POL.ACC Politician Accountability is an approach to address the Politicians as Project owners in critical public projects in developing our democracies beneficial to us, the people. 

The major inventive part of the model is described in chapter 3 and 4 in the homepage, www.plputvikling.no, chapter 3 the PA function reporting to the project owner, the politician and chapter 4 the decision model. Experiences to establish POL.ACC Politician Accountability as system, started out in a major inventive project in the years 1993-1994 in revising the procedures for a Norwegian State Fund, Regional omstilling. The politician role as project owner of critical public projects, is thus thoroughly founded. 

The corresponding pending patent application for the POL.ACC concept is US63/470,392.

We have organized the following Technical Description in 3 areas of challenges that our politicians have to take on:

  1. Addressing of corruption that is crucial for the integrity of any government

Concept, planning and implementation are defined as separate projects in our decision model reported to the politicians as Project Owners.  Transparency is secured in a blockchain-solution, thus making it easier to detect possible avenues of corruption in the implementation phase.

  • Bipartisan projects to bring together different political ambitions

How can the law contribute in the US where the Trump side uses lies as a primary strategy, hence attacking the moral base that has arguably been a battleship in our promotion and defence of the liberal democracies, i.e. what do we do to defend the Law against a strategy of lies?  Rhetorics as well as conspiracy can as we know be outright lies to stay in the lead.   

  • The present challenge in today’s society to secure decision quality within the advanced AI models like GPT

The decision model in POL.ACC secures human control for security check in the Concept room in the separate project stages; concept, planning and implementation in the project development.

POL.ACC Technical Description

21/09/2023  For and on behalf of plp utvikling as

The main hurdles to successful execution of projects for the betterment of public good include political corruption and partisanism. A new challenge has also emerged in recent years – that of the world of AI.

The POL.ACC concept (and corresponding pending patent) provides a solution to the challenges of managing long-term projects, highlighting issues such as a lack of transparency, complexity, and decision-making based on inaccurate information. It underscores the importance of adopting a systematic approach to project development.

The proposed system of the POL.ACC concept aims to tackle these challenges and enhance project tracking and accessibility. It comprises several components:

  • Project Modules: These modules encompass concept, planning, and execution submodules, each connected to a blockchain for recording irreversible actions.
  • Decision Nodes: Decision nodes within project modules facilitate user input by presenting relevant verified information, ensuring informed decision-making.
  • Authentication: Users are authenticated via multifactor authentication and cryptographic keys.
  • Active Information Module: This module scans the internet for up-to-date information related to live projects, executes a verification program, and presents relevant, verified information to users.
  • Simulation Submodule: This generates probabilistic simulations based on user input and verified information.
  • User Profiles: User profiles include educational, professional, and personal background information to determine relevant information presentation.
  • Blockchain: The system uses a decentralized blockchain structure for recording actions associated with project modules.

The method for improved project tracking and accessibility involves authenticated users accessing project modules, receiving verified information for decision-making, and storing user input in the blockchain. The active information module periodically searches the internet for relevant information, verifies it, and stores or discards it based on verification results, including quantified validity scores.

Addressing political corruption is crucial for the integrity of any government. To reduce political corruption, it is essential to implement a multi-pronged approach that enables the following:

  • Transparency and Accountability: Strengthen transparency laws and mechanisms, such as open government initiatives and financial disclosure requirements for public officials.
  • Independent Oversight: Establish independent anti-corruption agencies with the power to investigate and prosecute corrupt officials.
  • Whistle-blower Protection: Implement robust whistle-blower protection laws to encourage individuals to report corruption without fear of retaliation.
  • Ethics Training: Provide ethics training for government officials to raise awareness about corruption risks and the importance of ethical behaviour
  • International Cooperation: Collaborate with international organizations and other countries to share best practices and gather support for anti-corruption efforts.
  • Public Awareness: Educate the public about the negative impacts of corruption and engage civil society in anti-corruption initiatives.

The POL.ACC system and method developed by PLP UTVIKLING enables all of the above when running a project (however large).

Establishing a bipartisan project can include:

  • Constitutional Framework: Leverage the power granted by the US Constitution to encourage bipartisan collaboration on critical projects. This can involve invoking shared responsibility clauses or convening bipartisan committees.
  • Project Selection: Identify key bipartisan projects that align with national interests and have a broad base of support.
  • Legislative Mandate: Pass legislation mandating that critical projects must have bipartisan sponsorship and support before moving forward.
  • Public Pressure: Mobilize public opinion and advocacy groups to push for bipartisan cooperation on essential issues.

A new challenge in today’s society is securing decision quality within the advanced AI models environment.

When using advanced AI models like GPT in decision-making processes, ensuring decision quality is paramount. A technical approach to the above may be:

  • Data Validation: Carefully vet the data used to train and fine-tune GPT models to ensure it is representative and unbiased.
  • Explainability: Develop methods to explain the AI’s reasoning to decision-makers, making the decision process transparent.
  • Continuous Monitoring: Implement real-time monitoring of AI system performance to detect and mitigate biases or errors.
  • Human Oversight: Maintain human oversight of AI-generated decisions, especially in critical areas.
  • Regular Updates: Keep the AI model up to date with the latest data and technological advancements to improve its decision-making capabilities.

Incorporating the above technical approaches via the POL.ACC concept can significantly contribute to addressing these complex challenges and driving positive change.  The corresponding pending patent application for the POL.ACC political accountability concept is US63/470,392.

Security

Togetherness

plp utvikling as, mobil +47 975 25 412 –  e-post: pol.acc.global@gmail.com.