The REAL Timeline of AI's Future: It's Not What You Think

Summary

In this insightful video, Julia McCoy, founder of First Movers, breaks down key insights from Dave Shapiro about the future of AI. The next 36 months will see a monumental shift in knowledge work and automation, with early movers capturing significant value, much like during past revolutions. While full automation is decades away, those who act now will secure generational wealth. The script emphasizes the need for individuals and businesses to adapt, positioning themselves as AI orchestrators and focusing on roles that can't be easily automated. The question remains: who will control the future AI creates?

Takeaways

• 😀 The AGI revolution is coming, and we have more time than doomsayers believe. The key challenge is economic scale and deployment, not intelligence.
• 😀 Over the next 36 months (2025-2027), significant changes in knowledge work and digital capabilities will reshape industries.
• 😀 By 2025, we'll see the automation cliff for knowledge work, with autonomous agents executing complex tasks that once required human intelligence.
• 😀 By 2026, humanoid robots will enter the commercial market, with advanced models costing around $80,000 and basic utility robots ranging from $20,000 to $110,000.
• 😀 The period from 2027 to 2030 will see the arrival of ASI (Artificial Superintelligence), but full deployment will take time due to the gap between capability and real-world use.
• 😀 Between 2030 and 2040, the scaling era will begin, but rare earth metal shortages will limit robot production despite ramping up efforts.
• 😀 Full labor substitution across industries is projected between 2040 and 2060, with economies reaching saturation at different paces.
• 😀 The 2% of early movers who position themselves well within the next 3 to 5 years will capture disproportionate value, much like the early automobile industry pioneers.
• 😀 Some jobs will remain safe for now, including skilled physical labor, high-accountability roles (e.g., doctors, lawyers), meaning-driven roles (e.g., creators, spiritual leaders), complex relationship jobs (e.g., politicians), and capital owners who control AI and robots.
• 😀 If you're in knowledge work, act quickly to become an AI orchestrator, leveraging AI tools and transitioning to roles that require human connection and meaning.
• 😀 The silver linings include more time to adapt to economic disruption, the ongoing advantage of human bodies over robots, and the impracticality of a catastrophic AI takeover due to hardware constraints.

Q & A

What are the two competing truths discussed in the script regarding AI's advancement?

The two competing truths are: First, we have more time than the doomsayers think, and second, the 2% who get ahead now will corner the abundance in ways we haven't seen since the industrial revolution.

Why is the bottleneck in AI's advancement not intelligence or robotics capability?

The bottleneck lies in economic scale and deployment, rather than intelligence or basic robotics capability.

What is the predicted timeline for AI and automation advancements from 2025 to 2040?

From 2025 to 2027, we’ll see autonomous agents and AI-driven workforce deployments. By 2026, physical intelligence and humanoid robots will emerge. Between 2027 and 2030, ASI (Artificial Superintelligence) will arrive but won’t be fully deployed. From 2030 to 2040, robot production will scale, but constraints in resources will slow down full automation. By 2040-2060, global labor substitution will occur, leading to full automation across most sectors.

What is the 'automation cliff' predicted for 2025?

In 2025, the automation cliff for knowledge work is expected, where autonomous agents will begin executing complex tasks that previously required human intelligence. Hybrid workforces will emerge, with both humans and AI working together.

How does the scaling of AI differ from historical technological advancements like automobiles?

While past technological advancements, like automobiles, took decades to reach full saturation, AI technology moves much faster. Its capabilities compound exponentially, while deployment scales linearly, leading to a concentration of wealth for early adopters.

What categories of work are expected to remain safe from automation in the near future?

Several categories of work will remain safe for now, including skilled physical labor (due to a lack of enough robots), high-accountability jobs (like doctors and lawyers), meaning-based roles (such as creators and spiritual leaders), complex relationship jobs (like politicians and negotiators), and capital owners (who will benefit from AI and robots).

How should individuals in knowledge work prepare for the coming changes?

Individuals in knowledge work should prepare by becoming AI orchestrators, mastering the use of AI tools at an expert level, and transitioning to roles requiring authentic human connection and meaning. It's crucial to develop skills that will be in demand during the scaling era.

What should people in physical labor focus on to prepare for automation?

Those in physical labor should focus on complex, non-routine skills that will be harder to automate. They should also consider acquiring ownership stakes in automation through ESOPs, cooperatives, or investments, and prepare for shifts in industry demand as automation reshapes the economy.

What are the silver linings of the extended timeline for automation?

The silver linings include more time to adapt to economic disruption, the continued abundance and energy efficiency of human bodies, the implausibility of a catastrophic AI takeover due to hardware constraints, and the opportunity to develop better ownership models and policies for the transition.

What is the key choice facing society regarding AI and automation?

The key choice is whether we will develop cooperative ownership models for AI, where the benefits are widely shared, or if those who position themselves early will capture most of the value, creating lasting wealth disparities. The window for making this choice is closing rapidly.