A soft science is any academic discipline that studies human behavior, societies, or mental processes rather than physical or natural phenomena. Psychology, sociology, anthropology, economics, political science, and history are the fields most commonly given this label. The term draws a contrast with “hard” sciences like physics, chemistry, and biology, suggesting that soft sciences are less precise, less objective, or less rigorous. That suggestion is controversial, and many researchers consider the distinction misleading.
Where the Term Comes From
The roots of ranking sciences go back to the 19th-century French philosopher Auguste Comte, who arranged all scientific knowledge into a hierarchy. His ordering placed mathematics at the top, followed by astronomy, physics, chemistry, biology, and finally sociology. Each level in this ladder dealt with more complex subject matter than the one below it. Mathematics described the simplest, most universal patterns; sociology tackled the messiest, most tangled ones. Comte didn’t use the words “hard” and “soft,” but his framework planted the idea that some sciences are more fundamental and others are built on top of them.
By the mid-20th century, scientists themselves had adopted the hard/soft shorthand. A common version of the ranking put mathematical, physical, and biological sciences at the top as “hard,” with anthropology, psychology, sociology, economics, history, and their related disciplines further down as “soft.” The language stuck, especially in university settings and funding debates, even though no formal definition was ever agreed upon. The Oxford English Dictionary defines science broadly as “the systematic study of the structure and behavior of the physical and natural world through observation and experiment,” but says nothing about a hard/soft split.
What Makes a Science “Soft”
The label usually points to a few overlapping ideas, though people rarely specify which one they mean.
- Subject matter is abstract. Hard sciences deal with physical things you can hold, weigh, or look at under a microscope: rocks, cells, chemical compounds. Soft sciences deal with concepts like motivation, cultural norms, economic incentives, or emotional development. These are real, but you can’t put them on a lab bench.
- Variables are harder to control. A chemist can isolate a single variable in a test tube and hold everything else constant. A sociologist studying revolution or a psychologist studying grief cannot. As the evolutionary biologist Jared Diamond put it, “A lion hunt or revolution in the Third World doesn’t fit inside a test tube. You can’t start it and stop it whenever you choose.” In many soft science studies, researchers struggle to even decide what counts as a variable, let alone control it.
- Measurement is less exact. Hard sciences can measure outcomes in grams, volts, or wavelengths. Soft sciences often rely on surveys, interviews, open-ended questionnaires, and narrative analysis. Turning human experience into numbers requires judgment calls at every step, and two researchers can reasonably code the same interview differently.
These characteristics don’t mean soft sciences are unscientific. They mean the subject matter is inherently more complex. Diamond argued that soft sciences are often harder than hard sciences precisely because researchers face so many uncontrolled variables and must develop creative methods to work around them.
The Reproducibility Question
One common criticism of soft sciences is that their findings don’t replicate as reliably. Psychology, the soft science with the most replication data, has fewer than 400 published direct, independent replications across the entire field. A 2016 poll of 1,500 scientists by Nature found that 51% believed science as a whole is experiencing a replication crisis.
But this isn’t unique to soft sciences. A systematic comparison by the statistician Larry Hedges found that results from physical experiments were not strikingly more consistent than those from social or behavioral experiments. Physics and biomedicine have had their own high-profile replication failures. The difference is partly one of perception: people expect soft sciences to be less reliable, so failures there confirm the stereotype, while failures in hard sciences are treated as anomalies.
Why Many Researchers Reject the Label
The hard/soft distinction has real consequences. Fields labeled “soft” often receive less funding, less public trust, and less respect within universities. Some scholars argue the terminology should be dropped entirely. One public health researcher writing in Public Health Reports called the hard/soft moniker “vacuous, vapid, complacent, and ultimately counter-productive,” arguing that it discourages collaboration and slows progress toward simply doing good science regardless of the subject matter.
Part of the problem is that the boundary is blurry. Neuroscience uses brain imaging and molecular biology, but studies the mind. Behavioral economics uses controlled experiments and mathematical models, but studies human decision-making. Epidemiology collects hard biological data to answer questions about populations and behavior. Many modern fields sit squarely in the middle, making the binary label feel increasingly outdated.
How Soft Sciences Shape the Real World
Whatever you call them, these disciplines have enormous practical influence. Behavioral economics research has reshaped how governments design public programs, from retirement savings plans that use default enrollment (a psychological nudge) to school choice mechanisms that match students with schools more efficiently. Research on matching markets, originally an economics concept, now underpins the system that assigns medical residents to hospitals across the United States.
In the private sector, the skills developed in soft science programs feed directly into industries like banking, insurance, market research, human resources, and data consulting. Psychology graduates work as UX researchers testing how people interact with apps and websites. Sociology and anthropology graduates advise companies on consumer behavior, organizational culture, and ethical data use. Economics graduates move into finance, policy analysis, and management. The demand for people who can systematically study human behavior has only grown as technology companies collect more data about how people think and act.
Soft Science vs. Hard Science at a Glance
- Typical subjects: Soft sciences study people, societies, and economies. Hard sciences study matter, energy, and living organisms at a biological level.
- Primary methods: Soft sciences lean on surveys, interviews, observational studies, and statistical modeling. Hard sciences lean on controlled experiments, direct measurement, and laboratory analysis.
- Variable control: Soft sciences work with many interacting variables that are difficult or impossible to isolate. Hard sciences can often test one variable at a time.
- Data types: Soft sciences frequently work with words, narratives, and self-reported data alongside numbers. Hard sciences typically work with physical measurements.
The distinction is a spectrum, not a wall. Fields like cognitive neuroscience, biopsychology, and computational economics blend methods from both sides. As research tools grow more sophisticated and interdisciplinary work becomes the norm, the line between hard and soft continues to blur.