The phenomenon of ‘ hallucinations ’ in AI , where models provide baseless or incorrect responses , also poses a unique challenge . “ Furthermore , the advanced training of generative AI-powered tools allows them to convincingly manipulate humans through phishing attacks , introducing an unpredictable element to an already volatile cybersecurity landscape .
Bias in training data and the substantial energy consumption of AI models are other ethical considerations demanding attention . “ It becomes a significant ethical concern when AI is used in decision-making processes like hiring , lending , and criminal justice ,” Purohit describes . “ Furthermore , generative AI models consume vast amounts of energy both during training and while handling user queries . As these models continue to grow in sophistication , their environmental impact is bound to increase unless stringent regulations are enforced .”
Ethical frameworks and guidelines are essential for generative AI Purohit underlines the need for increased focus on accountability , ethics and fake detection in generative AI . The misuse of generative AI can lead to criminal and
122 March 2024