Forum Posts

Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Apr 27, 2021
In The Future of the Future
After watching the interview with Professor Stuart Firstein it made me think about forms of uncertainty in science in a whole new way. I especially enjoyed the part of his interview where he discussed ignorance about the future and scientific uncertainty. In this part of the interview Professor Goodman tied these ideas back to the classes discussions about free will and determinism. This made me think a lot about its connection to the scientific method. I had never really thought about it in this was in terms of how our uncertainty about science and the future is influenced and can sometimes be determined by ignorance and it can overshadow the importance of how we must not be ignorant about the events of today b equate they can then cause problems and more uncertainty in the future. That was how I thought deeper about that discussion in the interview and it made me want to explore more into how our determinism and ignorance has negatively impacted the outcomes of the future. This led me to one of my questions that I thought of while I was watching the interview. I was wondering how we can better understand where the sources of this ignorance comes from? I also wanted to see if Professor Firestein has studies any specific ways that this ignorance negatively impacts the science of the future? Is this ignorance coming from the public or is there ignorance within the scientific community that creates future uncertainty? There were just some of the questions that came about from this section of the interview. I really enjoyed this interview because it made me think even more deeply about the future of science and the external influences that shape the future of the future itself.
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Apr 22, 2021
In Earth
In watching the interview with Susan Murphy & Brendan Meade, I noticed how both interviewees discuss how difficult it is to make predictions that can pinpoint the anticipation of a health event like stress levels or an earthquake event. Both of them discuss the general processes that allow them to make predictions, but I am curious to know how external factors that can impact the validity of these predictions? In health, are there specific events that trigger stress over others, and what are their prevalence? In earthquake events, is there an increased likelihood of an earthquake occurring in connection to an earthquake happening somewhere else? These factors are something that can maybe help the public to understand how these predictions work as well, so it would be interesting to discuss this in an interview with these experts.
Questions: Deep dive into external factors that may impact health and earthquake predictions- Susan Murphy & Brendan Meade Interview content media
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Apr 22, 2021
In Earth
I enjoyed watching the interview with Susan Murphy & Brendan Meade because of the expanse of knowledge and parallelisms covered in this conversation which is told by the interview title "Predicting Health, and Earthquakes." I found it very interesting how Meade explained how there is a lot of uncertainty in predicting earthquakes that carry such a high level of risk because if these vents can't be predicted, it risks the lives and safety of many communities. I found it surprising that with the technology that continues to be developed that these predictions are still difficult to accurately forecast. He also comments on the differences between the job of seismologists and those who study when and where an earthquake will/might happen. I was very surprised when Meade said that what seismologist's study only makes up less than 1% of what the Earth is actually doing. That is very interesting and means that there needs to be more emphasis on the work of studying the earth prior to the earthquakes happening and gathering statistics to compare and reveal concrete patterns of the changes in the earth. Professor Murphy brings up an important idea that there are a lot of similarities with how we handle and predict health and earthquakes. Before watching this interview, these two topics were not associated directly with each other in my mind. The main similarity that she highlighted was that both of these topics are affected by things that happen in the short term; in health, it is a short term choice like what you eat that can affect your future health, and for earthquake studies, it is the small changes/shifts in the Earth that lead to the event of an earthquake. I also found the discussion about detection versus prediction to be really interesting and how we can make short-term changes and make predictions that can aid in our detection processes to prevent negative long-term outcomes. Below I added images of an earthquake map and an health/epidemiology map that I thought highlighted another parallel in data presentation and prediction in these two spheres.
Interesting Parallels Between Health and Earthquake Prediction- Susan Murphy & Brendan Meade Interview content media
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Apr 18, 2021
In Space
The interview with Professor Avi Loeb was super interesting and took a deep dive into astrophysics and its ties to prediction. Loeb discusses the beginning of the interview of how in order to know about the future, we must utilize the laws of physics. He explains that these laws can be applied to bodies and matter outside of our planet, and thus astrophysics becomes an essential part of understanding space and the galaxy. Professor Loeb mentions that these laws have been tested and proven to be true for scenarios outside of the confines of relating to Earth. If I were conducting this interview, it would be interesting to ask if he knew of the brief logistics and specific finding of these experiments that he references? It would also be interesting to ask if he or if Harvard has been a part of these experiments? Professor Loeb also talks about how now that these laws of physics have been tested to be pretty universal that they can then be applied to prediction scenarios to be able to forecast what will happen, when it will happen, and how it will happen. He mentions how technology has helped advance the making of these predictions. I wonder if some of the predictions made prior to the advanced technology today were proven incorrect or less accurate than if they were tested now or if, in some cases, this technology wasn’t needed to make just as accurate predictions about entities outside of the Earth using the basic laws and knowledge of physics?
Questions about the universal application of the laws of physics: Interview with Professor Avi Loeb content media
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Apr 18, 2021
In Space
I found the interview with Jill Tarter to be very interesting and insightful into a realm of science that has a lot of uncertainty and much to still be discovered. The idea of extraterrestrial life has always been a fascinating one because it widens the scope of life to not just focus on us on Earth but to provide space to question and theorize whether there are other living beings beyond the confines of what we know. Before watching this interview, I didn’t really know how scientists went about discovering and studying extraterrestrial life, so I found it interesting that for a long time, the method best thought to do this discovering was through the use of radio waves to intercept and detect communications from possible extraterrestrial life. As this tool seemed to become less useful and accurate, Tarter mentions how the Drake equations formed an essential idea for which scientists could try to estimate the amounts of communicating extraterrestrial life within the Milky Way galaxy but then explains that she finds it to be essentially useless/ unhelpful in this study to find these possible life forms because of the increased uncertainty it presents why trying to use/apply it. I also found interesting from this discussion of the Drake equation that not all scientists believe in its validity and that it causes discrepancies within this scientific community. One last interesting idea that I gathered from this interview was the idea of observation versus theory and how, in this field of science, it is better to focus on making observations, that is, concrete patterns or communications, rather than trying to speculate or predetermine something or some life beyond our planet that one might try to theorize exists.
What tools do we use to estimate/determine if there is extraterrestrial life? Interview with Jill Tarter content media
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Apr 06, 2021
In Thoughts from Learners
I found the interview with Professor Dan Gilbert very interesting in evaluating how humans make predictions and how we as humans can then make predictions about human behavior itself. Towards the beginning of the interview, I was already thinking a lot about things that I found interesting, some of which we have discussed in this class, but also other concepts that we have yet to really dive into. One of the first interesting points that Professor Gilbert brought up was how humans aren’t always predicting with accuracy in mind but rather predicting things that you hope will happen (a sort of manifestation tool to almost will something into happening). He talks about some of the reasons why people do this and highlights social rituals as the main reason but also incorporates the idea of how it is often a fun activity to dream and enjoy. I think another really interesting thought brought up by Professor Gilbert is that humans react to the outcomes of their predictions and how when we get our predictions wrong or another outcome occurs, we are often upset not so much at ourselves but at the prediction and outcome itself. It is these prediction outcomes that create a tone and mindset for humans towards predictions and often cloud our predictive judgement when we want something we predict to have the desired outcome.
Human influence of Human Predictions: How Humans Work to Control their own Destiny-Interview with Professor Dan Gilbert content media
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Apr 06, 2021
In Wealth
After watching the interview with Professor David Laibson, I was very interested in the discussion about behavioral economics and its connections to uncertainty and prediction, focusing on human behaviors in the world of economics. In this prediction class, we have discussed a lot of the origins of predictions starting the course with the topic of divination and how humans first used forms of prediction to try to better understand uncertainty. At the beginning of this interview, Professor Laibson explains the origins of behavioral economics. He explains that the study of behavioral economics was a field that emerged in the 1980s to withdraw the assumptions that economics makes of humans behaviors and look at it through a lens of evaluative psychology and human understanding. I am curious about these origins and would like to ask Professor Laibson about why this field only emerged in the 1980s? Was there a catalyst that sparked the need for closer observation of how human behavior is connected to economic studies? From watching this interview, it is clear that this field allows for better prediction and understanding of economics when we can evaluate the certainty and uncertainty of human behavior. Still, it also makes me curious about why behavioral economics wasn’t really studied sooner. It is hard to speculate how events would have happened differently in the past, but I wonder if there had been more calculated/accurate predictions of the economy with the ideas of human behavior in mind if there would have been better outcomes/avoidable outcomes of things like market crashes if we could use human behaviors as a predictive tool earlier in history. I wonder if Professor Laibson would have any thoughts or comments on that idea as well and might have asked about this in an interview with him.
The Emergence of Behavioral Economic Studies: What if questions? Interview with Professor David Laibson content media
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Apr 01, 2021
In Health
I learned a lot from watching the Immaculata De Vivo and Peter Kraft Interview about the impacts of population genetics on global health. I am really interested in learning more about the predictability of predisposition in genetics. De Vivo briefly talks about the difficulty with predictability and susceptibility surrounding non-Mendelian genetics. She highlights that there can be correlations between these non-Mendelian genetics and environmental factors, which can make predispositions more profound and can then impact the person's condition medically. Kraft talks about the high levels of uncertainty around predicting genetics. Both of their comments made me think about how these models can become more refined to narrow down the ways to better treat these predisposed patients. I wonder what predictive systems are in place outside of medical studies to use to make revisions to the current models, given the high levels of uncertainty in these diagnoses and their origins? I was also very fascinated by the discussion of the ethics of genetic-based treatments and how patients with these predisposing conditions are provided with their results from certain studies, and how privacy is becoming less and less secure because of database and information gathering systems in our daily lives. One question that I had was, are these public databases being utilized to their fullest potential to better understand how to see trends in global health and determine if there are correlations with geographic locations, environment, etc., that could shed more light on how these predispositions have connections outside of genetics? At the end of the interview, De Vivo and Kraft mentioned how human genetic understanding is constantly evolving and changing, which means that genomics and epigenomics have different overall changes depending on the span of time, meaning that one's singular genetic observation/early diagnosis can't necessarily predict one's lifespan or overall quality of life. Statistics can play a big role in understanding one's genetics, but it can't reveal everything. If I could ask a question to De Vivo and Kraft after this interview, I would want to know what combination of practices, studies, and observations discussed would give someone the highest likelihood of understanding all of their genetic predispositions and the factors that impact them? In other words, what genetic observational practices give someone the highest likelihood of these predictions being most accurate?
Questions for Immaculata De Vivo and Peter Kraft on Global Health and Population Genetics content media
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Apr 01, 2021
In Artificial Intelligence
In the Interview with Ben Schneiderman, I learned a lot about AI, not only the components of AI and machine learning but the current limits of this technology that more or less dictate its viability in certain predictive situations. I am not an expert in this technology field, so it was very interesting to learn more about the basic components and distinction of AI, especially the differences between machine learning methods and statistical methods. Before watching this video, I had a difficult time distinguishing the two methods from one another, which inhibited my understanding of artificial intelligence. What I learned from the interview in this context was more interesting than surprising but provided me with a better understanding of these distinctions. In the interview, two Harvard Undergraduate students worked alongside Schneiderman to highlight these differences. I was surprised that one of the students distinguished machine learning as providing the ability to look at a lot of different factors deeply to make strongly connected correlations that the student remarked were more of surface-level correlations with statistical methods. I had always had the understanding that statistical methods could also allow for a deeper understanding of connections rooted in quantitative knowledge, but from this video, it becomes clearer that there are both quantitative and qualitative aspects to AI that allow for better connections between idea/theory conception to then predictive modeling and understanding. Another interesting idea brought up in the interview was how one must be wary of making misguided assumptions about the correctness of the power of AI. Instead, we need to realize that there isn't "magic pixie dust" that creates these connections and that "mindless acceptance of their potency is extremely dangerous." One last surprising thing that I learned from this video is that AI can often be less accurate in its predictions compared to statistical methods because of the complexity of AI components. Schneiderman also highlights the danger of putting too much trust in the predictions of AI as a worrying understanding that many people have. This idea was the most surprising to me because before watching this interview, I felt that AI was something that would be able to more correctly predict compared to just humans evaluating statistical models, and yet experts in this field seem to say that this technology is a valuable tool but that its produced knowledge and predictions should be taken with some skepticism such as the problems with the Google flu trends in 2009.
Are AI predictions really that accurate? Surprising takeaways from the Ben Schneiderman Interview   content media
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Mar 30, 2021
In Earth
In watching the video interview with Dan Kammen, I was most struck and interested by his commentary on the “silver bullet vs. silver buckshot” approaches to climate change. I was specifically intrigued by how Kammen identified that the solution is not a one miracle technological solution like many think and hope, but rather a series of innovations and advancements that will contribute to improving the state of our Earth and climate. With all of that being said, I would have maybe gone off on this tangent idea a little bit more and discuss his phase of “silver buckshot” and what that means in terms of how scientists are currently combating climate change. Are there any notable breakthroughs going on that are contributing to this conglomerate of advancements that would support this way of thinking about the solution trajectory of climate change? Kammen also highlights how theory plays a significant role in sparking changes like the simple idea of how it is “better not to waste” and by utilizing the momentum behind these theories to change public mindsets and shifts to more eco-friendly practices. Learning about this perspective from Kammen, I would ask a follow-up question to this idea to ask about his opinion on other climate change theories and the feasibility to implement these theory-based changes on a more national and global scale? What would it take to make the uncertainties of solutions and theories more certain and widely accepted by the public to enact concrete changes? I was also curious about the ideas about “performance contracts” and if this would be able to be implemented in cities in the U.S. and also why it hasn’t already been put into practice in the U.S./more widely if it has not only financial benefits but also positive environmental implications?
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Aurora Avallone
Harvard GenEd 2021
Harvard GenEd 2021
Mar 30, 2021
In Earth
In watching these videos, I found a lot of interesting and surprising information surrounding climate change and the publics’ use and reactions to information on climate change in the interview with Gina McCarthy, which was very interesting to me. What particularly struck me was how she discussed that when using simulations to predict climate changes when there comes time to interact with the public and share this information, the simulations are not commonly explained because people seem to be more focused on asking the big buzz word questions rather than focusing on the substance of the issue. She also discussed a chain of information relaying where the scientists practice the science and test it to ensure that it is accurate; it is then given to people like McCarthy in the field of public health who process the information and makes it relevant to human beings; she translates the scientific information like simulations and models so that the public can more easily understand and digest the information. I had never really thought about this chain of information and that as the information goes from scientists to the public, there is a middle person who is verifying the information/predictions, solidifying the main claims, and boiling down the information to allow for it to be absorbed by as many people as possible. So the actual nitty-gritty science and simulation models don’t usually make it to public knowledge. This is not to say that not all of the information is being shared with the public, but to McCarthy’s point in the video, the public at large is not directly interested in the simulations and intricate science but rather the larger, more simple ideas and questions. One final note is that McCarthy also highlights a shift from the public being concerned about overarching empathy-inducing topics like “saving the polar bears” to a shift in focusing on solutions to things that are readily fixable and matter to the human condition. These ideas from this video were very interesting to me and have made me rethink my own consumption of knowledge and my want to better know and understand the solutions associated with some of the complex topics and predictions surrounding climate change, like predicting the rate of the rise of carbon dioxide trapped in the ozone layer and the rate at which this will present visible adverse effects to humans, for example. This example digs deeper than just the public’s question of how excess carbon dioxide harms humans and the environment? It asks for more information to understand the impacts of uncertainty in climate change science, which I have learned in this class and will apply later on in life.
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Aurora Avallone

Aurora Avallone

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Harvard GenEd 2021
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