TOP 5 TAKKAR NEWS OF THE DAY (5th JUNE 2023)

1. KAVACH: AUTOMATIC TRAIN PROTECTION (ATP) SYSTEM

TAG: PRELIMS PERSPECTIVE

CONTEXT: The death of over 288 passengers in the ghastly train accident on June 2 at Bahanaga Bazaar railway station in the Balasore district of Odisha has brought into sharp focus the safety mechanisms needed to prevent such tragedies.

EXPLANATION:

What is Kavach?

• Kavach is an indigenously developed Automatic Train Protection (ATP) system by the Research Design and Standards Organisation (RDSO) under Indian Railway (IR) in collaboration with Medha Servo Drives Pvt Ltd, HBL Power Systems Ltd and Kernex Microsystems.
• The railways has been developing its own automatic protection system since 2012 as Train Collision Avoidance System (TCAS), which got rechristened Kavach or ‘armour’.
• The trials were facilitated by the South Central Railway to achieve safety in train operations across Indian Railways.
• It is a state-of-the-art electronic system with Safety Integrity Level-4 (SIL-4) standards. It is meant to provide protection by preventing trains to pass the signal at Red (which marks danger) and avoid collision.
• ‘Kavach’ is one of the cheapest, SIL-4 certified technologies where the probability of error is 1 in 10,000 years.

Features of Kavach system:

• Kavach works on the principle of continuous update of Movement authority.
• It actively uses the SOS to prevent any kind of mishap and accidents.
• As part of the new system, railway tracks, signalling systems on railway tracks and the engines of trains are installed with radio frequency devices that continuously send signals back and forth on a real-time basis to indicate that the track on which the train is operating has no obstacles.
• The devices also continuously relay the signals ahead to the locomotive, making it useful for loco pilots in low visibility. Kavach also controls the speed of the train by an automatic application of brakes in case the loco pilot fails to do so. It helps the loco pilot in running the train during inclement weather conditions such as dense fog.
• Further operational improvement of Kavach is in the works, including change over from Ultra High Frequency (UHF) communication to LTE-4G communication.
• At the moment, Kavach uses ultra-high frequency radio waves but the Indian Railways is working to make it compatible with 4G Long Term Evolution (LTE) technology and develop the product for global markets.
• Kavach uses a network of devices mounted on trains to avoid collisions. The devices use radio technology and GPS to precisely assess the location of two trains and automatically initiate the braking system if they are at risk of colliding.

How it works?

• This Traffic collision avoidance system (TCAS), with the help of equipment on board the locomotive and transmission towers at stations connected with Radio Frequency Identification (RFID) tags, helps in two-way communication between the station master and loco-pilot to convey any emergency message.
• The instrument panel inside the cabin helps the loco-pilot know about the signal in advance without visual sighting, and the permissible speeds to be maintained.
• If a red signal is jumped and two trains come face to face on the same line, the technology automatically takes over and applies sudden brakes.
• Additionally, the hooter activates by itself when approaching a level crossing which serves as a big boon to loco-pilots during fog conditions when visibility is low.
• It activates the train’s braking system automatically if the driver fails to control the train as per speed restrictions.
• In addition, it prevents the collision between two locomotives equipped with functional Kavach systems.
• The system also relays SoS messages during emergency situations.
• An added feature is the centralised live monitoring of train movements through the Network Monitor System.

Where has Kavach been implemented?

• The trial of the Kavach working system implemented between Gullaguda-Chitgidda Railway stations on Lingampalli-Vikarabad section in the Secunderabad Division of South Central Railway.
• The South Central Railway (SCR) Zone is a pioneer in the implementation of the KAVACH – (TACS). The Kavach system has been deployed over 1,465 kms in the SCR limits in 77 locomotives and 135 stations till March this year.
• Additionally, the Secunderabad-based Indian Railways Institute of Signal Engineering & Telecommunications (IRISET) hosts the ‘Centre of Excellence’ for Kavach. IRISET has been mandated by the Railway Board to train the inservice railway staff on Kavach.

Earlier system:

• The Indian Railways has since 2002 been using an anti-collision device (ACD) developed by Konkan Railways, which was dubbed ‘Raksha Kavach’.
• The ACD system was invented by the former head of Konkan Railways Rajaram Bojji.
• While the older system is still in use in most trains operated by Indian Railways at the moment, the new system will be introduced across all trains in the next five years.
• The new Kavach system covers everything from railway stations, signalling systems and even types of trains, while the older ACD or the auxiliary warning system only works on individual trains and locomotives.
• The new system is also a lot more accurate in sending signals to trains and is faster as it works on a real-time basis while implementing safety measures as well.

2. ADVERSE POSSESSION

TAG: GS 2: POLITY

CONTEXT: 22nd Law Commission has said in its 280th report that there is no justification for introducing any change in the law relating to adverse possession. The Law Commission, headed by former Chief Justice of Karnataka High Court Ritu Raj Awasthi and comprising retired Kerala High Court judge KT Sankaran, said in its 280th report that there is no reason for increasing the period of limitation. However, two of its ex officio members filed a dissent note stating that the law does not stand judicial scrutiny and “promotes false claims under the colour of adverse possession”.

EXPLANATION:

What is adverse possession?

• The concept of adverse possession stems from the idea that land must not be left vacant but instead, be put to judicious use.
• Essentially, adverse possession refers to the hostile possession of property, which must be “continuous, uninterrupted, and peaceful.”
• According to the Law Commission’s report, the rationale behind this comes from considerations that the “title to land should not long be in doubt”, “society will benefit from someone making use of land the owner leaves idle,” and “persons who come to regard the occupant as owner may be protected.”
• The maxim that the law does not help those who sleep over their rights is invoked in support of adverse possession. Simply put, “the original title holder who neglected to enforce his rights over the land cannot be permitted to re-enter the land after a long passage of time.
• While the concept originally dates back to 2000 BC, finding its roots in the Hammurabi Code, the historical basis of “title by adverse possession” is the development of the statutes of limitation on actions for recovery of land in England.
• The first such statute was the Statute of Westminster, 1275. However, it was the Property Limitation Act, 1874, that set the period of limitation at twelve years from when the cause of action first arose, which laid the groundwork for the limitations model inherited by colonial India.
• The first attempt to bring the law of limitation to domestic shores was the “Act XIV of 1859”, which regulated the limitation of civil suits in British India. After the passage of the Limitation Act in 1963, the law on adverse possession underwent significant changes.

What provisions did the Limitation Act, 1963 bring with it?

• The 1963 Act fortified the position of the true owner of the land, as he now had to merely prove his title, while the burden of proof of adverse possession shifted to the person claiming it.
• Under the Limitation Act, 1963, any person in possession of private land for over 12 years or government land for over 30 years can become the owner of that property, as laid down in Articles 64, 65, 111, or 112 of the 1963 Act, relating to suits for possession of immovable property.
• According to Article 65 of Schedule I of the 1963 Act, a person in adverse possession of immovable property acquires title to that property.
• However, the possession must be open, continuous, and “in defiance of the title of the real owner for twelve years.”
• Similarly, Article 64 governs suits for possession based on previous possession and not on title.
• Meanwhile, Article 112, which applies to government property, mandates a requirement of 30 years for granting a title by adverse position.
• Further, Article 111 says that the limitation period for the State will be 30 years from the date of dispossession for land belonging to a private person where any public street or road or any part of it has been dispossessed and no suit has been moved for its possession “by or on behalf of any local authority”.

Why did the SC suggest changes to the law on adverse possession?

• A two-judge SC bench, in its 2008 ruling in Hemaji Waghaji Jat v. Bhikhabhai Khengarbhai Harijan and Others, while dealing with Article 65 of the Schedule of the Limitation Act, 1963, observed that the law of adverse possession “ousts an owner on the basis of inaction within limitation” and is “irrational, illogical, and wholly disproportionate”.
• “The law as it exists is extremely harsh for the true owner and a windfall for a dishonest person who has illegally taken possession of the property,” the court said. Adding that the law should not benefit the illegal action of a “rank trespasser” who had wrongfully taken possession of the true owner’s property, the court said that it also “places a premium on dishonesty”.
• Emphasising the “urgent need” for “a fresh look regarding the law on adverse possession”, the court recommended the government “to seriously consider and make suitable changes in the law of adverse possession”.
• Consequently, the 19th Law Commission prepared a “consultation paper-cum-questionnaire”. After receiving responses, the Commission concluded that the present provisions afforded sufficient protection to the land’s true owner and there was no need to amend the law. However, the Commission failed to file a final report on the subject.
• Owing to the importance of the subject, coupled with the fact that the reference had been pending since 2008, the present Law Commission found it “expedient to deliberate afresh over the subject.”
• While the Commission’s opinion was that the law on adverse possession should stay the same, two of its ex officio members, filed a dissent note saying that the law promotes false claims.

3. LARGE LANGUAGE MODELS (LLMS)

TAG: GS 3: SCIENCE AND TECHNOLOGY

CONTEXT: With more people getting on the generative AI bandwagon for work and play, context and cross-verification are the tools we need to guard against misinformation. In this regard, there is need to take a look on large language models and associated terminologies.

EXPLANATION:

• Large Language Models (LLMs) are foundational machine learning models that use deep learning algorithms to process and understand natural language.
• These models are trained on massive amounts of text data to learn patterns and entity relationships in the language.
• LLMs can perform many types of language tasks, such as translating languages, analyzing sentiments, chatbot conversations, and more.
• They can understand complex textual data, identify entities and relationships between them, and generate new text that is coherent and grammatically accurate.
• A large-scale transformer model known as a “large language model” is typically too massive to run on a single computer and is, therefore, provided as a service over an API or web interface.

General Architecture

• The architecture of Large Language Models primarily consists of multiple layers of neural networks, like recurrent layers, feedforward layers, embedding layers, and attention layers. These layers work together to process the input text and generate output predictions.
• The embedding layer converts each word in the input text into a high-dimensional vector representation. These embeddings capture semantic and syntactic information about the words and help the model to understand the context.
• The feedforward layers of Large Language Models have multiple fully connected layers that apply nonlinear transformations to the input embeddings. These layers help the model learn higher-level abstractions from the input text.
• The recurrent layers of LLMs are designed to interpret information from the input text in sequence. These layers maintain a hidden state that is updated at each time step, allowing the model to capture the dependencies between words in a sentence.
• The attention mechanism is another important part of LLMs, which allowsthe model to focus selectively on different parts of the input text. This mechanism helps the model attend to the input text’s most relevant parts and generate more accurate predictions.

Few examples of large language models:

1. GPT-3 (Generative Pre-trained Transformer 3) – This is one of the largest Large Language Models developed by OpenAI. It has 175 billion parameters and can perform many tasks, including text generation, translation, and summarization.
2. BERT (Bidirectional Encoder Representations from Transformers) – Developed by Google, BERT is another popular LLM that has been trained on a massive corpus of text data. It can understand the context of a sentence and generate meaningful responses to questions.
3. XLNet – This LLM developed by Carnegie Mellon University and Google uses a novel approach to language modeling called “permutation language modeling.” It has achieved state-of-the-art performance on language tasks, including language generation and question answering.
4. T5 (Text-to-Text Transfer Transformer) – T5, developed by Google, is trained on a variety of language tasks and can perform text-to-text transformations, like translating text to another language, creating a summary, and question answering.

5. RoBERTa (Robustly Optimized BERT Pretraining Approach) – Developed by Facebook AI Research, RoBERTa is an improved BERT version that performs better on several language tasks.

Few terminologies that take on new meaning with artificial intelligence

• Chatbot: A program that runs within websites and apps, and interacts directly with users to help them with tasks.
• Hallucination: When generative AI or a chatbot gives an answer that is factually incorrect or irrelevant because of limitations in its training data and architecture.
• Deep learning: A function of artificial intelligence that imitates the human brain by learning from the way data is structured, rather than from an algorithm that’s programmed to do one specific thing.
• Neural network: A method in artificial intelligence that teaches computers to process data in a way inspired by the human brain.
• Bias: A type of error that can occur in a large language model if its output is skewed by the model’s training data.
• Jailbreak: This is a way of breaching the ethical safeguards of a device. Every AI has content moderation guidelines to ensure it doesn’t commit crimes, or display graphic content. With the help of specific prompts, these guidelines can be bypassed.
• DAN (Do Anything Now): DAN is a prompt wherein ChatGPT is freed from the typical confines of AI. The bot can pretend to browse the Internet, access current information (even if made up), use swear words, display information that is unverified; basically, do everything that the original ChatGPT cannot.
• Abduction: A form of reasoning where baseless assumptions are made to explain observations, in contrast to deductive reasoning, where conclusions are based on perceivable facts and configurations.
• Prompt injection: This involves inserting malicious prompts that override an AI’s original instructions, to get it to manipulate and deceive users. As a result, hijackers can force an AI model to perform actions out of its purview. This is similar to a jailbreak, but more malicious.

4. CREDIT INFORMATION COMPANY AND CIBIL SCORE

TAG: GS 3: ECONOMY

CONTEXT: Kerala High Court said last week that a student’s credit score cannot be a factor in rejecting an education loan application. Calling students the “nation builders of tomorrow”, a Bench of Justice PV Kunhikrishnan added that the student’s education loan application should not have been rejected simply because he had a low CIBIL or credit score.

EXPLANATION:

What is the Issue?

• In a major move to ensure smooth process for the disbursement of loan from the financial Institutions, the The Kerala High Court ruled that application for education loan from the students should not be rejected by the banks simply because the CIBIL score of a student was low.
• The petitioner, who is a student, had availed two loans, of which one was overdue for and the other loan was written off by the Bank. The CIBIL score of the petitioner was low due to these reasons.
• The counsels placed reliance upon the decision and held that the unsatisfactory credit score of the parents of a student could not be a ground for rejecting an educational loan, since the repayment capacity of the student after his education ought to be the deciding factor as per the scheme.
• The counsels in this case averred that the petitioner had received a job offer from a Multi National Company and would thus be able to clear the entire loan amount. On the other hand, the counsels for the respondents argued that granting an interim order in this case, in accordance with the reliefs sought for by the petitioner, would be against the scheme framed by the Indian Banks Association as directed by the Reserve Bank of India.
• It was further submitted that the Credit Information Companies Act, 2005, the Credit Information Companies Rules, 2006 and the Circulars issued by the State Bank of India prohibits disbursement of loan in situations as that of the present petitioner.

What did the RBI circular say?

• On April 28, 2001, the RBI issued a circular in which it mentioned a comprehensive “model educational loan scheme” prepared by the Indian Banks Association (IBA) “for adoption by all banks”.
• The scheme aimed to provide financial support from the banking system to deserving or meritorious students pursuing higher education in India and abroad. Additionally, it was announced in the Union Budget for 2001–2002. While this scheme provided broad guidelines for banks to operationalise education loans, its implementation by banks varied.
• Following this, on June 24, 2019, the RBI advised all scheduled commercial banks to adopt the educational loan scheme formulated by IBA in 2001.

What is CIBIL score?

• A Credit Information Bureau (India) Limited (CIBIL) score is a three-digit numerical summary of one’s credit history, which involves an individual’s credit payment history across loan types and credit institutions over a period of time.

Credit Information Companies:

• A Credit Information Company (CIC) is an organization which collects and analyses credit and loan related data about individuals and companies and generates its products and services on the basis of this data.
• This data is provided to CICs by their member banks and other financial institutions. Credit Information Companies are also known as Credit Bureaus in India.
• A Credit Information Company needs to be a company that was formed and registered under the Companies Act, 1956 and is granted a Certificate of registration under sub-section (2) of Section 5, of CIC Act, 2005.
• They were licensed to work in the country under the Credit Information Companies (Regulation) Act, 2005 by the Reserve Bank of India (RBI).
• RBI reserves the right to determine the number of Credit Information Companies that can be granted with the Certificates of Registration to carry out the business of Credit Information, by taking into consideration various factors like the available business of Credit Information, the scope of expansion of existing CICs etc.
• Furthermore, RBI has the right to cancel the Certificate of Registration of any CIC as per the conditions laid out in Section 6, of CIC Act 2005.
• Currently there are 4 authorized Credit Information Companies in India.

1. Credit Information Bureau (India) Limited – CIBIL
2. Equifax Credit Information Services Private Limited
3. Experian Credit Information Company of India Private Limited
4. CRIF High Mark Credit Information Services Private Limited

As per Section 2 of CIC Act , ‘Credit Information’ refers to any information relating to

• Amounts and nature of the loans or advances, amounts outstanding under credit cards and other credit facilities granted (or to be granted) by a Credit institution i.e. banks or financial institutions to any borrower.
• The type and nature of the security taken (or proposed to be taken) by the credit institutions from the borrower in relation to the credit facilities being provided.
• The guarantee furnished by a credit institution to its borrowers.
• The creditworthiness of any borrower
• Any other information which the RBI may consider it to be necessary to be included in the Credit Information.

5. BIMA VAHAK

TAG: SCHEMES IN NEWS

CONTEXT: IRDAI’s plan to improve insurance awareness and penetration in the hinterland is all set to gain momentum with the insurance regulator issuing draft guidelines for Bima Vahak, a dedicated distribution channel to reach out to every Gram Panchayat. Insurance Regulatory and Development Authority of India (IRDAI) issued draft guidelines for Bima Vahaks.

EXPLANATION:

Bima Vahak Scheme:

• It is a core component of IRDAI ‘Insurance for all by 2047’ goal.
• It will be the crucial last-mile connect for insurers in the form of a field force comprising corporate as well individual regardless of their geographical locations.
• From the collection of proposal information, KYC documents and submissions to coordination and support in policy and claims-related servicing, the scope of activities of Bima Vahak will be wide and aimed at improving accessibility and availability of insurance in every nook and corner of the country.
• However, the insurer will remain responsible for ensuring KYC and AML compliance with respect to the policies sourced through the Bima Vahaks.

Draft guidelines:

• The primary objectives of the Bima Vahak guidelines are to establish a dedicated distribution channel focused on enhancing insurance inclusion and creating awareness in every Gram Panchayat (village council).
• A Bima Vahak will be permitted to sell and service the Bima Vistaar product approved by the Authority and work with only one life insurer, one general insurer and one health insurer and, where permitted, with the Agriculture Insurance Company of India Ltd.
• The Bima Vahak scheme will be closely aligned with the Lead Insurers that IRDAI had mooted in every State and Union Territory. Such Lead Insurers will coordinate deployment of resources to ensure maximum coverage of Gram Panchayats.
• With the Bima Vahaks engaging with the diverse needs and aspirations in every Gram Panchayat, insurers can adapt their offerings to provide comprehensive coverage and address emerging financial protection needs.
• The guidelines emphasize the identification and development of local resources within each Gram Panchayat, with a special focus on encouraging the onboarding of women as Bima Vahaks to gain the trust of the locals.
• The guidelines define two types of Bima Vahaks: Corporate Bima Vahaks and Individual Bima Vahaks. Corporate Bima Vahaks refer to legal entities registered under Indian laws and engaged by insurers. On the other hand, Individual Bima Vahaks can be either appointed by an insurer or appointed by a Corporate Bima Vahak.
• The guidelines outline several key requirements and policies that insurers must adhere to.
• These include norms for the appointment and engagement of Bima Vahaks, territorial allocation, educational qualifications and training standards, code of conduct, operational workflows and standards, use of electronic handheld devices, setting up of retail outlets, deployment of technology, the confidentiality of policyholder data, payment of a commission, operational and compliance requirements, and database management of policies solicited through Bima Vahaks.

Insurance Regulatory and Development Authority of India (IRDAI):

• It is a statutory body formed under an Act of Parliament, i.e., Insurance Regulatory and Development Authority Act, 1999 (IRDAI Act 1999) for overall supervision and development of the Insurance sector in India.
• The powers and functions of the Authority are laid down in the IRDAI Act, 1999 and Insurance Act, 1938.
• Its head office is located in Hyderabad and Regional offices at New Delhi and Mumbai. The Regional Office, New Delhi focuses on spreading consumer awareness and handling of Insurance grievances besides providing required support for inspection of Insurance companies and other regulated entities located in the Northern Region. This office is functionally responsible for licensing of Surveyors and Loss Assessors. Regional Office at Mumbai handles similar activities, as in Regional Office Delhi, pertaining to Western Region.
• The key objectives of the IRDAI include promotion of competition so as to enhance customer satisfaction through increased consumer choice and fair premiums, while ensuring the financial security of the Insurance market.
• The Insurance Act, 1938 is the principal Act governing the Insurance sector in India.
• It provides the powers to IRDAI to frame regulations which lay down the regulatory framework for supervision of the entities operating in the sector.
• Further, there are certain other Acts which govern specific lines of Insurance business and functions such as Marine Insurance Act, 1963 and Public Liability Insurance Act, 1991.
• Composition of IRDAI:

As per Sec. 4 of IRDAI Act, 1999, the composition of the Authority is:

1. a) Chairman;
2. b) Five whole-time members;
3. c) Four part-time members,

(appointed by the Government of India)

‘Insurance for all by 2047’:

• IRDAI is working on three-pronged approach — availability, accessibility and affordability — to ensure ‘Insurance for All by 2047’.
• India will attain 100 years of independence by 2047 and Insurance Regulatory and Development Authority of India (IRDAI) has taken several steps in the last 10-12 months to enhance penetration and density of life cover plan.
• A conceptual framework has been contemplated that this is being proposed through the Bhima trinity – Bhima Sugam, Bhima Vistar, and the woman-centric Bhima Vahak.
• IRDAI is moving from a rule-based approach to a principal-based approach, that the opportunity to invest in the insurance sector is immense given the size of the market, and low insurance penetration.
• To enhance penetration, attempts being made to reach the last mile through state level insurance plans in line with State-Level Bankers’ Committee (SLBC) on the banking side.
• There will be enhanced role of Insurance Information Bureau of India (IIB) in supporting data and tech-driven insurance solutions.
• Additionally, the need for risk based capital and solvency, convergence to Ind-AS, rationalizing expenses of management, developing talent pool, updating investment norms and sustainable growth of industry were also deliberated.
• It was also proposed to revamp the role and functioning of the life insurance and general insurance councils, to make them more vibrant bodies.

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