Ethics of AI in Decision-Making

Should AI have a role in hiring, healthcare diagnosis, or criminal justice? Where do we draw the line? The application of AI is reaching the edges. Starting from a single therapist to a big AI model, it has given researchers a lot ore ideas that made them think that they can make an AI assistant like Jarvice in Marvel Studios. AN AI that handled every single thought of Tony Stark, turning it into great inventions and innovations.  Now, when it comes to AI performance, there is no doubt that they are extremely obedient. They never question why their engineers made them the way they are, or very simply, they do not have any emotions. They are quite rational. They think what we have made them think. Just the way we want them to think. Nothing more, nothing less.  Now that is something very good. Having such an AI partner with no demands of food or emotions and just a friendly tone handling every task is something worth having.  But the question is, should we use AI in every field, such as human recruitment, healthcare, education, and law?

AI in the Justice System: Fair or Flawed?

AI as a Judge seems normal, as there is a law book that humans need to learn and remember all of the articles, clauses, and the constitution. They have to listen to the petitions and give a verdict based on the rules and regulations given in the Law book. But what if this human system is replaced by AI? They can speed up tasks like legal research and document review, which currently take human judges and lawyers weeks or months. In court, judges usually make decisions based on past legal cases (called precedents) and written laws. But because judges are human, their personal beliefs or emotions can sometimes affect how they decide a case. An AI judge, on the other hand, doesn’t have feelings, personal opinions, or perception. If it follows the laws and past decisions strictly, it could help make sure every case is judged in the same way. This would mean people could expect more consistent and predictable outcomes, no matter who they are.  There are still some limitations to that. Not every criminal is the same, not every crime is the same. We have seen in history that due to the virtue of judges, many criminals have repented, or there was a strong network of conspiracies that tangled the true and false facts, making an innocent face a deadly criminal, and only humanized thinking and insight have detected the very slight difference and saved thousands of such innocent people.

 AI in Healthcare: Helpful or Harmful?

•  Analyze medical images like X-rays, CT scans, and MRIs (e.g., spotting tumors or fractures).
• Predict diseases such as cancer, diabetes, or heart conditions based on health records.
• Suggest treatment options by comparing patient data to thousands of similar cases. 

 Ethical and Legal Concerns:

• What happens if the AI makes a wrong diagnosis?
• Is the doctor, the hospital, or the AI company legally liable?
• AI doesn’t have legal “personhood,” so someone must take the blame.
• Patients are often not told that an AI helped make decisions about their health.
• That raises ethical issues around informed consent, shouldn’t patients know?

This would simply result in the loss of life, and no one to blame. Doctors might start trusting the AI findings blindly. Also, this could lead to misdiagnosis of the diseases. The IBM Watson for Oncology failure is a real example. 

AI in Hiring: Amazon’s Controversial Experiment

AI as a sole E-commerce partner also has some limitations. In 2014–2017, Amazon built an internal AI tool to help with hiring by reviewing job applicants’ resumes. It was meant to automate and speed up recruitment, especially for technical roles. The AI learned from past hiring data, which reflected Amazon’s own historical bias, favoring male candidates for tech roles. The model disfavored resumes that included the word “women’s” (e.g., “women’s chess club captain”) and treated graduates from all-women’s colleges less favorably and favored male candidates, even when equally or more qualified female applicants applied. Amazon quietly shut down the AI hiring project around 2018. The company recognized that the system was not neutral, but rather exaggerated past human biases, raising serious ethical concerns. 

Lack of Transparency

One of the biggest concerns with using AI in hiring is that candidates often don’t even realize their applications are being filtered by a machine. They don’t know what the system is looking for, how it scores their resume, or why they may have been rejected. This lack of transparency makes it impossible for applicants to understand or challenge the decision.

 No Accountability:

 On top of that, there’s a serious fairness and accountability issue: if a qualified person is unfairly rejected because of a biased or flawed algorithm, who is to blame? The AI can’t take responsibility, and companies rarely explain their decision-making process. This creates a system where mistakes can happen, and no one is held accountable.

Draw the Line Before It’s Too Late

As we continue to advance AI technology, the key question remains, not just what AI can do, but what it should do. While AI can offer speed, consistency, and support in complex tasks, its lack of emotion, empathy, and ethical reasoning makes it unfit to handle every domain without oversight. Especially in fields that touch human lives, like justice, health, and hiring, decisions should not be left solely to machines. We must draw a clear boundary between automation and human responsibility. AI should remain a tool, not a judge of humanity. As we move forward, our challenge is not just to build smarter machines, but to use them wisely, with accountability, transparency, and most importantly, with empathy.