One aspect of the behavioral economics discussion that I watched between David Laibson and Alyssa Goodman came during the discussion of economic modeling. I found it surprising how forthcoming Professor Laibson was about the inability to project stock performance over any far-reaching time frame. He used the term "random walk" which stood out to me since I'm and economics concentrator myself. The stock market plays a central role in many senses to the economy of the United States and more broadly the world. Because of this, an inability to forecast the success or failure of a stock in the long term is an interesting revelation from this interview. Laibson's certainty of this is what surprised me most. In terms of a question I would have asked Professor Laibson, as a former student of his, I would want to ask him about the ways in which predictive methods and uncertainty in those methods effects that ways in which he presents economic models in his curricula. I would imagine these factors make significant impacts on how he chooses to conduct his courses but would love to know more details on how exactly these effects manifest. David Laibson has always been one of my favorite professors I've ever had and because of this I really enjoyed this discussion.

The video which I listened to was the Lord Martin Rees podcast on climate change. One thing that I found interesting was his concession that the difference between what's possible and what's realistic are two starkly different things. He talks about the means by which people's pollutive habits could be reduced down to net zero by 2050. However, he also says that these practices do not take into account all of the legislative hurdles and red tape that tend in the way of these practices. I found it refreshing for someone to be forthcoming about how realistic these hopes are as opposed to using the sometimes blind optimism that others do. I would have loved if this discussion got into a bit more of an in-depth discussion of uncertainty. This i touched upon a bit in at least one question that's posed. However, I think uncertainty is one of the keys to understanding the climate's change. Additionally, I'd love to get a sense of how and why an expert like him thinks that symbolic "goal posts" of prediction have been moved many times as the climate change issue has developed in recent times. It seems that targeted years in which things have to happen continue to be pushed back and it would be inciteful to hear Rees speak more to how these things evolve as well as the solutions to these problems evolve. Rees-AG-Sep 15, 2022 at 12_12_47.mp3 https://docs.google.com/document/d/11RRzvlVLmUNPv3y6n3gkqJJQnrL0O0sj/edit

During this interview, I think what I found most surprising and intriguing is the fact that there is still so much that is unknown. In these scientific fields, it can often feel as though experts’ understanding is universal and information is freely at one’s disposal. However, this interview showed how there are still gaps in knowledge that need to be bridged before predictive systems can be adequately created. Moreover, it also always surprises me how forthcoming experts are with there shortcomings in current knowledge. One may assume that experts would want to appear all knowing and in control but I think this interview shows that the smartest people are those who are willing to admit that there is so much that they don’t know. I think one question I would’ve liked to see asked would be why these two researchers got into their field. In the introductions, they briefly explain who they are and what they do professionally but at least for me, I always resonate more with an expert when I know why someone chose to take on the questions that they’ve devoted their lives to answering. I enjoy knowing how much one’s career is driven by passion and the journey that people go on to find that passion. I also like to understand when people realized that this was what they wished to do with their career but I think I may be alone in enjoying the professional context of these experts’ inquiries. However, overall I think the interview was well-conducted in terms of providing informational context for the predictive systems themselves.