Nowadays, AI is developing so fast and a large area of the population is now using it for day-to-day work. Big companies like Google (Gemini AI), Microsoft (Copilot), Open AI (Chat GPT), Meta (Meta AI), Samsung (Galaxy AI), etc., are using it to make a lot of their tasks easier and automatic, without any human interference. Then what is Ethical AI ? Let’s understand it practically.
A vast majority of companies, no matter how big or small, want to invest in this AI technology to make the most of it. As AI is a powerful tool and can do anything you ask for, sometimes it may be dangerous to the public. Now, a lot of questions will arise in your mind: With the large area of application of AI, how can it be handled without any public law violation, or what if anyone will use it to do dangerous things like hacking databases, getting private data directly through AI, which should not be shared publicly, etc. Therefore, in these types of situations, Ethical AI comes into play.
Now, let’s try to answer the questions that arising in your mind.
Table of Contents
What is Ethical AI ?
In simple words, Ethical AI includes the design, development, and deployment of artificial intelligence (AI) systems in such a way that they comply with the public law and orders. It is also designed to keep fairness and social values in mind. Every person who uses AI should be bound by these rules and can’t misuse the AI for any unethical or illegal activities.
Let’s understand it better by taking some real life scenarios into consideration.
Example 1: Most of you know about how some AI software or apps convert a regular user’s image into a cartoon-like image. It seems like a very fun activity, and the majority of social media users often use these to show their unique AI generated images in their profiles. But if we deep dive into the core concept of it, you’ll get to know the application of Ethical AI here. Like, how does the AI handle or use the user data? Is there any loophole in the algorithm used while AI takes a personal image of you and converts it into the desired result? For these particular scenarios, privacy, transparency, and fairness are crucial.
Example 2: While AI models are trained, gender and skin-type biases have a higher chance of occurring. A research paper from MIT and Stanford University stated this and warned that these AI training data can lead to unfair outcomes, elaborating on the need for ethical considerations in machine learning while training these types of AI models. (Source: MIT)
Example 3: In 2016, a computer-generated painting called “The Next Rembrandt” was created using AI and a 3D printer. Now, you’ll think, What’s the unethical thing here? You’ll be surprised to know that this happened 351 years after the original artist’s death. Therefore, this example raises questions about authorship, creativity, and the role of AI in cultural production. (Source: unesco)
As of now, you know that what Ethical AI is, and without it, how our lives can be affected in the cyber universe or digital era. It’s time to discuss the key aspects of Ethical AI.
Key Aspects
1. Privacy: Without our prior consent, AI systems collect large amounts of personal data. And, as usual, we as users have less control over what information is taken and how it’s used. Another example to consider is that AI-generated voice clones can impersonate people and extort them. AI developers could repurpose personal data for training models that were once used for some other purpose
For the above reasons, Ethical AI is crucial when it comes to balancing innovations with the privacy rights of a user.
2. Bias and Fairness: As we discussed in Example 2, addressing possible biases in AI algorithms ensures fair outcomes for all users. So, developers should quickly and carefully address and resolve any biased information that may harm individuals or cause loss of life.
3. Transparency: The path should be clear as to how AI came to a certain decision and what the source of that particular information was that it provided to the user. AI should not be allowed to give information from a certain source that is harmful or illegal. And, if it is doing so, it’s the user who can know about these things and may report them to the developers of that particular AI tool to avoid such results in the future.
From the above scenario, you must be clear on how crucial transparency is for AI to be ethical.
4. The Hu-Ce Design: In today’s era, AI performs tasks to simplify human lives, allowing individuals to concentrate on other essential matters beyond what AI accomplishes more accurately and also efficiently. We named this as Hu-Ce Design (Human Centric Design). Its main aim is to prioritize human well-being over technical goals. Ethical AI considers the broader context and consequences.
5. Accountability: Every developer or organization that develops a particular AI is accountable for their actions. This also includes who is responsible for AI decisions, as we also discussed in the Hu-Ce Design aspect above. As users, we can raise questions like: Who designed the AI model?, Who trained it?, Who validated its performance?, and Who monitors its impact on users and society? etc.
6. Explain ability: When a user understands how an AI arrives at its conclusion, there is a high chance that the user will trust the subject provided by the AI. This ability holds developers or organizations accountable for AI model behavior. On the other hand, the benefit of this aspect is that users can identify biases and catch errors. This transparency makes sure that the user can make informed decisions.
Each AI should follow these six main aspects of Ethical AI to ensure public safety and welfare. Of course, there are more key aspects to Ethical AI, but the ones mentioned above are the primary ones.
As a reader, you should now have a brief idea of what Ethical AI is all about. Now, let’s discus the above-described subjects and see what we can conclude with our Ethical AI.
Navigating the Ethical Labyrinth of AI
1. The Ethical Imperative: Artificial intelligence (AI) has transcended its sci-fi origins to become an integral part of our daily lives. From recommendation algorithms to autonomous vehicles, AI shapes our decisions, interactions, and even our perceptions of reality. However, this technological marvel comes with ethical complexities that demand our attention.
2. The Unseen Hand of Bias: Bias lurks within the lines of code, subtly influencing AI outcomes. Whether it’s racial bias in facial recognition systems or gender bias in hiring algorithms, the consequences are real. Ethical AI requires us to scrutinize training data, question assumptions, and actively mitigate bias. After all, an AI system is only as fair as the data it learns from.
3. The Black Box Dilemma: Imagine a magical oracle that predicts the weather but refuses to reveal its reasoning. That’s the black box of AI – an enigma wrapped in neural networks. Explainability is our lantern in this darkness. Techniques like LIME and SHAP peel back the layers, allowing us to understand why an AI made a particular decision. Trust hinges on transparency.
4. The Accountability Quandary: Who’s responsible when an AI misjudges a loan application or recommends inappropriate content? Developers? Organizations? The AI itself? The answer lies in shared accountability. We must delineate roles, establish guidelines, and ensure that those who wield AI power do so with care. Accountability isn’t a burden; it’s a safeguard against unintended consequences.
5. The Tug-of-War: Privacy vs. Progress: AI thrives on data – the more, the better. But privacy is the currency we trade for progress. Striking the balance is our ethical tightrope walk. We need robust data protection laws, informed consent, and algorithms that respect personal boundaries. Otherwise, our AI-driven utopia risks becoming a surveillance dystopia.
6. The Human-AI Symbiosis: AI isn’t our adversary; it’s our reflection. It amplifies our biases, mirrors our intentions, and reflects our values. Ethical AI isn’t about replacing humans; it’s about augmenting our capabilities. Imagine a world where AI assists doctors in diagnosing diseases, helps teachers personalize education, and also aids policymakers in equitable decision-making. That’s the symbiosis we seek.
7. The Road Ahead: As we traverse the ethical labyrinth of AI, let’s remember that technology isn’t neutral. It reflects the choices we make the biases we embed, the transparency we provide, and the accountability we uphold. Therefore, let’s foster interdisciplinary dialogues, engage policymakers, and empower users to demand Ethical AI. Only then can we navigate this brave new world with wisdom and compassion.
Lastly, Ethical AI isn’t a luxury; it’s our moral compass. As creators and users of AI, we hold the pen that writes its future. Let’s choose a narrative that uplifts humanity – one where algorithms serve justice, fairness, and empathy. Hence, the journey continues, and the stakes have never been higher.
Remember, the path to Ethical AI isn’t linear; it’s a dance between innovation and conscience. Hence, dance wisely.
Thank You
