Monday, June 22, 2020

How COVID-19 helped Netanyahu beat Benny Gantz for Israeli prime ministership

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Kanika Bajaj

Article Title

How COVID-19 helped Netanyahu beat Benny Gantz for Israeli prime ministership

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Global Views 360

Publication Date

June 22, 2020

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Benjamin Netanyahu and Benny Gantz

Benjamin Netanyahu and Benny Gantz | Source: US Department of State via Wikimedia

In March 2020, when COVID-19 was causing the near collapse of health systems across the world, Israel had just voted third time in the parliamentary election for the third time in less than a year. This was so because no political party was able to muster the majority in Knesset (Israeli parliament) after earlier elections in April 2019 and Sept 2019. Benjamin Netanyahu has been acting Prime minister since the time when he went for the dissolution of Knesset December 2018 with a hope of securing an extended majority for his right wing coalition. However he failed to secure even the simple majority in three elections on April 19, Sept 19, and March 20. Then came the COVID-19 and he sensed an opportunity to make a comeback from the brink of political disaster to reclaim the prime ministership of Israel.

The COVID-19 pandemic tested the Israeli citizens just like the other countries and  Benjamin Netanyahu kept on telling that unless it is effectively controlled, there will be devastation not seen since the Middle Ages. He also stressed that even the First world countries such as the US and UK are at the brink of losing control. Many Israelis expressed admiration towards Netanyahu’s quick response to the pandemic which helped to contain the pandemic in earlier stages. They flattened their curve by shutting down public places such as parks, schools, educational institutions, and the hotspot areas. He followed two stage strategies — first, to locate and isolate the infected population and then to engage the healthy population in economic activities during the conditions of a semi-lockdown. These steps were taken to save the economy. His plan also carried a huge amount of tests in the hope that it could be established that some people were developing antibodies to resist the virus and could safely be “freed” from isolation. Although the steps being acknowledged, they still raised a lot of questions against Netanyahu. He was supposed to be facing charges for breach of trust and bribery in the month of March. The court shutdown ordered by Israeli Law minister delayed Netanyahu’s charges by two months. Israel also used the cell phone of citizens to monitor their movement to track the spread of pandemic for which he was criticised for breaching the citizen’s privacy. Yohanan Plesner, the president of the Israel Democracy Institute said that Israelis trust the Shin Bet to protect them and not to abuse that trust, and the cellphone monitoring may have serious long-term effects on that trust. Netanyahu, however, defended himself with usual combativeness by stating that the courts were under a temporary shutdown and he has received permission from the General Attorney for cellphone usage data which was valid for 14 days. He also said “If the Shin Bet is to

infringe on our basic privacy, they could have done it many years ago”.

After managing to convince the citizens that he had handled the COVID-19 situation effectively, he quickly approached the rival Benny Gantz with a proposal to form an “emergency unity government”. As part of the deal he offered to share the power with Gantz’s Blue and White party for three years during which Netanyahu was to be prime minister and Benny Gants Dy prime minister for the first 18 months and the role reversal afterwards. He kept on harping the disastrous consequences of the virus and mentioned “It could affect 60-80% of the population” and said “nobody knows” how devastating the virus would ultimately prove. 

It was not easy for Benny Gantz to accept the proposal to align with Netanyahu as his whole campaign was on the issue of never supporting Netanyahu. However Netanyahu, who is acknowledged by friends and foes alike as a shrewd politician willing to go to any extent in safeguarding his own interest, finally won the war of attrition. Benny Gantz accepted the deal offered by Netanyahu and agreed to let him continue to be the prime minister for the first 18 months of the alliance period. The COVID-19 calamity has effectively turned into an opportunity for Netanyahu to hold on to the power and continue to be the prime minister of Israel.

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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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