1.2 Shared Reality and Modeling

Science is grounded in belief in a common, shared reality with some degree of regularity.

The Lesson in Context

In this lesson, we lay the philosophical groundwork for future topics by establishing a common set of assumptions and attitudes in science, namely, that the world is full of regular patterns that can be studied empirically, and that scientific knowledge is constantly evolving in light of new evidence.

1.1 Introduction and When Is Science Relevant

• Decision making relies on knowing the effects of each decision in the real world. Collective decision making thus relies on a collective understanding of the shared reality through the scientific method.

2.2 Systematic and Statistical Uncertainty

• Our understanding of the shared reality is never perfect, but is always improving. When it comes to measured quantities, it is possible and necessary to quantify the inaccuracy or imprecision in our description of the shared reality.

3.1 Probabilistic Reasoning

• Since every claim of fact is to some degree uncertain, each claim should be associated with a level of confidence, or a probability that it is correct.

5.2 Scientific Optimism

• Although the first step of a scientific attitude is to admit one's ignorance or the uncertainty in one's knowledge, it is still possible to make progress by successive iterative improvements.

6.1 Correlation and Causation

• One important aspect of the shared reality is cause and effect, which is studied in a series of future lessons on causation.

8.1 Orders of Understanding

• When constructing a model of a complex system, we need to abstract out the most important aspects of the system in relation to the question at hand. This requires understanding (or hypothesizing) the order of importance of various aspects of the system, so that only the top one(s) are considered.

13.2 Deliberative Polling

• A type of event that helps the public make better group decisions after being informed on the relevant (shared) facts about an issue.

Takeaways

Learning GoalsDefinitionsExamplesCommon Misconceptions

After this lesson, students should

1. Understand that the self-correcting and ever-changing nature of science is a strength, not a weakness.
2. Feel optimistic about the capacity of science to help solve problems for societal and personal decision-making.
3. Understand the assumption of shared reality with regular patterns and the power of empirical evidence as a way to study this shared reality.
4. Appreciate that scientific knowledge is built more like a raft than a pyramid.
5. Understand the need for scientific modelling and how our knowledge of reality is necessarily expressed in terms of models.

It's easy for students to get hung up on philosophical minutiae or edge cases of what really is reality, or does it even exist. Try to pull students back to the main goal of making practical decisions in our lives or in society by using science to understand the assumed shared reality. We only need things to be as real as the table in the middle of the room, so one can walk around it and avoid hurting oneself.

Raft vs. Pyramid

Two different metaphors for scientific progress.

• The Raft

Every scientific claim is subject to question and reevaluation; we can use the rest of our scientific knowledge to question any one claim at a time, though we cannot question the entire edifice at once.

• The Pyramid

Science builds on fixed foundations to ever higher levels of knowledge.

Scientific Models

An activity with the aim making a particular part or feature of the world easier to understand, define, quantify, visualize, or simulate. This is often done by referencing it to existing and usually commonly accepted knowledge.

Assumption of Reality

Scientists assume an external reality, which is shared by and affects all people and has enough regularity to lend itself to induction. This external reality is what scientists seek to describe accurately.

Empirical Evidence

Science is based on appeal to empirical evidence, which is publicly accessible on the assumption of reality (although may require special instruments and/or expertise to acquire).

Evaluation of Models

The extent to which a scientific model is as useful tool for describing some real external thing. There are several features that determine the usefulness of a model.

• Ability to explain past observations.
• Ability to explain future observations.
• Simplicity or ease of use.
• Refutability and the ability to characterize our confidence in the model for a given problem.

Science vs. Decree

Science gains its authority from its self-questioning character, not from the concentrated power of individuals.

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Additional Definitions

What follows are additional definitions that appear in or are relevant to the lecture, but aren't deeply covered in this discussion's lesson plan. They do, however, come up quite a bit later in the course. We would like to cover them if we had more time. They are especially relevant to 11.2 When Is Science Suspect.

Realism vs. Idealism

Two different ideas for the construction of the physical world.

• Realism

We all inhabit a common reality, which has a structure that exists independently of what people think and say about it (except insofar as reality is comprised of, or is causally affected by, thoughts, theories, and other symbols). The structure of the world is regular, such that the patterns we observe are likely to hold in new contexts.

• Idealism

The physical world is dependent on the conscious activity of humans. Also called phenomenalism.

Scientific Realism vs. Anti-realism

Differing views for how the world is described by science.

• Scientific Realism

Science aims to provide a true description of the world, which is assumed to exist in a mind-independent fashion, and it often succeeds (or at least is approximates the truth).

• Scientific Anti-realism

Anti-realist theories of science differ from one another. Among the views defended:

• • Scientific theories can never "reach beyond" experience in what they say.
  • Perhaps scientific theories can make claims that reach further, but we can't ever expect to get claims of that kind right.
  • The objects of scientific study themselves do not exist in a truly mind-independent fashion.

Metric

A numerical value intended to represent the extent or magnitude of a real-world phenomenon, often obtained by combining one or more measurements. We discuss three main types of metrics.

• Conventionalist Metrics

When an individual scientist or the scientific community at large define some metric to be correct by convention.

• Operationalist Metrics

When the truth of a metric is taken to consist of the operations involved in proving or applying it.

• Realist Metrics

When the truth of a metric isn't based on human choices, but instead on some real phenomena in the world at large.

Types of Metrics: Development of Thermometers

When scientists first developed thermometers, several different substances were used. The problem was, these substances had different rates of expansion, yielding different ways to quantify "temperature." For example, water, alcohol, and mercury expand at different rates: if you set up thermometers with "0 degrees" equalized, each of the substances will hit "100 degrees" at a different temperature. How, then, do we know which kind of thermometer to use? Is the temperature "really" 100 degrees when a mercury thermometer says so, or when a water thermometer says so?

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Operationalism vs. Realism: Colors

Whose reality is more representative of the "true" colors of the world? ours or that of the mantis shrimp?

• The operational answer is that we can't compare these two because both are correct in their own way.
• The realist answer is that neither animal can fully see the full spectrum and through science we can try to understand it.

The point is that the mantis shrimp sees more of the real world than we do but neither has a perfect representation of the world.

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Spherical Cows

A common "joke" among physicists is that cows can be modeled as spheres for the purposes of solving many types of problems (such as those involving mass, volume, surface area, and the like).

Spherical Cows

A Wikipedia article with more information.

Science always changes its mind. One day drinking wine is good for you, the next day it isn't anymore. Why should we trust anything scientists say?

When scientists make any claim, they make it always with some level of uncertainty, leaving open the possibility that they may be wrong. Any claim is subject to scrutiny and may be overturned or amended by new evidence. The ever changing and improving nature of scientific knowledge is a strength, not a weakness.

Taking the logs of the science-raft for "ideals" rather than claims. Well, I just happen to think that if you punish people whenever they misread a word they will learn to read much faster—and most people agree with me. So...

The central characteristic of a scientific theory is that it is falsifiable. Every scientific claim is subject to question and reevaluation; we can use the rest of our scientific knowledge to question any one claim at a time, though we cannot question the entire edifice at once.

I want to understand physics well enough to write a program that closely simulates our universe. How to achieve this as fast as possible?

Finite computation power means that it is necessary to simplify our models for simulation. The simplification has to depend on the question one is trying to answer with the simulation. It is infeasible to "simulate everything" also because even the best model involves simplifications and idealizations.

So what if our model of reality is "wrong" if it makes our lives more harmonious? And maybe we can just agree to disagree.

If it's a belief that affects a decision and its likely outcome than at some point your misconception is going to catch up with you.

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2.1 Senses and Instrumentation