Recommendation #1: Open the semantic space around Pro-Human AI
The words we choose at the beginning of a movement do more than describe its intentions. They help determine which questions we ask, whose interests we notice, and what kinds of solutions feel natural. Before “Pro-Human AI” becomes a settled destination, I would suggest spending some time exploring the semantic space around each of its terms, and around the relationships those terms imply.
This is a recommendation offered through a Meta-Layer lens, with no expectation that anyone adopt it. The purpose is to make room for possibilities that our starting language may obscure. My own inclination is toward Pro Human-Nature-AI, held lightly as a direction worth exploring rather than a definition everyone needs to accept.
What are we saying yes to?
“Pro” sounds straightforward until we ask what it commits us to. Supporting human flourishing might mean protecting people from harm, increasing their capacity to act, strengthening the communities they depend on, or preserving the conditions that allow future generations to flourish. Those aims can reinforce one another, but they can also pull in different directions. An AI that satisfies an immediate preference may weaken a person's longer-term autonomy, just as a service that is convenient for individuals may erode an institution they collectively need.
Consider a personal assistant that gradually becomes the only way someone encounters news, finds work, or participates in public debate. It may be useful and responsive while quietly narrowing the person's field of view. A meaningful interpretation of “pro” should help us examine that whole relationship, including the power exercised by the companies, institutions, and information systems around the assistant.
Which understanding of human?
“Human” can refer to an individual, a community, humanity as a whole, or generations not yet born. A movement can affirm human agency while leaving unresolved which of these scales it intends to protect. The interests of a present user, a neighborhood, and a future population will not always coincide.
Individual agency matters. People should be able to understand, refuse, redirect, and leave systems that act on their behalf. But human life also depends on collective agency: our ability to deliberate, develop shared knowledge, establish institutions, and act together. A collection of capable personal assistants does not by itself provide the shared spaces where people can question one another, build trust, or decide what they want to do in common.
Through a Meta-Layer lens, those shared spaces are part of the design question. Can people gather around the same information, see where they agree and disagree, and carry the context of their conversation forward? Who governs that space, and can the participants change its rules? These are questions about human agency even when no individual AI is behaving badly.
What do we mean by AI?
“AI” can mean a model, an assistant, an agent with delegated authority, or an ecosystem of systems embedded in everyday life. Those are different objects of attention. A model's responses tell us something about its behavior, but less about the effects of thousands of agents operating through concentrated infrastructure, commercial incentives, and unevenly distributed authority.
Imagine the same capable model in two settings. In one, it can suggest actions that a person reviews. In the other, it can spend money, change records, influence other agents, and retain access indefinitely. The model may be identical, but the surrounding architecture changes both the opportunity and the risk. Our language should leave room to evaluate that architecture, not just the intelligence inside it.
A hyphen changes the question
Pro-Human AI puts the emphasis on AI's orientation toward humans. It invites questions about service, loyalty, accountability, and control. That is a useful starting point, especially when people are already experiencing systems whose incentives they did not choose.
In a Meta-Layer Monday call where we reviewed the Pro-Human AI statement, Emory professor Benn Konsynski suggested moving the hyphen to be between human and AI. Pro Human-AI shifts attention toward the relationship. Benn's suggestion of this framing opens a conversation about human-AI symbiosis: how distinct participants might augment one another while retaining meaningful boundaries. It does not settle questions about AI consciousness, moral status, or rights. It does make the quality and durability of the relationship a more explicit design concern.
I would add nature to that frame. Pro Human-Nature-AI asks whether the relationship supports the living systems on which human life depends, as well as human autonomy and the development of intelligence. A highly productive human-AI partnership could still accelerate ecological damage. Including nature makes it harder to treat that damage as someone else's problem or as a cost outside the system we are designing.
A direction, lightly held
The possibility I want to explore is a durable, non-dominating relationship among humans, nature, and AI. That does not mean pretending the three are interchangeable or that their interests are easy to identify. Nature is not a single negotiating party; humans disagree; and the capabilities and status of future AI remain uncertain. Those difficulties belong inside the conversation.
For present-day design, this framing could encourage concrete commitments: protecting human autonomy, making ecological costs visible, limiting concentrations of authority, preserving diversity, and keeping decisions open to challenge and revision. For more capable future systems, it raises an additional question about whether commitments to coexistence and flourishing could endure beyond the mechanisms we currently use to enforce them. That is an open research and governance question, not a claim that we know how to achieve it.
I offer this as a recommendation with no expectations attached. Others may prefer the existing language, find a better formulation, or conclude that several framings should coexist. The useful outcome would be a clearer understanding of what each framing brings into view and what it leaves out.
An invitation to explore
We could begin with a small, open exercise: articulate the strongest interpretation of each framing, identify the assumptions it carries, and test it against ordinary situations. Changing AI providers, protecting a watershed, organizing a community response, or challenging an automated decision can reveal differences that remain hidden in abstract language. The results could then inform the Desirable Properties we ask an ecosystem to support.
Three questions seem especially useful for the conversation:
- What does each framing help us notice, and what might it cause us to overlook?
- Where do individual agency, collective agency, and ecological flourishing reinforce one another, and where do they conflict?
- Which commitments would remain valuable if AI capabilities changed far more rapidly than our institutions?
The next recommendation takes this inquiry into a collaborative North Star Analysis: defining the Desirable Properties of the ecosystem before particular solutions become the destination.
Continue to the North Star Analysis →