Goodman’s New Riddle of Induction

What is Goodman’s New Riddle of Induction?

The New Riddle of Induction is a puzzling question that makes us think hard about how we learn things from what we see and experience. When we use induction, we take specific things we’ve observed and jump to general conclusions about them. For example, after seeing several white swans, we might conclude that all swans are white. But if we suddenly find a black swan, do we have to rethink our reasoning? Goodman’s riddle goes even deeper, asking us to question how we come up with logical reasons in the first place.

A simple definition of the problem could go like this: Imagine a color-shifting object that’s green before a particular time and blue afterward. If you learn about the object being green numerous times, you might expect it to always be green. However, knowing that it will actually be blue after a specific time challenges how you predict what the object’s color will be in the future. Goodman’s riddle asks us to consider how we justify what we consider to be true or false based on what we see and how tricky it can get when the rules change over time.

Origin

Goodman’s challenge comes from a long history of thinking about how we draw conclusions based on observations. People have been pondering this since ancient times, with every new philosopher adding their twist to the issue. In the 18th century, a thinker named David Hume asked whether things we’ve seen happen before are guaranteed to happen the same way again. Goodman pushed this idea further by hinting that maybe the labels we use when we group things together are part of the problem.

Key Arguments

The Problem of ‘Grue’:
Goodman created a strange word, ‘grue’, which describes something that is green before a set time and blue after. If we predict that all apples are green based on seeing them before the time switches, we could be taken by surprise when they turn out to be blue later on. This challenges the way we expect things to stay the same.
Conventionality of Projectible Predicates:
Goodman suggests that the terms we use to describe things don’t come from the objects themselves but from our habits. We say something is green not because there’s anything inherently special about being green, but because we’re used to talking about it that way.
Challenge to Justification:
Goodman’s riddle really tests how we back up our choices when we reason. If different logic can support completely opposite predictions (like something being green or grue), how do we decide which one to go with? Why do some choices just feel more right than others?

Answer or Resolution

Philosophers have been trying to unwrap Goodman’s tangled riddle, but so far, no one has found an answer that everyone can agree on. The solutions proposed usually revolve around practicality or the patterns we see in language and past events:

Pragmatic Approach:
Some say we should choose the terms we use based on what works best, which often means going with tried-and-true terms like ‘green’. These are easier to use when we’re trying to predict what happens next
Entrenched Predicates:
Goodman himself thought that terms deeply rooted in the way we talk and think were more likely to be picked for making educated guesses. This doesn’t make them better by nature, just more familiar based on past use.
Rules of Induction:
Others believe that this riddle shows a need for clear rules about when and how it’s okay to use inductive reasoning to make sure our logic is solid.

Major Criticism

While Goodman’s thought experiment has been influential, it has definitely faced its share of critics. Some argue that the way he distinguishes between terms like ‘grue’ and natural-sounding terms like ‘green’ doesn’t really make sense and doesn’t actually trip up our thinking process. They believe that we naturally understand which terms can be predicted to carry on in the future through their role in scientific theories and everyday use, so the problem Goodman raises wouldn’t usually even come up.

Practical Applications

Scientific Inquiry:
The riddle pushes scientists to question the terms they use when setting up experiments. It’s a reminder that rules we believe are set in stone might just be based on what we’re used to.
Artificial Intelligence:
The puzzle is relevant for AI, too, where picking the right categories for machine learning can make a significant difference in how AI systems process information and make decisions.
Legal Reasoning:
The legal world also sees the effects of Goodman’s riddle. When lawyers look at past cases to guess the outcome of new ones, the ways they group cases together can really sway their predictions.

In the end, the New Riddle of Induction reminds us to stay sharp and critical in how we form beliefs and understandings. It provokes us to always check the basis of our logic and the systems we use to make sense of science and the world around us. The riddle isn’t just a brain-teaser, but a real issue that affects the core of how we learn and interpret new information about the world.