The Union Budget 2025 introduced several measures to formally recognize gig and platform workers, providing them with social protection schemes. However, the Periodic Labour Force Survey (PLFS) 2025 has not been updated to capture the unique nature of gig work, leaving significant gaps in official labour statistics.

The NITI Aayog's 2022 report on India’s gig and platform economy projects that the gig workforce will grow to 23.5 million by 2029-30. Despite such projections and legal recognition under the Code on Social Security, 2020, the PLFS still categorizes gig workers under ambiguous classifications like self-employed, own-account workers, or casual labour. This statistical invisibility makes it difficult to fully understand the employment conditions of gig workers and hampers effective policy planning and welfare delivery.

Key Points to Understand:

Rise of the Gig Economy in India

• Gig and platform-based work is expanding rapidly, with jobs in food delivery, ride-hailing, digital freelancing, and home services becoming mainstream.

  NITI Aayog's 2022 report projects that India's gig workforce will grow to 23.5 million by 2029-30.

  In response, the 2025 Union Budget extended key social protection measures to gig workers, marking a significant step toward acknowledging their role in the economy.

Legal Framework for Gig Workers

• Code on Social Security, 2020: This code recognizes gig workers as those involved in income-generating work outside traditional employer-employee relationships, such as platform-based work (using digital platforms to access clients or services).

  Challenges:

  • Legal definition of gig workers remains too broad. It fails to sufficiently distinguish gig workers from other categories like self-employed or casual laborers.

  • Social Security Fund: A fund for gig and unorganised workers is mandated, but its effective functioning relies heavily on precise labour data.

Limitations of PLFS

• Inclusion Without Visibility:

  • The PLFS includes gig workers within broad categories like self-employed or own-account workers. However, it does not specifically identify gig workers.

  • This means key aspects of gig work — such as multiple app-based employment, income volatility, and lack of formal contracts — remain unaccounted for.

  Misclassification and Misrepresentation:

  • PLFS treats gig workers (e.g., food delivery drivers) the same as traditional self-employed individuals like shopkeepers, even though their work conditions, income sources, and risk exposures differ significantly.

  • Gig work often entails:

    • No formal contracts.

    • Dependency on digital platforms.

    • Flexible but precarious task-based jobs.

    • These aspects are not adequately captured in the survey data.

Why Gig Work is Unique

Gig work stands apart from traditional self-employment in several critical ways. Here's a comparison between traditional self-employment and gig work, highlighting the distinct nature of gig work:

Government Initiatives: Recognition Without Representation

• Initiatives like e-Shram registration, digital ID issuance, and inclusion in schemes like Ayushman Bharat PM-JAY aim to bring gig workers into the formal welfare framework.

• Problem: These initiatives are difficult to track and monitor without accurate data on gig workers, undermining their ability to deliver effective social protection.

Recent Improvements in PLFS

• The 2025 PLFS revision introduced some changes, such as:

  • A larger sample size.

  • Monthly estimates.

  • Expanded rural coverage.

  However, it still does not distinctly identify gig workers or address the core issue of statistical invisibility.

Towards More Inclusive Labour Statistics

To adapt to the changing workforce, India's labour statistics framework needs to evolve. Key suggestions include:

1. Updating PLFS Codes: Incorporate a distinct category for gig and platform workers.

2. Survey Modifications: Introduce special survey modules or time-use surveys to better capture task-based work.

3. Leverage Digital Data: Use digital trace data from platforms (e.g., Uber, Urban Company) to supplement and improve official statistics.

4. Welfare Monitoring: Ensure that beneficiary data from welfare schemes is fed back into national employment databases to monitor delivery and outcomes.

Importance of Accurate Labour Data

• Having inclusive and accurate labour data is essential not only for representation but also for ensuring that welfare policies are effective, equitable, and reach the right people. It will enable the government to make informed policy decisions, monitor the gig economy, and track welfare outcomes.

Conclusion

India’s growing gig workforce requires a more precise and inclusive approach in official labour statistics. By updating the PLFS and developing tailored survey methods, India can better address the needs of this increasingly important segment of the workforce and ensure that gig workers are adequately supported under the country's social security and welfare schemes.

The Madras High Court's judgment quashing the 2011 phone-tapping order issued by the Union Ministry of Home Affairs (MHA) marks a crucial turning point in the interpretation of the right to privacy and the limitations of executive powers in India. This ruling aligns with the growing body of constitutional jurisprudence that places the right to privacy as an intrinsic part of the fundamental rights under Article 21 of the Indian Constitution.

Key Highlights of the Judgment:

1. Violation of Article 21 – Right to Privacy:

• The Madras High Court emphasized that phone tapping constitutes a violation of the right to privacy unless it follows legal procedures laid down under Indian law.

  The Court ruled that surveillance or phone tapping could only be permissible if it met the stringent conditions of public emergency or public safety—the exceptions provided under the Indian Telegraph Act.

  Key observation: The Court specifically noted that the phone tapping order did not satisfy these exceptions and was thus unconstitutional.

2. Legal Framework and Judicial Precedents:

• The judgment cited several landmark decisions to bolster its reasoning:

  • PUCL v. Union of India (1997): It had established that phone tapping is permissible only under strict legal conditions and due process.

    K.S. Puttaswamy v. Union of India (2017): The Supreme Court had earlier elevated the right to privacy to a fundamental right under Article 21, stating that any action impacting this right must adhere to the procedure established by law.

    Maneka Gandhi v. Union of India (1978): The Supreme Court also held that any law or procedure that affects fundamental rights must be just, fair, and reasonable.

3. Case Background and Legal Basis:

• The surveillance order was authorized in 2011 under Section 5(2) of the Indian Telegraph Act, 1885, and Rule 419-A of the Indian Telegraph Rules, 1951, which allows interceptions only in the case of a public emergency or in the interest of public safety.

  The Central Bureau of Investigation (CBI) justified the surveillance on the grounds of detecting a bribe of ₹50 lakh, but the Court disagreed, finding the phone tapping was not justified under the exceptions outlined in the law.

4. CBI’s Argument and Court’s Response:

• CBI's Argument: The CBI claimed that the surveillance was necessary to uncover a bribe, especially after ₹50 lakh in cash was seized from a vehicle associated with an accused Income Tax officer.

  Court’s Rebuttal: The Court rejected the CBI’s argument, stating that the petitioner was not involved in the seizure of the cash. The Court also ruled that the scope of Section 5(2) could not be extended to support covert surveillance aimed at crime detection, as the legal conditions for public emergency or safety were not met.

Broader Constitutional Implications:

1. Right to Privacy:

   • The Madras High Court’s judgment follows the evolution of the right to privacy, from British common law to landmark US Supreme Court cases (like Katz v. United States), and culminating in the Indian Supreme Court’s interpretation in Puttaswamy (2017).

     The ruling reinforced the idea that executive overreach, particularly in the form of surveillance, threatens democratic values and the fundamental rights of individuals.

2. Limitation of Executive Powers:

   • The Court reaffirmed that any action that impacts fundamental rights must follow due process, aligning with the principles of natural justice.

     The ruling highlights the vital role of the judiciary in safeguarding the rights of individuals from unlawful state actions, especially in the age of advanced surveillance technologies.

3. Surveillance and Democracy:

   • The judgment further stressed the importance of safeguards in the use of surveillance technologies by the state.

     It also warned against unchecked powers of the executive, ensuring that the state’s actions should not be beyond scrutiny or arbitrary.

Conclusion:

This judgment from the Madras High Court is a landmark in defending the right to privacy under the Indian Constitution. It reinforces the constitutional limitations on executive powers, particularly in the use of modern surveillance methods. The ruling also strengthens the judiciary's role in upholding individual freedoms and ensuring that government actions remain within the bounds of the law. With privacy being affirmed as a fundamental right, this case contributes to shaping India’s privacy jurisprudence and its application in the digital age.

The recent legal rulings involving AI companies like Anthropic and Meta have significant implications for the intersection of copyright law and the rise of generative AI tools. These decisions help clarify the legal standing of AI models' use of copyrighted material for training purposes, especially in the context of claims like those from authors and content creators.

Key Highlights:

Case 1: Writers vs. Anthropic

• Plaintiffs: Writers Andrea Bartz, Charles Graeber, and Kirk Wallace Johnson filed a class action lawsuit against Anthropic, claiming that their books were used without permission for training the Claude LLMs (Large Language Models).

• Allegation: The writers accused Anthropic of pirating their books and using them to train its AI models, which they argued negatively affected their livelihoods by facilitating the generation of cheap or free content.

• Court's Decision: The Northern District of California court ruled in favour of Anthropic, stating that the use of the authors' works was covered under the fair use doctrine.

  • Fair Use: The court held that the use was transformative, meaning the AI created something new, not merely replicating or replacing the original content. It compared the AI's use to a reader’s learning process, which contributes to creating something distinct.

  • Judge's Key Quote: “Like any reader aspiring to be a writer, Anthropic’s LLMs trained upon works… to create something different.”

Case 2: Writers vs. Meta

• Plaintiffs: Thirteen authors filed a class action lawsuit against Meta (creator of the LLaMA language model), alleging that their copyrighted works were used without permission to train Meta's AI models.

• Allegation: The plaintiffs claimed that Meta copied substantial portions of their texts, with LLaMA generating content that directly mimicked their original work.

• Court's Decision: The judge ruled in Meta's favour, stating that the plaintiffs failed to prove the AI's use harmed the market for their original works.

  • Market Harm: The court found that there was no significant market harm, a key element in fair use analysis. It stated that Meta’s use did not directly compete with the original works.

  • Transformative Use: The court acknowledged that AI’s use of copyrighted works is transformative but emphasized that tech companies should find ways to compensate original content creators.

  • Judge's Remarks: While the court supported fair use, it flagged concerns over compensation for the authors, suggesting that tech companies benefiting from AI technologies should work out fair compensation systems for the original creators.

Legal Context: Fair Use and AI Training

What is Fair Use?

• Fair use allows limited use of copyrighted material without permission under certain circumstances, such as for criticism, comment, teaching, scholarship, or research.

• For AI models, the courts focused on whether the training process resulted in something transformative—i.e., not a direct copy but rather something new or restructured.

The Transformative Nature of AI:

• Both courts upheld the argument that AI models like those developed by Anthropic and Meta use copyrighted content in a way that transforms the material.

  • This transformation occurs because the AI does not reproduce the content verbatim but instead processes and reinterprets it in a manner that is distinct from the original.

Ongoing Legal and Ethical Concerns

Unresolved Legal Battles:

• Both Anthropic and Meta still face multiple lawsuits, especially from music publishers, visual artists, and journalists, claiming unauthorized use of their content to train AI systems.

• The Books3 database issue: Pirated data sets like Books3 may still create legal challenges for AI companies, as it remains uncertain whether using pirated works can ever be considered fair use.

• Concerns over Compensation: Despite the legal victories, content creators remain unsatisfied with the lack of compensation mechanisms. There’s growing demand for AI companies to acknowledge the rights of the original creators and provide fair remuneration, especially as AI-generated content becomes more prevalent.

The Global Context: India and AI Copyright

• In India, the legal landscape surrounding AI is evolving. For example, ANI filed a lawsuit against OpenAI for using Indian copyrighted content without permission in 2024.

  • Major Indian media houses have also hinted at rising domestic litigation, indicating that global rulings like these might have international consequences.

  • India's digital media landscape could face significant challenges as AI models increasingly tap into vast amounts of content from news publishers, bloggers, and other content creators.

Significance of the Rulings

1. Support for AI Companies: The rulings reflect a growing legal acceptance of the notion that using copyrighted material to train AI models can be considered fair use. This could set an important precedent for other tech firms involved in AI development.

2. Fair Use for Public Interest: The judgment reinforced that the purpose of the AI's use must be transformative and serve the public interest. This aligns with arguments that AI, when used responsibly, can provide innovative, educational, and research-driven contributions.

3. Ethical and Financial Implications: While the courts ruled in favour of AI companies, they also flagged the need for compensation to the creators. This points to a future challenge for tech companies to balance the use of copyrighted content with the fair remuneration of creators.

Conclusion

These recent rulings are a significant step in defining the legal parameters for AI development in the context of copyright. While tech companies like Anthropic and Meta have won their cases based on fair use, the ethical and financial concerns surrounding the impact of AI on content creators and the future of copyright law remain unresolved.

As AI tools like ChatGPT and Gemini continue to evolve, these cases are likely to shape the legal framework for using copyrighted material and force a broader societal debate over intellectual property rights, data ethics, and the responsibility of AI developers. The ruling may have long-term implications for AI regulation, intellectual property law, and the tech industry’s approach to content creation.

The presence of plastics, particularly microplastics, is indeed a growing concern due to their potential impacts on human health.

1. Endocrine System:

The endocrine system is critical for regulating many bodily functions through hormones. It includes glands like the thyroid, pituitary, adrenal glands, and gonads, which produce hormones that influence:

• Growth and development

• Metabolism

• Mood and behavior

• Sexual function

• Reproductive health

Any interference with this delicate system can lead to a range of health issues.

2. Endocrine-Disrupting Chemicals (EDCs):

EDCs are chemicals that can disturb the endocrine system, mimicking or blocking the action of natural hormones, thus altering bodily functions. These chemicals are everywhere:

• BPA (Bisphenol A): Found in plastic containers, food can linings, and water bottles. It can mimic estrogen, a crucial hormone in both male and female bodies, leading to reproductive issues.

• Phthalates: Often used in plastics to make them flexible, phthalates can affect hormone production and cause developmental issues, particularly in children.

• Other EDCs: They can alter thyroid function, interfere with insulin regulation, and even lead to early puberty in children.

3. Impact of Microplastics and EDCs on Human Health:

As plastics break down into microplastics, they’re increasingly found in:

• Air: Tiny particles in the air we breathe, potentially impacting lung function.

• Food and Water: Microplastics can be ingested through contaminated food and drinking water.

• Skin: Plastics and their chemicals can also be absorbed through the skin via lotions, cosmetics, and other products.

4. Health Effects of EDCs:

Long-term exposure to EDCs can have:

• Reproductive and developmental effects: Lower fertility rates, birth defects, and changes in sexual development.

• Metabolic issues: Increased risk of obesity, diabetes, and other metabolic disorders.

• Cancer risk: Some EDCs are linked to cancer, especially hormone-related cancers like breast and prostate cancer.

• Neurodevelopmental impacts: Exposure to certain EDCs during critical developmental stages may impair cognitive function in children.

5. Why is This a Growing Concern?

• Ubiquity of Plastics: Plastic is pervasive in modern life, from food packaging to household items, and its breakdown into microplastics means that no part of the ecosystem is untouched, including our bodies.

• Invisible Threat: Microplastics and EDCs don’t always show immediate symptoms, which means their impact can be insidious, building up over time.

6. What Can Be Done?

• Regulation: Governments and international bodies must implement stronger regulations on the production and use of harmful chemicals like BPA and phthalates.

• Alternative Materials: Investing in biodegradable or safer alternatives to plastics and chemicals used in everyday products.

• Awareness: Encouraging consumers to reduce plastic usage and supporting eco-friendly brands.

The link between plastic pollution and endocrine disruption underscores the need for urgent action, both in regulating chemicals in consumer products and reducing plastic waste. It’s an important area of concern for public health, environmental sustainability, and human welfare.

The recent amendments proposed by the Ministry of Information and Broadcasting to the Policy Guidelines for Television Rating Agencies (2014) are aimed at making the Television Rating Point (TRP) system more reflective of the diverse and evolving media consumption habits of Indian viewers.

What is a Television Rating Point (TRP)?

Television Rating Point (TRP) is a metric that measures the popularity and viewership of television programs. It helps assess:

• How many viewers are watching a particular program.

  The duration of time viewers spend watching specific programs.

  How popular a program is relative to others.

Key Points about TRP:

• Higher TRP: A higher number of viewers translates to a higher TRP for a program.

  Advertiser Influence: Advertisers use TRP ratings to decide where to place their ads. Channels with higher TRPs attract more advertising revenue.

  Investor Decisions: TRPs are also used by investors to make decisions about funding and investing in programs or channels.

How is TRP Calculated in India?

In India, TRP is calculated by BARC India (Broadcast Audience Research Council), using a combination of technologies and sampling methods:

1. BAR-O-meters (People Meters):

• BARC India installs BAR-O-meters (a type of "people meter") in the televisions of selected households.

• 58,000+ Impanelled Households: The meters are installed in over 58,000 households across the country to ensure a diverse sample.

• Viewership Tracking: The people meters track which TV channel or program is being watched by the family members. The data is collected in real-time.

2. Data Extrapolation:

• The data from these selected households is extrapolated to estimate the viewership of the entire population.

• This allows for an estimation of what the viewership trends would look like for a larger audience, based on a sample size.

3. Picture Matching:

• In addition to the people meters, picture matching is also used.

• The people meter records a small portion of the image being watched on the TV. This data is later analyzed to determine the program being watched.

4. Weekly TRP Results:

• BARC India releases weekly TRP results every Thursday, ranking TV channels and programs based on their viewership data.

Implications of the Proposed Amendments to TRP Policy Guidelines

The Ministry's proposed amendments aim to address the following evolving needs:

1. Reflect Changing Media Consumption Patterns:

   • The current TRP system may not fully capture the shift in viewership habits. Digital streaming, OTT platforms, and mobile viewership have drastically changed how people consume content. The amendments may integrate these new consumption patterns into the TRP system.

2. More Accurate Representation of Diverse Audiences:

   • India's diverse population and regional preferences require a more nuanced approach to understanding viewership. The changes could make the system more representative of the multi-lingual and multi-regional nature of Indian television.

3. Improved Transparency and Fairness:

   • The TRP system has faced criticism for being susceptible to manipulation. The amendments may address concerns related to transparency and accuracy, ensuring that the TRP ratings better reflect the true preferences of viewers.

4. Adapting to Technological Advancements:

   • With the advent of smart TVs, streaming services, and mobile apps, more integrated methods of tracking viewership may be introduced, including using digital data.

5. Incorporating Behavioral Insights:

   • A move towards incorporating behavioral insights and more detailed demographic data might help in understanding why viewers watch certain content, not just what they watch.

Conclusion:

The proposed amendments to the TRP Policy Guidelines are expected to address the growing need for a modernized and fair system that accommodates changing viewing habits and technological advances. As India moves into an era where digital content consumption is surging, this update will be pivotal in ensuring that advertisers, broadcasters, and viewers receive more accurate and representative data about television viewership.

India's progress with the DengiAll vaccine is a major development in the global fight against dengue, and it highlights the country's growing capability in the field of indigenous vaccine development.

DengiAll: The Indigenous Tetravalent Dengue Vaccine

Development and Collaboration:

• Developer: The vaccine is developed by Panacea Biotec Limited under a licensing agreement with the National Institutes of Health (NIH), USA.

• Composition: DengiAll is a tetravalent vaccine, meaning it targets all four types of dengue virus (DENV). It uses a weakened form of the four virus subtypes, with the same virus composition as the vaccine developed by the NIH but with different inactive ingredients.

Clinical Trial Phases:

• Phase I & II Trials: Initial trials conducted in India showed that the vaccine elicited a balanced and robust immune response against all four types of dengue. The vaccine was also found to be safe and well-tolerated in participants.

  Phase III Trial: India has recently reached the 50% enrolment mark for the Phase III clinical trial, which aims to test the efficacy, immunogenicity, and safety of DengiAll. The trial is being carried out in collaboration with several institutes, including those under the Indian Council of Medical Research (ICMR).

ICMR Institutes Involved:

• The ICMR-National Institute of Translational Virology (NITVAR) and ICMR-National AIDS Research Institute (NARI) are playing key roles in trial coordination.

  These institutes will ensure that the vaccine's performance and safety are rigorously tested across diverse populations.

Key Facts About Dengue

What is Dengue?

• Dengue is a mosquito-borne viral infection that occurs mostly in tropical and subtropical regions, particularly in urban and semi-urban areas.

Transmission:

• The disease is transmitted to humans via the bite of infected Aedes mosquitoes carrying one of the four types of dengue virus (DENV).

  Dengue is not contagious from person to person, except in rare cases where it is passed from a pregnant person to their child.

Symptoms:

• Common symptoms include:

  • High fever

  • Headache

  • Body aches

  • Nausea

  • Rash

  Dengue Hemorrhagic Fever (DHF): A small proportion of patients may experience severe symptoms leading to Dengue Hemorrhagic Fever, which is life-threatening.

Treatment:

• There is no specific antiviral treatment for dengue.

  Supportive care is provided to manage symptoms, particularly focusing on pain relief and fever reduction.

Significance of DengiAll's Development

1. Indigenous Vaccine: This marks a significant step towards self-reliance in vaccine production, with India taking a leading role in the development of a tetravalent dengue vaccine.

2. Global Health Impact: Dengue is a major health concern in many parts of the world. A successful vaccine can greatly reduce the burden of the disease, especially in endemic regions.

3. Efforts in Vaccine Development: This project reflects India's ability to develop cutting-edge medical technology in collaboration with global research bodies like NIH, making it an important milestone for Indian scientific innovation.

Conclusion

The DengiAll vaccine trial's success could be a game-changer in the global fight against dengue. The Phase III trial is crucial for determining whether the vaccine can provide long-term protection against all four dengue virus types. India's indigenous capabilities in vaccine development are growing, and DengiAll represents a significant leap toward reducing the public health threat posed by dengue.