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Emily Axelsen
Harvard GenEd 2021
Apr 24, 2021
In Thoughts from Learners
After watching the interview with Professor Stuart Firestein, I was left with questions about revision in science. During the interview, Professor Firestein explained that revision is perceived as a victory in science. He suggested that science depends on iteration and constantly revising theories based on new data. Although I agree that science depends on iteration, it is not the only field of study that depends on iteration. For example, writing in History and English is about revision and clarification. I would therefore like to ask Professor Firestein what he thinks about other fields of study also depending on revision. Image Source I was interested in Professor Firestein’s discussion of time as providing the sense that the future continues outward. He explained that time is innate for humans but not for others. For what other creatures is some sense of time not innate? Does following circadian rhythms “count” as having a sense of time? What does it actually mean to have a “sense of time” and can that mean different things in different contexts? To watch the Prediction X interview with Professor Stuart Firestein, please see the link here!
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Emily Axelsen
Harvard GenEd 2021
Apr 24, 2021
In Wealth
The most surprising bit of information I learned during the Prediction X interview with Professor Stuart Firestein is that experiments are conducted at different rates in different fields of scientific study. I found it intriguing that Professor Firestein explained that experiments in Chemistry and Biology are often a lot shorter in duration than experiments in astronomy, for example. This, therefore, influences how different fields of science understand and prepare for the future. Connecting back to the course theme of prediction, astronomers may have to think through more long-term predictions as opposed to short-term predictions that might be more prevalent in chemistry and biology. Although I previously understood that different fields of science would have different types of experiments, I did not know that the duration of experiments could vary so drastically. Image Source Another section I found interesting in the interview with Professor Firestein is that science combines curiosity from childhood with skepticism from adulthood. In this way, science combines knowledge from two very different segments of life. To watch the Prediction X interview with Professor Stuart Firestein, please see the link here!
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Emily Axelsen
Harvard GenEd 2021
Apr 21, 2021
In The Future of the Future
After watching the interview with Professor Brendan Meade and Professor Susan Murphy, I had a few questions about data science and modeling in science. Although Professor Susan Murphy’s definition of data science as anytime scientists are using data to try to improve the field is useful in its simplicity, are there multiple ways to interpret “improvement”? Further, what one person interprets as “improvement” might be perceived by another person as an encroachment on their free will and personal choice. For example, self-driving cars are seen by many scientists as an “improvement” but many other people are not supportive of the concept of self-driving cars. I was interested in the idea that more interesting problems are often more complex. What are some examples where this is true? During the interview, I also wondered about fields other than science where “triangulation” can add additional meaning and understanding. Finally, in the process of experimenting and inventing new things, how do scientists continually find new areas of study after they understand a previous topic well? Image Source Here is the Prediction X interview with Professor Brendan Meade and Professor Susan Murphy!
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Emily Axelsen
Harvard GenEd 2021
Apr 21, 2021
In The Future of the Future
The most surprising bit of information I learned during the Prediction X interview with Professor Ned Hall are some of the negative implications of machine learning. Although I’ve often heard about the benefits of machine learning in media articles, it was insightful to learn that one of the negative elements of machine learning is that it can de-emphasize explanations. It was interesting to learn from Hall’s view that the final prediction is not the only benefit of the traditional framework because the understanding we receive from explanations is just as valuable. I agreed with Professor Goodman’s statement that we should avoid using machine learning blindly. In addition to separating what is important from what is convenient, I think scientists could also distinguish between the predictions that actually further a field of study versus simply add extraneous information. Image Source I was also intrigued by Hall’s comment that historical and religious influences can impact the type of explanations that are offered in the prediction framework. It seems to me that in the prediction framework, these historical and religious factors could play a role in both the observation, data, and explanation categories. I would be interested in learning more about the concept of the “real” scientific method and how predictions elad to experiments which lead to an eventual stopping point. Here is the Prediction X interview with Professor Ned Hall!
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Emily Axelsen
Harvard GenEd 2021
Apr 12, 2021
In Thoughts from Learners
If I had conducted the interview with Dr. Jill Tarter, I would have asked more about how we might be able to teach science in a way that does not encourage the idea that science is “solved.” Instead, how can we show that science is more about the unknowns than what we actually know? This also connects to Dr. Jill Tarter’s comment that scientists often don’t know what they’re looking for. She also shared the example of how scientists only learned that lightning moves upward when they developed high-resolution cameras. Further, Dr. Jill Tarter suggested that it can be challenging to determine what to look for if the more you know reveals how little you actually know. If scientists don’t know what they’re looking for, then how can they know when they’ve come across something notable? How can scientists decipher the commonplace from the extraordinary and develop tools that will help draw this distinction? I was also interested in Dr. Jill Tarter’s discussion of science fiction. Thus, could the use of science fiction help us teach science in a way that shows it is full of unknowns? Image Source To learn more about Dr. Jill Tarter’s life and work, please see the PredictionX interview here!
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Emily Axelsen
Harvard GenEd 2021
Apr 12, 2021
In Thoughts from Learners
The most surprising bit of information I learned when watching the PredictionX interview with Professor Avi Loeb is that the presence of uncertainty in science can actually improve our understanding of reality. Although I often think of science as definitive facts, I was surprised to learn that most of science is filled with uncertainty. I also found it intriguing that Professor Loeb sees uncertainty as a resource that helps scientists understand variations in the universe. Instead of referring to uncertainty as only quantifying what scientists don’t already know, Professor Loeb’s comments suggest that uncertainty can help scientists understand how far away something is from an accepted explanation, prediction, or theory. By exploring how systems work, such as the engine in a car, the interview with Professor Loeb demonstrated the importance of understanding the problem first. After understanding the problem, scientists can then apply data to create predictions in a directed way. Just as a side note, when I watched the interview with Professor Loeb, I was surprised by Professor Goodman’s comment that systems heal themselves in life sciences but not in physical sciences. I hadn’t previously thought about how different fields of science can recover at different rates and the relative stability of the universe. To learn more about Professor Avi Loeb’s work and prediction, please see the PredictionX interview here! Image Source
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Emily Axelsen
Harvard GenEd 2021
Apr 05, 2021
In Thoughts from Learners
Image Source After watching the PredictionX interview with David Laibson, I had a number of follow-up questions about the connection between individual choice and psychology. I agreed with Laibson when he explained that it can be hard to rationally make beneficial choices due to noise and poor advice. In order to make good choices, Laibson suggested that it can be helpful to experience an event multiple times to learn from any mistakes. Indeed, it is difficult to learn with limited experience which brings us to the first question I would ask Laibson if I had conducted the interview. Is there a way we can combine many people’s knowledge to provide the tools for many people to make better choices? Is this essentially the function of the Internet? Further, can researching and combining the knowledge of multiple people actually help us make better decisions? Should people learn about what the best choice might be or is it better for people to figure out the best choices for them on their own? This calls into question the role of societal structures and free will. Thus, should society step in to help people make better decisions? To watch the PredictionX interview with David Laibson, please see the link to the interview here!
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Emily Axelsen
Harvard GenEd 2021
Apr 05, 2021
In Thoughts from Learners
When I watched the PredictionX interview with Dan Gilbert, I was surprised to learn that there are numerous similarities between the past and the future. Gilbert’s statement that remembering is using imagination as a lens with which to look at the past especially intrigued me. I often think that imagination is more pertinent to the future because it is often connected with what we hope will happen. Further, although the past is limited by the presence of data, I enjoyed learning that we can also use our imagination to remember events from the past. After watching the interview with Dan Gilbert, I realized that we can perhaps change our memories by using our imaginations or use factual events to maintain an accurate view of the past. However, it is challenging to determine how happy something will actually make us. Therefore, does memory exist in the space between imagination and factual events in the past? Image Source I also found Gilbert’s statement about only looking for the good parts of the future surprising. When I think about the future, I find that I’ll sometimes only think about the bad parts, rather than avoiding them as Gilbert suggested. However, I agree that how we look at the future is determined by how we will react to future events instead of just what will happen. I also enjoyed learning about the connections between the past, present, and future. Although Gilbert explained that the future is often the focus of our thoughts because the present is a small moment and the past is no longer interesting because it’s over, I think that thinking about the past can be just as interesting as thinking about the future. Indeed, when I think about the past, I can imagine how things could have gone differently or what might have happened if I made a different decision. Just as Gilbert explained in the interview, imagination can be whatever we want it to be. To watch the PredictionX interview with Dan Gilbert, please see the link to the interview here!
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Emily Axelsen
Harvard GenEd 2021
Mar 31, 2021
In The Future of the Future
Image Source If I had conducted the interview with Ben Shneiderman, I would have delved more deeply into the discussion of AI and the rate at which new innovations are developed. I found it insightful that Shneiderman felt that the development of new innovations is too rapid and stressed the importance of building in protections. However, he did not provide an example of what these protections might look like. I would also like to learn more about how innovations in different industries might be able to accommodate different consumer preferences. Although innovations with loan mortgages are likely approximately the same for all consumers, people might have different levels of risk tolerance when it comes to medical devices for example. Further, what might the tradeoffs look like between the convenience and increase in accessibility that might come with new innovations and the risk of innovations not working in the way they are intended? Is there a way to quantify the risk of an unintended outcome actually happening? I also would have asked Shneiderman to include a few examples of protections for new innovations. My final question would be to ask Shneiderman how protections might be able to accommodate people who are comfortable with different levels of risk. Here’s a link to the interview with Ben Shneiderman!
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Emily Axelsen
Harvard GenEd 2021
Mar 31, 2021
In Health
When I watched the PredictionX interview with George Church, I was surprised to learn the reasons why people may or may not want to learn more about their genomes. While I can understand why it might cause people stress and anxiety if they know more about their genetics, I agreed with Professor Goodman that if someone else knows about my genetics then I would also want to know. Further, I would want to be able to conduct additional research on any genetic diseases that I had and contribute to the development of new medical findings by participating in medical studies, as Church also suggested. One specific piece of information that I found surprising is that 80% of the families who influence the gender of their child decide to have girls. I found Church’s comment that this fact is not consistent in all countries interesting and I would be interested in learning about how that statistic might vary across different countries. Image Source Although it might seem that different fields of science might have different modeling techniques, Professor Goodman suggested that methods of processing and understanding information are consistent across different fields of science. Therefore, I found it surprising that genome modeling and astronomy can have similar methods of 3D reconstruction. Just as a side note, I was interested in watching the interview with George Church because I recently read a Wall Street Journal article that discussed a recent World Health Organization report on the origins of COVID-19. The article, linked here, explained that genome analysis revealed that the COVID-19 virus was not purposefully developed in a lab. Here’s the link to the interview with George Church!
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Emily Axelsen
Harvard GenEd 2021
Mar 29, 2021
In Earth
If I had conducted an interview with Gina McCarthy, I would have asked a follow-up question to the ideas she shared when discussing the connections between psychology and climate change. I would start by asking about the connections between people’s everyday lives and lawmakers. For example, I would ask that given that people are more willing to act on events that are relevant to their lives and problems with probable solutions, how can lawmakers create policies that add relevance to climate change and work toward solutions? Further, which elements of new policies are most important: rhetoric, examples, consequences of inaction or something else entirely? In addition, it seems that an understanding of science is an important part of making change. Thus, how might institutions of higher education impart the importance of science to future policymakers and consider the implications of science during the policymaking process? And, how can policymakers present the science in ways that people care about and understand? To watch the PredictionX interview with Gina McCarthy, you can find it here!
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Emily Axelsen
Harvard GenEd 2021
Mar 29, 2021
In Earth
Although climate change can seem to be an insurmountable challenge, I learned that coordinated effort among the largest companies in the world could significantly impact the impact humans have on the climate. This brings us to the most interesting bit that I learned from the PredictionX interview with Rebecca Henderson: about 1,000 companies make up 70% of the world’s GDP. The interview with Henderson not only identified the number of companies that make up the majority of the GDP but also explained a method through which companies can evaluate uncertainty. I was fascinated to learn about the two-by-two matrix method of considering industry-wide uncertainties Henderson discussed during the interview. Despite its simple appearance, the two-by-two matrix method is an impactful way to visualize uncertainties. To create the matrix, Henderson explained that industry experts are first asked to choose which two uncertainties are most pressing by evaluating which questions would result in significant company changes. Next, she drew the matrix and wrote in the extreme scenarios for each question on either side of the matrix. After identifying the time frame, Henderson explained that the industry experts are then asked to generate the odds of each scenario. I found it intriguing that the generated odds pointed towards normal business functions. The process of creating an uncertainty matrix was especially surprising to me because it revealed how psychological limitations can impact the predictions individuals make. Although psychological factors can make accurate predictions more challenging, they can also allow people to evaluate their own biases and visualize alternatives. By writing down implications, firms may take tangible steps to confront climate change. This also reminded me of a later part in the interview where personal beliefs and employee opinions influence how companies think about climate change. Despite models that predict climate change with high levels of certainty, it seems that what people want to believe (i.e. with the financial crisis and physics models) and psychological limitations can often have outsized impacts on the course of events. To watch the PredictionX interview with Rebecca Henderson, you can find it here!
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Emily Axelsen
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