Zoe Nie

For the NSF REU internship, we looked at the field of blockchain, smart contracts and ICOs. To be specific, we went through the major and interesting startups that participated in ICOs, looked at their white papers and recorded the essential information in a white paper “database”. Furthermore, we read and talked about some related literatures which exposed us to the anthropologic view on the field of blockchain. In addition, we did code walkthrough on particular projects to explore how the blockchain projects are designed and written in Solidity. In the end, we did a presentation which concludes our findings and perspectives.

This experience helped me learn more about the field of blockchain technology which I was not familiar as it’s a relatively new technology. The experience also gave me the opportunity to know many wonderful people, Professor Maurer, our mentor Farah, Manager Jenny, my coworkers, etc. Moreover, I learned how to look at events and renovations in social science point of view, and I enjoyed discussing about its social effects of technologies and policies in an open environment.

The internship is indeed quite interdisciplinary, as it brings computer science undergrads with Anthropology mentors looking at Blockchain, which has major impact not only in the field of computer science but also in the field of politics and economy. In the project, we had lots of discussion on the recent news and reality, at the same time, we had code walkthroughs where we present our findings from the code of actual projects, which we find on GitHub.

In Computer Science, we usually only discuss about things related to the code and the architecture of the project, but in this internship, we got the opportunity to learn about each other’s view towards many things in this world, especially about Blockchain technology. It enabled us to look at the field in general and actually think about the moral and effect of projects. Happily, it also brings us closer in this way, bringing out a better working atmosphere.


Aditesh Kumar

Over the four or so months I worked on the NSF REU, I gained a bleak new perspective on the world of cryptocurrencies and learned a new approach towards analyzing evidence in a qualitative manner.

Prior to starting my work on the project, I had some experience developing dApps on the Ethereum blockchain, but I had not explored the community surrounding cryptocurrency in much detail. Going into the project, I expected that the communities would have started to become relatively stable, given the large cryptocurrency craze that had occurred less than a year prior. However, I was surprised to find the cryptocurrency space bloated with opportunists and incomplete products, as well as an abundance of eccentric leaders that often clashed with each other, leading to a highly volatile environment. There were plenty of smaller currencies that failed to offer any meaningful development over the main blockchains, which were clearly created by individuals rushing to cash in on the cryptocurrency boom. Furthemore, there were some currencies that made extremely vague and unrealistic promises about their product, and what they could accomplish with funding. Their claims were so unfeasible that we spent a good amount of time covering its issues in the presentation where we covered our findings. Moreover, when I did my code walkthrough on the clash that led to the split between Bitcoin Cash and Bitcoin SV, I discovered a lot about the politics of the cryptocurrency community, which further contributed to the cynical view of the cryptocurrency space I developed while working on the REU.

On the more positive side, I learned interesting ways of breaking down the data we collected over the course of the project. The data we collected was less quantitative than qualitative, which meant traditional methods like the regression tests I was used to, were out of the picture. Analyzing the data in more qualitative ways, specifically focusing on categorizing currencies and different ways and noting unique qualities of each coin, helped me discover a new technique for finding relationships between the currencies and trends in the data. Additionally, when making observations in the first place I was forced to consider the bias in the news sources in more detail, as there were a few large players who owned the main news sources specifically target at the cryptocurrency community. I felt that was a useful skill to have further trained, which I had not developed much in the past.

Aside from those more specific details, I felt working on the project itself was really interesting as everyone else’s perspective on certain sources we found often differed from my own, and being able to hear those perspectives was quite valuable. Additionally, I received the opportunity to learn a good amount about anthropology and social science in general through the different readings we did over the weeks, definitely piqued my interest in the field.


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