Our Case Study Queue...

We view science fiction as mythology for the industrial age. Mythology is not merely a collection of fantastical stories, but provides many archetypal characters, situations, problems and solutions to help people navigate through the world. Magic and fantastical elements often allow for more directly exploring important philosophical concepts. Science Fiction uses many of the same tools and, whether intentionally or not, seems to have filled a similar niche for helping audiences understand and navigate the world of tomorrow. We intend to research the history of science fiction with a focus on understanding how different waves of scifi have varied in their ability to fill this niche.

Campbell's "Hero's Journey" and other frameworks for storytelling are common guidelines today, but seem to create homogeneity in stories. Many old stories from centuries past can be very strange by modern standards. There are also modern examples of storytelling - from environmental storytelling in video games to works such as the SCP Wiki - which are evidently very compelling to modern audiences but that do not fit into conventional guidelines. We plan on studying stories from centuries past to look for storytelling techniques that may have been forgotten or downplayed.

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Manufacturing automobiles is a uniquely difficult problem. Immensely complex machines must be produced, made at low enough prices and high enough volumes to be available to common people, the culture had to be terraformed to give people a reason to travel long distances frequently, and political strings had to be pulled to enable vast road networks. While other industries have faced similar problems, few have faced a combination of these problems and on such scale. There are many tactics made by companies such as Michelin and Ford that seem outside of the common entrepreneur's toolbox today that may inform the origins and roadmaps of difficult-but-impactful industries of the future.

Modern discourse around AI is very obsessed with what AI can or could do, but seems to have very few arguments that can constrain it in terms of what it can't do. This creates discourse that has no way of countering completely absurd ideas about AI capabilities. However, there has been a significant amount of theoretical research in recent decades regarding the fundamental limitations of learning algorithms and related computational tools. Much of this research suggests that machine learning and cryptography are opposing fields; the situations where you can securely hide information are also situations where it is fundamentally difficult to extract patterns through learning. We aim to make the results of this research more accessible to audiences without the deep theoretical knowledge that such papers assume in order to give the public and our writers better tools for discourse around AI. Further, adjacent fields such as SAT solvers may offer alternative perspectives on the dynamics of such complex tools without their behavior being as obfuscated by black-box algorithms.

While physical constraints and human ingenuity are often seen as the limits of innovation and technology, the systems that influence where resources are allocated to and what technologies and scientific insights get the most attention and status also play a significant role. While far from the whole picture, Venture Capital plays a major role here and is worthy of study. This covers the financial tools involved and their various strengths and weaknesses, as well the worldviews and information systems that influence the human decision-making that ultimately guides these financial tools.

Have an idea for us to peruse/pursue? Want to do a cast study with us? Drop us a line!

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