Lateral thinking: still important
AI is only fed by what has already been done. Calvin Ross Carl on why humans still own the lateral leaps that land on genuinely new ideas.
Summary
Calvin Ross Carl agrees with a viewer, Jared, that AI is only fed by what has been done. Humans are filters too, and we reach new ideas by understanding something about the old. But machines, at least so far, aren’t good at the super lateral thinking that jumps completely outside a knowledge base to run with a different idea. Maybe they’ll get there someday, Calvin says, but in the meantime he’s keeping it old school.
Highlights
- AI is only fed by what has already been done.
- Humans also build new ideas from understanding the old.
- Machines still struggle with truly lateral leaps.
Key insights
Everyone starts from the old
Calvin points out that humans and machines both build on existing knowledge.
The leap is the difference
What humans can still do is jump outside that knowledge entirely, which is where new ideas live.
Detailed analysis
Calvin keeps the comparison fair. He doesn’t claim humans create from nothing; he locates the gap in the leap. Lateral thinking is the move from what’s known to what isn’t, and that’s the part prediction-based tools haven’t mastered yet.
Conclusion
For now, the lateral leap is still a human job.
And yeah, Jared: it’s only fed by what has been done. Yep. That’s the challenge. We humans are our own little filtration machines, and the only way we ever get to new ideas is by understanding something about the old. But for some reason, machines—yet, I should say—aren’t great at that super lateral thinking, where you jump completely outside of the knowledge base and run with a different idea. So maybe we’ll be there someday. I don’t know. In the meantime, I’ll keep it old school for now.