ABU DHABI (ALETIHAD)
A new research study by TRENDS Research & Advisory, "The Role of AI in Predicting Political Stability," has emphasised that AI opens new prospects for predicting political stability.
The study reveals AI's ability to analyse vast amounts of political, economic, and social data and uncover complex patterns that enable more accurate predictions of political risks, such as social unrest and coups, compared to traditional methods.
Prepared by Dr. Sayed Ali Abu Farha and Abdullah Al-Khaja, the study explores various AI technologies used in political data analysis.
These include natural language processing (NLP) for analysing political discourse and news reports to extract early indicators of crises, machine learning for building predictive models based on historical data and identifying key factors affecting political stability, and deep neural networks for detecting complex patterns in large datasets, thereby improving the accuracy of predictions.
Additionally, the study highlights several challenges in using AI for political analysis.
A significant challenge is the lack of reliable data, as political datasets often suffer from issues of quality and credibility, which can undermine the accuracy of the models.
Another challenge is bias in AI models, as they may reflect prejudices in the training data, leading to unfair outcomes.
Moreover, the “black box” nature of deep learning models makes it difficult to interpret their outputs, which can reduce trust in their results.
The study offers several recommendations to overcome these challenges.
It calls for integrating diverse data sources to improve the comprehensiveness and accuracy of models, developing explainable AI techniques to enhance transparency and trust, fostering collaboration between researchers and practitioners to create models that meet real-world needs, and addressing ethical concerns such as privacy and bias to ensure responsible AI usage.
The study concludes that AI is a powerful tool for helping decision-makers understand political dynamics and make informed decisions.
However, it emphasises the importance of developing and using this technology responsibly and cautiously to maximise its benefits and minimise risks.