On June 30th, 2020, the U.S state of California filed a lawsuit against the tech company Cisco for discriminating against an Indian-American engineer based on caste. It was filed against the company's San Jose headquarters campus, which has a workforce predominantly of South-Asian origin.
The lawsuit was filed by the California Department of Fair Employment and Housing for discriminating against the employee on the grounds that he belonged to the population that was once known as the ‘untouchables’ under the caste system of India.
The Indian American employee who preferred to stay anonymous named two employees Sunder Iyer and Ramana Kompella, for harassing and discriminating against him based on caste. The two named employees work as supervisors at Cisco and belong to a high-caste.
The suit says that the engineer was allegedly forced to accept the caste hierarchy in the workplace, and when he refused to do so, they isolated him, decreased his role in the team, and reduced his salary. They even retaliated against him and assigned him to work with deadlines that were impossible to meet.
It is alleged that Iyer told other workers that the employee was Dalit and gained entry into the Indian Institute of Technology through affirmative action. The lawsuit further went on to accuse Cisco of failing to take ‘corrective action’ despite multiple investigations.
The Department of Fair Employment and Housing cited this as the civil rights violation of the engineer under Title VII of the Civil Rights Act of 1964, which prohibits workplace discrimination based on race, sex, colour, religion and national origin.
Though the law doesn’t explicitly state discrimination with regards to caste, it does prohibit workplace discrimination that is based on arbitrary factors. Currently, the case is still pending, and Cisco says it intends to ‘defend itself’.
Though this is America’s first case against the caste system, it doesn’t mean it is a new problem, and neither is caste-based discrimination an exclusive issue of Cisco. This issue has been widely prevalent across numerous workspaces in America.
“This is the first civil rights case in the United States where a government entity is suing an American company for failing to protect caste-oppressed employees and their negligence leading to a hostile workplace,” said Thenmozhi Soundararajan, Executive Director of Equality Labs.
Equality Labs is an organisation that seeks to fight against the issue of caste in the United States. The organisation’s survey in 2016 titled ‘Caste in the United States’ found that 67% of Dalits living in America have faced verbal or physical assault at their workspace based on their caste.
The same survey also reports that one in three Dalit students suffered some form of caste-based educational discrimination in the States. Dalit women too face their own set of challenges in workspaces. In addition to facing slurs that are manifested in caste, they are often subjected to sexual harassment in connection to the prevalence of caste-based sexual violence in India.
The lawsuit against workplace discrimination at Cisco has made several Dalit employees across America to come forward and speak up about the harassment they have been subjected to due to their caste. This is why California’s case is especially significant as it sheds light onto the sheer scale of this caste-based discrimination at both the work and educational spaces.
It is a landmark case as it shows that there is a need to include caste in the protected category and enable more such civil rights litigations. It formally recognises the existence of caste elements at work and educational spaces that form the breeding grounds for systematic discrimination, bullying and ostracisation to thrive.
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Detecting The Ultra-High Energy Cosmic Rays With Smartphones
Smartphones have become the most commonplace objects in our daily lives. The unimaginable power that we hold in our hands is unrealized by most of us and, more importantly, untapped. Its creativity often gets misused but one can only hope that it’s fascinating abilities would be utilized. For example, did you know that the millions of phones around the globe can be connected to form a particle detector? The following article covers the CRAYFIS (Cosmic RAYs Found in Smartphones) phone-based application developed by the physicists from the University of California—Daniel Whiteson, Michael Mulhearn, and their team. CRAYFIS aims to take advantage of the large network of smartphones around the world and detect the cosmic or gamma rays bursts which enter the Earth’s atmosphere almost constantly.
What Are Cosmic Rays?
Cosmic rays are high velocity subatomic particles bombarding the Earth’s upper atmosphere continuously. Cosmic ray bursts have the highest energy compared to all forms of electro-magnetic radiation. When we say ultra-high energy particles (energy more than 10<sup>18</sup> eV), we mean two million times more energetic than the ones that can be produced by the particle colliders on Earth. These rays are thought to be more powerful than typical supernovae and can release trillions of times more energy than the Sun. They are also highly unpredictable as they can enter Earth’s atmosphere from any direction and the bursts can last for any period of time ranging from a few thousand seconds to several minutes.
Despite many theoretical hypotheses, the sources of these ultra-high energy cosmic rays are still a mystery to us even after many decades of their discovery. These rays were initially discovered in the 1960’s by the U.S. military when they were doing background checks for gamma rays after nuclear weapon testing. Cosmologists suggest that these bursts could be the result of super massive stars collapsing - leading to hypernova; or can be retraced to collisions of black holes with other black holes or neutron stars.
How Do We Detect Them?
When the high-energy particles collide with the Earth’s atmosphere, the air and the gas molecules cause them to break apart and create massive showers of relatively low-energy particles. Aurora borealis i.e., the Northern and the Southern lights are the lights that are emitted when these cosmic rays interact with the Earth’s magnetic field. Currently, these particles are hitting the Earth at a rate of about one per square meter per second. The showers get scattered to a radius of one or two kilometers consisting mostly of high-energy photons, electrons, positrons and muons. But the fact that these particles can hit the Earth anytime and anywhere is where the problem arises. Since the Earth has a massive area, it is not possible to place a detector everywhere and catch them at the exact moment.
Energetic charged particles known as cosmic rays hit our atmosphere, where they collide with air molecules to produce a shower of secondary particle | Source: CERN
Detecting such a shower requires a very big telescope, which logically means a network of individual particle detectors distributed over a mile or two-wide radius and connected to each other. The Pierre Auger Observatory in South America is the only such arrangement where 1,600 particle detectors have been scattered on 3,000 square kilometers of land. But the construction cost of the same was about $100 million. Yet, only a few cosmic ray particles could be detected using this arrangement. How do we spread this network around the Earth?
In addition to being cost-effective, such a setup must also be feasible. The Earth’s surface cannot possibly be dotted with particle detectors which cost huge fortunes. This is where smartphones come into the picture.
Detecting The Particles Using Smartphones
Smartphones are the most appropriate devices required to solve the problem. They have planet wide coverage, are affordable by most people and are being actively used by more than 1.5 billion users around the planet. Individually, these devices are low and inefficient; but a considerably dense network of such devices can give us a chance to detect cosmic ray showers belonging to the highest energy range.
Previous research has shown that smartphones have the capability of detecting ionizing radiation. The camera is the most sensitive part of the smartphone and is just the device required to meet our expectations. A CMOS (Complementary Metal Oxide Semiconductor) device is present in the camera- in which silicon photodiode pixels produce electron-hole pairs when struck by visible photons (when photons are detected by the CMOS device, it leaves traces of weakly activated pixels). The incoming rays are also laced with other noises and interference from the surroundings. Although these devices are made to detect visible light, they still have the capability of detecting higher-energy photons and also low-ionizing particles such as the muons.
A screenshot from the app which shows the exposure time, the events- the number of particles recorded and other properties
To avoid normal light, the CRAYFIS application is to be run during nighttime with the camera facing down. As the phone processor runs the application it collects data from its surroundings using a camera as its detector element. The megapixel images (i.e., the incoming particles) are scanned at a speed of 5 to 15 frames per second, depending on the frame-processing speed of the device. Scientists expect that signals from the cosmic rays would occur rarely, i.e., around one in 500 frames. Also, there is the job of removing background data. An algorithm was created to tune the incoming particle shower by setting a threshold frequency at around 0.1 frames per second. Frames containing pixels above the threshold are stored and passed to the second stage which examines the stored frames, saving only the pixels above a second, lower threshold.
The CRAYFIS app is designed to run when the phone is not being used and when it is connected to a power source. The actual performance would be widely affected by the geometry of the smartphone’s camera and the conditions in which the data is being collected. Further, once the application is installed and is in the operating mode, no participation is required from the user, which is required to achieve wide-scale participation. When a Wifi connection is available the collected data would be uploaded to the central server so that it could be interpreted.
There is much complicated math used to trace back the information collected from the application. The most important parameters for the app are the local density of incoming particles, the detection area of the phone and the particle identification efficiency. These parameters are used to find the mean number of candidates (photons or muons) being detected. Further, the probability that a phone will detect no candidates or the probability that a phone will detect one or more candidates is given by Poisson distribution. The density of the shower is directly proportional to the incident particle energy with a distribution in x and y sensitive to the direction in which the particle came from. An Unbinned Likelihood (it is the probability of obtaining a certain data- in this case the distribution of the cosmic rays including their energy and direction, the obtained data is arranged into bins which are very, very small) analysis is used to determine the incident particle energy and direction. To eliminate background interference, a benchmark requirement has been set that at least 5 phones must detect and register a hit to be considered as a candidate.
It is impossible to express just how mind-blowing this innovation is. As the days pass, Science and Technology around us keep on surprising us and challenge us to rack our brains for more and more unique ways to deal with complex problems. The CRAYFIS app is simply beautiful and it would be a dream-come-true to the scientists if the project works out and we are able to detect these high energy, super intimidating cosmic rays with smartphones from our backyard.
Further Reading
The paper by Daniel Whiteson and team can be found here.
An exciting book “We Have No Idea” by Daniel Whiteson and cartoonist Jorge Cham can be found here.
