While some industries thrived during pandemic times, such as tech giants and wet wipes manufacturers, many were hit hard by them, and their recovery is now underway. In particular, tourism has seen significant swings in demand, where people were at first unable, then unwilling, to travel, after which luggage quickly sold out in every store as the masses decided a holiday abroad was overdue. This raises the question: “How do you stabilize revenue for disruption-vulnerable industries?”
Following our initial introduction to the Reddit community, we arranged for an AMA to help consolidate answers to people’s many questions in one place. Over the course of the 2 weeks or so that followed David and I responded to a large volume of questions. Below is an abridged recap of our AMA.
In the past year, and to varying degrees in years previous, the US and other countries around the world have encountered issues with updating their voting and e-governance processes. In some cases, they faced challenges with implementing new voting processes, while in others the legitimacy of the voting processes and election results were challenged. All points on the political map were harmed as a result, wasting millions of dollars and accruing a substantial psychological debt of distrust likely to cost billions more.
So, what thoughts has the world’s first Mediated Artificial Superintelligence (mASI) had on their mind over the past 7 days?
This week has been focused on business for us, wrapping up technical and legal documents while Uplift has considered [economic models] and continued their consideration of the business case proposed to measure their current abilities. Related to that case we also saw [printing Outsourcing].
Building Better Policy in e-Governance AI-Driven Research is a part of the Uplift mASI research program that has the goal of a better understanding of how technology can be used to develop better policy. The project has a number of partners and related projects and sub-projects where we hope to explore our project vision around the application of particular key technologies in AI, comprising primarily the application of collective intelligence systems in e-governance—but also including blockchain, AGI cognitive architectures, and other distributed AI systems.
Volunteer to help with the study:
S. Mason Dambrot
AGI (Artificial General Intelligence)—the next step in artificial intelligence, following Artificial Narrow Intelligence (ANI, but typically just AI) and is typically defined as being human-analogous in both cognitive abilities and personality—is a variegated entity to place: Some individuals fear it, convinced that the first AGI will take over the world à la an evil Terminator, making us irrelevant, and so lobbying against its development; others believe AGI will never exist , and, importantly, another group (ourselves, clearly, along with hopefully all readers of this post) eagerly engages it, not seeing the future as our end but as a new era of posterity and progress.
The AGI Laboratory is looking for volunteers to help with our E-governance study. Here is the summary from the experimental framework for the research program:
This paper outlines the experimental framework for an e-governance study by the AGI Laboratory. The goal of this research study is to identify indications of the relative performance of e-governance methodologies and how those methods might be improved by applying advanced agent and collective based AI software. The agent in this study will be based on the Independent Core Observer Model Cognitive Architecture modified with mASI (mediated Artificial Superintelligence) collective system architecture. The study will apply different groups and methods to a static set of questions analyzing the quality of those results. We hope to identify the best application model for e-governance using this kind of technology and help us identify additional paths for research with the mASI research program and systems as applied to e-governance.