A collaborative space for emerging scholars and innovative thinkers to share and develop research on the evolution and governance of transformative technologies.
The goal of this paper is to present an intuitive summary of computational learning theory, and its application for analyzing the most popular learning algorithms in machine learning, neural networks.
Despite the adoption of various patent-based mechanisms, the inadequacy of patent systems in incentivizing green technology is well documented and persists. A potential solution to capture more positive externalities associated with green technologies involves the implementation of a patent prize system, also known as a “patent reward.”
While significant research has focused on the economic and technological aspects of central bank digital currency, the governance perspective has not received enough consideration.
Technology-facilitated gender-based violence (TFGBV) is a pervasive aspect of digital societies and requires urgent and innovative solutions, which include the adoption of smart regulations. The EU Digital Services Act is a recent example; however, challenges that may jeopardize its potential for success in addressing TFGBV must be addressed.
Climate change is the quintessential global challenge, while also perhaps the issue that has experienced the most polarization in recent years. New policies and approaches for policy development and implementation will be required to match the alacrity of the proliferating online flows of misinformation and disinformation.
An institutional framework for global artificial intelligence (AI) governance should incorporate lessons from international organizations to guide AI’s ethical development and deployment within and beyond national borders.
This paper presents the proposition for a gig economies living lab model that potentially serves as a hub and space for multi -stakeholder research, data gathering, cooperation, engagement and innovation.
With the surge in generative artificial intelligence (AI) models, voice cloning bots are rapidly surfacing, allowing users to replicate the voice of any artist or celebrity of their choice. This working paper deciphers the use of AI in creative fields and provides some recommendations on policy developments.
Research institutions, for example, research libraries, archives and universities, are an essential part of society that are at high risk for artificial intelligence (AI) adoption within basic systems such as search and cataloguing functions. This working paper surveys existing policies for AI in universities, ethical frameworks for library and archive associations, and existing international and national policies that are relevant to helping to construct a policy framework based on existing norms, practices and values.
Large language models through generative artificial intelligence (AI) offer a unique opportunity to bridge linguistic gaps for international students, assisting non-native English speakers while minimizing universities’ costs. This paper also explores the ethical considerations of their usage and suggests a university policy framework for responsible generative AI use in academic settings.
