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The recent upheavals at OpenAI and OpenAIs Chief Scientists apprehensions regarding the safety of AI have ignited a fresh wave of concerns and fears about the march towards Artificial General Intelligence (AGI) and Super Intelligence.

AI safety concerns the development of AI systems aligned with human values and do not cause harm to humans. Some of the AI safety concerns that Ilya Sutskever, OpenAIs Chief Scientist and one of the leading AI scientists behind ChatGPT, has expressed are:

Sutskever reportedly led the board coup at OpenAI that ousted CEO Sam Altman (Altman has since been reinstated at OpenAI) over these AI safety concerns, arguing that Altman was pushing for commercialization and growth too fast and too far without adequate attention to the safety and social impact of OpenAIs AI technologies.

The wild agitation about AI becoming misaligned with human goals or developing their own goals that conflict with ours is an overwhelmingly essential and critical topic. If you want a refresher on how AI can go wrong, watch the movie Eagle Eye. In the movie, an AI model (ARIIA) was designed to protect American lives, but that desired outcome wasnt counter-balanced against other desired outcomes to prevent unintended consequences.

With these concerns about AI models going rogue, Im going to present a multi-part series on what would be required to create a counter scenario AI and Justice in a Brave New World that not only addresses the AI concerns and fears but establishes a more impartial and transparent government, legal, and judicial system that promotes a fair playing field in which everyone can participate (have a voice), benefit, and prosper.

The Challenge. In this AI scenario, elected officials would still make societys laws and regulations. Unfortunately, these laws and regulations are not enforced fairly, consistently, or unbiasedly in todays legal and judicial systems. Some people and organizations use their money and influence to bend the laws and regulations in their favor, while others face discrimination and injustice because of their identity, background, or position in society. This creates a system of inequality and distrust that leads to social disenfranchisement and political extremism. We need to ensure that the laws and regulations are enforced with fairness, equity, consistency, and transparency for everyone.

The Solution. To address the unfair, inconsistent, and biased enforcement issue, we could build AI models that would be responsible for enforcing the laws and regulations legislated by elected officials. With AI in charge of enforcement, there will be no room for prejudice or biased decision-making when enforcing these laws and regulations. Instead, AI systems would ensure that the laws and regulations are applied equitably, fairly, and transparently to everyone. Finally, justice would truly be blind.

This requires that our legislators define the laws and regulations and collaborate across a diverse set of stakeholders to define the desired outcomes, the importance or value of these desired outcomes, and the variables and metrics against which adherence to those outcomes could be measured. This would necessitate substantial forethought in defining the laws and regulations and identifying the potential unintended consequences of these laws and regulations to ensure that the variables and metrics to flag, avoid, or mitigate those unintended consequences are clearly articulated. Yes, our legislators would need to think more carefully and holistically about including variables and metrics across a more robust set of measurement criteria that can help ensure that the AI models deliver more relevant, meaningful, responsible, and ethical outcomes (Figure 1).

Figure 1: Economic Value Definition Wheel

Here is the good news: those desired outcomes, their weights, and the metrics and variables against which the AI model will use to make its decisions and actions could be embedded into the AI Utility Function, the beating heart of the AI model.

The AI Utility Function is a mathematical function that evaluates different actions or decisions that the AI system can take and chooses the one that maximizes the expected utility or value of the desired outcomes.

Figure 2: The AI Utility Function

Analyzing the performance of the AI Utility Function provides a means to audit the AI models performance and provide the ultimate transparency into why the AI model made the decisions or actions that it did. However, several deficiencies exist today that limit the AI Utility Functions ability to enforce societys laws and regulations.

The table below outlines some AI Utility Function challenges and what AI engineers can do to address these challenges in designing and developing a healthy AI Utility Function.

Table 1: Addressing AI Utility Function Challenges

Maybe Im too Pollyannish. But I refuse to turn over control of this conversation to folks who are only focused on what could go wrong. Instead, lets consider those concerns and create something that addresses those concerns and creates something that benefits everyone.

Part 2 will examine a real-world case study about using AI to deliver consistent, unbiased, and fair outcomesrobot umpires. We will also discuss how we can create AI models that act more human. Part 3 will try to pull it all together by highlighting the potential of AI-powered governance to ensure AIs responsible and ethical application to societys laws and regulations.

Read more:

A Different AI Scenario: AI and Justice in a Brave New World Part 1 - DataScienceCentral.com - Data Science Central