Pentagon-Funded Study Uses AI to Detect ‘Violations of Social Norms’ in Text

Pentagon-Funded Study Uses AI to Detect ‘Violations of Social Norms’ in Text

In recent years, artificial intelligence (AI) has been making groundbreaking advances as an effective tool for natural language processing. A recent study funded by the Pentagon and conducted by researchers from the University of Southern California shows how AI is being applied to help detect violations of social norms in text.

The objective of the study was to develop an AI system that could effectively and accurately detect real-world language that violates social norms. To do this, the researchers collected a dataset of online conversations from Reddit and manually annotated it to identify violations of social norms. This dataset was divided into two parts: a training set and a testing set. The training set was used to train a neural network-based model to detect violations, and the testing set was used to evaluate the performance of the model.

The model was tested on two benchmarks for detecting social norm violations: the DailyDialogue dataset, which is comprised of conversations about everyday topics, and the Reddit-large dataset, which is comprised of conversations about any topic. The results of the study showed that the AI model was able to identify violations of social norms with a high degree of accuracy.

The study showed how AI can be utilised to detect violations of social norms in real-world conversations. This technology has a variety of potential applications, such as helping to better understand the social dynamics of online interactions, identifying hate speech, and addressing cyberbullying. It could also potentially be used in the education sector to help identify students who are in need of counselling services or more support.

The AI model developed in this study can operate in five different languages: English, Spanish, French, German and Italian. In the future, it is expected that the system will be able to be trained to detect cultural norms, which could enable it to be applied to a much wider range of languages. This could have practical implications for all forms of online discourse.

Overall, this study serves as an example of the many ways in which AI can be used to detect social norm violations in text. The implications of this technology could be far-reaching and are undoubtedly worth further exploration.

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