Publication Library
Smart Blockchain Networks Revolutionizing Donation Tracking in the Web 3.0
Description: A donation-tracking system leveraging smart contracts and blockchain technology holds transformative potential for reshaping the landscape of charitable giving, especially within the context of Web 3.0. This paper explores how smart contracts and blockchain can be used to create a transparent and secure ledger for tracking charitable donations. We highlight the limitations of traditional donation systems and how a blockchain-based system can help overcome these challenges. The functionality of smart contracts in donation tracking, offering advantages such as automation, reduced transaction fees, and enhanced accountability, is elucidated. The decentralized and tamper-proof nature of blockchain technology is emphasized for increased transparency and fraud prevention. While elucidating the benefits, we also address challenges in implementing such a system, including the need for technical expertise and security considerations. By fostering trust and accountability, a donation-tracking system in Web 3.0, empowered by smart blockchain networks, aims to catalyze a profound positive impact in the realm of philanthropy.
Created At: 05 December 2024
Updated At: 05 December 2024
A combined network and machine learning approaches for product market forecasting
Description: Sustainable financial markets play an important role in the functioning of human society. Still, the detection and prediction of risk in financial markets remain challenging and draw much attention from the scientific community. Here we develop a new approach based on combined network theory and machine learning to study the structure and operations of financial product markets. Our network links are based on the similarity of firms' products and are constructed using the Securities Exchange Commission (SEC) filings of US listed firms. We find that several features in our network can serve as good precursors of financial market risks. We then combine the network topology and machine learning methods to predict both successful and failed firms. We find that the forecasts made using our method are much better than other well-known regression techniques. The framework presented here not only facilitates the prediction of financial markets but also provides insight and demonstrate the power of combining network theory and machine learning.
Created At: 05 December 2024
Updated At: 05 December 2024
Mapping Philanthropic Support of Science
Description: While philanthropic support for science has increased in the past decade, there is limited quantitative knowledge about the patterns that characterize it and the mechanisms that drive its distribution. Here, we map philanthropic funding to universities and research institutions based on IRS tax forms from 685,397 non-profit organizations. We identify nearly one million grants supporting institutions involved in science and higher education, finding that in volume and scope, philanthropic funding has grown to become comparable to federal research funding. Yet, distinct from government support, philanthropic funders tend to focus locally, indicating that criteria beyond research excellence play an important role in funding decisions. We also show evidence of persistence, i.e., once a grant-giving relationship begins, it tends to continue in time. Finally, we leverage the bipartite network of supporters and recipients to help us demonstrate the predictive power of the underlying network in foreseeing future funder-recipient relationships. The developed toolset could offer funding recommendations to organizations and help funders diversify their portfolio. We discuss the policy implications of our findings for philanthropic funders, individual researchers, and quantitative understanding of philanthropy.
Created At: 05 December 2024
Updated At: 05 December 2024
Blockchain in a nutshell
Description: Blockchain enables a digital society where people can contribute, collaborate, and transact without having to second-guess trust and transparency. It is the technology behind the success of Bitcoin, Ethereum, and many disruptive applications and platforms that have positive impact in numerous sectors, including finance, education, health care, environment, transportation, and philanthropy, to name a few. This chapter provides a friendly description of essential concepts, mathematics, and algorithms that lay the foundation for blockchain technology.
Created At: 05 December 2024
Updated At: 05 December 2024
The Ethics of Advanced AI Assistants
Description: This paper focuses on the opportunities and the ethical and societal risks posed by advanced AI assistants. We define advanced AI assistants as artificial agents with natural language interfaces, whose function is to plan and execute sequences of actions on behalf of a user, across one or more domains, in line with the user's expectations. The paper starts by considering the technology itself, providing an overview of AI assistants, their technical foundations and potential range of applications. It then explores questions around AI value alignment, well-being, safety and malicious uses. Extending the circle of inquiry further, we next consider the relationship between advanced AI assistants and individual users in more detail, exploring topics such as manipulation and persuasion, anthropomorphism, appropriate relationships, trust and privacy. With this analysis in place, we consider the deployment of advanced assistants at a societal scale, focusing on cooperation, equity and access, misinformation, economic impact, the environment and how best to evaluate advanced AI assistants. Finally, we conclude by providing a range of recommendations for researchers, developers, policymakers and public stakeholders.
Created At: 05 December 2024
Updated At: 05 December 2024