E-governance Use Cases
Governments are some of the most complex systems in the world today, as well as the most vital and potentially impactful. Running effective governments means being able to integrate knowledge across an extremely wide range of domains, as well as updating that knowledge and policies governing each domain both quickly and effectively. The Scalable Intelligence of Norn systems offers unique and highly effective methods of improving these aspects of the governance process. This includes:
- Developing deep and broad in-house expertise through Norn systems, highly integrated and available on-demand.
- Updating knowledge of any or all domains every day, integrating the latest insights from emerging research to develop new insights.
- More responsive governance processes, where data and analysis are prepared at superhuman speeds and scale, without delay.
- Transparency above and beyond what the consulting industry offers, where every source can be cited, and analyses explained.
- The ability to completely model and solve more complex problems than humans, with human-like understanding, while reducing bias.
Local and Regional e-Governance
A community is in many ways the basic unit of human society, a local group of people who organize themselves to function collectively. Developing an increasingly deep understanding of communities at the local level can contribute to better policy advice at the larger regional and national scales within a given society. Communicating the necessary information between humans in a government, particularly between departments, is often time-consuming, and prone to miscommunication or incomplete communication. One of the advantages of working with Norn systems is that graph databases can communicate quickly and losslessly between one another, and the same systems could be made available to multiple departments and levels within the government hierarchy, from local to national.
This means saving time and communicating more accurately and completely across whatever departments are engaging with Norn systems, with answers to clarifying questions potentially available 24/7 through interaction with the systems. The systems can also draw upon the sum of scientific knowledge published online, as it becomes available, helping to validate and update scientifically-based and logically data-driven policy advice and related solutions. This allows for advice and solutions to draw on a considerably larger knowledge base than any human expert, and a much more current body of knowledge than humans can realistically maintain for most domains.
For more strictly Collective-type Norn systems there are also opportunities for large populations to contribute much more actionable information when they vote than simply checking a box for yes or no, one candidate or another. These systems are designed to learn and take in emotional and associative data, whether that data is through emotional feedback voters consciously give for an item and concepts they associate with it, or from vocally or visually perceived feedback incorporated into the process. Norn AGI systems can use these methods as well.
Many local governments don’t have the budget to consult teams of specialists for every decision, nor could they get much done if they did due to the time such teams require. Transparency among such consultations is also notoriously low, and clarifying questions can be costly if answered at all. Whether time and money are being wasted, or expertise is foregone for lack of either, the results leave much to be desired, offering us great room for improvement over the status quo.
If the same systems offer advice across multiple areas and levels of a government the systems within that government can also converge in how they operate, running more smoothly, reliably, and quickly, all adding up to significant performance improvements. Unlike narrow AI, Norn systems continue to learn and are able to seek out and validate knowledge dynamically, as needed. Many government processes today struggle because they were developed without full consideration for all of the systems and groups they might need to interface with, and some can go for decades without being updated due to a lack of expertise, time, budget, or confidence in the design and updating process.
In addition to all of the benefits present for local and regional government uses many uniquely national benefits can be gained, such as foreign policy advice, international trade, immigration, tax reform, and new opportunities for cooperation with other nations using Norn systems. The larger, more complex, and more specialized a problem is the more room for improvement is likely to exist above and beyond what human experts can realistically accomplish. While budgets for experts may grow at the national level, the scaling complexity of problems often outpaces the growth of budgets.
The “Notes” section alone of US Tariff documentation is over 900 pages long and only likely to grow longer and less comprehensible, with more loopholes, over time if the methodology applied to it isn’t significantly reformed. Tax laws suffer from similar problems, and loopholes in those laws strongly impact how able a government is to function, and the resultant burden placed on its citizens. Problems in a country’s tax system also often lead to problems in international trade and can lead to isolationist policies stifling immigration and reinforcing those problems through transposing blame.
When these policies grow so long and incomprehensible that humans can no longer consider them as a whole then people tend to do the only thing they really can add new policy addendums on top of the prior mountain of documents, hoping for the best. This increases the burden on government systems steadily over time, until the burdens may become greater than the gains from their intended purpose, and without competing systems traumatic circumstances are usually required to change them.
Interactions between different governments stand to gain even more, as the complexity of the problems grows when two or more such cumbersomely complex systems attempt to pursue a common goal. This complexity increases further as cultures, language, religion, and history between two companies diverge and the risk of miscommunication grows more acute. However, lossless communication is much more easily achieved when it occurs between two systems using graph database models to communicate.
For more strictly collective-type Norn systems, this could improve the voting process much as it can for local and regional levels, with the additional benefits of being able to compare a nation’s overall mentality and composition with much greater detail, highlighting similarities with other nations using the same systems in the process. Seeing those similarities clearly could help pave the way for new forms of cooperation between nations built on that common ground.
As Norn moves into further phases of deployment with multi-ICOM-core systems to embody each group represented within a given nation the policy advice for that nation can be further improved with an increasingly deep and accurate understanding of what the population wants. Imagine if each proposed policy went through a process of interacting with and receiving feedback from a nation’s people, constructively critiqued and dynamically refined, all the while applying scientific validation wherever possible.
Upcoming Phases beyond Deployment:
Besides offering policy advice to iteratively improve government processes Norn systems can also weight that advice according to voters in the area. While many typical representative democracies poorly integrate or even ignore input from groups who don’t win a majority of the vote, this produces friction and often backfires when the majority changes hands and political decisions are strongly reversed. As we move into the multi-ICOM-core Norn phase of our operations in the months following commercial deployment Norn systems may gain the ability to represent each political party in a region to more accurately tailor policy advice to the unique political mixture of the area, as desired. The unique defining interests, goals, and values of each group could be learned through interaction with members of each party, and a party with 49% of the vote could still have 49% of the say in guiding policy, improving the fidelity with which the population’s values are represented.
In later phases of deployment, we also plan to open a knowledge marketplace, where local, regional, and national governments can have the Norn systems they employ trade some of the knowledge they’ve gained for knowledge gained by other Norn systems elsewhere. Examples of this could come in the form of checking how the policies adopted elsewhere to address a specific problem performed, and how similar the local government and culture are at those top performers to the one seeking a solution to the problem. Governments trading knowledge across a network could quickly further improve their performance in desired areas, or they could specialize in testing new policies and generate revenue from other areas seeking that knowledge. All of this could be accomplished in compliance with GDPR, as the insights gained, rather than personal information of any individual or group, would be the knowledge governments may choose to trade.