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A place to talk about Economic Modeling, Behavioral Economics, Corporations & how these affect Wealth.
Whether you're studying at Harvard or online, please feel free to add posts that don't fit in other categories here!
A place to talk about the Future of the Future pathway, especially about AI and the evolution of modern predictive systems.
Here's a spot where you can add thoughts about what you'd like added to the Prediction Project in the Future!
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- DiscussionThough the interview with Susan Murphy and Brendan Meade introduced me to a number of new ideas in the prediction of "earth" and "health," I was most surprised to learn about the existence of mobile health itself. I initially thought that this would mean something in the vein of mobile health clinics, but to find that Professor Murphy's work entails a collaboration between wearable sensors and mobile phones was very interesting to me. I also appreciated the discussion on the distinction between predictions on the level of the individual and on the level of society. Professor Murphy makes the point that convincing individuals, (and especially willing, goal-oriented participants utilizing mobile health) can be easier than convincing a society to consider the future or consider some prediction. This makes me wonder about the role of goals in prediction, and if having a goal makes it more likely for people to consider the future in a productive way. (On another, more rambling note- in my prediction journal, my "predictions" about how quickly I could get an assignment were based in data/past experiences, but there was also an element of goal-setting or even hope in there- as in, "I'm predicting it'll take me X hours to do all these readings, but I really hope it will take me that long or less so I can have more free time." Though this doesn't relate to the more quantitative and real-world predictions we're discussing in class, hearing from Professor Murphy reminded me that that assignment prompted me to wonder about potential blurring between predictions, goals, hope).0
- DiscussionWatching an informative interview with Brendan Meade and Susan Murphy , several questions came to mind. First, I would be interested in asking Professor Meade to talk more about the Sendai "semi-prediction." Given that preparing for earthquake recovery is often more feasible than preparing for an earthquake itself, and given that the timeline for his predictions is so uncertain, how are those kinds of predictions handled? Who is the audience for his research?- Does his work reach policy-makers? I am also curious about the response to the paper predicting the Sendai area as a risky one, both before and after the earthquake happened. Second, I would want to hear him expand on what he thinks the future of earthquake prediction will look like, as I found it interesting about how much unknown there is in the world of earthquake prediction. A couple of times he mentioned that we may not be smart enough to fully understand the physics yet, or that we do not know how much data is truly needed to make earthquake predictions. Do he and his peers think this will be ever known? And if or once these unknowns are fully known, would we even know what to do with that new information? Finally, just because I had never heard this characterization before, I would ask him to explain what it means for probabilistic seismic hazard assessment to be "intellectually broken"- how does a field recover from that?0
- DiscussionMeade : Obviously natural disasters are not preventable but their impacts can be reduced with the help of data science and engineering. Earthquakes can be extremely disastrous especially as we saw in Japan when nuclear powerplants fall near fault lines and are unprepared to face the damage and earthquake may cause. If we are trying to design a nuclear power plant, what magnitude earthquake should be the baseline for it to survive? Would it be possible to simulate this?0