The most surprising thing that I heard in the Professor Firestein video was the discussion of our perception of time before the era of clocks. How did humans navigate their material world differently without a concerted sense of time? Firestein's mention of the annular and cyclic vs the longitudinal and linear was really interesting in terms of illustrating an overarching shift in human perception. I wonder how future technologies may continue to change our basic understanding and means of interacting with the world around us. I found Professor Firestein's Ignorance course to be a really fascinating parallel to this class with Prof. Goodman which had me thinking about the connection between our lack of knowledge/the undiscovered and the nature of prediction. While these have been put in the unknown unknowns slot in the context of this class, I wonder if the ignorance framework considers time more or less in the process of discovery. Does the act of predicting initiate a discrete process where the process of ignorance to knowledge acquisition is more gradient-like and as such lends itself to a different way of looking at science and uncertainty in general? These questions were definitely floating around their conversation. Video

The conversation of earthquake modeling reminded me in many ways of our discussion for modeling alien life and extraterrestrial contact. Meade comments on the complexity of the polycrystalline aggregates, for example, which comprise just one aspect of the uncertainty and difficulty entailed in predicting earthquakes. This, like our data collection on the cosmic microwave background, seems to be a trove of rich data information but may be too complex for our modeling and understanding to fully interpret intelligibly. Meade comments optimistically on the usage of deep learning and AI to modify the predictive models levied to forecast earthquakes which also had proliferative impacts that benefited other infrastructural sectors of society. I was wondering how trying to solve the problem of alien life might benefit us in other parts of society that we might not foresee right now. I had a question for professor Murphy in her endeavor to apply statistics to bolster mobile health insights. The concept of hypothesis-free science seems to fly in the face of some probabilistic modes of thinking but immensely useful for approaching conundrums with several unknowns unknowns. I was wondering to what extent can we aggregate data to recognize features in useful ways? Again how do we make the data that we encounter using these deep learning models useful to the people that didn't develop them or simply the most amount of people period?

Professor Loeb's discussion of uncertainty especially its importance to the study of astrophysics and science more broadly raised a few interesting points regarding predictive models. Discriminating between stable and unstable systems was interesting in Loeb's framework especially when integrated with AI applications. The concept of opening up the hood to both stable and unstable models to better understand how things like AI may work was so interesting. Have we fully opened the hood of medical studies? Can we ever completely figure out life sciences if we determine the underlying determinants and initial conditions? It seems that professor Loeb would support the blue sky research camp that emphasizes uncovering these fundamental natures of reality, as such, how do we ever know what we don't truly know? Link

I have always associated the exploration of the stars, no matter how precise and reasoned it may be, with the realm of the futuristic and science-fiction. As such, Jill Tarter's description of the potential futures we may encounter through advances in technology and the exploration of space especially deep space were really interesting. In particular, the notion that this century is the century of biology both on Earth and in space was intriguing for the potential Tarter seemed to be suggesting for contact or at least advances towards understanding extraterrestrial biology. If this indeed is the century for biology here and beyond, I am excited to see the advances considering physics came from Laplace to landing on comets! Here is the link to Jill's video.

Gilbert's perspective on social change from an organizational/institutional perspective was really interesting. The herd animal standpoint seems to work for getting people to recycle but how far can we take that method of persuasion. As Gilbert notes, fear will only get you so far in terms of getting people to work together for the common good. However, making it easy to recycle seems to be an essential part of what Gilbert was discussing, when everyone is doing something it makes it easier to do it yourself. So how do we start to turn our society holistically towards a more climate-conscious lifestyle? What infrastructural changes would make it easiest for the most people to have the most impact? 2. David Laibson's synthesis of machine learning and machine learning when discussing prediction of the stock market was really interesting. I liked how Professor Goodman injected considerations to the fact that humans may want explanations for market forecasts beyond what a machine may be able to provide. I would have liked to ask professor Laibson if he sees any long term implications or changes coming to the stock market with this huge influx of ai.

In Ben Shneiderman's interview with Prof Goodman he discusses the potential ethical issues in Microsoft algorithms to which Goodman argues these early technological advancements are just precursors to the actual operable technology. While I have no doubt that Tesla's current self driving cars can be appropriately compared to the Apple Newton, I am concerned with the idea that the ends justifies the means. As Grace indicated in her post, excessive reliance paired with intrinsically discriminatory AI for example, raises concerns about unfair hiring practices, and as such the damage of improving these systems in public contexts could presage serious social harms. I felt that Ben appropriately linked the tool or instrumentality of AI to the creators underlying them--primarily large corporations--who should first and foremost be held accountable, morally and financially, for the damages they incur. As more and more people begin to understand the implications of AI automation on neoliberal capitalism, I believe points like those made by Shneiderman will grow even more salient. Interview here Listening to professor Church discuss the issues of personal genomics really opened my eyes to our intensely personal relationship we all have to our genetics despite our amazing ability to model them on large scales. If I had given the interview I would have asked professor Church about how the nature vs nurture debate has evolved in light of advances in gene sequencing and modeling. Further I would love to understand better how possible modeling future trends in genomes is or could be in the coming years. Interview here

Professor Henderson's entire interview felt very future-forward and insightful on both the public health and climate fronts notwithstanding her grounding in business and economics. Her view that economic stimulation can be gleaned through heavy emphasis on education and healthcare invigoration rather than consumer spending was particularly interesting. Resisting the proclivity to adhere to a kind of techno fanaticism as described in the interview, I think that her breakdown struck a balance between additive value resulting from technological innovation as well as the innumerable value of intrinsic human potential as maximized through education and sustained through healthcare. While I do think that technologies like fusion may be a useful tool to address issues like climate change, it felt that Prof. Henderson wanted to emphasize that the most important factor in the climate change issue is the deployment of human capital and the knowledge of those humans rather than firm level innovation. https://www.labxchange.org/library/pathway/lx-pathway:825945a0-367c-45dc-82b7-3d160c6e6f7a/items/lx-pb:825945a0-367c-45dc-82b7-3d160c6e6f7a:lx_simulation:6e9eaf62?source=%2Flibrary%2Fclusters%2Flx-cluster%3AModernPrediction. During the discussion with Dan Kammen there was a discussion about social media and the impacts of emerging technologies/data collection methods on the climate and climate activism. If I were giving the interview I would have asked if there were other emerging digital technologies, e.g. cryptocurrency, that had unforeseen benefits or detriments to the environment. I have always wondered what kind of footprint the internet has on the physical world and felt that this discussion revealed some insights but could have gone deeper given more time. I also think that all of these technologies will soon become so intimately enmeshed with our daily lives as citizens that education about these things will become integral to good citizenship as well. https://www.labxchange.org/library/pathway/lx-pathway:825945a0-367c-45dc-82b7-3d160c6e6f7a/items/lx-pb:825945a0-367c-45dc-82b7-3d160c6e6f7a:lx_simulation:fa741ca2?source=%2Flibrary%2Fclusters%2Flx-cluster%3AModernPrediction.