Ethics in Natural Language Processing: Addressing Bias and Misinformation

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Explores global data justice, social fairness in data governance, algorithmic ethics, and the political responsibility of researchers.

Explores data ethics, focusing on fairness, justice, and Al systems' broader implications.

Covers the ethical implications of artificial intelligence in technology, focusing on data, algorithms, design, sustainability, and accountability.

Delves into advancements and challenges in NLP, along with ethical considerations and potential harms.

Addresses data collection, annotation processes, and biases in natural language processing.

Explores the ethical implications of deploying machine learning algorithms and emphasizes the importance of fairness in decision-making processes.

Explores advancements in generative AI and reinforcement learning, focusing on their applications, safety, and future research directions.