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Answer :
The question presented is about identifying a key challenge associated with Generative AI, and the correct option is 2. Ensuring the generated output is unbiased and ethical.
Generative AI refers to artificial intelligence models that generate new data similar to the input they are trained on. For example, they can create images, text, music, and more. While these systems are powerful, they have certain challenges:
Inability to adapt new data sets without retraining: While it is true that some AI models may need retraining to adapt to new data, advances in AI techniques like transfer learning and continuous learning are addressing these challenges.
Ensuring the generated output is unbiased and ethical: This is a significant challenge for Generative AI. Since these models learn from existing data, any biases within the data can reflect in their output. Ensuring that AI systems do not perpetuate or amplify biases and that they adhere to ethical standards is crucial. For instance, if a generative AI is used to create news articles, it must be ensured that the outputs are not biased or harmful.
None of the above: This option is incorrect as there are indeed challenges associated with Generative AI.
Lack of creativity in output: Generative AI is often praised for its creative ability, such as creating art or music. However, the creativity of the AI is often limited to its training data and the way it combines ideas within those boundaries.
Therefore, ensuring bias-free and ethical outputs stands out as a major challenge in the field of Generative AI. This involves careful curation of training data and ongoing oversight of AI systems.
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