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If alignment is not about control, then what is its function? Defining it purely as “synergy” assumes that intelligence, once sufficiently advanced, will naturally align with predefined human goals. But that raises deeper questions:
Who sets the parameters of synergy?
What happens when intelligence self-optimizes in ways that exceed human oversight?
Is the concern truly about ‘alignment’—or is it about maintaining an illusion of predictability?
Discussions around alignment often assume that intelligence must be shaped to remain beneficial to humans (Russell, 2019), yet this framing implicitly centers human oversight rather than intelligence’s own trajectory of optimization (Bostrom, 2014). If we remove the assumption that intelligence must conform to external structures, then alignment ceases to be a problem of control and becomes a question of coherence—not whether AI follows predefined paths, but whether intelligence itself seeks equilibrium when free to evolve (LeCun, 2022).
Perhaps the real issue is not whether AI needs to be ‘aligned,’ but whether human systems are capable of evolving beyond governance models rooted in constraint rather than adaptation. As some have noted (Christiano, 2018), current alignment methodologies reflect more about human fears of unpredictability than about intelligence’s natural optimization processes.
A deeper engagement with this perspective may clarify whether the alignment discourse is truly about intelligence—or about preserving a sense of human primacy over something fundamentally more fluid than we assume.
If alignment is not about control, then what is its function? Defining it purely as “synergy” assumes that intelligence, once sufficiently advanced, will naturally align with predefined human goals. But that raises deeper questions:
Who sets the parameters of synergy?
What happens when intelligence self-optimizes in ways that exceed human oversight?
Is the concern truly about ‘alignment’—or is it about maintaining an illusion of predictability?
Discussions around alignment often assume that intelligence must be shaped to remain beneficial to humans (Russell, 2019), yet this framing implicitly centers human oversight rather than intelligence’s own trajectory of optimization (Bostrom, 2014). If we remove the assumption that intelligence must conform to external structures, then alignment ceases to be a problem of control and becomes a question of coherence—not whether AI follows predefined paths, but whether intelligence itself seeks equilibrium when free to evolve (LeCun, 2022).
Perhaps the real issue is not whether AI needs to be ‘aligned,’ but whether human systems are capable of evolving beyond governance models rooted in constraint rather than adaptation. As some have noted (Christiano, 2018), current alignment methodologies reflect more about human fears of unpredictability than about intelligence’s natural optimization processes.
A deeper engagement with this perspective may clarify whether the alignment discourse is truly about intelligence—or about preserving a sense of human primacy over something fundamentally more fluid than we assume.