Overview of AI Copyright Lawsuits

The advent of artificial intelligence has led to numerous copyright lawsuits filed by authors, news outlets, visual artists, musicians, and other copyright owners. These lawsuits target major tech companies like OpenAI, Anthropic, and Meta Platforms for using copyrighted works to train AI content generators without permission or payment.

Key Issues in the Lawsuits

• Fair Use Argument
  • Courts will soon determine if the tech companies' use of copyrighted material can be considered "fair use," a critical issue in the AI copyright debate.
  • Technology companies claim their AI systems transform copyrighted material to create new content, while copyright owners argue it threatens their livelihoods.
• Potential Impact on AI Industry
  • Tech companies, including OpenAI and Meta, argue that paying for copyrighted content may hinder the AI industry's growth in the US.

Current Legal Landscape

• Some content owners are voluntarily licensing their content to tech companies, such as Reddit, News Corp, and the Financial Times.
• Others, including major record labels and best-selling authors, continue to press lawsuits.
• Judges in various jurisdictions might reach different conclusions, leading to potential appeals.

Notable Cases

• Thomson Reuters vs. Ross Intelligence
  • Thomson Reuters accused Ross of misusing its legal research platform Westlaw to develop an AI-powered search engine.
  • Ross claimed fair use, and further arguments on this are expected to lead to a new ruling.
• Music Publishers vs. Anthropic
  • The lawsuit involves the use of song lyrics to train Anthropic's chatbot, Claude.
  • US District Judge Jacqueline Corley is evaluating fair use in this context.
• Raw Story and AlterNet vs. OpenAI
  • The case was dismissed as the outlets failed to prove injury from alleged copyright management information removal.

Semiconductor Development Projects and AI Initiatives in India - 2024

Semiconductor Development Projects

• Approvals in 2024: Four semiconductor projects received approvals, consisting of one chip fabrication facility and three chip packaging units. 
• Chip Fabrication Facility:
  • Location: Dholera, Gujarat 
  • Investment: ₹91,526 crore 
  • Partnership: Joint venture between India’s Tata Electronics and Taiwan’s Powerchip Semiconductor Manufacturing Corporation (PSMC) 
  • Capacity: 50,000 wafer starts per month 
• Chip Packaging Units:
  • Locations: Morigaon, Assam and Sanand, Gujarat 
  • Combined Capacity: Over 70 million chips per month 
  • Key Projects:
    • Assam Facility: Built by Tata Electronics, costing ₹27,120 crore with a capacity of 48 million chips per month 
    • Gujarat Facility 1: Joint venture by CG Power, Renesas Microelectronics, and Stars Microelectronic, costing ₹7,584 crore and capacity of 15.07 million chips per day 
    • Gujarat Facility 2: Built by Kaynes Technology India, costing ₹3,307 crore with a production capacity of 6.33 million chips per day 

AI Development and Deployment

• India AI Platform: Launched to ensure safe and trusted AI deployment, while fostering innovation within the country. 
  • Investment: ₹10,372-crore programme approved by the government 
  • Features: Portal includes sections on news, articles, case studies, research reports, startups, investment funds, and more. 

Conclusion

The year 2024 marked significant progress in India's semiconductor and AI sectors, underpinned by substantial investments and strategic partnerships, enhancing the country's technological landscape.

Disparities in App-Based Taxi Fare Based on Phone Type

Recent observations suggest that there may be a difference in the fares displayed on Android and iPhone devices for the same rides booked through app-based taxi services. This could imply that pricing algorithms might be designed to charge Apple users higher rates.

Survey Insights by LocalCircles

LocalCircles, a community platform, conducted a survey to explore consumer experiences with dark patterns in ride-hailing apps. The survey received responses from 33,000 users across 269 districts in India.

• Demographics: 
  • 61% of respondents were men, while 39% were women.
• Key Findings: 
  • 42% of users encountered hidden charges not disclosed upfront.
  • 84% experienced 'forced action', being compelled to cancel a ride.
  • 78% reported 'bait and switch' tactics, where the waiting time shown was significantly less than the actual time.

Dark Patterns Employed by Ride-Hailing Platforms

• Uber: Utilizes forced action, interface interference, bait and switch, and drip pricing.
• Ola: Employs forced action, bait and switch, and drip pricing.
• BluSmart, InDrive, Rapido: All use drip pricing.

Prevalence of Dark Patterns

According to the survey, eight in ten app taxi users reported experiencing dark patterns such as bait and switch and forced action, while four in ten confirmed experiencing drip pricing.

Central Drugs Standard Control Organisation (CDSCO) Alert Summary

Overview

The CDSCO flagged select batches of two drugs as spurious and listed 111 other drugs and formulations as not of standard quality (NSQ) in their November 2024 update.

Spurious Drugs Identified

The flagged spurious drugs include:

• Pan D marketed by Alkem Laboratories.
• Augmentin 625 Duo marketed by GlaxoSmithKline Pharma.

The alert does not name the drug manufacturers as the batches were reportedly not produced by them but were imitated by unauthorized entities.

Investigation and Regulatory Surveillance

An investigation has been initiated to identify unauthorized manufacturers. The CDSCO conducts continuous surveillance by sampling drugs from sales/distribution points and maintains a monthly list of spurious drugs to inform stakeholders.

Non-Standard Quality (NSQ) Drugs

A total of 111 drugs were identified as NSQ, categorized by the following:

• 41 drugs identified by central drug laboratories.
• 70 drugs flagged by state drug testing labs.

Examples of NSQ drugs include:

• Ozomet PG2 tablets by Ozone Pharmaceuticals (hypertension medication).
• Tofajak tablets by Cipla (treatment for rheumatoid arthritis).
• Monit SR30 tablets by Intas Pharma (chest pain medication).

Geographical Production Insights

Most of the NSQ drugs were produced in major pharmaceutical hubs like Ahmedabad, Baddi, Puducherry, Haridwar, and Roorkee.

Significance of Reporting

The increased reporting from state drug authorities to the central database signifies improvement in the tracking and availability of quality medicines.