Source URL: https://epoch.ai/gradient-updates/most-ai-value-will-come-from-broad-automation-not-from-r-d
Source: Hacker News
Title: Most AI value will come from broad automation, not from R&D
Feedly Summary: Comments
AI Summary and Description: Yes
**Summary:** The text presents a critique of the prevailing belief that AI’s primary economic impact will stem from its automation of research and development (R&D). Instead, it argues that most economic value will likely arise from broad automation of labor across various sectors. It emphasizes that R&D contributes less to economic growth than commonly perceived and warns against underestimating the complexity involved in automating R&D jobs.
**Detailed Description:**
The text dissects the optimistic forecasts about AI’s role in revolutionizing the economy, particularly through automation of R&D. Here are the critical points and insights presented:
– **Importance of R&D Misconception:**
– Many industry leaders, like Dario Amodei and Demis Hassabis, advocate for R&D as the main channel via which AI will create societal benefits. However, the text contends that R&D’s direct contribution to economic growth is minimal compared to broader automation of labor.
– R&D represents only a small slice (approximately 0.2%/year) of productivity growth in the U.S. economy from 1988 to 2022, totaling a mere 20% of labor productivity growth.
– **Perception vs. Reality:**
– The expectation that AI will first transform R&D before automating other sectors might be misguided. Instead, as R&D fully integrates AI, it will be preceded by widespread automation impacting a larger section of the workforce.
– **Challenges in Automating R&D:**
– R&D is not just “reasoning tasks”; it involves agency, multi-modal understanding, and physical manipulation of environments. Only a minority of critical scientific tasks can be accomplished by abstract reasoning models.
– A significant portion of R&D cannot be automated without AI systems that can effectively engage with physical environments and complex datasets.
– **Implication of Labor Market Changes:**
– The anticipated wave of automation will likely occur across a myriad of job sectors, leading to transformative economic growth through massive labor automation rather than through isolated R&D advancements.
– **Future Economic Landscape:**
– Businesses may find it more profitable to create AI systems that automate regular tasks across industries than to focus solely on enhancing capabilities for specialized research.
– A deep understanding of public sentiment regarding AI should evolve over time, particularly concerning the imminent waves of automation and labor displacement expected as AI systems develop further.
– **Long-term Speculations:**
– The piece argues for a cautious approach to projecting AI advancements. Economic impacts may materialize more progressively instead of through sudden breakthroughs, advocating for preparatory measures in workforce planning and investment strategies.
Overall, the text offers significant insights into the complexities of automating R&D, the reality of AI’s potential economic impact, and the broader implications for industries, public policy, and personal future planning.