In Peer Prediction Mechanism , I (Charles Adjovu) introduced the aforementioned mechanism for eliciting truthful information from participants when there is no ground truth, areas of application for the mechanism in Web3 (i.e., blockchain) and beyond, and a short list of supplementary readings on the mechanism.
In this conversation, I talked with Dr. Kensuke Ito, Project Researcher at the Endowed Chair for Blockchain Innovation at the University of Tokyo, Tokyo, Japan, to discuss how he got interested in Web3 and his research on applying the Peer Prediction mechanism to decentralized oracles.
The interview transcript proceeds with the speaker as the heading and their response in the following line as normal text.
How did you get interested in Web3?
I got interested in Web3 after reading Satoshi Nakamoto's whitepaper, Bitcoin: A Peer-to-Peer Electronic Cash System  in 2015.
I had heard of “Web3” and “Cryptocurrencies”, but at that time, I thought they were research fields in other disciplines (e.g., computer science, cryptography) and not relevant to me.
However, Nakamoto's whitepaper taught me that the Bitcoin protocol, especially its mechanism for consensus-building on the legitimacy of transaction records, is based exactly on my backbone, economics.
Since then, the concept of Web3 has suddenly seemed familiar to me.
Very cool. I think that people are starting to become more aware of the fact, especially with decentralized finance and the work of organizations like Blockscience , that the blockchain is a great environment for creating new economic systems (and simulating systems you could not reasonably run in real life).
Yes, I think you are absolutely right. Especially from the standpoint of economics, cryptoeconomics looks like a huge frontier, like a new continent.
How did you get interested in the Peer Prediction mechanism?
I got interested in the Peer Prediction mechanism after conducting a literature review in 2018.
One of my research topics on the Bitcoin protocol was to extend its decentralized consensus-building from objective information inside the blockchain (i.e., transaction records) to subjective information outside the blockchain (e.g., the quality of an academic paper).
This subject has already been discussed as a so-called decentralized oracle, but several challenges still remain for its widespread adoption (e.g., Keynesian beauty contest ).
As a result of the literature review, I strongly felt that the Peer Prediction mechanism would be the best solution to the challenges of the decentralized oracle, in that it can offer the maximum reward to peers who report their true beliefs on subjective matters.
I found it interesting that your consensus-building process used a network-based recommender (Personalized PageRank) for the curator assignment to avoid the issues associated with token-staking.
Do you think there is too much of an emphasis on using staking for task assignment in Decentralized Applications (DApps) , rather than using other methods like your network-based recommender?
I do not think so, especially since staking is probably one of the simplest means to task assignment. The token-staking scheme would be worth emphasizing as a first step for DApps.
On the other hand, as the content of the task becomes more specialized (e.g., peer-review of academic article, critique of a work of art), we will probably need to combine other measures besides staking. It could be the citation graph that my studies dealt with, or it could be the so-called social graph, token graph, or other reputation scores.
In other words, in the process of making DApps more generic, we will need to extend the token-staking scheme in task assignment.
And needless to say, there are still some challenges in using token-staking for consensus-building rather than task assignment.
Do you mind discussing your paper, Token-Curated Registry with Citation Graph ?
In my article introducing the Peer Prediction mechanism, I included the paper as part of the readings under supplementary material.
I really liked your paper for primarily three reasons. First, because it shows the interdisciplinary understanding required for developing a blockchain DApp. Second, you attempted to resolve the inability for decentralized oracles to handle subjective information by applying the Peer Predication mechanism to a Token-Curated Registry (TCR) . Lastly, the use of a decentralized oracle for peer reviewing academic papers aids in showing that blockchain can be very beneficial to incentivize researchers to engage in open science practices.
My paper, Token-Curated Registry with Citation Graph , is the main output on the application of Peer Prediction mechanism to one of the decentralized oracles―Token-Curated Registry.
This paper aims to incorporate the expertise of (anonymous) peers into the consensus-building of decentralized oracles, by leveraging not only the Peer Prediction mechanism but also citation relationships among intellectual products.
Please refer to the following slides for the specific process of consensus-building: Token-Curated Registry with Citation Graph .
I see that you recently published your thesis. Do you mind also discussing your thesis?
Consensus-Building on Citations in Peer-to-Peer Systems  is my Ph.D. thesis, which consists of several papers, including Token-Curated Registry with Citation Graph .
This thesis also covers the Peer Prediction mechanism and consensus-building on subjective (and technical) information, even though its story focuses on citation relationships rather than decentralized oracles, due to conflicts with other papers.
The full-text is available to anyone, so I would be very happy if you could read, comment, and cite my latest output.
What are your thoughts on how blockchain can develop novel incentive mechanisms for open science?
First of all, I am very positive about the potential of blockchain for open science.
My proposals in Token-Curated Registry with Citation Graph and Consensus-Building on Citations in Peer-to-Peer Systems are clear examples of how blockchain can incentivize researchers to engage in open science practices.
Moreover, in a slightly different context from open science, the project #FREEHAWAIIPHOTO  proposes another approach that makes photos available to anyone once they are sold as Non-fungible Tokens  (NFTs) (i.e., this project assumes that the more widely the photos are used, the higher the value of corresponding NFTs).
These are examples of how we can leverage blockchain to make open access and rewards for creators compatible.
I would like to emphasize above all that blockchain can be a technology for open science (by balancing open access and rewards for creators) depending on its incentive design, although it is often interpreted as a technology that leads to the occupation of digital data, partly due to the recent NFT boom.
Do you think one of the reasons why we have not seen many blockchain and open science projects make significant headway is because of their lack of understanding on why and when to use a blockchain?
Or that the problem they intend to address cannot readily be solved with a blockchain?
I think it is both. On the one hand, there is still a lack of public understanding of blockchain, and on the other hand, people who know a lot about blockchain seem to have a hard time designing innovative DApps (probably because designing them requires interdisciplinary knowledge, such as computer science, economics, and cryptography).
Therefore, we should promote blockchain awareness and exchange of researchers between different fields in parallel.
Thank you for reading the article!
If you have any questions, comments or concerns, please DM me on Twitter or send an email to firstname.lastname@example.org.
You can find Dr. Kensuke Ito on the web via the following links:
- Blog: https://knskito.com/
- Twitter: https://twitter.com/knskito
- Google Scholar: https://scholar.google.com/citations?user=bQTxPTMAAAAJ&hl=en&oi=ao
- LedgerbackØDCRC. “Peer Prediction Mechanism.” Greyscail Blockchain Review, 25 Dec. 2020, https://medium.com/greyscail/peer-prediction-mechanism-9004f53a6b5d.
- Nakamoto, S. “Bitcoin: A Peer-to-Peer Electronic Cash System.” (2008) (accessed 3 December 2019) https://bitcoin:org/bitcoin:pdf.
- BlockScience. https://www.block.science/. Accessed 23 Dec. 2021.
- “Keynesian Beauty Contest.” Wikipedia, 9 Dec. 2021. Wikipedia, https://en.wikipedia.org/w/index.php?title=Keynesian_beauty_contest&oldid=1059457029.
- “What Are Decentralized Applications (DApps)?” Investopedia, https://www.investopedia.com/terms/d/decentralized-applications-dapps.asp. Accessed 23 Dec. 2021.
- Ito, Kensuke and Hideyuki Tanaka. “Token-Curated Registry with Citation Graph.” Ledger 4 (2019): n. pag.
- “What Is A Token Curated Registry.” District0x Education Portal, https://education.district0x.io/general-topics/understanding-ethereum/token-curated-registry/. Accessed 23 Dec. 2021.
- Ito, Kensuke, Consensus-Building on Citations in Peer-to-Peer Systems (August 27, 2021). Available at SSRN: https://ssrn.com/abstract=3936833 or http://dx.doi.org/10.2139/ssrn.3936833
- “#FREEHAWAIIPHOTO.” #FREEHAWAIIPHOTO, https://www.freehawaiiphoto.com. Accessed 23 Dec. 2021.
- “Non-Fungible Token (NFT).” Investopedia, https://www.investopedia.com/non-fungible-tokens-nft-5115211. Accessed 23 Dec. 2021.