Funders Must Rethink How to Lead Through Tech-Inflected Uncertainty

2025 forced leaders in public interest technology to confront what has always been true: uncertainty is unavoidable. Political upheaval, climate instability, and technological “disruption” all point in the same direction: we are in a moment of rapid and unpredictable change.

Philanthropic leaders, especially those focused on tech policy, feel this acutely. They work in complex, evolving systems but rely on tools and practices designed for certainty and control. The craft of making grants — including the practices and tools funders use to develop strategies, shape proposals, and measure impact — is dominated by if-then thinking, causal theories of change, fixed goals, long-term planning, discrete measurement, and attempts to catalogue ‘what happened’ and assess ‘impact.’

Artificial intelligence complicates this dynamic further. Companies are selling the narrative that AI is “changing everything” so that their solution — all-purpose answer machines — hits the mark. But generative AI tools don’t manage uncertainty, they collapse uncertainty and complexity into a neat interface. The answer offered is a flattened facsimile of reality. Generative AI as it is currently configured only obscures uncertainty and plays into our human desire for control. This is the challenge philanthropic leaders — and, indeed, the broader public interest technology community — must confront at this moment: how to adapt amidst uncertainty in an organizational context that doesn’t tolerate it, and within a broader system that makes it harder to see clearly.

We propose that public interest technology leaders should stop viewing uncertainty as a problem to solve and instead see it as a reality to navigate in relationship with one another. This requires a mindset shift —from an if-then approach that presumes control and predictability to one that embraces uncertainty, adaptivity, and attunement. And, it requires a more strategic shift that we characterize within philanthropy as an evolution from grant craft to systems craft.

Ultimately, this moment requires leaders to build what we and others call relational infrastructure — with one another and the organizations and communities they support — to sense, act, and adapt together. We focus here on philanthropic leaders because their decisions significantly impact the choices organizations can make and the approaches they can pursue, but much of the below applies to organizations stewarding responsible and public interest technology, and technology policy more broadly.

Worldview and mindset

In her famed work “Places to Intervene in a System,” environmental scientist Donella Meadows names “the power to transcend paradigm” as the deepest and most impactful node of intervention in systems change work.

Across sectors, much of work is premised on the logic that well-defined problems can be solved. This if-then mindset is rooted in cartesian logic, linear positivism, and reductionism.

• Reductionism says that a system can be understood by breaking it down into simpler component parts and studying those parts in isolation. If you understand the parts, you understand the whole.
• Cartesian logic treats a system like a machine. You break the system into its parts — actors, technologies, organizations, etc. — and then assume cause and effect between the parts, such that if you do x, y will result. This thinking underpins most theories of change and allows you to assume that you can predict and control outcomes.
• Positivism assumes knowledge is valid only if it comes from observation, measurement, or experiment. In other words, if it can’t be measured, it doesn’t count.

One of the first things grant makers in strategic philanthropy learn is how to interpret an incoming proposal through the lens of problem solving: what well-defined “problem” will be solved, over what time horizon, by which stakeholders, doing what, and requiring what resources? What will be different as a result? This formula extends past a comparative heuristic, becoming an inherited blueprint for describing how a particular grant fits a strategy.

Most recently, the rise of AI risks deepening this problem-solving logic with the promise of optimization and prediction. Surely problem-solving approaches have delivered innumerable gains across fields. But as was pointed out in the 1970s by the scholars Horst Rittel and Melvin Webber, social phenomena do not lend themselves well to problem solving. The systems philanthropic leaders seek to change aren’t machines. They’re dynamic, adaptive, and unpredictable. Much of what matters — relationships, trust, power, beliefs, culture — can’t be neatly measured. And the macro change in the system is often more than the sum of its parts.

Working in complex systems means letting go of control. It means designing adaptive, iterative strategies; focusing less on fixed goals and more on relationships, feedback, and ongoing learning. This requires a mindset that centers ‘relational infrastructure’ — stitching together networks that reorganize problems by changing the flow of information and resources across the system.

In systems change, it’s common to say: change the relationships, change the system. But a ‘relational infrastructure’ approach goes further, contending that the success and health of a system isn’t just built on relationships — it evolves through them. Indeed, time and again, collective sense-making across different groups not previously connected are a necessary precursor to defining and solving any problem. For grantmakers of sociotechnical phenomena paying close attention, it becomes clearer and clearer that relationships are the intervention. Solidarity is the solution. What might this shift look like at the level of strategy?

Strategy and theory of change

Typically, a grantee will outline a strategy up front, a funder will approve it, and the grantee endeavors to adapt its theory of change as it learns what works and doesn’t. And theories of change are useful. They help us see our work in relation to others’, help us define what is ‘in scope’ and what’s out, and act as a forcing function for imagining what will be different in the future as a result of our efforts. But theories of change also invite linear positivism and object orientation: if we do X, Y results. We know that grantees operate in complex, uncertain systems that are dynamically changing, yet are often forced to fit theories of change into if-then constructs, fixed plans, and rigid targets that suggest measurable impact, demonstrable solutions, and a theoretical point at which “change” has occurred.

Systems craft requires rethinking not just theories of change, but measurable goals. Goals can limit ongoing learning and sense-making in any setting, but they become a real liability in complex, uncertain systems. As Indy Johar puts it, goals can “collapse diversity…and leave systems brittle in the face of uncertainty.” We set a target assuming stability — then the system shifts, and the goal no longer fits. Your intervention misfires because the system reacts in ways you didn’t foresee, and now every stakeholder is scrambling to adjust. But effective adaptation requires the ability to sense, interpret, and respond — not stick to a fixed, causal plan. Targets, goals, and optimization-based technologies ask for certainty and control. Complex systems demand flexibility and continuous learning.

This doesn’t mean we should abandon goals — but we do need to rethink their role. Goals shouldn’t be fixed endpoints or static measures of success. They should invite disparate actors to become part of a common project. They should be “provisional, situated, and subject to continual renegotiation as the system evolves,” as Johar explains. In other words: use goals to orient, not to define the destination. Hold them lightly. Let them go when they limit your ability to sense, adapt, and respond.

If traditional targets no longer capture what successful systems change looks like — what should take their place? Right relationship.

Like the tugging of balancing scales, ‘right relationship’ is not only a mathematical and material condition but also an ongoing process; an orientation; a general relativity whose center of gravity is perhaps more readily felt than understood. Like balance, “right relationship” is not found and established but rather constantly sought through attention, participation, and discernment. Our work in strategic philanthropy, then, commonly positioned as a general project to theorize how change happens and measure our success by how its unfolding matches up to our expectations, can also be understood as an invitation to participate in cultivating the conditions for right relationship on an ongoing basis, collectively witnessing and feeling its emergence and resonance as the fruits of our efforts.

Where problem-solving approaches and optimization based technologies assume we can predict and control complex systems, relational infrastructure invites us to build systems that can evolve through trust, feedback, and shared meaning. An approach that centers relational infrastructure lets the strategy emerge from the relationships — from what each stakeholder can now see about the system it’s trying to impact. Relational strategies start with a directional orientation, and outcomes emerge from a process of relationship building, collective sensemaking, ongoing learning, and opportunistic collective action. Rather than primarily operating from a specific theory of change, relational funders’ “strategic” energy focuses on supporting grantees to see each other’s work and mission clearly, understanding and shaping system dynamics through participation, and cultivating the capacity for stakeholders to learn across their differences.

Implementation and learning

Funders often operate through a portfolio model, investing in grantees who are loosely connected to a body of work. The authors, for example, have both been involved in the field-building project of Public Interest Technology. The relationship between a funder and a grantee is one-to-one. Funders resource specific, individual projects and work within an organizational structure that requires accountability for performance and results. Any program officer needs a clear answer to the questions: what did you spend money on, and what was the impact? A ‘project’ has clearly defined boundaries with a specific theory of change. Learning, in turn, looks a lot more like reporting. We know that grantees’ work is enriched by being in relationship with other grantees, but we ask them to put their energy into writing reports that will languish in a review queue destined for our eyes only.

By contrast, a relational infrastructure approach focuses on how the system evolves through relationships. The capacity to navigate difference amidst implementation, adapt amid conflict, and reach shared understanding through dialogue is what allows a system to hold multiple versions of good at once — and “maintain coherence” even as it changes or diverges. This is especially challenging in the context of AI because, while everyone might be using the same terms, we’re all talking past one another. For some, it’s a probabilistic text generator; for others, a machine that reasons like a human. Some see it as a mechanism that encodes past inequities, while others frame it as a driver of progress and productivity. The task of the philanthropic leader is to help translate across differences. Translation is the practice of bridging languages, values, and logics so people can coordinate without needing to think the same way. You know translation is taking hold not when everyone converges on a single view but when people with genuinely different lenses can still coordinate effectively because they understand how each other makes meaning.

In this way, funding approaches that seek to build relational infrastructure focus centrally on how to cultivate and resource relationships between stakeholders in their system. As these connections are stitched together, systems evolve: from one-to-one siloed relationships, to many-to-many networked relationships. New learning and insights are shared through these networked relationships, enabling the system to adapt in response.

Philanthropic leaders stop measuring discrete quantitative targets meant to convey ‘what happened’ and focus instead on what is happening:

• Narratives: Are new frames circulating and gaining traction?
• Relationships: Are new alliances forming or previously excluded voices joining?
• Behaviors: Are small practices replicating on their own?
• Technical shifts: Are new defaults, categories, or protocols being adopted?
• Feedback loops: Is information flowing differently, in ways that shift power imbalances?

Stewarding relational change means attending to subtle shifts in the system and amplifying those that cultivate coherence and move toward the directional goals. In this context, funders put less emphasis on singular projects, focusing more on the ‘in-between,’ on the complementary approaches and shared values that cut across projects. These funders map and identify how a constellation of organizations and collectives are directionally aligned, substantively and normatively, and support the infrastructure they need to thrive, learn, and adapt. When funders nurture new relationships among grantees or help to translate across differences, they change the information flow within a system: they change what each grantee is seeing, how they’re making sense of the system, what they’re learning, and how they’re adapting.

Conclusion

The work of grantmakers today is a paradox: how to navigate uncertainty in systems that seek certainty and obscure change. The only way out of this paradox is to build a bridge between the neatly categorized and controlled work of a bygone era and to the current necessity to show up as effective resource mobilizers in an increasingly uncertain, complex system. But while it can be tempting to frame the moment as requiring us to move “from” a set of practices that no longer serve “to” a set of practices better fit for purpose, this framing itself recapitulates the sort of binary thinking that no longer authentically corresponds to reality. All around us, we are living in many worlds at once.

We are being challenged to be and do both/and — navigating not only a set of institutional practices designed for compliance and cohesion, but also an emergent call to be in deeper, more coherent relationships with the systems we are in a position to impact. This is an attempt to align grant craft with systems craft: centering relational infrastructure and the insight that effective strategy emerges from shared sense-making with people who share stakes in the future.