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Source-This post on High-Quality Data for Safe and Equitable AI Development has been created based on the article “AI needs cultural policies, not just regulation” published in “The Hindu” on 1 August 2024.
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Context– The article emphasizes the need for high-quality data, the challenges in acquiring it, and the importance of digitizing cultural heritage.
Data is fundamental to AI development because more data improves AI performance, especially for LLMs (Large Language Models). Larger volumes and diversity of human-generated text enhance LLM capabilities. Data, along with computing power and algorithmic innovations, is a critical driver of AI progress.
What are the Challenges in Data Acquisition?
1) Insufficient Digital Content -Humans do not produce enough digital content to meet the growing demands of AI models, and current training datasets are already enormous—such as Meta’s LLaMA 3, which uses 15 trillion tokens.
2) Data Contamination-There are concerns about public data contamination by LLMs that could amplify biases and reduce diversity.
Read More- India’s Digital Personal Data Protection Act
3) Ethical Concerns-It include the use of pirated content, unclear principles in data collection, training on a mix of licensed and publicly available data, and biases due to overrepresentation of English-language and contemporary content.
3) LLM Access to Diverse and Historical Data -Current LLMs lack access to primary sources, diverse languages, and archival documents. Historical texts are underrepresented, and there is a lot of untapped data in cultural heritage, like Italy’s State Archives.
What is the significance of digitizing cultural heritage?
A) Enrich AI’s understanding of humanity’s cultural wealth.
B) Improve accessibility to world knowledge and foster global innovation.
C) Revolutionize historical understanding.
D) Safeguard cultural heritage from negligence, war, and climate change.
E) Provide economic benefits by enabling smaller companies and startups to develop AI applications.
What should be the Way Forward?
A) Balance regulation with policies promoting high-quality data as a public good.
B) Prioritize digitization of cultural heritage and diverse languages.
C) Recognize the cultural, economic, and technological benefits of promoting low-resource languages.
D) Accelerate the digital transition while preserving and utilizing world cultural heritage.
Question for practice
What challenges are associated with data acquisition, and why is digitizing cultural heritage important?
