The rise of artificial intelligence (AI) has brought about significant advancements, particularly in fields like healthcare and transportation. However, allowing AI to make life-and-death decisions raises critical ethical concerns. While AI can improve efficiency and reduce human error, it lacks the empathy required for such decisions, introduces risks of unforeseen malfunctions, and raises accountability issues. Therefore, society must carefully weigh the benefits against these risks before delegating life-or-death decisions to AI. Even though AI can reduce human errors, I still believe that it should not be allowed to make life-and-death decisions as it lacks empathy, humane behaviour, and accountability.
One argument in favor of AI making life-and-death decisions is that it can reduce human error. In fields like healthcare, mistakes in diagnoses or treatment can have fatal consequences. AI algorithms can analyze vast amounts of data quickly and accurately, offering more consistent results than human professionals. For example, AI can assist in surgeries or predict complications faster than humans. Similarly, autonomous vehicles could save lives by making split-second decisions to avoid accidents that human drivers may fail to react to in time.
However, AI lacks the empathy required for life-or-death situations. Human decisions in such cases are often influenced by emotions, ethics, or compassion, which AI systems cannot replicate. For example, a doctor deciding to prioritize one patient over another might take personal circumstances into account, while AI will rely strictly on data and pre-set algorithms. This inability to factor in human nuances can lead to morally questionable outcomes.
Moreover, AI systems are prone to malfunction or unexpected behavior. A glitch in a medical AI or an autonomous vehicle’s software could have catastrophic consequences, resulting in injuries or fatalities. Since no technology is entirely error-free, relying on AI for critical decisions introduces uncertainty. The risks of technical failures must be minimized before such responsibilities can be entrusted to machines.
Another significant concern is the issue of accountability. If AI makes a fatal mistake, it becomes unclear who should be held responsible—the developers, the users, or the AI itself. In high-stakes situations like healthcare, assigning responsibility is essential for justice and improvement. A lack of accountability could create legal and ethical challenges, eroding trust in AI systems.
In conclusion, while AI has the potential to reduce human error and increase efficiency in life-or-death scenarios, it is not without significant risks. The lack of empathy, potential malfunctions, and accountability issues must be carefully considered. Therefore, it is crucial to limit AI’s role in such decisions to assistive rather than autonomous functions, ensuring human oversight is maintained.