First of all i wanted to thank everyone from the ea community. i hope it might be useful. i also wanted to apologize if there is already ongoing work in this direction and i'm not aware of it. thank you guys, everyone, it means a world to me. and i have no idea how EA in practice actually works. It's an outsider type of view.
For most of its history, Effective Altruism has focused on persuasion.
We built a community.
We developed frameworks.
We encouraged individuals to change careers, donations, and priorities.
That work mattered — but it has limits.
Even if every private donor optimized perfectly, most of the world’s decisions would still be made by governments, corporations, NGOs, and international agencies. Those institutions control vastly more resources than any movement ever will.
If we want large-scale impact, we cannot rely only on convincing exceptional individuals.
We have to change how ordinary institutional decisions get made.
The next phase is not movement building.
It is infrastructure building.
The goal is simple:
Make rigorous decision-making the default professional standard — not a personal philosophy.
Many institutional failures don’t happen because leaders are unintelligent or malicious.
They happen because everyday decision processes are weak.
A mid-level analyst prepares a report without comparing alternatives.
A grant program measures outputs but not counterfactual impact.
A corporate ESG team reports activity instead of outcomes.
A policy proposal gets funded because no one quantified uncertainty.
These are not rare breakdowns. They are routine.
In complex systems, performance is limited by the weakest step in the decision chain — not the smartest person in the building.
So instead of only trying to recruit top talent, we should raise the epistemic floor for everyone.
That means giving ordinary professionals structured tools that make better reasoning automatic.
Not moral conversion.
Not intellectual identity.
Just better default procedures.
When we say “epistemic infrastructure,” we do not mean philosophy.
We mean mundane, boring, unavoidable tools.
For example:
These are small procedural changes — but they shape behavior.
Professionals do what forms require.
They justify what templates demand.
They measure what reporting standards define.
If rigorous reasoning is built into ordinary workflows, institutional behavior changes without anyone needing to join a movement.
For these tools to spread across sectors and countries, they cannot dictate values.
Different institutions legitimately pursue different goals.
A public health agency, a climate fund, and a development bank will not share identical moral priorities — and they shouldn’t have to.
So the infrastructure should govern how decisions are evaluated, not what goals must be chosen.
Think of it like accounting standards.
Accounting rules don’t tell companies what to produce.
They require transparent, consistent reporting.
Similarly, epistemic infrastructure would require structured reasoning:
Different actors can still disagree — but their reasoning becomes visible and contestable.
3.5 The Ground-Up Entry: Seeding Standards Inside Institutions
Change begins from within, not from broadcasting a movement. Individuals embed small, high-utility tools — asymmetric assets — into the institutions where they already operate.
Key steps:
Through this approach, rigorous decision-making spreads by proving its value, not by persuasion. The narrative arc becomes clear: individual contributor → institutionally embedded tool → widely adopted standard. By starting in real institutions and speaking their language, EA-inspired standards gain traction naturally while supporting both professional goals and broader social impact.
At this point, a natural reaction is:
“Great — let’s just build good templates and distribute them.”
But that is not enough.
Any tool used widely will eventually become routine.
Routine becomes checkbox compliance.
Checkbox compliance becomes empty ritual.
We have all seen this happen:
If decision tools become infrastructure, they must be actively maintained, audited, and improved.
Otherwise rigor decays into bureaucracy.
That is why infrastructure needs governance.
If decision protocols become professional standards, we need institutions responsible for maintaining and challenging them.
In practice, this means several concrete mechanisms.
Just as accounting and engineering standards are periodically revised, decision protocols must be updated as knowledge improves.
For example:
Independent bodies would issue revised versions of standard templates and guidance.
Good infrastructure should not automate judgment away.
Instead, it should require users to document reasoning explicitly.
A grant evaluation template might require:
If those fields are empty, approval cannot proceed.
The goal is not to produce “the right number.”
It is to produce a transparent reasoning trail.
Every dominant framework develops blind spots.
So criticism must be structural, not optional.
Dedicated review groups should be funded specifically to:
Their role is not to cooperate — it is to stress-test the system.
Because these tools shape real resource allocation, they cannot be controlled only by technical experts.
Professional associations, regulators, and affected stakeholders must participate in revisions and review cycles.
Decision standards must remain publicly contestable.
Better reasoning alone does not produce adoption.
Institutions change when standards help them manage risk and responsibility.
Decision protocols become attractive when they:
For example:
An insurer might recognize a standardized decision framework as evidence of responsible governance.
A regulator might require structured impact analysis for major programs.
An accreditation body might require documented uncertainty analysis.
At that point, rigorous reasoning is no longer optional — it is professional compliance.
The goal is not to make everyone identify with Effective Altruism.
The goal is normalization.
Success looks like:
A budget analyst requesting expected value estimates because every proposal requires them.
A grant officer documenting counterfactuals because the form has a mandatory field.
A project review including uncertainty ranges because reports cannot be submitted without them.
People use these tools not because they are persuaded — but because they are standard practice.
The movement dissolves into the environment.
If this direction is correct, the community’s comparative advantage shifts.
Instead of primarily producing arguments, we should also produce professional-grade decision tools.
Concrete priorities might include:
And importantly:
Structures for maintaining, revising, and criticizing those tools over time.
Persuasion changes individuals.
Infrastructure shapes institutions.
Governance preserves infrastructure.
If we want rigorous reasoning to influence decisions at civilizational scale, it cannot remain a niche intellectual practice.
It must become ordinary professional procedure.
Not a philosophy people adopt.
A standard people inherit.
The aim is not to win arguments.
It is to build the floor beneath institutional decision-making — so that better reasoning becomes the path of least resistance.
Note: If EA helps improve decision quality and impact across society — including among people and institutions that never identify with the movement — this could also make it easier to build broad support for high-impact policies and funding priorities. In practice, that may mean greater public and political willingness to back interventions that are evidence-based but currently seen as difficult or unpopular, such as health-related taxation (e.g., sugar or salt) or other highly efficient large-scale measures.
Additional note: In some ways, this shift is already happening. EA ideas, tools, and decision frameworks are gradually spreading beyond the boundaries of the self-identified community. But there is still much more to explore here. Rather than relying primarily on costly strategies focused on visibility — heavy marketing, branding, or media exposure — it may be valuable to invest more in exploration: finding scalable ways for EA-informed thinking to diffuse organically into institutions, professions, and public decision-making, whether or not people adopt the label, but where we show the effectiveness of our approaches and let people come to the conclusion. Even if it's a for profit business, overall economic growth could have additional effects on solving global issues.