Sir Ronald Cohen critiques the philanthropic model, arguing that relying on donations keeps charitable organizations small, underfunded, and perpetually begging for capital. This prevents them from achieving the scale needed to solve massive problems, a flaw that impact investing aims to correct by creating self-sustaining models.

For robust, high-stakes grantmaking, separate analysis into three layers. First, empirical uncertainty (what will happen?). Second, normative uncertainty (what outcomes are most valuable?). Third, meta-normative uncertainty (how should we aggregate different moral views and risk preferences?). This framework clarifies thinking.

John Arnold distinguishes philanthropy from charity, arguing its core function is to tackle long-term, systemic problems. Foundations can take risks—political and economic—that governments and corporations are not incentivized to take, funding experimental solutions with a high probability of failure but massive potential societal upside.

Government funders like the NIH are inherently risk-averse. The ideal model is for philanthropists to provide initial capital for high-risk, transformative studies. Once a concept is proven and "de-risked," government bodies can then fund the larger-scale, long-term research.

Reaching a 100x increase in charitable impact isn't from a single change but from combining principles that each act as a multiplier. For instance, shifting focus to a more neglected problem (10x) and choosing a leveraged policy solution (10x) can result in a 100x total improvement.

A critical flaw in philanthropy is the donor's need for control, which manifests as funding specific, personal projects instead of providing unrestricted capital to build lasting institutions. Lasting impact comes from empowering capable organizations, not from micromanaging project-based grants.

Frame philanthropic efforts not just by direct impact but as a "real-world MBA." Prioritize projects where, even if they fail, you acquire valuable skills and relationships. This heuristic, borrowed from for-profit investing, ensures a personal return on investment and sustained engagement regardless of the outcome.

The 'effectiveness' in Effective Altruism creates a bias toward quantifiable problems like global health, while overlooking harder-to-measure but potentially higher-impact areas. For instance, preventing political dysfunction or misinformation among influencers could have a far greater downstream effect than many targeted donations, but it's not a typical EA cause because its impact is difficult to quantify in advance.

A charity like Make-A-Wish can demonstrably create value, even exceeding its costs in healthcare savings. However, the same donation could save multiple lives elsewhere, illustrating the stark opportunity costs in charitable giving. Effective philanthropy requires comparing good options, not just identifying them.