This article is part of a special edition of The Atlantic magazine, to be published Monday, June 30.
The first installment of the special edition was published in December 2015, and it is here with an exclusive interview with Dr. Mark Adler, co-author of the new book, “Psychological Predictions: A History of Psychology.”
Adler is a professor of psychology at the University of California, Berkeley.
He is the co-director of the Berkeley Center for the Study of Prediction and Decision Making, and has published widely on prediction science.
His latest book, Predicting the Future, will be released by MIT Press on June 1.
In this exclusive interview, Adler explains why he is so excited about this book.
You can read the entire interview with Adler here.
What is the purpose of this book?
Dr. Adler has been involved in many of the most important predictions that have occurred in the history of science.
We now have a new, very sophisticated understanding of the structure of our brain, and we now know that we can predict with greater accuracy what is going to happen in the future.
The question is how do we predict the future, and what are the kinds of predictions that we should make?
This is a critical problem.
And we have a lot of evidence to show that the more you know about what is actually happening in the world, the better off we are.
And this is a problem that I believe we need to tackle now more than ever.
What are the key predictions that you think have been correct in the past?
Well, I believe that the basic idea of forecasting is that we have to get into the prediction process, the process of making a prediction.
And then the prediction itself, I would say, should be about predicting what will happen next.
We all know what happens when we make predictions, because they’re very powerful.
But we have never had a way to actually predict what will actually happen, and so I think that’s the way we should be looking at these predictions now.
So what is the process?
We can see the prediction as being about what will be the outcome of a given situation.
So a situation could be an event that occurs, or it could be a situation that doesn’t.
And so there is a certain kind of prediction that you make, where you have a hypothesis about what it is that is going on, and you’re trying to see how much the hypothesis predicts what is happening.
And the more information you have about that situation, the more accurate you can make your predictions.
So you can look at a given scenario and see whether or not there is evidence that it’s happening, and if so, how much.
Now, how do you get information about that?
There is the sort of general idea that you have to have a kind of knowledge of what is in the environment.
You have to know how the environment is changing, and that is, for example, the ability to predict the weather.
You know, if there is an event happening and there’s an actual change in the weather, you can predict how it will change, because you have that kind of understanding.
But there are also very specific aspects of weather that are quite difficult to predict, because the weather is so complex.
So there is this question, well, how can you predict the temperature of a hot summer?
The way you can do that is to know that you know what the weather conditions are, and then you have this knowledge of temperature and the other things that are changing in that particular weather system.
But how do I know that I know this information?
And I think this is something that you can really only know with the help of a really good prediction model, because there is so much that can go wrong.
So how do people get information?
Well we know that a lot has to happen, because if you have all the information, you have the best chance of making your prediction.
You might have to go out to the weather station and say, oh, there’s something going on.
And if you know that there is something going to change, you are going to be much more accurate.
And that is because there are so many variables that you need to know about to make that prediction.
But the main thing is that you should have a model that predicts what the environment will be like, and how it is going.
So the most efficient model that you get is one that predicts the environment in a way that allows you to predict what the future will be.
Is that a prediction that can be made?
So, this is the basic problem of predicting.
It’s like trying to predict whether or no someone is going in the shower.
If you can get that information, that’s really good.
But if you can’t, well then you’re just predicting what you’ll get.
And you’re probably going to get wet.
And there are a lot more things that you’re not predicting