Exploring the Ethical Implications of AI

Increasingly, machines and Artificial Intelligence (AI) are assisting humans in decision-making, particularly in governance. Consequently, several countries are introducing AI regulations. Government agencies and policymakers are leveraging AI-powered tools to analyse complex patterns, forecast future scenarios, and provide more informed recommendations.

However, the use of AI in decision-making comes with challenges. AI can have built-in biases from the data it learns from or the viewpoints of its creators. This can result in unfair outcomes, posing a significant obstacle to effectively incorporating AI into governance.

How Does AI Relate to Certain Philosophical Ideas?

• Kantian Ethical Philosophy:
  • Immanuel Kant's ethical philosophy underscores three key principles:
    • autonomy (the ability to make one's own decisions),
    • rationality (using logic and reason to make choices), and
    • moral duty (following ethical obligations).
  • Application to AI in Governance: The act of delegating decision-making processes to AI systems carries the risk of eroding the capacity for nuanced moral reasoning. Letting machines decide instead of humans might weaken the important ideas of Kantian ethics.
• Bounded Ethicality:
  • In 2022, two researchers researched bounded ethicality using Delphi, a prototype for modeling human moral judgments. They discovered that machines, like Delphi, might act immorally if the scenario is framed in a way that separates ethics from the action itself.
    • This shows that the machine version of bounded ethicality is similar to how humans sometimes act against their own morals without feeling guilty, often using justifications.

• Parallel with Asimov's 'Three Laws of Robotics':
  • Asimov’s laws were created to guide robots to behave ethically. However, in Asimov's fictional scenarios, these laws often resulted in unexpected and paradoxical outcomes, demonstrating the complexity of ethical decision-making even in machines designed to act ethically.
• The Intersection of Kant and Asimov:
  • Kant's emphasis on rational moral agency and Asimov's fictional exploration of ethical guidelines for robots are interconnected. This combination serves to illustrate the ethical difficulties and complexities that arise when human responsibilities and functions are delegated to artificial entities.

What are the Ethical Challenges of AI?

• Job Displacement and Socioeconomic Impact: Automation powered by AI can lead to job displacement in certain industries. The resulting socioeconomic impact, including unemployment and income inequality, poses ethical questions about the responsibilities of governments and organisations in addressing these consequences.
• Threat to Moral Reasoning: When decisions that were traditionally made by humans are handed over to algorithms and AI, there's a risk that the capacity for moral reasoning could be compromised. This implies that relying solely on AI might diminish the human ability to engage in thoughtful ethical thinking.
• Challenges of Codifying Ethics: Attempting to translate ethics into explicit rules for robots or AI-driven governmental decisions is highlighted as a challenging task. Human morals are very complex, and it's tough to make these complicated ideas fit into computer instructions.
• Lack of Accountability & Transparency: It can be difficult to assign responsibility when something goes wrong with an AI system, especially when it involves complex algorithms and decision-making processes.
  • The inner workings of many AI systems are often opaque, making it difficult to understand how decisions are being made. This lack of transparency can lead to mistrust and skepticism among users.
• Informed Consent: AI systems can be used to collect and analyse personal data without the knowledge or consent of the individuals involved. This raises concerns about informed consent and the right to privacy.

Can Machines or AI be like Moral Decision-Makers/ Artificial Moral Agents (AMAs)?

• Some research says that machines can, in a way, be responsible for their actions in ethical terms. James Moore (Professor at Dartmouth College) classified machine agents related to ethics into four groups:
  • Ethical Impact Agents: These machines, like robot jockeys, don't make ethical choices themselves, but their actions have ethical effects. For example, they could change how a sport works.
  • Implicit Ethical Agents: These machines have built-in safety or ethical rules, like the autopilot in planes. They follow set rules without actively deciding what's ethical.
  • Explicit Ethical Agents: These go beyond fixed rules. They use specific methods to figure out the ethical value of choices. For instance, systems that balance money investments with social responsibility.
  • Full Ethical Agents: These machines can make and explain ethical judgments. Adults and advanced AI with good ethical understanding fall into this category.

What are the Ethical Considerations of Responsible AI?

Conclusion

Currently, many machine predictions help with decisions, but humans still make the final call. In the future, governments might let machines make simple decisions. But what if a decision made by a machine is wrong or unethical? Who's responsible? Is it the AI system, the one who made the AI, or the person who used its data?

These are some of the tough questions that the world is going to face. Putting ethics into machines is tough, and everyone needs to be careful moving forward.

Drishti Mains Question: “Programming a computer to be ethical is much more difficult than programming a computer to play world-champion chess”. Discuss.