What is Ethical AI and Explainable AI?

14-Nov-24
A
rtificial intelligence (AI) has become an integral part of our daily lives in recent times. Whether we talk about chatbots answering customer queries, recommendation systems suggesting movies, or even self-driving cars, AI is the catalyst that is redefining the way humans interact with technology. But as AI becomes more influential, there are growing concerns about its impact on the privacy, fairness,and decision making.
 

We have seen in recent years that AI based systems has emerged as a very integral part of our lives. Be it a chatbot answering your customer queries or a recommendation system suggesting movies or even self-driving cars, AI has served as a stimulus that is changing the way humans interact with technology. Although, this increasing influence of AI is giving rise to growing concerns about its effects on privacy, fairness, and decision-making. It is here that Ethical AI and Explainable AI come to the picture.

Understanding Ethical AI

Ethical AI refers to artificial intelligence that follows clearly defined ethical principles concerning core values such as individual rights, privacy, non-discrimination, and non-manipulation. Organizations that implement ethical AI establish transparent policies and robust review processes to ensure compliance with these ethical standards. It emphasizes the importance of ethical considerations in determining the acceptable and unacceptable uses of AI.

The practice of ethical AI is different from what is allowed legally. Legal limits regarding AI usage establish a minimum acceptability threshold, while the policies of ethical AI have to be more than compliant with the law to remain respectful of fundamental human values. For instance, although AI algorithms that successfully push people – teenagers, mostly – to self-destructive behavior may be legal, they are not ethical AI.

Decoding XAI (Explainable AI)

Explainable AI, in short XAI, is based on the idea of making decisions of AI systems clear and understandable to the human race. The machine learning models sometimes operate as "black box" systems. These systems make it difficult to understand how these models arrive at certain decisions. Explainable AI seeks to make these processes transparent. This is done to help people see how AI systems make decisions and why they arrive at specific outcomes.

Principles of Ethical AI

There are some key principles that Ethical AI is based on. Such principles serve to ensure that AI technologies are applied and used responsibly.

  1. Privacy protection: AI should respect the privacy of people. It should safeguard personal data and not use it in ways that may violate trust of the customer.
  2. Transparency: The decision-making processes based on AI should be open and understandable. The workings of AI systems and how it makes certain choices should be visible to the people. This is where Explainable AI becomes important.
  3. Accountability: Whoever is creating and utilizing artificial intelligence-whether individual or organization-should have accountability for its actions. Such an AI system should be accountable if it causes any harm or makes a mistake. There has to be someone responsible for fixing it.
  4. Fairness: AI must not exhibit any form of discrimination and treat everyone alike. The AI systems must not be biased and show unequal judgments based on colour, gender, age, or any other personal bias.
  5. Sustainability aspect: AI must be developed and used in a way that sustains the environmental and social good.
  6. Safety and security: The design of AI systems should be such that it can be operated safely and remain resistant to misuse. They should not pose risks to people or society.

The Relevance of Ethical AI in the modern world

With the adoption of AI technologies in every sector, the importance of Ethical AI process Is incredibly significant. Here are the major reasons:

  1. Preventing harmful effects

AI may prove harmful to individuals or a group of people, if left unregulated, either in terms of biased decision making or unauthorized use of one's personal data. For example, when an AI model refuses a loan application, the AI model has to state why it did so. This feature of transparency enables users to determine if the decision was fair or unfair.

  1. Encouraging innovative solutions

The more developers focus on developing Ethical AI, the more likely these systems will benefit everyone rather than just a few. Such a focus often leads to innovative and improved AI solutions that have a broader, more positive impact on people's lives.

  1. Trust building

If people understand the workings behind AI systems, they are more likely to trust them and believe in their fairness. Ethical AI practices aim at building public confidence in these technologies.

  1. Compliance with regulations

Many governments worldwide are launching new regulations on AI. The most recent example would be the European Union's AI Act. So, now it becomes inevitable for corporations to be Ethical in AI to stay compliant and safe from lawsuits.

  1. Human rights protection in artificial intelligence

Ethical AI supports protecting essential human rights including privacy and non-discrimination. This is achieved by incorporating these values during the development of ML and AI based systems.

Explainable AI: Why transparency in AI is so essential?

Transparency can be a point of issue to AI technology, especially when related to Explainable AI or XAI. Please find the reasons for this:

  1. Lack of bias: Bias is easy to spot in transparent AI models. The users will be able to trust the decisions made by the AI systems. For instance, a recruitment AI that favours male candidates over female candidates can be spotted and corrected if the decisions are explainable.
  2. Better decision-making: Humans can collaborate with AI systems to create better results only if they understand how AI decides. Clear AI systems allow people to challenge and fine-tune model, hence enhancing the accuracy and reliability of models over time.
  3. Ethical issues: Lack of transparency in decision making by AI results in the unethical output of the machine. XAI keeps the machine accountable to human values.

Analyzing Ethical AI and Explainable AI Differences

Though Ethical AI and Explainable AI (XAI) are close cousins, they emphasize various facets of AI technology. Here's how they differ:

  1. Focus:

  • Ethical AI refers to the development of AI technologies and application in a manner which has fairness, transparency, and respect toward human rights.
  • XAI is particularly concerned with explaining the decision-making process of AI in a manner comprehensible to humans only.

  1. Scope:

  • In case of Ethical AI, the scope is vast. In fact, it ranges from fairness and accountability to privacy and security.
  • On the contrary, XAI is very specific and more concerned about explanation and transparency of decisions of AI.

  1. Output:

  • Output in case of Ethical AI is that the AI system shall be aligned with values both moral and societal.
  • XAI aims to explain the decision-making process of AI systems, thus allowing users to trust and verify AI outputs.

Final remarks

For AI to be truly ingrained in all aspects of life, it must first be ethical and transparent. Ethical and Explainable AI ensure that AI technologies are not only effective but also aligned with human values. This approach allows AI systems to operate in a clear, accountable, and understandable manner, ensuring they remain intelligible and responsible to end-users.