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Subjectivity in the Age of Artificial Intelligence
Artificial Intelligence (AI) has rapidly evolved in recent years, and there have been remarkable successes in many fields. There are AI systems that can suggest diagnoses for medical conditions, predict weather patterns and natural disasters, and even play complex games like chess or Go. However, AI systems also have significant limitations and do not have the full range of human capabilities. Subjectivity and biases are examples of limitations when it comes to AI.
The development of AI systems is dependent on data, and that data is often gathered from human sources. There are instances where human data may be biased or subjective. Additionally, algorithms designed by humans to train AI systems may also introduce biases unintentionally. For instance, an AI algorithm might be trained on data that consistently underrepresents or misrepresents a certain group, leading to biased predictions.
Subjectivity is also an issue for AI in creative fields. While AI-powered systems have the ability to generate art, music, and literature on their own, the outputs are limited to the rules they are programmed to follow. For instance, an AI system that creates music may never fully understand human expression or emotions because it does not have the capacity to feel them.
There is a growing need to address AI’s limitations, and some believe that the solution is to create ethical frameworks to govern AI development. An example is the IEEE Global Initiative for Ethical Considerations in AI and Autonomous Systems, which is working to develop consensus guidelines for the development of ethical AI. Additionally, some organizations are actively working to address AI skills gaps, which include researching ways to mitigate bias in AI programs.
In all, the development of AI is an exciting time. However, as AI technology continues to advance, it is essential to be mindful of the potential limitations and biases that may unduly influence it. Addressing these challenges will make AI more reliable, ethical, and effective in the long run.
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