Learner Posts and Discussions

how the interview relates to your chosen final project topic. My project is about predicting sea level rise in New York City, so this interview was quite enlightening because it discussed climate change and climate policy. Gina McCarthy's discussion about a climate change "silver bullet" was really

My final project is about the uncertainty related to galaxy collisions. In this interview, Jill Tarter talks about how scientists were at one point sure that the most likely method to discover communication from aliens would be through radio waves, but as our technology has advanced, we've found tha

The most surprising bit of information I learned from the excerpt is the concept of a course called "Ignorance" taught by a professor at Columbia University. This course focuses on what scientists don't know rather than what they do know, which challenges the traditional approach to teaching sci

I think the most interesting part of this interview was the connection between computational abilities and genomic sequencing. I’ve previously been exposed to the idea of a law, more specifically Moore’s law, governing the advancement of computational ability over time. The link between the ability

It was interesting to reflect upon the theory, mixed, and pure data aspects of Professor Henderson's discussion. I think something that was missing from her talk was more discussion on the extent of lag that we see between the economic theory that demand will create supply, which we see today with t

Identify and explain (in a paragraph) the most surprising bit of information you learned. The most surprising bit of information I learned in the Population Genetics interview was that risk factors for certain diseases and epidemiological disorders can vary widely, and aren't always just genetic. F

I chose to watch the behavioral economic interview with David Laibson. My topic is online poker, which involves an interesting combination of pure game theory and human irrationality. While online poker is typically more mathematical in nature than traditional poker, its outcomes are still very much

One thing I will remember most about this interview a year from now is that AI is not as special as we think it is. They are just tools that empower human beings. Yes, they may seem to have mental human-like capabilities, but this is because humans trained them on enormous amounts of data. After all

https://docs.google.com/document/d/11RRzvlVLmUNPv3y6n3gkqJJQnrL0O0sj/edit  What do you, personally, think you will remember most about this interview a year from now?  A year from now, I’ll remember Lord Martin Rees’ thoughts on the interplay between private and public funding for space explorati

What do you, personally, think you will remember most about this interview a year from now? • I had no idea about Bayes' theorem before watching this interview. Now, with a better understanding of how probability works and affects our daily lives, I can make more informed decision making in my futu

I really enjoyed watching the interview with Gina McCarthy and learning a lot about climate change and climate policy. I thought that the most surprising piece of information was in their discussion about what a proposed "silver bullet" for climate change would be. While I was expecting at least som

I thought these interviews were very informative in providing diverse perspectives on understanding scientific inquiry and communication of delivering such findings. For example, Firestein emphasizes the value of embracing uncertainty and re-examining/repeating experiments to progress scientific kno

Identify and explain (in a paragraph) the most surprising bit of information you learned: I thought the story behind how life insurance was invented was fascinating— I had no idea the same Halley behind Halley’s comet was the one who laid the foundation for tabulating annuities and determining life

What is most important about statistical inference and our decision making is that the latter constantly burdens the former. In order to lessen the daunting weight of uncertainty in prediction, we must iteratively update our priors. Doing this makes our decisions more relevant , though not necess

(Making this forum post because I missed the in class discussion on 4/17) McCarthy talks a bit about the psychology of climate change and her theory about why people don't respond to it as much as, say, a public health crisis is because it's pretty invisible on the short time scale. In addition, the

In Ben Shneiderman’s interview, he spoke about many concepts that lie on the spectrum of theory and data. His main goal was to emphasize that AI and machine learning only work because humans create programs based on their own theory. This is why he warned that if an AI machine ever gets to a point w

In this interview, we explored both theory-driven and data-driven points regarding disease predisposition. Theoretical insights highlighted the multifaceted nature of genetic predisposition, emphasizing that it is influenced by a combination of environmental, lifestyle, and genetic factors. By consi

link: https://docs.google.com/document/d/11RRzvlVLmUNPv3y6n3gkqJJQnrL0O0sj/edit?usp=sharing&ouid=107129726799581308318&rtpof=true&sd=true One thing that stood out to me in this interview is the discussion on public awareness of climate change. I think that although more and more people are becomin

https://docs.google.com/document/d/1gTK8TOV0MD-gJc-oCinToR0c3XsQm4ee/edit What I will remember about this interview a year from now is the investigation into how human expectations influence scientific inquiry. The discussion focused on how our preconceptions and prejudices might affect how we re

What do you, personally, think you will remember most about this interview a year from now? Personally, in a year from now I think I will remember the conversation around the challenges and the opportunities presented by future pandemics and the role that cooperation can play to address global crise

Alyssa Goodman's interview with Megan Murray, a leading epidemiologist, revealed interesting details about forms of data collection and changing predictions based on individual or governmental actions. Murray discusses the importance of considering individual risk factors when modeling disease preva

The most surprising information I learned was about the Brain Initiative and the comprehensive approach that it takes to understand the brain. I found it fascinating how the project collects and integrates data on multiple aspects of brain function and structure, including activity (how the brain

A part of my final project on the predictive models in soccer is related to people’s understanding of the predictive model. Ultimately, the nature of this model is partly social. It is not as important to people’s lives as weather forecasts are but it is an important part of one’s social experience

Explain (In a paragraph) how the interview relates to your chosen final project topic. Ned Hall's distinction between rules and theories can be related to people making predictions and placing bets during March Madness. When people make predictions and place bets during March Madness, they often re

One of the most surprising parts of this interview was about Google's venture into using search trends to predict flu outbreaks yielded an unexpected twist: despite the promising theory, the program failed to accurately anticipate flu activity. This outcome serves as a stark reminder of the limitati

The most surprising bit of information I learned from this interview was the process by which gene therapy occurs. I had no idea that these “nanocatalysts” were programmed by computers to target one particular place in the body and treat the disease. I was also amazed that you could take cells out o

What do you, personally, think you will remember most about this interview a year from now? I think I will remember the conversation about the role of "rules" vs "theory" in scientific progress, and the perspective of being cautious when using machine learning/AI for predictions. The discussion abo

I remember taking CS50, Introduction to computer science, in the spring of 2022 where during every lecture, we would spend a few minutes discussing the ethics of computer science. This has been a topic which I found important then and would to this day revisit sometime. In this interview, Professor

One thing from this interview that I will likely remember in a year from now is how Firestein mentions that "it wasn't until [he] got to graduate school that [he] realized people cared more about what questions [he] had then what crap [he] knew" (16:15). This was particularly interesting to me becau

What do you, personally, think you will remember most about this interview a year from now? After watching this interview, my biggest takeaway was understanding how important mathematicians and scientists are when presenting statistical information to the public. Using complicated jargon like mathe