This is a work in progress. If you have feedback - comments, questions, or pointers to related content - please email me.

Introduction

Governments shape human society by selecting and implementing policies in various areas: taxation and distribution of wealth, health care, land use, environmental regulation, education, law enforcement and the penal system, social safety nets, and so on. These policies define economic systems.

Most current governments (including the U.S.) are performing poorly. Their policies

• aren't working well in the short term: Most people in the world are poor, miserable, and hopeless. There are endless wars.
• are even worse in the long term. They haven't adequately addressed our most dire problems: climate change, water supply, and (the 900 lb. gorilla) human overpopulation. Unless policies change, it's possible that human civilization may not survive much longer.

Governments have chosen many bad policies: policies that don't accomplish their goals, or that have the wrong goals in the first place, of that provide short-term benefit but do long-term harm (most commonly: maximizing short-term wealth at the cost of long-term environmental disaster).

Various forms of government have been tried: oligarchy, dictatorship, theocracy, monarchy, and variants of democracy. None of these has worked very well. In many countries, governments are run by malevolent dictators, or have collapsed completely. The vaunted U.S. democracy has been subverted by billionaires and turned into an oligarchy. Systems designed 200 years ago have broken down in the presence of concentrated wealth and ubiquitous social media.

As a thought experiment, let's design a new and better form of government - a government that adopts effective policies that achieve good short- and long-term goals, and that resists corruption. Let's not worry about how to get there from here; let's focus on what "there" should be.

Government as optimization problem

In mathematics, an 'optimization problem' is one where we have an "objective function"

f(x1, x2, ... xn)

and we want to find the values of x1 ... xn that produce the largest possible value of f().

Suppose the x1 ... xn are government policies and f() is a measure of societal well-being. We want to find the policies that maximize f(). This is simplistic, but it's a good starting point for thinking about government.

Economic measures like Gross Domestic Product (GDP) are sometimes used as objective functions. But they may have little to do with societal well-being; e.g. most Americans are rich and miserable. In 1972, Bhutan's King Jigme Singye Wangchuck coined the phrase gross national happiness and proposed that policies should be evaluated based on this index. This was not done in a systematic way in Bhutan, but I think he was on the right track.

We need a good objective function. Let's call it "Governmental Figure of Merit", or GFM. GFM must be precise and measurable, and it should arguably approximate "societal well-being" or "happiness".

Defining GFM requires addressing three issues:

• Balancing multiple objectives. Happiness is the end goal but it's hard to measure. In practical terms we need to combine more tangible components: physical and mental health, wealth, crime rate, We also need to include the health of the environment (and of the biosphere as a whole; humans are not the only species). How do we combine these components into a single measure? If we use a weighted average, what are the weights? Do we use ideas from multi-objective optimization?
• Aggregate statistics. Consider a component - say, wealth - that varies between individuals. How do we measure this component for the population as a whole? The mean won't work - we could end up with a few super-rich people and a lot of paupers (kinda like what we have now). We could use a robust statistic like the median, but that could still result in lots of people starving. It comes down to: what fraction of people does the government care about? 1%? 90%? 99.99% We need to pick a number. Not everyone can be rich, but most people should not be poor.
• Time scales. Government policies have effects on multiple time scales. Current energy policies make people rich today, but will have disastrous consequences in 100 years. How do we balance the present and the future? Suppose we can keep 100 people from starving today, but doing so will cause 1000 people to starve in 20 years. Should we do this?

These questions are fundamental: they are the three main dimensions in describing the effects of government. Most "political differences" are, at their core, disagreements over how to answer these questions. E.g., conservatives emphasize the wealth of a minority over a short time scale, while liberals take a broader and longer view.

In the U.S. system, these disagreements resurface (with increasing rancor) in the debate over each and every policy. In scientific government, we answer these fundamental questions once, in a rational way. We don't constantly rehash them. Thus the counter-productive acrimony of current "politics" will hopefully disappear.

Scientific government: summary

Suppose we've agreed on a GFM, and we want to maximize it. How can we design a government that will do this? To this end, I propose what I call Scientific Government. This borrows ideas from science, namely:

The scientific method

In science, theories are judged on the basis of reproducible experiments. Scientific Government selects policies using a similar method. It chooses policies that are shown to work by experiments, rather than ones based on traditional beliefs and prejudices, or the beliefs of individuals, or the economic interests of a minority.

Broad, merit-based organizational structure

Academic science (i.e., science practiced in universities and government research labs) has evolved its own organizational structures. In the U.S., this is a tripartite system consisting of journals, research institutions, and funding agencies. This system has done a good job of enabling and enforcing the scientific method, and has been remarkably resistant to corruption. Power is decentralized, and people gain power (mostly) by being good scientists. It's not completely a meritocracy, but it approximates one. The organizational structure of Scientific Government is inspired by this.

In the U.S., Scientific Government would largely replace the current executive and legislative branches, at the national, state, and local levels. It could eventually form the basis of a (desperately needed) world government.

By the way: when you read "Scientific government", you might jump to the conclusion that I'm proposing turning scientists (like physicists and chemists) into government leaders. That's not the case. Please put that idea out of your mind and keep reading.

Leaders considered harmful*

It's ingrained in us that governments must have "leaders" who make policy decisions for us. (As with religion, this may stem from our psychological need for strong parent figures.) These leaders might - for example - be elected by popular vote. On the surface this model sounds good, but it's flawed. In practice, leaders are chosen on the basis of how they look on TV, how well they orate, and their Machiavellian skills.

So we end up with leaders who are not qualified to make good policy decisions: they don't know much history, economics, sociology, or statistics; they're largely concerned with retaining or increasing their power. It's like having the Pope decide the laws of planetary motion. As Adam Grant points out, the worst people run for office. And when they get power, they're often corrupted by it.

Scientific Government has no leaders of this sort. People (government employees, educated and trained for this role) propose policies, design and carry out experiments, and implement policies. But they do not choose the policies. Policies are selected on the basis of experimental outcomes, not the intuition and prejudice of individuals.

In Scientific Government, power is spread across lots of people. People get power by being (provably) good at their job. The power of any one person is limited. If they stop being good at their job, they lose power.

The scientific method

The scientific method was developed to explain the physical world. It involves several related ideas:

• Instruments that make quantitative measurements, with known precision and error distribution.
• Theories that try to explain measurements, typically mathematically.
• Experiments that use instruments to test theories. Theories are disproven if they fail to predict the result of an experiment. If there is no possible experiment that could disprove a theory, the theory has little value.

New theories may meet resistance: organized religion tries to suppress science that contradicts its belief systems; oil and tobacco companies fight science that threatens their profits. The scientific community itself can form internal power structures that suppress research which threatens dominant paradigms.

The scientific method is designed to resist these pressures. Disproven theories must be discarded, no matter how entrenched and powerful their supporters. The truth - even if there's initially overwhelming opposition to it - eventually wins.

It's worth noting that:

• The scientific method is stable; it's existed with the same basic principles for hundreds or thousands of years.
• Science is the same in all cultures. There is no separate "Bolivian Physics" or "Hindu Chemistry".

The scientific method has been successful in "hard science" domains: physics, chemistry, astronomy, engineering, biology, medicine, and so on. It has converged to universally accepted core theories in these areas.

In other areas - economics, psychology, sociology, humanities - there have been efforts to use the scientific method. The results have been less successful, because in these domains it can be hard to:

• make accurate quantitative measurements;
• design experiments that control for factors other than the one being studied;
• design experiments that don't potentially harm human or animal subjects.

Using scientific methods in government, as I propose, will face all these difficulties. Things will be messy. It won't achieve perfection; there is no perfection. But I think it can do much better than what we have now.

Scientific government: concepts

Science has theories, government has policies. In the same way that science uses experiments to evaluate theories, Scientific Government uses experiments to evaluate policies. The general idea:

1. Define a "governmental figure of merit" (GFM): a quantitative measurement of the short- and long-term health and well-being of society, as discussed above.
2. Propose policy changes intended to increase GFM.
3. Perform experiments that test these policy changes - i.e. that estimate their effect on GFM.
4. Based on experimental results, use the policies that maximize GFM.
5. Repeat 2-4 indefinitely.
6. Redefine GFM as needed.

This was inspired by the documentary Sex, Drugs, and Democracy, which describes the Netherlands' approach to social issues such as sex education, drug use and prostitution. Dutch officials identified figures of merit: the rates of drug abuse, crime, teen pregnancy, STDs, violence against women, poverty, and so on. They experimented with novel policies, such as legalizing and regulating drug use instead of criminalizing it. They found that these policies greatly improved the figures of merit; for many of them, Holland's numbers are the best in the world.

This demonstrates a key capability of experimentation: it can discover good policies that go against societal tradition, or that are counterintuitive.

Sadly, few other countries learned from this success story; American social policies are still rooted in Old Testament principles of punishment and revenge, and often exacerbate the problems they try to solve.

Governmental figure of merit

Let's return to the idea of GFM. GFM should be a numerical measure of how well governmental policies are working. It might be a function of components such as

• Happiness.
• Health (physical and mental).
• Wealth, and its distribution.
• Crime.
• The health of the environment (for humans and other species). This might include biodiversity (species extinction), air and water pollution, and extreme weather.

The definition of GFM must specify how each component is measured. For example, for happiness we'd need to specify

• Which people are included; we might want to exclude infants, people with mental illnesses, etc.
• How do we measure the happiness of an individual? A 1-10 poll? A psychological test?
• How are population numbers aggregated? Suppose 95% of people are very happy and 5% are miserable. Is this better or worse than 100% being somewhat happy?

The definition must then specify how these components are combined. Maybe a weighted average, with a robustness mechanism to ensure that all components are included? Maybe some form of Pareto optimality?

Policies can have different short- and long-term effects. Drilling for oil might increase wealth over 1 year, but cause poverty and death 100 years from now. Assuming that people care about the well-being of their descendants (and their own well-being a decade or two in the future) GFM should reflect long-term policy effects.

We can measure GFM components like health and wealth in the present day. But we can't predict them with any degree of accuracy. However, we can predict environmental factors: climate scientists can predict average temperature increase given the level of CO2 emission, and hydrologists can predict how much water will be available in particular aquifers, given the rate of consumption. So the component of GFM dealing with future effects might be limited to environmental components, and it could be based on the predictions of the best available science.

It could be argued that GFM should have only one component, happiness. Perhaps the other components are all reflected in this, and measuring them separately is counter-productive. This is possible, but measuring happiness is probably noisy compared to other components, making it harder to interpret experiments.

To simplify things, a policy change might focus on a particular objective GFM component, like crime rate. But we need to be careful, because components can interact; e.g. a repressive policy might reduce crime but decrease happiness.

Democratic selection of GFM

GFM defines the goal of government. It defines what sort of society, and world, we want to live in. It's the crux of everything. So, how should it be defined? This is a hard question. I don't have a complete answer; here are some ideas.

Ideally, government gives people what they want; it doesn't tell them what they should want. So the public should decide on the GFM. But not everyone wants the same things; people will have different ideas for how GFM should be defined.

In addition, there could be Scientific Governments at world, country, and state levels. Different instances (e.g. countries) might have different GFMs. But for a given instance there can only be one GFM. So we need a mechanism for picking a GFM that takes peoples' values and desires into account.

Furthermore, peoples' wants may change over time, or an existing GFM may not be working as intended. So we need a way to tweak the definition of GFM.

The obvious thing is to have periodic GFM elections. Each election would have a small number of proposals: changes to GFM components, or the addition or removal of a component, or changes to how components are aggregated. Each proposal would have pro and con arguments, as with the ballot initiatives in existing elections. Each proposal could be decided by simple majority, or by a larger threshold, or by some other criterion.

GFM proposals might come from the government itself (see below). There should also be a mechanism where people can collect signatures to get a proposal on the ballot (though this needs to be controlled carefully).

For the success of Scientific Government, it's critical that the GFM actually reflect what people want, and that the GFM elections not become a conduit for corruption by deception or election-buying.

To this end, there must be some form of campaign-spending limits (though at the same time we want to allow large-scale discussion of proposals; this is tricky).

Furthermore, there must be constraints on how GFM is defined:

• The definition must be simple enough that most people can understand it. If it's too complex, deception will be possible, and also fewer people will participate in the elections.
• Policies can't be directly included in the GFM. For example, it can't have "availability of guns" as a component. If gun proponents think that guns make people safer, they can propose weighting safety more heavily in GFM. Experiments would then decide how changing the availability of guns affects safety, and hence GFM.

The democratic component of the current U.S. government involves voting for candidates and for ballot measures (usually bonds linked to vaguely-defined policies). Both of these are fundamentally flawed. Voting for candidates devolves into identity politics and demagoguery; voting for policies perpetuates bad policies; the public are not policy experts.

In Scientific Government, the democratic component is the selection of GFM. Any society will inevitably have disagreement and debate. One of the goals of scientific government is to move this debate to the highest level - well-defined differences of opinion about what society should be - rather than personalities, identity politics, and propaganda.

Policies and experiments

Once GFM has been established, the general flow of scientific government is:

• Government "Policy scientists" (see below) propose a policy change P.
• An agency made up of policy scientists decides whether it is feasible that P could significantly increase GFM, whether it's possible to design an experiment to prove this, and whether the benefit is likely to justify the costs.
• If so, the government carries out this experiment.
• If the experiment shows that P increases GFM, the policy is adopted (possibly replacing existing policies).

If other countries or societies have adopted P, it may not be necessary to do an experiment; it may be possible to estimate P's effect on GFM from existing data.

There are a number of potential problems in doing social experiments:

• The experiment's subjects may have a prejudice about P.
• It may be hard to control other factors.
• The experiment may create hardship for some of the subjects. But letting people opt out of experiments would undermine them. Scientific government needs global buy-in; people need to be willing to make sacrifices for the common and future good.
• Some policies may not impact GFM right away (or may impact it negatively), but will increase it in 20 years. How to evaluate such policies?

Scientific government must address these issues.

Possible outcomes

Some areas of government policy that might be addressed by the scientific approach:

• Medical care.
• Other potentially socialized services, e.g. car insurance.
• Safety nets: social security, welfare.
• Minimum wage.
• Environmental regulation.
• Anti-trust regulation.
• Foreign trade policy (tariffs).
• Taxation structure.
• Criminal code and penal system.
• Gun control.
• Drug policy.
• Immigration policy.

What policies will scientific government converge to? It's impossible to say. The data will decide - that's the whole point. But my intuition is that the policies will be something like:

• The economic system will be highly regulated capitalism. The regulations will ban or heavily tax sources of external costs (carbon emissions, pollution, resource depletion).
• People will be guaranteed a subsistence-level living (food, housing, medical care) regardless of whether they work. People will have an incentive to work and contribute to society, but those who can't do so won't starve to death. People who work will be guaranteed a living significantly better than subsistence level.
• The wealth of individuals will be capped at a certain level - say $100M. Inheritance will be limited. People will have an incentive to create large, efficient businesses, but they won't become demi-gods.
• The government will use economic incentives to achieve and maintain a target population size.
• Arts and music will be heavily subsidized.

Murder

We can assume that GFM contains terms that favor a low murder rate. What policies are likely to achieve this, and how can they be assessed?

Most people think of this solely in terms of punishment, with the idea that harsher punishment is a deterrent, with capital punishment at the extreme. But some studies suggest that harsher punishments don't result in lower murder rates. Who knows - maybe it works best to give murderers psychotherapy and job training. This may be difficult for some people to swallow.

In any case, I suspect that systemic factors have a vastly larger impact on murder rate than does the choice of punishment. If people don't have economic opportunity, if paths to wealth are criminalized, if mental health care is not freely available, if guns are easy to get - then we're going to have lots of murders, regardless of deterrents.

Scientific government would do experiments involving these causal factors. It would find and fix the reasons why most murders happen.

When there's plane crash, the NTSB investigates it in tremendous detail. They find why it happened - mechanical failure, airplane design, problem with cockpit communication, whatever - and they make recommendations to prevent that kind of crash from ever happening again.

My personal view is most murders are like plane crashes: they reveal a systemic failure of some sort. There should be an NTSB for murders. Each murder should be investigated to find its root causes, and policies to address these causes should be explored.

Abortion

In the U.S., abortion is primarily a wedge issue created by the right wing. Any government in the U.S. needs to address the views of a big chunk of the populace, regardless of how those views got there.

How does the availability of abortion impact GFM? It has been shown that it lowers crime - not surprising, since there are fewer unwanted children. But this doesn't address the concerns of anti-abortionists, who view fertilized ova as being fully-privileged people.

I think what it comes down to is: do the measures of happiness embodied in GFM apply to fetuses? This needs to be specified in GFM. Which means that in scientific government, the abortion issue would be put to a popular vote. Which is about as good as we can do, I think.

Corruption resistance

When a body governs competing entities (like companies), those entities will typically try to get head by circumvent the rules, or by subverting or corrupting the government.

Government systems are often unstable - they don't work as originally designed for more than a few decades. All communist governments have quickly been taken over and transformed into dictatorships or oligarchies. In the U.S., corporations and billionaires have figured out how to buy the electoral process, and have created an oligarchy with the facade of democracy.

The American 'founding fathers' did their best to define a stable system. But they couldn't anticipate that wealth would become so concentrated, that the negative effects of economic activity could be so extreme, and that popular information systems (e.g. Facebook) would become so pervasive and susceptible to corruption.

The U.S. government

In civil government, the sources of corruption are too numerous to list. The most serious is corporate money.

One way to fight corruption is divide government into several parts, and to structure things so that if one part is corrupted, the others can contain and eventually repair it. For example, in the U.S. federal government we have

• The executive branch: the president and federal agencies.
• The legislative branch: Congress.
• The judicial system: the courts.

The government structure has what are called 'check and balances': The president can veto congress, congress can impeach the president, the courts can declare laws unconstitutional, and so on.

This breaks down, of course, if the corrupters infiltrate all the branches simultaneously, as with the current religio-fascist attempted take-over.

The governance of academic science in the U.S.

The "scientific method" described earlier is an ideal. In practice, scientists need money for salaries and equipment. Most modern societies, recognizing the economic value of science, have created organizational structures to support science.

Academic science in the U.S. has its own governance structure, and it's resisted corruption better than the civil government. In the context of science, possible sources of corruption include:

• Creationists try to have their fictional beliefs presented as truth, or as an 'alternative'.
• Corporations use economic subterfuge to suppress research that's contrary to their interests. For example, Monsanto paid $500M for new building for the UC Berkeley biology department, then successfully got them to deny tenure to a professor who studied the spread of Monstanto's Franken-seeds into the wild.
• String theorists commandeered physics for a couple of decades, even after their claims were debunked.

Scientific governance also has a tripartite structure:

• Funding agencies
• Journals and professional organizations
• Research institutions

• Journals publish papers. Papers cite other papers. The number of citations of a paper measures its "impact". The "impact factor" of a journal is the average impact of its papers. A reputation of a scientist is estimated by the number and impact of their publications. Journals are operated by companies and professional societies. Each one has an editor-in-chief and an editorial board, who generally are well-connected scientists with good reputations. When a paper is submitted to a journal, the editor picks a set of reviewers who have expertise in the area. The decision of whether to publish the paper is based on these reviews.
• Research institutions such as universities and research labs provide a framework for training scientists and for conducting research. Hiring and tenure decisions are based largely on publication record, and on reputation in the scientific community.
• Funding agencies (such as the NSF and NIH in the U.S.) fund research. Typically the funding agencies have "program managers", who are academic researchers. They are have limited terms (2-3) years. Decisions about what areas of research to fund - the topics listed in "calls for proposals" - are made by panels convened by the agencies. Grant proposals are reviewed by researchers selected by the program managers. Funding agencies check for conflicts of interest - for example, research that might benefit a company in which the researcher has ownership. The criteria for funding generally emphasize novelty. Other countries have somewhat different structures: for example, Germany has a set of "Max Planck Institutes", each of which receives long-term funding, and each institute has a permanent director. Both the U.S. and German systems have worked fairly well.

The scientific organization has been fairly corruption-resistant - certainly far more so than government. Why is this?

This structure has various checks and balances:

• Meritocracy. It's hard to get a foothold in science without being smart and doing something good and useful. A few charlatans have attained prominence, and a few great scientists became nut-cases later in life, but there have been no Donald Trumps.
• Transparency. Major processes - like hiring decisions at universities and grant proposal decisions - are documented, and these documents are public.
• Power is distributed across lots of people.
• Positions of power - like department chairman and NSF program officer - are held for limited periods.
• The general public is involved only indirectly; riling up the masses via propaganda has little impact on science.

Of course, there have been attempts to corrupt the scientific structure.

• The Koch brothers have undermined climate research by creating a propaganda mill (Fox News) and electing an anti-science president.
• Monsanto has given lots of money to universities in return for power that enabled them to suppress research (e.g. about the spread of genetically engineered corn in the wild) that conflicted with their business goals.
• There is a certain class of academics (I could name a few) who do lousy research, but do just enough of it to get into positions of some power (conference organizing, journal editorship, funding agency activity).

Implementing scientific government

Policy science

Scientific government requires people who are able to reason objectively about policies. Such people may currently exist, but in the long term we need more of them, and better.

To this end, I suggest that a new area of study be established, Policy Science. Policy science is about designing and evaluating government policies. It's an academic area - you can major in it or get a PhD in it - and also a career path (see below).

Policy Science involves several existing areas:

• Statistics
• Sociology
• Psychology
• Public health
• Environmental science
• Economics
• Civil engineering
• Political science

Aside: I'm surprised that Policy Science doesn't already exist.

The structure of scientific government

What are the functions of scientific government?

• Conduct elections for figures of merit. Decide what goes on the ballot. Run elections in such a way that they can't be bought: no advertising? Keep the figures of merit short and simple enough that people can understand them.
• Decide what new policies will be considered.
• Design and conduct experiments, interpret the results of experiments, select winning policies.
• Enforce policies.

How to implement Scientific Government?

What is a plausible organizational structure for Scientific Government? I think a good starting point is to 1) piggyback on the existing organizational structure of science; 2) in extending this to a government, use the same underlying principles: meritocracy, distribution of power, transparency, etc.

Here's a possible structure for scientific government:

• There is a "policy experiment agency" (PEA). It is analogous to a research lab. Its staff includes permanent "researchers", analogous to professors, who have PhDs in political science, statistics, or related fields. Researchers carry out policy experiments and write up the results in research papers, which can be published in peer-reviewed journals. Hiring and promotion of researchers is based on their publication-based reputation.
• There is a "policy decision agency" (PDA). Its task: given a budget for experiments, decide which policy proposals to study. This is a complex problem; proposals may differ greatly in the cost of studying them, and in their potential payoff. The PDA is analogous to a funding agency. It is divided into "directorates" for different policy areas. Each directorate is staffed by rotating "program managers" with limited-term appointments. Program managers can be academics or PEA researchers, and are chosen on the basis of their reputation.
• Anyone (e.g. special interest groups) can policy proposals to the PDA. These proposals are analogous to grant proposals. They are expected to make a compelling argument that the proposed policy would increase GFM, and to outline a plausible experiment that would prove this.
• Proposals are evaluated similarly to NSF grant proposals. The relevant program manager identifies 3-5 blind reviewers (academics or PEA researchers).
• On the basis of these reviews, the PDA decides which proposals to accept. Each accepted proposal is passed to the PEA, where it is assigned to a group of researchers. These researchers design an experiment to test the policy change (usually but not necessarily based on the proposed experiment). They conduct this experiment (which may take months or years) and they write a paper describing the results.
• When the results paper for a proposal has been completed, the PDA reviews it and decides what policy to implement.

In designing the above structure, we need to anticipate various kinds of corruption.

• People in the PDA and PEA may have opinions and prejudices about policies. We need to prevent these from unduly affecting funding decisions, the design and execution of experiments, and the final decisions.
• Special interest groups my attempt to influence the outcome of experiments.

Note: it's possible and desirable that a new academic field of "government studies" arise, which would focus on how to conduct policy experiments. People who want to go into government could major in this.

Self-sizing government

Bloat is general problem of governments. Once an agency has been created, there is no incentive for it to downsize or eliminate itself even if its function becomes irrelevant. This if doubly damaging because it promotes general distrust of government, and the mistaken belief that the less government the better.

Scientific government provides a theoretical basis for deciding how much government is best. GFM will have some component that reflects disposable income. A given policy (or governmental function) costs money, and therefore decreases disposable income. If a policy's net effect on GFM is negative, it should be discarded.

This is analogous to the practice in many corporations of estimating the revenue brought in by each employeed, and firing those whose salary exceeds this.

What about bloat in the mechanisms of SG itself, i.e. in the PEA and PDA? We need a way to estimate how large these agencies need to be in order to do their job well; the reputation system described earlier provides a basis for deciding who to fire.

How can we get there from here?

It's unlikely that scientific government would rise out of the ruins of a completely failed existing government, so we need to think about a continuous transition. This would have to start small; some possibilities:

• A candidate for some office - say, mayor or governor - announces that, if elected, they will use scientific methods rather than relying on prejudices. Or an incumbent starts doing this.
• Identify an area of state or national government policy that's not highly political, and that's amenable to experiments. Set up a small version of the above structure, and use it optimize policy in the area. Maybe when people see how well it works they'll think about expanding the domain.
• A community or small town (of enlightened people) jointly agrees to govern itself scientifically. Their success would spread to other towns and eventually to larger scale.

In any case, scientific government will have a hard time getting started in a society where lots of people hate each other, hate government, are uneducated, and don't understand or trust science. These conditions currently exist in the U.S. So a necessary first step is to reduce these factors in the context of existing government (if that's possible). The number one thing is to improve education and make it universally available.

World government

The most important government issues - e.g. environmental policies - are now global. Dealing with them on a national level doesn't work; no country is willing to drastically reduce its carbon emissions (much less its population) because doing so would place it at an economic disadvantage. For such issues, scientific government at the national level is insufficient, especially if it's adopted only by a few countries.

So we need a global scientific government, whose domain is global issues: resource usage, environment, population, immigration, trade etc.

I'm on the fence about whether the idea of "nation" has any place in the future. Preserving cultural diversity is generally good, but I don't think we need national governments to do it. In any case, national governments can continue to exist separately from the global government, and could determine policies that are internal to that country.

Related work

"Freakonomics" by Dubner and Leavitt examines a number of social-science issues - some big, some small - through a scientific lens. The conclusion is that when you look at data carefully and objectively, you often find surprises.

Nicholas Gruen writes about evidence-based policy. This is the idea that policy-makers in the current elected-leader framework should be expected to provide evidence that justifies their policies. Apparently this has been proposed, and people claim to do it, but it hasn't actually happened. It seems to me it's unlikely to ever happen, or to affect policy decisions, in the current framework.

The V-Dem Institute in Sweden maintains data on governments and their outcomes.

Feedback

I've shown this essay to a few friends. Most of them either didn't actually read it, or dismissed it as quixotic and frivolous. They mostly live in the Bay Area, where climate change isn't a problem (yet). And they're well off. So they don't think of the current state of government as a crisis, like I do. With all due respect, I think their heads are buried in the sand.

Specific feedback:

Dave W. feels that academic scientific governance is not as much of a meritocracy as I make it out to be, and that many funding, hiring, and publishing decisions are political and bogus.

Sabine Hossenfelder (a science YouTuber whom I respect tremendously) says academic science is increasingly producing "bullshit research". Science in in trouble and it worries me.

I agree with both. I think that the corruption occurs in part because the academic science world is artificially inflated. Hundreds of universities are charged with being "research institutions", creating tens of thousands of "research" jobs, and there aren't enough real scientists (or ideas) to go around.

Scientific government ideally wouldn't suffer from this, because it would be only as large as necessary (see above).

My son Noah asks: would Scientific Government fund basic science research, if it doesn't directly contribute to GFM? No. If we want basic research, we need to define GFM to allow it. One way to do this is to observe that historically, basic research leads to beneficial technology after a few decades. Quantum mechanics in the 1930s enabled lasers and microchips in the 1960s. So if we evaluate policies based on their expected long-term effects on GFM, we'd fund basic science. And we'd leave it up to the scientific community to decide what kinds of basic science to pursue, as we do now.

What about research in things like pure math? And what about space exploration? It's hard to argue that these will ever put food on anyone's table. But maybe understanding the universe makes people happy, and would therefore increase GFM.

Noah points out that government has to deal with unexpected short-term issues and crises; for those we need competent leaders who can make good snap decisions (based on intuition, not experiments). True, but outside of the scope of this essay (though some of its ideas apply there as well).

Noah also points out that experimentation means that some people will suffer from sub-optimal policies. True, but this is no different from clinical drug trials. A small amount of suffering during an experiment is better than perpetual and universal suffering because of a bad policy. Also: the size and duration of experiments can be minimized by using modern (Bayesian) statistics.

Ron K. thinks that meaningful experimentation is impossible in social domains. I don't think this is correct. Every real-world government policy is a potential experiment. But current governments typically don't even bother to collect the data, much less analyze it or use it to guide future policies. Scientific Government does all three.

For example, the U.S. "war on drugs" and various "three strikes initiatives" can be viewed as experiments. They caused a huge amount of human suffering, especially among blacks. They produced lots of data, which proved the ineffectiveness of the policies. But this data was ignored, and the policies are mostly still in place.

Several people thought I was proposing putting scientists in charge of government. I can only conclude that they didn't actually read the essay. Perhaps they looked at the title, formed a mental model of what the essay must say, and moved on.

• Introduction
• Government as optimization problem
• Scientific government: intro
• Leaders considered harmful
• The scientific method
• Scientific government: concepts
  • Figure of merit
  • Democratic selection of the figure of merit
  • Policies and experiments
• Possible outcomes
• Corruption resistance
  • The U.S. government
  • The governance of academic science in the U.S.
• Scientific government: implementation
  • The structure of scientific government
  • How to implement scientific government
• How can we get there from here?
• World government
• Related work
• Feedback