Friday, July 31, 2020

Stonewall Riots: A Pillar In The Movement For American LGBTQIA+ Rights

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Vanshita Banuana

Article Title

Stonewall Riots: A Pillar In The Movement For American LGBTQIA+ Rights

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Global Views 360

Publication Date

July 31, 2020

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The Stonewall Inn in 1969

The Stonewall Inn in 1969 | Source: David via Flickr

The Stonewall Riots are globally remembered as the cornerstone of Pride Month, and rightfully so. Fifty-one years ago, a routine police raid on Stonewall Inn, a gay bar in New York turned into an upheaval against homophobic society, laws, and policing.

In the early hours of June 28, 1969, a police raid— often conducted on secret or private bars that exclusively served LGBTQIA+ patrons— turned its head on the New York Police Department.

The Stonewall riot in 1969 | Source: David via Flickr

Some accounts say that the pivotal moment came when few of the lesbians who were brutally shoved into a police wagon showed resistance. In response, the crowd lit up in anger and resistance. Instead of running away to save themselves, the patrons fought back, even leading to the police barricading themselves within the bar itself as they waited for backup.

The Stonewall riot in 1969 | Source: David via Flickr

News of the clash spread and more people gathered, throwing anything they could find: nickels, garbage cans, broken bottles, and yes, bricks too, though ‘the first brick’ may have been more myth than real. Eventually, it took the fire department and a riot squad to quell the riots on the first night.

Defiant, Stonewall reopened the next evening, and the confrontation between police and community members continued for the rest of the week, drawing hundreds and upto thousands of community members. A total of twenty one protestors were arrested over the week, with the majority being arrested on the first night itself.

It’s hard to pinpoint what exactly led to the Stonewall riots, or the status that it earned in present-day Pride and LGTBQ+ liberation movements. The movement for LGTBQ+ rights existed before Stonewall (if relatively subdued relative to what came after), and so did the concept of ‘Pride,’ in the form of ‘Personal Rights in Defense and Education’ (PRIDE) that went on to become the Advocate magazine.

Stonewall wasn’t even the first time the community clashed with the police. It has been postulated that the act of naming, “the first to be called the first,” and the decision of organizers to commemorate its anniversary in the form of ‘Christopher Street Liberation Day’ contributed largely to Stonewall becoming a permanent and popular fixture in LGBTQIA+ history and collective memory.  

Regardless of the contributing factors, the cultural impact of Stonewall on American and Western LGBTQIA+ communities was immediate and intense. It became the epicentre of a louder, more radical movement. The community had tried it the ‘respectable’ way through organisations such as Mattachine, but it didn’t get them anywhere.

The number of LGTBQ+ focused organisations and magazines soared after Stonewall, going from around two dozen to four hundred. These included radical organisations such as the Gay Liberation Front and Radicalesbians.

The year after Stonewall, Sylvia Rivera and Marsha P. Johnson, who were present at the riots and are considered transgender icons, created the Street Transvestite Action Revolutionaries (STAR), which focused on struggles of drag queens and trans and gender-non-conforming youth who often lived on the streets.

Stonewall Inn as it existed no longer stands, but the new Stonewall Inn in the same street and the park across it have been recently declared as a historic national monument.

The old Stonewall was not a luxurious bar in terms of drinks or furnishings. It was not a place frequented by upper or middle class, white, cisgender gay men. Being a dance bar whose patrons included working class or homeless LGBTQIA+ people and drag queens, it was often looked down upon. All of that changed in one week, and the spirit that shone in Stonewall that night continues to resonate and be celebrated in the hearts of all LGBTQIA+ people.

In light of the ongoing Black Lives Matter protests and the rioting that happened alongside, many LGBTQIA+ people on social media have responded to criticism by reminding people of Stonewall, and how the “first Pride” was a riot led by Black and Latin transgender women, gender non-conforming youth, and other LGBTQIA+ people of colour, the very people whose history and resistance has often been white-washed, diminished, or erased altogether.

As said by Martin Luther King Jr., “A riot is the language of the unheard.”

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February 4, 2021 5:22 PM

Automated Facial Recognition System of India and its Implications

On 28th of June 2019, the National Crime Records Bureau (NCRB) opened bids and invited Turnkey Solution providers to implement a centralized Automated Facial Recognition System, or AFRS, in India. As the name suggests, AFRS is a facial recognition system which was proposed by the Indian Ministry of Home Affairs, geared towards modernizing the police force and to identify and track criminals using Facial Recognition Technology, or FRT.

The aforementioned technology uses databases of photos collected from criminal records, CCTV cameras, newspapers and media, driver’s license and government identities to collect facial data of people. FRT then identifies the people and uses their biometrics to map facial features and geometry of the face. The software then creates a “facial signature” based on the information collected. A mathematical formula is associated with each facial signature and it is subsequently compared to a database of known faces.

This article explores the implications of implementing Automated Facial Recognition technology in India.

Facial recognition software has become widely popular in the past decade. Several countries have been trying to establish efficient Facial Recognition systems for tackling crime and assembling an efficient criminal tracking system. Although there are a few potential benefits of using the technology, those benefits seem to be insignificant when compared to the several concerns about privacy and safety of people that the technology poses.

Images of every person captured by CCTV cameras and other sources will be regarded as images of potential criminals and will be matched against the Crime and Criminal Tracking Networks and Systems database (CCTNS) by the FRT. This implies that all of us will be treated as potential criminals when we walk past a CCTV camera. As a consequence, the assumption of “innocent until proven guilty” will be turned on its head.

You wouldn’t be surprised to know that China has installed the largest centralized FRT system in the world. In China, data can be collected and analyzed from over 200 million CCTVs that the country owns. Additionally, there are 20 million specialized facial recognition cameras which continuously collect data for analysis. These systems are currently used by China to track and manipulate the behavior of ethnic Uyghur minorities in the camps set up in Xinjiang region. FRT was also used by China during democracy protests of Hong Kong to profile protestors to identify them. These steps raised concerns worldwide about putting an end to a person’s freedom of expression, right to privacy and basic dignity.

It is very likely that the same consequences will be faced by Indians if AFRS is established across the country.

There are several underlying concerns about implementing AFRS.

Firstly, this system has proven to be inefficient in several instances. In August 2018, Delhi police used a facial recognition system which was reported to have an accuracy rate of 2%. The FRT software used by the UK's Metropolitan Police returned more than a staggering 98% of false positives. Another instance was when American Civil Liberties Union (ACLU) used Amazon’s face recognition software known as “Rekognition” to compare the images of the legislative members of American Congress with a database of criminal mugshots. To Amazon’s embarrassment, the results included 28 incorrect matches.. Another significant evidence of inefficiency was the outcome of an experiment performed by McAfee.  Here is what they did. The researchers used an algorithm known as CycleGAN which is used for image translation. CycleGAN is a software expert at morphing photographs. One can use the software to change horses into zebras and paintings into photographs. McAfee used the software to misdirect the Facial recognition algorithm. The team used 1500 photos of two members and fed them into CycleGAN which morphed them into one another and kept feeding the resulting images into different facial recognition algorithms to check who it recognized. After generating hundreds of such images, CycleGAN eventually generated a fake image which looked like person ‘A’ to the naked eye but managed to trick the FRT into thinking that it was person ‘B’. Owing to the dissatisfactory results, researchers expressed their concern about the inefficiency of FRTs. In fact mere eye-makeup can fool the FRT into allowing a person on a no-flight list to board the flight. This trend of inefficiency in the technology was noticed worldwide.

Secondly, facial recognition systems use machine learning technology. It is concerning and uncomfortable to note that FRT has often reflected the biases deployed in the society. Consequently, leading to several facial mismatches. A study by MIT shows that FRT routinely misidentifies people of color, women and young people. While the error rate was 8.1% for men, it was 20.6% for women. The error for women of color was 34%. The error values in the “supervised study” in a laboratory setting for a sample population is itself simply unacceptable. In the abovementioned American Civil Liberties Union study, the false matches were disproportionately African American and people of color. In India, 55% of prisoners undertrial are either Dalits, Adivasis, or Muslims although the combined population of all three just amounts to 39% of the total population (2011 census). If AFRS is trained on these records, it would definitely deploy the same socially held prejudices against the minority communities. Therefore, displaying inaccurate matches. The tender issued by the Ministry of Home Affairs had no indication of eliminating these biases nor did it have any mention of human-verifiable results. Using a system embedded with societal bias to replace biased human judgement defeats claims of technological neutrality. Deploying FRT systems in law enforcement will be ineffective at best and disastrous at worst.

Thirdly, the concerns of invasion of privacy and mass surveillance hasn’t been addressed satisfactorily. Facial Recognition makes data protection almost impossible as publicly available information is collected but they are analyzed to a point of intimacy. India does not have a well established data protection law given that “Personal data Protection Bill” is yet to be enforced. Implementing AFRS in the absence of a safeguard is a potential threat to our personal data. Moreover, police and other law enforcement agencies will have a great degree of discretion over our data which can lead to a mission creep. To add on to the list of privacy concerns, the bidder of AFRS will be largely responsible for maintaining confidentiality and integrity of data which will be stored apart from the established ISO standard. Additionally, the tender has no preference to “Make in India'' and shows absolutely no objections to foreign bidders and even to those having their headquarters in China, the hub of data breach .The is no governing system or legal limitations and restrictions to the technology. There is no legal standard set to ensure proportional use and protection to those who non-consensually interact with the system. Furthermore, the tender does not mention the definition of a “criminal”. Is a person considered a criminal when a charge sheet is filed against them? Or is it when the person is arrested? Or is it an individual convicted by the Court? Or is it any person who is a suspect? Since the word “criminal” isn’t definitely defined in the tender, the law enforcement agencies will ultimately be able to track a larger number of people than required.

The notion that AFRS will lead to greater efficacy must be critically questioned. San Francisco imposed a total ban on police use of facial recognition in May, 2019. Police departments in London are pressurized to put a stop to the use of FRT after several instances of discrimination and inefficiency. It would do well to India to learn from the mistakes of other countries rather than committing the same.

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