Quotes About Predictions

Consumers of forecasting will stop being gulled by pundits with good stories and start asking pundits how their past predictions fared—and reject answers that consist of nothing but anecdotes and credentials.

The pollsters and pundits will keep trying to read voters' minds.

Qué maravillosos descubrimientos haríamos en astronomía si pudiésemos sobrevivir a nuestras predicciones y confirmarlas, observando la marcha y el regreso de los cometas, con los cambios de movimiento del sol, la luna y las estrellas!

Everyone wants to pencil you in as the kind of player that you're going to be after a few years in the big leagues. When you're still really young, they think that's what you're going to be forever.

I believe that we are going to have a much deeper appreciation of what kinds of abnormalities in cancer cells and in the surrounding cells that feed and respond to cancers are vulnerabilities that will allow us to make better predictions of which kinds of drugs will work to treat these cancers.

Health care - the ability of neural networks to ingest lots of data and make predictions is very well suited to this area, and potentially will have a huge societal impact.

I think the NFL season starts with the first three or four games and all the predictions come out. You're either great on offense, bad on defense, great on defense, bad on offense. You're either going to have a Super Bowl chance or you won't. And I think after that, people kind of think everything's set in stone.

Examples of the planning fallacy abound in the experiences of individuals, governments, and businesses. The list of horror stories is endless.

Why are experts inferior to algorithms? One reason, which Meehl suspected, is that experts try to be clever, think outside the box, and consider complex combinations of features in making their predictions. Complexity may work in the odd case, but more often than not it reduces validity. Simple combinations of features are better.

predictive judgments that provide input—for instance, how a candidate will perform in her first year, how the stock market will respond to a given strategic move, or how quickly the epidemic will spread if left unchecked. But the final decisions entail trade-offs between the pros and cons of various options, and these trade-offs are resolved by evaluative judgments.

people who spend their time, and earn their living, studying a particular topic produce poorer predictions than dart-throwing monkeys who would have distributed their choices evenly over the options. Even in the region they knew best, experts were not significantly better than nonspecialists.

Intuitive predictions are almost completely insensitive to the actual predictive quality of the evidence.

In other words, people who spend their time, and earn their living, studying a particular topic produce poorer predictions than dart-throwing monkeys who would have distributed their choices evenly over the options. Even in the region they knew best, experts were not significantly better than nonspecialists.

The reliance on the heuristic caused predictable biases (systematic errors) in their predictions.

Some of us may need the security of distorted estimates to avoid paralysis. If you choose to delude yourself by accepting extreme predictions...you will do well to remain aware of your self-indulgence.

Philip Tetlock, a psychologist at the University of Pennsylvania, explored these so-called expert predictions in a landmark twenty-year study, which he published in his 2005 book Expert Political Judgment: How Good Is It? How Can We Know?

The number of studies reporting comparisons of clinical and statistical predictions has increased to roughly two hundred, but the score in the contest between algorithms and humans has not changed. About 60% of the studies have shown significantly better accuracy for the algorithms. The other comparisons scored a draw in accuracy, but a tie is tantamount to a win for the statistical rules, which are normally much less expensive to use than expert judgment.

Worry predictions aren't based on what's likely to happen. They're based on what would be terrible if it did happen. They're not based on probability—they're based on fear.

I don't like being called a denier because deniers don't believe in facts. There are no facts linking the concentration of atmospheric carbon dioxide with imminent catastrophic global warming there are only predictions based on complex computer models.

Reckless predictions of the second coming of Christ create an artificial excitement among believers followed by a corresponding depression. In addition, it hardens skeptics in their unbelief and provides new fodder for cynics to mock the Christian faith.

an understanding of the infinite tree of universes seems to be needed in order to make statistical predictions about the properties of our own universe, which is assumed to be a typical "branch" on the tree.

I'm not a pessimist, even though I do think awful things are going to happen.

Over the years, CBO has been all over the board on healthcare. The only consistent point is they've missed the mark on different pieces. That's the nature of a scorekeeper.

When I started out modelling, people kept warning me that I would only last five years.