This was an incredibly interesting interview to me because it felt like we received two contrasting perspectives on how to think about the future. On the one hand, Agustin Rayo represented a very philosophical perspective, Professor Goodman provided one rooted more firmly in science. It was a very interesting discourse and I don't think either side seemed to think they were "right", rather, both perspectives are relevant and inform each other. One thing that troubled me from Rayo's perspective was his claim that human behavior is very predictable. He cited the fact that a lot of what humans do relies on knowing what other humans will do, like showing up for the interview and being able to predict that Professor Goodman would as well. I would have asked for his thoughts on the idea that even if large scale human actions can be predicted, every single second a human does a billion tiny things, like the way in which they sit, who they look at most in the room, etc., that, put together, actually do have a large effect on the future and on the outcome of that person and the people around them. I would argue that as a result it is actually quite hard to predict human behavior and to predict what lies in the future of any one individual person, even if that person is someone you know very well.

I was interested and surprised by the fact that many predictive models, like models predicting factors associated with the highest likelihoods of different types of cancer, often have limited practical use in terms of actually fighting cancer. For example, a model might show that smoking increases the likelihood of cancer, but people will often not heed the advice of such models because of anecdotal evidence based on certain individuals who smoked and lived long, healthy lives. On the other hand, there might be genetic factors that are predicted to have a higher chance of association with cancer, but this does not necessarily provide the patient with relevant information as to what they can do to increase their chances of survival. Going off of this, I would ask, how can such predictive models be of use to a doctor who is actually trying to cure cancer, or another disease, in a patient? If a patient has been diagnosed with cancer, is it of any use to know that they possess certain characteristics that could have helped to predict that they would ultimately get cancer, or is this information useless given that the patient has already been diagnosed? As in, is there any way that the data about correlation between certain risk factors and cancer can actually be used to treat the cancer itself.

I was surprised, and perhaps a bit concerned, to learn exactly how much information that businesses and corporations already have on how their behavior impacts the climate. Surprised because I had thought perhaps many business executives just didn't have the full picture and knowledge, concerned because I had assumed (or perhaps wishfully hoped) that they would prioritize the well-being of our planet a bit more. Perhaps the most important part of the policy aspect of the future of climate change is not who sits in policy-making government decisions, but who sits in power at major government-independent companies and corporations whose actions contribute to pollution and climate change. I would have asked a specific question about the models scientists typically use to predict the future. Since a 95% Confidence Interval can be determined for any given statistical model that involves uncertainty, I might wonder what the "95% Confidence Intervals" are for models predicting Earth's future; in other words, what are the worst and best extremes which scientists see as realistic possibilities for Earth's future?