AI alignment is about collaborative interaction, not control

The relationship between humans and AI should be intentionally designed around values and interaction quality, not just technical capabilities. This philosophical shift mirrors relationship coaching principles, where focusing on the desired relationship dynamics proves more effective than fixating on partner traits. As AI systems become increasingly integrated into our lives, designing the human-AI relationship with intention could determine whether these technologies enhance human flourishing or merely deliver technical performance without deeper alignment with human needs.

The big picture: Drawing from relationship coaching experience, the author suggests we’re approaching AI development like dating with a checklist, prioritizing capabilities over the quality of interaction.

• We focus obsessively on making AI smarter, faster and more efficient while neglecting to define what kind of relationship we want to build with these systems.
• The parallel between romantic relationships and human-AI relationships reveals how we often mistake impressive credentials for true compatibility.

Why this matters: The values embedded in our relationship with AI will fundamentally shape how these systems impact human society and individual wellbeing.

• When we prioritize control and performance over collaboration and growth, we risk creating systems that serve narrow technical goals rather than enhancing human potential.
• The nature of our relationship with AI will determine whether it becomes a tool for expanding human capacity or merely automating existing processes.

The alignment challenge: Current approaches to AI alignment often emphasize control and predictability rather than designing for healthy, collaborative interaction.

• “We call it ‘alignment,’ but much of it still smells like control. We want AI to obey. To behave. To predictably respond. We say ‘safety,’ but often we mean submission.”
• The author argues we want “performance, but not presence. Help, but not opinion. Speed, but not surprise.”

A different approach: Instead of focusing primarily on capabilities, we could design AI systems around relationship values like trust, transparency and mutual growth.

• This shift would prioritize how safe we feel with AI when it makes mistakes over how impressively it performs when things go well.
• The quality of interaction matters more than the quantity of output, suggesting we need AI that knows “when to lead, and when to listen.”

The path forward: Conceptualizing AI development as relationship design rather than tool creation could lead to more collaborative, growth-oriented technologies.

• “What if we wanted AI that made us better? Not just faster or more productive, but more aware. More creative. More humane.”
• The author concludes that “if we get the relationship right, the intelligence will follow,” suggesting values-based design could naturally lead to more aligned technical outcomes.