Researchers Advocate Viewing AI as a Normal Technology Not a Superintelligence Threat

Artificial intelligence (AI) is often framed in extremes: either as a utopian breakthrough or a dystopian threat. However, two researchers from Princeton University, Arvind Narayanan and Sayash Kapoor, propose a third perspective—viewing AI as a normal, general-purpose technology undergoing gradual adoption.

Despite AI’s growing ubiquity and impressive capabilities, the researchers caution against hype around concepts like “superintelligence” and fears of an AI arms race. They argue these ideas are speculative and detract from practical considerations about AI’s real-world applications and societal impacts.

Narayanan and Kapoor compare AI’s adoption trajectory to that of electricity or the internet, technologies that took decades to permeate society fully. They emphasize the distinction between rapid technological development in labs and the slower, more measured pace of societal adoption and impact.

The researchers highlight several key points:

• Terms like “superintelligence” are incoherent and should be avoided in serious discourse.
• AI will not automate all jobs but will create new roles focused on monitoring and supervising AI systems.
• AI is likely to exacerbate existing societal issues such as inequality, labor market disruption, and democratic backsliding rather than create entirely new problems.

They also critique the prevalent narrative of an AI arms race, especially between the US and China, calling it “shrill” and unrealistic given the rapid global dissemination of AI knowledge and research.

Instead of focusing on controlling hypothetical superintelligent AI or winning an arms race, the authors advocate for practical policy measures:

• Strengthening democratic institutions to better manage AI’s societal impacts.
• Increasing technical expertise within government bodies.
• Improving AI literacy among the general public.
• Incentivizing defenders to adopt AI responsibly to mitigate harms.

This pragmatic approach contrasts sharply with the sensationalism often surrounding AI discourse. By normalizing AI as a technology with a gradual adoption curve, society can better prepare for its integration and address real challenges effectively.

While the authors acknowledge the rapid militarization of AI, they exclude it from their current analysis due to limited access to classified information, promising future research on this critical issue.

In summary, treating AI as a normal technology encourages measured expectations, informed policy, and focused efforts on managing its societal impacts rather than speculative fears. This perspective fosters a more constructive dialogue about AI’s role in shaping the future.