What's New

STAND UP TO BREAKING NEWS

Relevance:

• GS 3 – Science and Technology- developments and their applications; Awareness in the fields of IT, Space, Computers, robotics, nano-technology, biotechnology and issues relating to intellectual property rights.
• GS 4 – Ethical concerns and dilemmas in government and private institutions; Information sharing and transparency in government

Why in the News?

• Recent Forbes article describes Perplexity’s (an AI powered answer engine) actions as ‘cynical theft’.
• AI summaries often lack the precision required for accurate news reporting.
• Unlike Wikipedia, AI summaries don’t have human oversight or verification processes.
• Risk of Spreading Unverified Information:
  • AI can unintentionally pick up and present unreliable or unverified information from articles as facts.
  • Users who are not knowledgeable or unable to identify inaccuracies may accept AI-generated summaries as accurate news.

Perplexity – An AI Application

• Wikipedia-like Approach to News: Parses through verified news sources.
  • Compiles information into an easy-to-understand format with key facts.
• Interactive Question-Answer Feature: Allows users to ask questions.
  • Generates answers on the fly based on sources.
• Perplexity as an ‘Answer Engine’:
• Perplexity positions itself similarly to a search engine. Publishers allow search engines to scrape content because it drives traffic back to their sites.
• Different from Search Engines: Search engines index content and direct users to original websites, creating a symbiotic relationship.
• Concerns About Perplexity :
  • Content Aggregation Issues: Perplexity takes content without permission. Republishes work, presenting itself as though it were a media outlet.
    • Forbes article describes the actions of Perplexity as plagiarism, Not Copyright Violation.
  • Reduces traffic to original sources: Perplexity and AI summaries address user needs directly, reducing traffic to original sources.

Comparison with Wikipedia:

Challenges Posed by AI Summaries (Including Google’s Feature):

• Accuracy Issues:
  • Often lack the precision required for accurate news reporting.
  • Can pick up unreliable or unverified information from articles as facts.
• Extractive and Cannibalistic Tools:
  • Such AI tools reduce the need for anyone to visit the original source.
  • They effectively steal the source’s audience and means of monetization (advertising/subscription).
• Lack of Human Oversight:
  • Unlike Wikipedia, AI summaries don’t have human oversight or verification processes.
• Potential for Misinformation:
  • Users who are not knowledgeable or unable to identify inaccuracies may accept AI-generated summaries as accurate news.
• Human Sharing vs. AI Copying:
  • Comparing AI tools to humans sharing information in their own words.
  • Public readability doesn’t imply permission for copying or AI training.
• Permission and Compensation:
  • Generative AI often uses third-party information without permission.
  • Mass content accumulation for AI training should not be equated with human learning.
• Disproportionate Impact:
  • AI’s ability to ingest, learn, and replicate content at scale has exponential effects.
  • The impact on original content creators is disproportionate.

Impact on News Publishers:

• Consequences of Dying News Sources:
  • Without news reporting, AI tools would rely on unverified tweets and unreliable sources.
  • The quality and reliability of information would significantly decline.
• Monetization Challenges:
  • Reduced traffic means fewer opportunities for subscription and advertising revenue.
  • AI tools addressing users’ needs directly diminish the value of original content.
• Exclusion from AI Indexing:
  • Publishers can opt out of AI bot indexing, but bots often ignore these requests.
  • The rapid increase in new AI models makes exclusion a significant task.
• Uncompensated Use of Work:
  • News publishers’ work is used as raw material to generate AI summaries without any compensation.
• Fair Usage and Copyright Concerns:
  • Facts are not protected by copyright, as their dissemination is an essential public service.
  • ‘Fair usage’ allows derivative works based on facts, provided additional value is added.
  • Perplexity’s and Google’s AI summaries add zero original value (no additional reporting, no original context).
• Gap in Copyright Law:
  • Current laws don’t adequately protect incentives for news organizations.
  • Ensuring the survival of news sources is crucial for the quality of information AI tools can provide.

Broader Implications:

• Not Just a ‘Big Tech vs. Publishers’ Issue:
  • This issue differs from the ‘link tax’ debates in Canada and Australia.
  • Link taxes are based on aggregating links, which adds value to publishers.
• Focus on AI Summaries:
  • AI summaries cannibalize publishers’ work rather than adding value.
  • Licensing deals with AI companies may perpetuate the problem.

Recommendations for Publishers:

• Content Licensing Deals: Signing deals with AI companies may not be beneficial in the long term. Publishers should focus on protecting their content from being cannibalized by AI summaries.
• Implement Robust Anti-Scraping Measures: Use technical measures to block AI bots from scraping content.
• Explore Licensing Agreements Carefully: Ensure any licensing deals with AI companies are beneficial and protective of content.
• Increase Awareness and Advocacy: Raise public and industry awareness about the impact of AI on content creation.
• Leverage Exclusive Content: Create premium, subscriber-only content to maintain revenue streams.
• Collaborate with Tech Companies: Work with AI developers to create fair use policies that benefit both parties.

Source: https://economictimes.indiatimes.com/opinion/et-commentary/stand-up-to-breaking-news/articleshow/111120143.cms?from=mdr

Mains question

Discuss the ethical and legal challenges posed by AI-generated summaries on the news industry, and suggest measures for protecting original content and ensuring fair use. (250 words)