Which causes deserve priority?
The framework I find most useful for thinking about cause prioritisation is ITN: Importance, Tractability, and Neglectedness. Importance asks how much suffering or flourishing is at stake. Tractability asks whether additional resources can realistically make progress. Neglectedness asks whether the problem is already receiving substantial attention and funding. What I find valuable about the framework is that it forces me to separate questions that are often blurred together. A cause can be hugely important and still be a poor target for marginal donations if progress is extremely difficult or if enormous resources are already flowing into it.
Applying this framework has gradually shaped how I think about giving. Global health still receives the largest share of my donations because the evidence base is unusually strong and the impact is measurable in a way that inspires relatively high confidence. At the same time, I remain persuaded by the importance and neglectedness arguments for areas like AI safety and animal welfare, even where the uncertainty is much greater. None of these allocations feel final or perfectly resolved to me. Cause prioritisation ultimately requires making provisional judgements under real moral and empirical uncertainty, and being willing to update them as new evidence emerges.
Most charity evaluation measures the wrong thing
Singer's argument answers the whether question. It does not answer the how. Once I accepted that giving substantially was both morally sensible and practically required, I found myself facing a different and considerably harder problem: how do you know whether a charity is actually worth giving to?
My first instinct was to look for external validation. Charity watchdogs exist precisely for this purpose: Charity Commission filings in the UK, Charity Navigator in the US, assorted rating schemes that purport to separate responsible organisations from careless ones. What I found was a methodology built almost entirely on the wrong question.
I gave to charity for eight years before asking if it worked
In 2007, the year our first child was born, I set up a direct debit to Cancer Research UK. It felt meaningful. I had no way of knowing whether it was. That question would take me the better part of a decade to begin answering properly.
Over the years that followed, the portfolio grew the way most people's giving grows: incrementally, emotionally, and without much strategy. A colleague mentioned a charity. A news story prompted a one-off donation. Each choice felt right at the time of making. None were made on the basis of any clear idea what the money was actually achieving. This is, I suspect, how most people give. The intention is genuine. The method is essentially nonexistent.
What changed things was a single short essay, written in 1972, that I heard mentioned on a podcast at roughly the right point in my life.
Why you should consider giving more of your money away effectively and why you should talk about it
In a world where individual choices can have global consequences, how we give matters as much as whether we give at all. Donating to effective charities is not just an act of generosity but a way of directing resources where they can do the most measurable good. Evidence suggests that some organisations achieve far greater impact per pound than others, often by a substantial margin, through a focus on cost-effectiveness, transparency, and rigorous evaluation. This has shaped my own approach: I aim to support causes and organisations where careful analysis suggests that additional funding can meaningfully improve outcomes. Over time, this has led me towards global health, long-term risks, and other areas where the potential impact is especially high. At the same time, I continue to support some causes for personal reasons, even if they are less cost-effective. More broadly, I believe there is value in being open about giving. Talking about it can help normalise thoughtful, impact-driven philanthropy and encourage others to consider not just giving more, but giving more effectively.
Empiricism makes everything better
Empiricism, at its core, is the idea that our beliefs should be grounded in evidence derived from observation and experience. While both empiricism and rational reasoning play a role in how we come to understand the world, it is empirical thinking that has driven much of human progress, from scientific discovery to technological advancement. In an organisational context, this mindset translates into a commitment to seeing reality as it is, rather than as we would prefer it to be. Where empiricism is absent, decisions tend to be driven by hierarchy, intuition, or narrative rather than evidence, leading to persistent blind spots and ineffective execution. Practising empiricism, however, is not straightforward. It requires a culture that values truth over comfort, access to reliable data and meaningful measurement, and a degree of intellectual humility that is often at odds with incentives in many organisations. Despite these challenges, grounding decisions in evidence, continuously testing assumptions, and updating beliefs in light of new information remains one of the most effective ways to improve both individual judgement and organisational performance.
The Yahaba Technique
The Yahaba technique is a simple but powerful way to bring the perspective of future stakeholders into present-day decision-making. Inspired by an experiment in Japan where participants were asked to represent future generations, the approach involves assigning some members of a decision-making group to act as advocates for the people who will live with the consequences of today’s choices. In practice, this helps organisations surface long-term risks and trade-offs that are often overlooked in the pressure to deliver short-term results. By explicitly introducing a “future voice” into discussions, teams are better able to balance immediate priorities with longer-term sustainability, whether in strategy, technology, or organisational design. The technique is lightweight and adaptable, but its effectiveness depends on participants engaging seriously with the exercise and being willing to challenge assumptions. While it is not a complete solution, even a modest application of Yahaba thinking can significantly improve the quality of decisions by making the long-term more tangible and harder to ignore.
How I think about: Organisational Maturity
Organisational maturity is the ability of an organisation to achieve complex objectives well, not merely quickly or by following a particular framework. A mature organisation can balance short-term delivery with long-term resilience, adapt to change, create value sustainably, and improve continuously across technical, operational, product, financial, and governance dimensions. Too often, organisations either underinvest in maturity, assume they can “do it later”, adopt frameworks without connecting them to outcomes, or optimise locally while ignoring the wider system. The challenge is that maturity growth competes with immediate delivery pressures, so it should be treated not as a problem to solve once, but as a polarity to manage continuously. Doing this well starts with an honest, evidence-based understanding of where the organisation really is, followed by clear choices about what needs to improve, why it matters, how success will be measured, and what investment is required. Done properly, growing maturity becomes one of the most important ways an organisation improves execution, innovation, adaptability, and long-term performance.
How I think about: Productivity
Productivity in knowledge work, particularly in software engineering, is often misunderstood by applying models borrowed from manufacturing, where outputs are tangible and repeatable. In reality, knowledge work is inherently complex, non-linear, and difficult to measure, with outputs that are multi-faceted and often intangible. As a result, attempts to reduce productivity to a single metric, or to evaluate individuals in isolation, tend to produce poor outcomes, encouraging gaming, local optimisation, and a focus on outputs rather than real value. Instead, productivity should be seen as a combination of factors such as pace, quality, collaboration, maintainability, and learning, all of which contribute to the organisation’s ability to create meaningful business and customer value. The goal is not to maximise productivity as a standalone measure, but to improve the overall system through better communication, clearer priorities, reduced friction, and continuous improvement. In this context, focusing on outcomes, teams, and end-to-end value flow, while interpreting metrics carefully and within context, is far more effective than trying to optimise any single dimension in isolation.
How I think about: Uncertainty
Uncertainty is a fundamental feature of both the world and the organisations we operate in, yet we are naturally inclined to resist it. We seek control through planning, analysis, and prediction, often underestimating how limited that control really is. In practice, uncertainty takes multiple forms, from gaps in knowledge (epistemic) to irreducible randomness (aleatory), as well as differences in understanding (ontological) and meaning (semantic). Treating all uncertainty as something that can simply be “reduced” leads to wasted effort and poor decisions. Instead, effective organisations learn to recognise the type of uncertainty they are dealing with, assess whether it is worth reducing, and invest accordingly. Just as importantly, they build the capability to operate under uncertainty by improving adaptability, decision-making, and systemic resilience. Rather than attempting to eliminate uncertainty entirely, the goal is to understand it, manage it, and where possible, use it to uncover opportunities.
J.S. Mill: On Liberty - Quotes
Mill was one of the people who were decades ahead of his time and his ideas laid foundations for modern ethics, feminism, equality, free speech and liberal order. Together with his uncle Jeremy Bentham, Mill is also regarded as the father of Utilitarianism.