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What Differentiates Social Sciences?

Sukhayl Niyazov
The World Times
Published in
27 min readFeb 20, 2020

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How do you tell a communist? Well, it’s someone who reads Marx and Lenin. And how do you tell an anti-communist? It’s someone who understands Marx and Lenin. — Ronald Reagan

Ronald Reagan’s words illustrate reflexive fallibility, a framework for explaining the problems inherent in social disciplines. He gives an example of a theoretical construct: communist dogma with its historicist belief in the inevitable triumph of the proletariat revolution. The quotation alludes to human fallibility, personified by intellectuals ranging from Karl Marx and Friedrich Engels to Vladimir Lenin and Mao Zedong, with their different interpretations of communism. Finally, Reagan indirectly invokes reflexivity, the process whereby perceptions of reality influence what actually happens. Anti-communists understood Marx, not only by comprehending the theory expressed in Das Kapital, but by undertaking actions that rendered Marx’s predictions invalid.

By implementing social democratic policies in the wake of the Great Depression, anti-communists precluded a communist revolution in the West by improving the living conditions of the working class and thus luring the communists’ core base to less radical, mainstream parties. Marx’s forecast was reflexive: people’s comprehension of reality brought about changes in the actual state of affairs, and, in particular, eradicated the underlying conditions necessary for the emergence of a revolutionary working class.

Social sciences, such as economics, and their close relatives in the humanities, politics and philosophy, are the backbone of contemporary societies. They provide a robust framework for managing human affairs, fighting the tide of entropy and overcoming the challenges of modernity.

Even though empirical findings from economics and political science have been quintessential to facilitating the unprecedented progress that has lifted billions out of poverty, social disciplines suffer from serious underlying limitations. These problems are inevitable because, unlike the natural sciences, the social sciences study events with thinking participants.

The implications of this are profound. The distorting effects of theoretical constructs, fallible human thinking and reflexivity cumulatively contribute to a discrepancy between reality and people’s interpretation of reality. This is the root cause of many of our problems. It is hard to devise precise, data-driven and evidence-based solutions because reflexive fallibility hampers our understanding.

I have modified George Soros’s theory of reflexivity to create a framework I call reflexive fallibility, which shows how social disciplines differ from the natural sciences. The model has three main tenets:

  1. Theoretical constructs. The constructs are incapable of providing a full picture of reality. Statistics, paradigmatic assumptions, comparisons, generalizations and other constructs misrepresent the world. Since most people assume that constructs present true information, some contemporary debates are based on flawed premises.
  2. Fallibility. The implementation of theoretical constructs yields facts. Facts are interpreted differently by each individual, and, since humans are fallible, almost no view can claim to be absolutely right and go unchallenged. While the multiplicity of opinions is a critical pillar of open societies, when people remain firmly attached to their opinions, rather than collaborating to reach the truth, the resulting lack of consensus contributes to polarization, partisanship, government gridlock and the fragmentation of society into political tribes.
  3. Reflexivity. In situations in which people not only analyze the world but act on the basis of the knowledge acquired, a self-reinforcing loop forms, whereby perceptions of reality lead to decisions which, in turn, affect the actual course of events. The subsequent changes to reality then result in decisions that alter reality further, and so on, in a self-reinforcing cycle. Reflexivity is the reason for the formation of financial bubbles and social scientists’ inability to make reliable predictions, but it is also a crucial factor in an open society’s ability to successfully navigate into the future and prevent ominous forecasts from coming true.

This uncertainty inherent in the social sciences — the divergence between reality and perceptions of reality — hinders our ability to attain the truth.

How can we address the underlying weaknesses of social disciplines like economics, politics and political science and make them more certain and definitive, more like the natural sciences, if possible?

TABLE OF CONTENTS

I. THEORETICAL CONSTRUCTS: ASSUMPTIONS IN THE WOODWORK

II. FALLIBILITY: TOO MANY OPINIONS, NOT ENOUGH SOLUTIONS

III. REFLEXIVITY: IN PURSUIT OF CERTAINTY

IV. SOLUTIONS: REACHING FOR THE TRUTH

V. APPENDIX: TABLE AND MODEL

VI. REFERENCES: BOOKS, RESEARCHES, REPORTS AND ARTICLES

Photo by Giammarco Boscaro on Unsplash

I. THEORETICAL CONSTRUCTS: ASSUMPTIONS IN THE WOODWORK

Most of the change we think we see in life is due to truths being in and out of favor. — Robert Frost

The difficulty lies not so much in developing new ideas as in escaping from old ones. — John Keynes

People utilize theoretical constructs to better understand the world. These include statistics, indicators, paradigmatic assumptions, similes and generalizations. Constructs are imaginary: they are created by humans, to help us model and understand the world. Theoretical constructs are assumptions that are deeply ingrained in human thinking.

The human brain is incapable of processing vast economic and political processes, in which millions of transactions and interactions occur at every moment. Constructs simplify understanding of our complex world, yet this simplification comes at the expense of accuracy. By covering only certain aspects of reality constructs can twist our perception of the real world.

The main problem with theoretical constructs is that their assumptions can prove unfounded. Flawed constructs can send the course of debates in the wrong direction and provide a basis for misguided actions. For example, politicians boast about their country’s performance based on GDP, while economists argue over the best way to increase GDP, even though a rise in GDP is not always accompanied by an increase in human well-being. It is doubtful that more money actually brings more happiness. Many politicians are focusing on reducing inequality, in spite of the fact that it may not even have increased over the past several decades.

Statistics

Statistics is the most widely utilized theoretical construct. As Hans Rosling has said, “Data allow your political judgments to be based on fact, to the extent that numbers describe realities.”

There are often enormous variations in the ways in which economists estimate the state of the economy. Some of these encourage flawed policy proposals. For example, as the Economist notes,

Estimates of inflation-adjusted median-income growth in America in 1979–2014 range from a fall of 8% to an increase of 51%, and partisans tend to cherry-pick a figure that tells a convenient story. The huge variation reflects differences in how you treat inflation, government transfers and the definition of a household, but the lowest figures are hard to believe.

The Economist therefore suggests that inequality numbers could be lower than most people think.

The infamous US debt clock shows a figure of more than $23 trillion, which is more than the country’s entire GDP. Many media sources cite this number. Yet these statistics ignore the almost $6 trillion of intragovernmental debt, the money government agencies owe each other. Yet borrowing from your brother or sister will not increase your family’s overall debt. So the US debt is overstated by $6 trillion. The Congressional Budget Office, the Council on Foreign Relations, and other respected organizations take this into account in their calculations, but untrue narratives are spread by less credible media sources.

When estimating America’s trade balance, the US Census Bureau only counts cross-border trade. By this measure, the US is running at a trade deficit of approximately $600 billion each year. However, if we also consider the overseas sales of American multinationals, “the U.S. had a ‘surplus’ of $1.7 trillion in 2016 — three times larger than the U.S. trade deficit of $502 billion that year.” The possible lack of a US trade deficit suggests that trade wars might be pointless.

Conservatives cite facts to argue that we should not prioritise tackling inequality because it has not increased by as much as liberals claim. Liberals, in turn, refer to another set of facts to back up their opposing views.

Economists likewise disagree on how to reduce the US trade deficit and whether the US should have a trade deficit at all. Meanwhile, it is possible that the so-called trade deficit might not even exist in the first place.

Indicators

Almost every government seems to be obsessed with raising GDP, which is supposedly the best way to advance human wellbeing. While it is true that a rise in GDP is often associated with improvements to other significant aspects of human life, it does not always lead to a rise in human happiness (even if we assume that happiness is both measurable and desirable). American GDP rose tenfold from the 1950s to today, but Americans are even unhappier than they were in the past.

There is a growing disconnect between human wellbeing and GDP. Using GDP as a proxy for progress can distort our policy priorities. As the Stiglitz-Sen-Fitoussi report puts it, “[w]hat we measure affects what we do.”

GDP does not account for the tremendous benefits the digital economy provides (Google and Facebook are free). GDP rises even when economic growth causes environmental degradation. A growth in GDP can increase inequality. If an earthquake hits and rebuilding is required, GDP increases, even though we would surely be better off without the earthquake.

GDP is just a number: it does not accurately reflect underlying conditions. It directs our attention only to particular aspects of reality. GDP is a means to an end, not an end in itself.

Paradigms

Paradigms — or, as economist Kaushik Basu calls them “assumptions in the woodwork” — are so deeply integrated into our thinking that we are often unaware of them. As philosopher Thomas Kuhn, the coiner of the term paradigm, has pointed out, “we see the world in terms of our theories” and “the answers you get depend on the questions you ask.”

One of the most influential paradigms of the modern era is neoliberalism, the economic ideology that promotes free markets, deregulation, lower government spending, etc. But, like many other paradigms, neoliberalism, as Joseph Stiglitz has put it,

imposed an intellectual orthodoxy whose guardians were utterly intolerant of dissent. Economists with heterodox views were treated as heretics to be shunned, or at best shunted off to a few isolated institutions.

Pioneered by Ronald Reagan in the US and Margaret Thatcher in the UK, neoliberalism represented a sharp break with the Keynesian consensus of the past, a response to Keynesianism’s inability to tackle the stagflation of the 1970s. Neoliberalism and its accompanying globalization managed to spur strong economic growth through the 1980s and beyond, lifting hundreds of millions of people out of poverty all around the world.

But, just like any other paradigm, it faced its moment of truth — the 2008 global financial crisis discredited the ideology, leaving a void to be filled by other paradigms.

One of the ingrained assumptions of neoclassical economics, on which neoliberalism is based, is a faith in the rationality of market players, as exemplified by theories like the theory of rational expectations, the market efficiency hypothesis and perfect competition. As a result, when the housing bubble began to form, authorities took few steps to stop it, because they believed that prices represented actions undertaken by rational participants, who drew their conclusions from analysis of available information. The bubble burst, and so did neoliberal dogma, while the economy plunged into the worst crisis since the Great Depression of the 1930s.

Thinking within the safe boundaries of a paradigm enables scientists to base their work on allegedly true assumptions. In economics, the assumption of human rationality allows for the creation of beautiful mathematical models — which are often completely detached from reality. Nassim Nicholas Taleb gives an interesting example of this phenomenon in Antifragile:

There is an anecdote about Professor Triffat (I am changing the name because the story might be apocryphal, though from what I have witnessed, it is very characteristic). He is one of the highly cited academics of the field of decision theory, wrote the main textbook and helped develop something grand and useless called “rational decision making,” loaded with grand and useless axioms and shmaxioms, grand and even more useless probabilities and shmobabilities. Triffat, then at Columbia University, was agonizing over the decision to accept an appointment at Harvard — many people who talk about risk can spend their lives without encountering more difficult risk than this type of decision. A colleague suggested he use some of his Very Highly Respected and Grandly Honored and Decorated academic techniques with something like “maximum expected utility,” as, he told him, “you always write about this.” Triffat angrily responded, “Come on, this is serious!”

Paradigmatic thinking is damaging because it limits creativity and innovation; paradigms are grand, all-encompassing theories, but the world is too complex to be explained by a single theory.

Since paradigms always replace one another, no single paradigm can lay claim to revealing the ultimate truth. Consequently, thinking within paradigmatic frames inevitably leads to imperfect conclusions and policies.

Comparisons

People love to use comparisons to better model and understand events. Such an approach can be fallacious. Comparisons are rarely able to encompass the sheer complexity of social events. Projecting the lessons of the past onto the present and future, while useful in specific circumstances — when the effects of other variables can be disregarded or easily taken account of — can be misguided. Social events, unlike natural phenomena, do not unfold in accordance with universal laws, because they involve humans, whose constantly changing perceptions of reality considerably alter the situation itself.

For example, there is a growing media consensus that contemporary US–China relations resemble US–USSR relations during the Cold War. However, there are more differences than similarities between the two. Such a way of thinking might lead to dangerous self-fulfilling prophecies.

Generalizations

Generalizations are conclusions drawn from analysing several instances of a phenomena. Though proofs by example are effective in the natural sciences and mathematics, this is not the case in social disciplines because of the sheer complexity of the world and phenomena known as black swans.

For instance, even if there is a correlation between A and B, this does not imply that A is caused by B, because, in complex situations, A is affected not only by B but also by C, D, E, etc. Economics and politics study events involving many factors, and very often we perceive only the most obvious chains of causation. For example, most economists seem to agree that the US trade deficit is caused by low savings rates among Americans, despite powerful counterarguments that the deficit is the result of the dominance of the US dollar.

Economists still cannot derive a formula for robust and stable economic growth, in part because it is affected by too many variables and too many complex interdependencies and interrelationships. As the winners of the 2019 Nobel Prize in Economics, Abhijit V. Banerjee and Esther Duflo, write in Foreign Affairs,

at a more fundamental level, these efforts to discover what causes growth make little sense. Almost every variable for a given country is partly a product of something else. Take education, one factor positively correlated with growth. Education is partly a function of a government’s effectiveness at running and funding schools. But a government that is good at doing that is probably good at other things, as well — say, building roads. If growth is higher in countries with better educational systems, should the schools that educate the workforce get credit, or the roads that make trade easier? Or is something else responsible? Further muddying the picture, it is likely that people feel more committed to educating their children when the economy is doing well — so perhaps growth causes education, and not just the other way around. Trying to tease out single factors that lead to growth is a fool’s errand. So, by extension, is coming up with corresponding policy recommendations.

Another problem with generalization is the existence of black swans — unpredictable, rare and undirected events with dramatic consequences. Generalizations are conclusions based on many instances of a particular phenomenon, and they are unable to account for black swans, which set a new precedent rather than represent a continuation of a past trend. Nassim Nicholas Taleb cites World War I, the dissolution of the USSR, the 9/11 attacks and the rise of the Internet as examples of black swans. Generalization models dismiss black swans as outliers. This severely limits our ability to prepare for and cope with them.

Photo by David Gavi on Unsplash

II. FALLIBILITY: TOO MANY OPINIONS, NOT ENOUGH SOLUTIONS

There are no facts, only interpretations. — Friedrich Nietzsche

A variety of opinions is not enough to create democracy; if separate factions adopt opposing dogmas the result is not democracy but civil war. — George Soros

Not only is our understanding of the world impaired by the limitations of theoretical constructs, but even the faulty information constructs provide is perceived differently by each individual.

With most important societal issues, our chief concern should be lack of consensus. However, for issues that elicit little to no disagreement, such as whether we should fight poverty, famine and war, the main challenge is the effective implementation of policy. And, as the history of human progress demonstrates, solutions are possible when the appropriate resources are available.

Even if we correctly determine the level of inequality, some will say it is a dire threat, while others will regard this as a delusion. Should we prioritize tax cuts or government spending? Is it better to use force or diplomacy in international relations? Should we reduce government debt?

The Fall of Consensus Democracy

Each individual has a unique method of processing incoming information, determined by character traits and personal biases and prejudices. That is why we seldom encounter consensus on societal issues. And it is very hard to find out who is right since human fallibility in analyzing information makes the pursuit of truth difficult.

Our failure to resolve most contemporary issues is the result of our inability to discover and agree on definitive, evidence-based solutions. Instead, we are mired in the endless, pointless politicized debates that result from differing interpretations of reality.

In the modern west, society has been fractured into identity groups and political tribes, locked into their respective ideological frames. On almost all fundamental social issues, society seems to be more divided than ever before. Opposing factions not only do not engage in rational discourse, but disagree on what they should even be talking about.

Not so long ago, the leaders of the west were not polarizing ideologues blindly pursuing their party’s agendas, but representatives of a societal consensus on basic issues, such as how foreign policy should be conducted and what constitutes good government. Bill Clinton in the US, Tony Blair in the UK, France’s Jacques Chirac and Germany’s Gerhard Schröder pioneered this so-called third way consensus.

When people divide into camps, instead of political arguments and reasoned deliberation process we have competition between ideologies, paradigms, dogmas and doctrines.

The Case for Open Societies

All theories that claim universal validity are flawed. In social disciplines, universally applicable laws are practically impossible to formulate. Most modern politicians’ primary aim is not the pursuit of truth but the pursuit of power, often through manipulation and outright deceit. Elections today, instead of forging a national consensus, only deepen existing social and political fissures.

A multiplicity of opinions is quintessential to the proper functioning of open societies. However, the ultimate aim should be a search for the truth, not entrenchment in one’s own beliefs and the imposition of such beliefs on others. The truth exists, but it is difficult to attain because people interpret the world differently. By considering all opinions and handling disagreements through dialogue, we can find effective solutions to our problems.

Social media has accelerated the fragmentation of society into political tribes, by segregating users into information bubbles: digital ghettos, where, due to personalization algorithms, people’s own beliefs are constantly confirmed and reinforced, because of their limited exposure to differing perspectives. As Francis Fukuyama had observed in Identity “[social media] connected like-minded people with one another, freed from the tyranny of geography” and “permitted them to communicate, and to wall themselves off from people and views that they didn’t like, in ‘filter ‘bubbles.’” Nowadays, we are exposed to many opinions on almost all issues, from both experts and the general public. This not only undermines trust in experts, but makes it more difficult to reach compromise and makes ordinary people more susceptible to populist rhetoric.

Most people are more likely to engage with emotive, sensational information that instills extreme feelings of hatred, admiration or fear, while finding balanced and impartial analyzes boring — as the popularity of fake news demonstrates. After the Brexit vote, eminent biologist Richard Dawkins observed in the Statesman that “ignorant voters like him” should not have been entrusted with the fate of the country: “you might as well call a nationwide plebiscite to decide whether Einstein got his algebra right, or let passengers vote on which runway the pilot should land.”

It is highly unlikely that we can transform contemporary democracies into the kinds of open societies Karl Popper envisioned, for it is very difficult to fight against human nature. A truly open society would be free from the harmful effects of political polarization and partisanship — effects that are the inevitable consequences of human nature.

Photo by M. B. M. on Unsplash

III. REFLEXIVITY: IN PURSUIT OF CERTAINTY

Those who have knowledge, don’t predict. Those who predict, don’t have knowledge. — Lao Tzu

An economist is an expert who will know tomorrow why the things he predicted yesterday didn’t happen today. — Evan Esar

One intrinsic shortcoming of social disciplines is their inability to make reliable predictions. Natural sciences deal with events that occur independently of what people think about them. In natural sciences, people are only observers: human perception does not affect reality. Observing the movements of the stars and making statements about them will never change the actual behavior of the stars.

But if an economist announces the discovery of the laws by which business cycles and financial markets work and publishes them in an academic journal, the economy itself will change, since the players will respond to the new information, ultimately rendering the laws irrelevant.

An analysis by the IMF’s Prakash Loungani has revealed that economists failed to predict 148 of the past 153 recessions. Reflexivity is the reason for this inaccuracy.

George Soros’s theory of reflexivity is based on the following tenets:

  1. Our understanding of the world in which we live is inherently imperfect.
  2. Imperfect understanding gives grounds for deluded actions.
  3. Actions, in turn, change the situation.
  4. Changes in the situation result in changes in people’s views of reality.

And so on in a self-reinforcing loop.

There are many examples of reflexivity in the economy and financial markets.

Reflexive Events

People with different political views perceive the economy differently. For staunch Trump supporters, the economy is performing magnificently and there will be no recession in 2020. For Democrats, the economy is in poor condition and a recession is likely.

A Trump supporter and a Democrat will therefore make different investment decisions. The Democrat will invest most of her portfolio in safe government bonds, whereas the Trump supporter will invest in the riskier but more profitable stock market (let us assume that rationality demands a 50/50 split between bonds and stocks). As a result of their actions, the prices of both assets will diverge from the rational equilibrium point.

When this occurs on the scale of millions of participants, the resulting distortions can be considerable, especially when what Nobel laureate Robert Shiller calls narratives spread. Flawed narratives have contributed to economic crises, including the Great Recession (neoliberalism) and the Great Depression (laissez faire) and play a major role in determining the course of events.

Fears of a recession can induce a recession, because businesses and consumers will cut back on spending and investment, thereby lowering demand and forcing companies to lay off workers because of falling profits, and so on, in a vicious cycle.

On the other hand, optimism and faith in a stable future will lay the grounds for a booming economy. In US economy, according to Robert Shiller, the “bullish Trump effect” has been empowering citizens to spend more, thus driving up overall demand and generating the longest economic expansion in America’s history, in spite of trade wars and other risks to the global economy.

Reflexive Predictions

Reflexivity affects predictions as well, as this article explains. If a meteorologist predicts rain so you grab an umbrella, you will not thereby affect the weather. But if an economist forecasts that inflation will be 4% next year, workers’ unions will demand that wages are raised by at least 4%. The increase in wages will lead to a growth in demand, higher prices and hence inflation. Inflation is now likely to rise by more than 4%. A forecast changes the fundamentals from which it is derived.

This is why, until Paul Volcker became chairman of the Federal Reserve, the US failed to rein in its inflation — expectations of higher inflation led to more inflation, in a self-reinforcing cycle.

The same applies to political forecasts. If someone predicts that candidate A will win against candidate B, some of A’s supporters, complacent that A will win, might not show up at the voting booths. The inaccuracy of the polls on Brexit and Trump is proof that precise political predictions are problematic.

The Need for Reflexivity

The process of human development reacts to predictions made about it. Marx’s ominous forecasts of a communist revolution did not come true because his prediction led to the changes in behavior: western governments undertook steps that improved the condition of the working class, thereby stifling potential uprising by peaceful means.

For many years, we have managed to invalidate the gloomiest of forecasts: we did not face a shortage of oil or other energy sources, full-scale global nuclear war did not occur, massive famines and disease outbreaks did not kill half of humanity, machines have not yet replaced humans, etc.

This is because negative predictions engender discussions of how to tackle future problems. The predictions hence become irrelevant because we change the course of events and the fundamentals on which the original forecast was based. Reflexivity is the reason why we have overcome so many seemingly impossible challenges.

This phenomenon is similar to what historian Yuval Harari calls the paradox of knowledge: by definition, knowledge that does not lead to changes in behavior is useless, but knowledge that does change behavior quickly loses its relevance. History rapidly alters course as a result of changes to our actions and the knowledge acquired soon becomes outdated.

Don’t Call Them Sciences

This indeterminacy, the discrepancy between reality and our perception of it render social disciplines unlike true sciences. Political science and economics are incapable of providing deterministic explanations and predictions.

As Nobel laureate Paul Samuelson has remarked, “economics has never been a science.” Bill Gates has also noted that “economists do not actually understand macroeconomics” in the way that physicists understand nature. Robert Shiller agrees that there is some truth to this claim.

The ground is always shifting under social scientists’ feet. As Robert Skidelsky has noticed, “it is the changeability of the object being studied that demarcates social sciences from natural sciences.” We cannot precisely estimate and predict dramatic swings in consumer sentiments, nor how forecasts themselves affect the reality we seek to understand.

Social scientists prefer to eliminate reflexivity from their theories because it introduces an incalculable degree of uncertainty that will render their work of little to no value. Most classical economic models assume that humans are rational utility maximizers, but this is not true. Economists’ unwillingness to recognize the inherent limitations of economics is part of the current paradigm. People have limited data-processing capacity, and thus our behavior is not that of rational actors analyzing all available information. On the contrary, people make decisions based on the information they select, which makes their view of reality — and hence their decisions — imperfect. Expectations play a paramount role in shaping economic outcomes.

The emerging field of behavioral economics, pioneered by Robert Shiller, Richard Thaler, Daniel Kahneman and others, aims to generate a more accurate understanding of human behavior. But behavioral economics, while admitting the mistaken assumptions of the dismal science, still finds it difficult to provide deterministic explanations and predictions.

Reflexivity conceals the truth about the state of the world. If we want to make better forecasts, we will have to find ways to measure the effect of human thinking on events.

Photo by Greg Rakozy on Unsplash

IV. SOLUTIONS: REACHING FOR THE TRUTH

As a technologist, I see how AI and the fourth industrial revolution will impact every aspect of people’s lives. — Fei-Fei Li

What we need and what we want is to moralize politics, not to politicize morals. — Karl Popper

The three fundamental shortcomings of social disciplines can be addressed as follows:

  1. Theoretical constructs. Big Data and AI (esp. machine learning) could be leveraged to correct the flaws of statistics. Freedom of opinion is essential to breaking paradigms, while a recognition of the limitations of generalizations, indicators and comparisons will help us better understand the world.
  2. Fallibility. The use of AI in politics to complement or maybe even replace the process of human decision-making will promote an open society, facilitate the pursuit of the truth and reduce polarization and government gridlock.
  3. Reflexivity. Decentralization will make predictions unnecessary, since the system will be robust enough to sustain any shocks.

The AI Revolution

Artificial intelligence could help scientists overcome these seemingly insuperable hurdles, bringing social disciplines more in line with the hard sciences, such as physics.

The advent of AI will mark a turning point in the history of social disciplines by alleviating the consequences of uncertainty, the disjunction between reality and human perception of it. This will bring us closer to attaining truth and help put an end to endless political debates.

Statistics have limitations, but AI, capable of analyzing tremendous amounts of data, will not limit itself to particular facets of reality but provide a more comprehensive and objective overview. Powered by AI, economists’ datasets will no longer be limited by the amounts of material their research assistants can handle, to paraphrase one economist. Using AI and Big Data, scientists will be able to spot otherwise indiscernible patterns, trends, chains of causation, etc.

Richard Feynman once said that

you don’t know the rules of the game, but you’re allowed to look at the board from time to time, in a little corner, perhaps. And from these observations, you try to figure out what the rules are.

AI will allow us to take a look at the board of reality as a whole, rather than only certain parts of it.

In fact, in the long run, AI might even actualize Nietzsche’s concept of the Übermensch. AI will not suffer from the problems of human thinking and will have a superior ability to judge events and resolve all issues with certainty and objectivity. This is unlikely to happen in the near term, but, given current advances in biotechnology and artificial intelligence, it is by no means impossible.

AI algorithms are not susceptible to ideological constraints, prejudices, biases and logical fallacies; they will allow us to pursue evidence-based policymaking. As I write in Human Events, “instead of relying on personal experience, irrational instincts, misguided dogma, or harmful biases and prejudices, decision-makers could rely on data and A.I. algorithms.”

As Daniel Esty and Reece Rushing point out,

Policymaking, as it currently stands, can be like driving through a dense fog in the middle of the night. Large data gaps make it difficult to see problems clearly and chart a course forward …

New information technologies make possible — and affordable — a series of monitoring opportunities, data exchanges, analytical inquiries, policy evaluations, and performance comparisons that would have been impossible even a few years ago …

By more effectively harnessing these technologies, government can begin to close data gaps that have long impeded effective policymaking. As problems are illuminated, policy-making can become more targeted, with attention appropriately and efficiently directed; more tailored, so that responses fit divergent needs; more nimble, able to adjust quickly to changing circumstances; and more experimental, with real-time testing of how problems respond to different strategies. Building such a data-driven government will require sustained leadership and investment, but it is now within our reach.

Importantly, the advent of AI might reinstate direct democracy. Candidates are beginning to utilize AI to conduct Big Data research into voter preferences, thereby enhancing the democratic process and increasing the bandwidth of communication between the electorate and politicians.

Ultimately, AI might help reduce polarization and political tribalism, forging consensus by combining and balancing differing perspectives and providing evidence-based and data-driven policy suggestions.

Aknowledging the Limitations of AI

Without doubt, AI is not a panacea. While AI will be the key to tackling the social sciences’ fundamental problems, there are some unsolvable impediments that result from the fact that humans are thinking participants.

We must learn to estimate the impact of the public’s subjective perceptions on the actual state of affairs and determine a true point of equilibrium that is not defined by humans’ irrational actions. We must study reflexivity, and explore both the dangers of self-fulfilling prophecies (in inducing recessions, for example) and the possible benefits (for example, in preventing the appearance of dangerous financial bubbles).

But, even if a brilliant economist precisely predicts a recession, his prediction may cause the recession itself, because consumers and businesses will reduce their spending and hence provoke a fall in demand and induce an economic downturn. Consequently, even accurate predictions can lead to major policy shifts that will, in turn, result in changes that render the prediction useless. Reflexivity cannot be eliminated: it is an inherent feature of human events.

Antifragile, Decentralized and Reflexive

The present is too different from the past for us to be able to make truthful predictions. And forecasters rarely, if ever, discern black swans, which are bound to occur sooner or later. The worst event in history has always been preceded by a previous worst event that we initially thought would never be repeated (remember that the First World War was called the war to end all wars). Nothing can safeguard us from the appearance of outliers.

It is unlikely that we will be able to make efficient forecasts anytime soon. As Nassim Nicholas Taleb has remarked, “[w]hat is nonmeasurable and nonpredictable will remain nonmeasurable and nonpredictable”.

Thus, we must create a system that does not need predictions. Instead of trying to predict the future, we should focus on making forecasts irrelevant.

Society should be antifragile and decentralized. Decentralization means that, in case of a disaster, the probability of the whole system collapsing is much lower because the negative effects are distributed among many actors. Antifragility means that the system is not only robust enough to sustain dramatic, unpredictable changes but benefits from shocks by learning to adapt to changing conditions and getting rid of weak players during turbulent times.

Reflexivity is the reason why we have been able to curtail undesirable developments. There is no point in making predictions since most forecasts will not come true, as the discussion of a disastrous possible future scenario usually fuels reforms that prevent the unwished-for course of events.

Great Changes Begin From Within

Just because social disciplines are imperfect, we should not stop relying on expert opinion. Social disciplines are faulty, but not useless. They have played a paramount role in human flourishing. We should do our best to correct their deficiencies, while capitalizing on their strengths.

But we must do our best to change ourselves. Unless we alter the standards of political discourse, we will never be able to effectively overcome threats to humanity. Effective proposals will get stymied by partisanship and polarization. We should also heed Harlan Ellison’s wise remark: “You are not entitled to your opinion. You are entitled to your informed opinion. No one is entitled to be ignorant.”

An open society depends on its members’ recognition of their fallibility and on their readiness to accept opposing perspectives and the willingness to seek consensus.

Don’t argue to prove that you are right; engage in argumentative discourse with reasonable opponents to pursue truth. Don’t remain attached to a single ideology: dogmas are wrong, for they are too all-encompassing to be able to correctly reflect all aspects of our multifaceted world. Instead, seek to be balanced and fair.

Rely more on data (while ensuring it reflects the truth), since the data is objective and impartial and is not prone to human fallacies and biases. That’s the only way for us to save the free world and successfully guide human society into the future.

V. APPENDIX: TABLE AND MODEL

Implementing the Model of Reflexive Fallibility in the Real World

Credit: Author

Model of Reflexive Fallibility

Credit: Author

VI. REFERENCES: BOOKS, RESEARCHES, REPORTS, AND ARTICLES

Books

  • Basu, K. 2010. Beyond the Invisible Hand: Groundwork for a New Economics.
  • Fukuyama, F. 2018. Identity: The Demand for Dignity and the Politics of Resentment.
  • Harari, Y. 2016. Homo Deus: A Brief History of Tomorrow.
  • Kahneman, D. 2011. Thinking, Fast and Slow.
  • Popper, K. 1945. The Open Society and Its Enemies.
  • Shiller, R. 2019. Narrative Economics: How Stories Go Viral and Drive Major Economic Events.
  • Skidelsky, R. 2018. Money and Government: The Past and Future of Economics.
  • Soros, G. 1987. The Alchemy of Finance: Reading the Mind of the Market.
  • Soros, G. 2008. The Crash of 2008 and What it Means: The New Paradigm for Financial Markets.
  • Taleb, N. 2010. The Black Swan: The Impact of the Highly Improbable.
  • Taleb, N. 2012. Antifragile: Things That Gain From Disorder.

Researches and reports

  • An, Z., Jalles, J. and Loungani, P. 2018. How Well Do Economists Forecast Recessions? IMF.
  • Stiglitz, J., Sen, A. & Fitoussi, J. 2009. Report of the Commission on the Measurement of Economic Performance and Social Progress. CMEPSP.

Online articles

Originally published in Areo Magazine

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Sukhayl Niyazov
The World Times

Written by Sukhayl Niyazov

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