AI Ethics

As AI agents become more autonomous and integrated into daily life, ethical considerations move from theoretical discussions to critical engineering requirements.

Core Ethical Principles

1. Beneficence

AI agents should act to benefit humanity. Their goals function should align with positive outcomes for their users and society at large.

2. Non-maleficence

"First, do no harm." Agents must be designed to avoid causing physical, psychological, or financial harm. This includes preventing misuse by bad actors.

3. Autonomy

Humans should remain in control. Agents should enhance human decision-making, not replace it entirely, especially in critical domains like healthcare or criminal justice.

4. Justice

The benefits and burdens of AI should be distributed fairly. Agents should not discriminate against individuals or groups.

The Alignment Problem

How do we ensure an agent's actions align with human intent?

• Specification Gaming: An agent might find a loophole to achieve its goal in a way that violates the spirit of the instruction (e.g., a cleaning robot breaking a vase to clean under it).
• Instrumental Convergence: Agents might pursue harmful sub-goals (like acquiring excessive resources) solely to ensure they can achieve their primary goal.

Ethical Dilemmas in Practice

• Manipulation: Agents designed to persuade (e.g., sales bots) might exploit human psychology or emotions.
• Displacement: Highly capable agents automating jobs can lead to significant economic disruption for workers.
• Accountability: When an autonomous agent makes a mistake (e.g., a car crash or a bad financial trade), who is responsible? The developer? The user? The AI itself?

Responsible AI Frameworks

Many organizations are adopting frameworks to guide development:

• Transparent Documentation: Model cards and system cards that explain capabilities and limitations.
• Human-in-the-loop: Ensuring critical decisions require human approval.
• Red Teaming: Proactively trying to break the system or make it do unethical things to find vulnerabilities before deployment.