** ** *** acquired ******* ** * transparent *** ********** ***.We *** ***** ****** **** ***** ** ***** ********** *** ************ ******. [emphasis added]

**. ******** ******** **. Vidal, ******* ******* ********** regulation "****" *** ****** that **** ********, ***** health *** ******** ******** contribute ** *** **** of ** ******* ****** debate ** ****** *********** within ******:

* ***** **'* ****** because ***** *********** **** weak ** ****** ** no **********. **** **** of ********** ** **** prevalent ** *********** *******.I ***'* **** ** *** ********** ** ****** ***** **** **********. First, because for a regulation to exist, a public debate must take place, led both by experts in civil society and by representatives in Congress. I believe that the reason for this lack of transparency or regulation is, first of all, the attention given to other bigger problems such as basic sanitation, corruption, education, unemployment, etc. [emphasis added]

***** ****** *** **** of ********** *******, ******* noting **** ***** *********** are ****** ********* ***** to *** ************** ** facial *********** ***********:

There ** ** ***** ********** ** *** ******* ***** *** **** ****** *********** ** *** ***** *** ***** ******. Without any specific rules on how to deploy the technology—if it should be deployed at all—private and public sectors have been adopting facial recognition technology for largely different purposes and in diverse manners. In addition to the lack of law, there *** ** ******** ** ********** **** ******* ************ ** *** *********** *** *** ** *** **********, so the risks involved and the harms of using facial recognition technology are not evident. Particularly in the public sector, there is no broad social discussion prior to the implementation decision. When it occurs, it normally happens after the decision-making process and includes very specific groups, such as companies, authorities involved, and eventually the media. In other cases, the ***** ******* ** ******* ******* *** ***** ******* **** ******* ***** ** *** ********** ***** ***** *******. [emphasis added]

*** **** ** ********** with ***** ******* *** noted ****** ** *****, ***** documented *** **** ** a ****** ** ********* *********** ****** *********** to ***** ******* ********** without ********** *******/********* **********.

Disagreement ** ******** ** ****** ****** *********** ***

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** ******,** ******** **** ***** by ****, *** **** *** turned ********* ******* ******/****** safety *** ** ****** recognition, ******* ******** ********** ************ restrictions *** **** **** weeks ***.

***** ****** ***** * similar ****** ****** ** the ******** ** ****** use ** ****** ***********, our ************ ********* ********* viewpoints ** *** ******, with *****-***** **. ******** setting ***** * ******* view, ******** *** **********'* advantages *** *************:

Facial *********** ** **** * **** ****, ** **** *** **** ** ******, **** ******* *** ************* ** ******** *******. The explicit advantage is to automate the search for faces, either to find suspects or to find missing people, with the help of hundreds of cameras scattered throughout the cities. The disadvantage, also evident, is the mistakes made by technology in the process of identifying people; if this automation is not scrutinized by a well-prepared human operator, we can obviously have unfair situations if the technology is used as judicial evidence, for example. [emphasis added]

**. ***** ****** ** favor ** ****** *** of ****** *********** ***** making **** ** *** technology's ******* ** ********** abuses ** *****:

Facial *********** ******* ****** ** **** ** * *** ** ****** ******** ********. This system can be an ally, but it is incapable of making Brazil safer on its own. The advantage, almost inherent to the use of this technology, is the facility it has to identify an individual for purposes of public service uses. Brazil is a continental country that, unfortunately, requires its citizens to prove that they are themselves. Often the bureaucracy required for a citizen to prove it is absurd. Now, with the use of a facial recognition system, this process can be fast and efficient. The biggest disadvantage is the fact that these systems allow, especially for government authorities who have controlling tendencies, the quick and effective monitoring of citizens, knowing what they do on a daily basis, including in their private lives[.] [emphasis added]

***** ****** ******* ****** sector ****** *********** ***, citing * **** ** government ************ ********* *** technology's ***********, **************, *** efficacy:

The *** ** ****** *********** ********** ** *** ****** ****** ****** **** ************* **** ******** ** ********. Law enforcement authorities are deploying facial recognition technology from different manufacturers. In *******, *** *********** *** ************** ********* *** ******* *** **********. The public, including civil society organizations such as LAPIN, faces various challenges to access the information related to the use of facial recognition technology by the police. [emphasis added]

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*** * **** *********** discussion ** *** **** of ************ ** ***** American ***** ************, ******** ******* ***** ************ Sales *** *********** **** NGO(*** ****** ***** ********).

Data ******* ********

****** *** * ********* record ** **** *******, with *********** ***** ** *******, *** *******'* ******* appellate *****, ***** *** victim *** **** ** ******** 2020 **** *********** *** court's ******** ******* *** over *** *****. ***********,***** ******** ** ******* 2021 **** * '********' had *****************(********** **** ****** ********) ******* ** **** 200 ******* **********:

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** ***** ** ***** known **** ******* ************, the ********* *** ***** advocated *** ********* *********** to ** **** ** protect ********' **** ******** by ****** *********** *******. According ** **. ********, facial *********** **** ***** allow * ********* ***** to ***** "*** ****** journey" ** * ******'* life:

**** ** * **** mine *** ********* *** governments. ****** ** **** data *** **** ************ power.Recognizing ******* ** * ****** ** *** ****** ********* *** ****** ******* ** ** **********'* ****: ****** **** *********, ****** *****, ******** *** ********** **************. This information can be used for both good and bad things. [emphasis added]

**. ***** ***** **** other ********* *** ********** in **** ** ********** given *** *******'* ****** diversity:

** ** ***** ******, due ** ** ******** and ************ **********, ****researchers **** ***** ********* ** *** ***** ** ****** *********** **** * ***** ******** ** ****** ****** **** ** *** ********* **********, mainly due to this wealth of diversity. Despite the General Law for the Protection of Personal Data (LGPD), in force in Brazil since 2018, there is no efficient way to verify the privacy details in the collections that are made, and, primarily, there is no way to monitor its effective application. [emphasis added]

**** *** ********** ********* the ***********, ** ********* by **** **** ******* advocates, **** ***** ******* may ** ******* ** a ********** ** ******* ground *** ************* ********** companies **'******** *********' **** *****, Hikvision, *** ****** **************** ******* ***** ************ Sales *** *********** **** NGO.

***** ********** *** ******* ground, ** "****** ***," point ***** ******* **** there ** ****** ********* in ***** ********* *** and **** ********** *********** can ***** ****** *********** data:

** ********* ******, *** acquisition *** ********** ********* of **** ************ ** the ****** ****** *** overwhelmingly *************. *********,little *********** ** ********* ********* *** ********** **** ******* ********* *** ***********, *** **** **** ******* *********** *** ***** *******, *** *** *** ** *** **** ********* ***** *** **********. Many places in Brazil may be a current living lab for facial recognition technology without citizens' knowledge and consent. [emphasis added]

**********

** ***** ** ***** above *** ** ******** in****** **** ****** ***** Surveillance ***** ***************** ***** ************ ****** Overview ****, **** ***** ******** countries, **** ** ******, are ******* ** **** rates ** ******* *****, especially *********.

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******** *********** **** **. Bolsonaro *** *ã* ***** state **********ã* *****(******** ** *** ******** capacity ** *ã* ***** city *****) ** ******, as **** ** ********* ** ****** *************** ** *****, **** ********* ** favor ** **********, ********* surveillance ******* *** ****** recognition, ** * *** to ****** ***** *** improve ******.

***********,** **** *** ********, there *** **** ********* and ******* ************** ****** any ****** ****** ************ deployment. ***** ************** **** reiterated ** **. ********:

[*]****** ******** *** ****** who ******* ***** *******, without ********** ** ****** preparation, *** ******* * transparent ********** ****** **** clear **********, ** **** can ** ********** ****. Prior ** *** ****, there **** ** ** investment ** *********. *** more ******** *** ****** are, *********, *** ***** the *********** ****** **** tends ** **.

***** ****** ***********, ** deployed ********, *** **** solve *****, ****** *********** or ************ ******* ***** cannot **** ******, ** any *******, *****, **** Dr. ***** ******* ** closing:

[*]* ** ** ****** mistake ** ** ********* or ******* ******** **** these ******* ***** *** capable ** ****** ****** safer.

Comments (1)

* **** **** ******* article **** **** ** arguments *** *** ******* facial *********** **********. ***** you ******!

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