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Anti-scale: a response to AI in journalism

Nov 24, 2024 - tylerjfisher.com
The article discusses the potential impact of generative AI on journalism, arguing that it is not the solution to the industry's problems. The author asserts that while AI can generate plausible content, it often lacks accuracy and can contribute to misinformation. Despite partnerships between news organizations and AI companies like OpenAI, the author remains skeptical, citing a lack of public trust in AI-generated news and the potential for AI to create a deluge of false content.

The author proposes an "anti-scale" approach to journalism, rejecting the idea of mass-produced content in favor of fostering deeper connections and community. They argue that journalism should focus on human stories and experiences, and that technology should be used to help journalists find and foster digital communities. The author also calls for new ways to measure the impact of journalism that move away from traditional metrics like pageviews and click rates.

Key takeaways:

  • The author argues that generative AI, despite its potential, is not the solution to the problems facing journalism, as it often produces plausible but inaccurate content and is not trusted by a majority of Americans.
  • Instead of embracing AI and competing through scale, the author proposes an anti-scale approach to technology in journalism, focusing on deeper connection and community.
  • The author suggests that technology in journalism should be recentered on helping people find information and solve problems, rather than chasing pageviews and user retention.
  • Key questions for the future include how to build tools to help journalists find and foster digital communities, how to differentiate good journalism in an ocean of AI-generated content, and how to quantitatively measure the impact of journalism.
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