I found the discussion of free will and determinism toward the end of the interview with Agustin Rayo to be very interesting. At one point in the discussion, Professor Rayo draws a distinction between what someone will do and what someone must do, saying that knowing what someone will do implies you know how they will exercise their free will, while knowing what someone must do implies that the action is compulsory. While describing this example, he goes as far as to say that it doesn't matter how deterministic a system is, as physics doesn't concern what must happen, only what will happen, meaning physics determines nothing about free will. While I think this is an interesting perspective, I wonder if in a fully deterministic system, is there any difference between what will happen and what must happen? If past events determine present events and since the system is deterministic, there can only be one correct set of present events, then the present events from a past perspective "must" happen, or from a present perspective had to have happened based on what events occurred prior. I would have liked to ask Professor Rayo about this perspective to hear his opinion.

Something that surprised me from the interview with Agustin Rayo was the point he made about how a lack of determinism imposed by quantum randomness or some other force doesn't necessarily equate to free will, as being governed by randomness doesn't incorporate any more individual agency than being governed by strict laws. I had a similar thought while watching the interview with Dan Gilbert and his discussion of Laplace's demon, so I was surprised to see Professor Rayo bring up the same point and discuss it. He went on to make the distinction that being able to predict someone's behavior doesn't mean they aren't free, it just means that you're good at predicting how they choose to exercise their freedom. This concept left me with additional questions, which I'll pose in a separate post.

After watching the interview with Brendan Meade and Susan Murphy and learning about how difficult it is to predict earthquakes, I was left wondering more about how prediction in the earth science field will advance, and how earth scientists feel about the difficulty required to advance. Because of the rarity of earthquakes and how difficult it is to collect meaningful data, simulation and AI are becoming much more helpful in predicting earthquakes. However, from how Professor Meade described the situation, it seems present earthquake models are so simplified that they aren't that helpful, and that making them more complex would require a leap in available computing power. Here I would have asked, "can the field advance without an increase in computer power for simulations? Does it ever feel hopeless to not have any new helpful data, and to instead have to simply wait for technology to advance?" This problem reminded me somewhat of the struggle particle psychists feel when there's a lapse between new large sources of data like particle accelerators. I took a freshman seminar with particle physicist Lisa Randall last semester who spoke a bit about this, and how they have to wait for a more powerful particle accelerator potentially decades away before they can make any new large discoveries.

While watching the interview with Brendan Meade and Susan Murphy, I was surprised to learn how little information earth scientists have to predict earthquakes with. This was really shown when Professor Meade discussed the Lyapunov time for predicting earthquakes, which he said could range from thousands of years to a nanosecond. Due to the rarity of earthquakes, and the difficulty in gathering relevant data prior to an earthquake happening, earth scientists have begun to rely heavily on AI and deep learning to find patterns that could potentially be helpful and predictive. This led me to wonder how earth scientists feel about how difficult it is to progress prediction in their field, which I'll elaborate on in my question post.

Something that surprised me from Jill Tarter's interview was her support for science fiction, for the reason that it helps us to imagine life as we don't yet know it. This surprised me, as I had previously viewed the main practical benefit of science fiction as a vehicle for garnering public interest in science, which would lead to increased funding for scientific projects, as well as more young people interested in becoming scientists. To think that real scientists actually take inspiration from works of science fiction is surprising, and I'd be interested in knowing how much of an effect science fiction actually has on the direction that science moves in.

In Jill Tarter's interview, she discusses her work with searching for extraterrestrial intelligence in the universe. It's mentioned towards the end of the interview that if given the chance to communicate with extraterrestrials, she would ask them how they managed to progress technologically without eliminating themselves through intra-species war. While this is interesting, I would have asked Jill more about what might be some of our goals in communicating with extra-terrestrials, which would answer the question of why do we want to communicate with them in the first place? Would we attempt to accelerate technologically by adopting alien technologies, or would we have other motives? Does any danger lie in contacting extra-terrestrials? I'd like to believe that a species far more advanced technologically than ours would also be far more advanced ethically and would have our best interests in mind, but I'd be interested in hearing Jill Tarter's thoughts.

When talking about determinism and the desire to predict and know the future, Dan Gilbert says that if the universe is entirely predetermined and there's nothing anyone could do to change the course of events, why would you have any desire to know the future? He goes on to say that even those who claim to believe in predeterminism don't really believe it, as everyone likes to think they can have an impact on the world. I would have responded to this point with the question "Is there still value in knowing the future, even if you can't change it?" I personally think there is, but I'd like to hear Professor Gilbert's opinion. An example that came to mind that somewhat answers this question involves narratives in entertainment, whether they be books or TV shows. In the vast majority of entertainment media we consume, the events of the narrative for that particular show or book have already been written, and there's nothing we can do to change them. However, this doesn't stop people from wanting to know what might happen in next week's unreleased episode, and coming up with their own predictions to try to find out. I think human curiosity alone is enough to motivate us to want to know the future, even if there's nothing we can do to change it.

Something that surprised me from the interview with David Laibson was him saying that the ability to predict economic events 20 years in the future would likely not be possible for generations, or perhaps ever. Economics is a system that is almost entirely based on human nature. While I agree that human nature can be very unpredictable, and that these uncertainties can compound to astronomical levels over long periods of time, I think it's short sighted to say that the ability to do something like this may never be possible. We learned in this course that we've only been making sophisticated predictions for a small fraction of human history, and a much smaller fraction of the history of the universe. Assuming our species isn't eliminated in the near future by an extinction event, we have lots of time for current technologies to develop and new technologies to emerge that are capable of things beyond our current comprehension, so who's to say that a seemingly impossible prediction in the present may be possible in the future?

An additional question I'd have asked in Rebecca Henderson's interview following the section about developing countries is "what's your take on allowing developing nations more leniency on using carbon intensive forms of energy (coal, natural gas) to help them "catch up" to developed nations?" I was prompted to think about this question when Professor Henderson mentioned how China is "building a coal plant a week" and how India was on a similar path, and how she found both to be "very problematic". While from a pure environmentalist perspective China and India expanding their use of coal when it's in everyone's best interest to reduce global carbon emissions is a bad thing, is it really fair to hold developing nations to the same carbon standard as places like the United States? The United States reached its place of prominence through heavy use of fossil fuels while it was developing, and only now can it consider moving towards cleaner alternatives. It seems like it'd be much more difficult for a developing nation to grow without access to the same cheap sources of fuel that current developed nations took advantage of.

Something that surprised me from the Dan Kammen interview was the idea that those who design predictive forecasts are on average twice as confident or half as uncertain as they should be. While it makes sense to me that those who designed a forecast are most invested in it, which might lead them to have more confidence in it than others, I'm left curious of how this overconfidence actually manifests empirically as uncertainty calculations are being made. Those who are making these forecasts are likely experts in their fields, so how do they end up calculating uncertainty so incorrectly? Do they account for all possible sources of uncertainty? Do they underestimate the amount of uncertainty that a given factor may cause? I would assume that the model maker's unconscious biases would cause them to more easily dismiss or underestimate uncertainty, leading to this phenomenon, however I'm still surprised that it has such a significant effect.