Introduction

Artificial Intelligence is transforming our lives in so many ways. From Siri and Alexa as virtual assistants to self-driving cars, AI agents are now integrated into our everyday lives, such as in health, finance, and entertainment. However, since it’s moving this fast, one must raise such questions: How do AI agents decide? And do the decisions of the AI agent become ethical?

  Ethics in AI is becoming a highly relevant issue. As more tasks are passed over to the decisions of AI systems, those decisions should be morally right and just. They should be explainable to people and morally agreeable to them. In this paper, we consider how decisions are made by AI agents, the ethical frameworks that inform them, and what difficulties surround the making of AI ethics decisions.
An AI agent is an artificial intelligence-based system that executes tasks, analyzes data, and decides. These agents could be very simple programs and highly sophisticated systems that learn and evolve.

Types of AI Agents

There are two types of AI agents:

• Narrow AI (Weak AI): Narrow AI performs one specific task. For example, AI can use facial recognition, translate language, or recommend products based on previous conduct. These systems can do one thing well but cannot adapt outside of their programming.

• General AI or Strong AI: Theoretically, it is supposed to be able to do anything a human being can do intellectually. Put simply, it does not yet exist but certainly is the aim of many researchers.

There has been a steady increase in AI agents in diverse industries. While AI is employed to help doctors diagnose diseases, in finance it helps in the detection of fraud and loan approval, and AI is responsible for split-second decision-making in cases of autonomous vehicles to ensure safe driving. Yet, with its increasing influence, we must wonder, how are decisions made, and whether they are ethical.

Why Ethics Matter in AI

Ethics is the study of what is right and wrong. Ethics in human society guides our behavior and decisions. But AI agents can’t “feel” right or wrong. They work on data and algorithms. Can AI systems make ethical decisions?

The short answer is that AI can only mimic the process of making ethical decisions, not understand ethics inherently. However, deciding through AI in an ethically good manner is important because AI can powerfully alter human lives and shape them as well. Some of the really bad and quite serious consequences of poor or bad AI decisions include:

• Discrimination in hiring practices

• Bias in medical diagnoses

• Unfair financial decisions, like loan rejections

• Unsafe or harmful behavior of the autonomous vehicle

Ethics in AI is about how the AI agents decide in a manner that is not only logical but fair, transparent, and just. The AI systems would aim to serve humanity, avoid harm, and respect human dignity.

How AI Agents Decide

Data Collection:

 Huge amounts of data are collected by AI systems. This data could have been obtained by sensors (e.g., self-driving cars), user interactions, or source information. The quality of the data is important to result in the right decision.

Processing the Data: 

AI processes this data with the help of algorithms. An algorithm is a set of rules or instructions followed by the AI to analyze and interpret the data. Machine learning algorithms enable the AI to learn from new data and improve decision-making over time.

 Once the data is processed, the AI gives a decision. For example, an AI inside a self-driven car decides whether to slow down or change lanes under the prevailing traffic situation.

Output: 

Now, based on its decision, the AI acts. For example, sending some recommendations to the user, steering a car, diagnosing a disease, etc.

Several models can be deployed by an AI agent while making decisions:

• Rule-Based Systems: These are systems that function according to a predefined set of rules. For example, an AI that would react by following some script in a customer care setting.

• Machine Learning Models are AIs that learn from data and adapt over time. For example, a recommendation system will recommend movies or products based on the user’s past activity.

• Reinforcement Learning: This model is based on feedback. In this model, AI is rewarded for making good choices and penalized for making bad ones. This model is often used by AIs that play games.

Challenges in Building Ethical AI

Making AI ethical is a hard task, even as the technology supporting AI decision-making is getting better. The following are a few of the major obstacles:

Lack of Universal Ethical Standards:

 Ethics often differs between one culture and another. What may be right in one place may not be in another. This makes it challenging to come up with universal AI ethics standards for all these places.

Bias in the Data: 

Whatever data AI is learning from has to be fed through it, during training. That means if this data is biased, the AI will not be any better. For example, an AI hiring system trained in biased hiring data might favor certain demographics over others unconsciously.

Unpredictability of AI Decisions: 

AI may decide in very complex and unpredictable ways. The consequences of an AI decision cannot be predicted, especially when it has to handle big data or vague conditions.

Lack of Accountability:

 It is often not clear who should be held responsible when AI systems make wrong or unethical decisions. Is it the AI itself? The developers? The company that deployed the system? This raises accountability and transparency questions.

Frameworks for AI-Driven Decision-Making

To address these issues, many ethical frameworks have been designed to guide AI decision-making. The goal is for AI systems to become in line with human ideals and, thus, transparent and equitable AI decision-making. Among the primary ethical frameworks are:

• IEEE Ethically Aligned Design: The company had already put in place a framework for the ethical design provided by the Institute of Electrical and Electronics Engineers, or IEEE, to focus on the morality and human well-being of the developers while making the AI system.

• EU Ethics Guidelines: Some of the actual guidelines that have been proposed by the European Union in terms of ethics are transparency, accountability, privacy, and fairness. These principles ensure that AI systems are developed in ways that benefit society and respect human rights.

• Asilomar AI Principles: This was designed by a team of AI researchers and policymakers who came together to develop AI in safety and morality. The set has 23 principles that serve as the underlying aspects of the safety of avoiding harm while being transparent and accountable through the AI system.

These guidelines are meant to guide developers, but no one rule applies to all AI systems. Every application of AI has a different purpose and exerts varying impacts.
For example, an AI trained on data from one racial group performs poorly for others.

AI in real-world world locations

• AI in Self-Driving Cars: It takes autonomous cars crucial real-time decisions so as not to collide and make mistakes, as with this incident where an emergency happens. The system is programmed to either cause more damage by harm—whoever poses a decision about who is cheaper than whose value human life may stand in for its moral determination.

• AI in Finance: The use of AI is in deciding creditworthiness, fraud detection, and investment decision-making. Financial data bias may lead to discriminatory treatment of certain groups. For instance, a biased historical record may cause an AI system to reject loan applications from certain groups unfairly.

Can AI Ever Truly Be Ethical?

The question is whether AI agents can ever be truly ethical. An AI agent, after all, does not possess a conscience and has no idea of right from wrong. An AI can merely do what has been programmed or inculcated into it as rules and data. Yet, the right frameworks for human oversight with transparent decision-making by AI could yield decisions ethically aligned with those of humans.

While AI can mimic ethical behavior, real ethical thought requires human input. Human oversight is important because this is what makes an AI system accountable to the values of society.

Future of AI and Ethics

The future of AI ethics is dynamic. The more AI advances, the more it creates ethical issues. We should all cooperate globally to develop standards and rules for AI to fulfill its full potential for improving humanity without harming it.

As AI becomes more mainstream, its ethical development will be integral to future creation. The greater our focus is on ethical AI, the greater the assurance that these technologies will be good.

Conclusion

AI is changing the world, and this has a plethora of ethical connotations. Understanding how AI agents make decisions and make decisions ethically goes hand in hand as an important aspect. We can navigate AI systems toward a future that is not only just and more transparent but also very fair with the imposition of ethical frameworks and human oversight. Therefore, ethical AI development is not a societal challenge but a technical one that calls for our collective effort.