## 2 Artificial Intelligence and Society  
The fast evolution of artificial intelligence in society depends on several factors; one is the simultaneous accessibility of powerful and cost-effective computing and of large datasets, and another is the speed of industry, which has raced ahead of academia. Until 2014, the most substantial machine learning models were announced by academia. Since then, industry has taken over [5].  
A recent study suggests that Chinese citizens feel more positively about AI products than Americans and that men tend to feel more positively about AI products and services than women [12].  
Figure 1: Interest over time in “artificial intelligence” obtained from Google Trends.  
In fact, artificial intelligence has wide-reaching potential for society in different scenarios, especially when speaking about health, finance, information technology, education, transportation, and environmental monitoring.  
In the realm of health, AI applications range from diagnostic tools and personalized medicine to predictive analytics that can help identify disease outbreaks and optimize healthcare resource allocation. The integration of AI technologies in healthcare systems has the potential to enhance patient outcomes, streamline processes, and contribute to the development of innovative treatments, self-monitoring, and coaching, for example. Furthermore, AI is expected to improve the quality of care and health of patients by decreasing human errors [27].  
In the finance sector, AI plays a crucial role in risk management, fraud detection, and algorithmic trading [28].  
The information technology (IT) landscape is continually evolving with AI-driven advancements. In IT, AI-driven advancements have led to transformative developments across various domains. Examples include the implementation of natural language processing (NLP) for improved human-computer interactions [29], the use of machine learning in cybersecurity for proactive threat detection [30], and the application of predictive analytics to anticipate and prevent system failures. Automated code generation and testing, personalized user experiences, and autonomous IT operations are other notable areas where AI enhances efficiency [31]. Additionally, AI contributes to data management and analysis, image and speech recognition, and robotic process automation in IT processes [32]. These advancements collectively optimize workflows, improve security, and elevate the overall user experience in diverse IT applications.  
In the field of education, AI applications include personalized learning platforms, intelligent tutoring systems, and educational analytics. Analyzing sentiment in media coverage can reveal societal attitudes toward AI in education, helping institutions tailor their strategies to meet the evolving needs of students, educators, and the workforce [33].  
The impact of AI on transportation is transformative, with applications ranging from autonomous vehicles and traffic management to predictive maintenance [34]. Understanding public sentiment through media analysis is crucial for policymakers and transportation authorities to address concerns related to safety, privacy, and the integration of AI-driven technologies in urban planning.  
Lastly, in environmental monitoring, AI-powered technologies assist in data analysis, climate modeling, and conservation efforts [35]. Analyzing sentiment in media coverage can shed light on public attitudes toward AI's role in addressing environmental challenges, helping shape policies that balance technological progress with ecological sustainability.  
In conclusion, sentiment analysis regarding media coverage of AI is a powerful tool for understanding societal expectations, concerns, and perceptions. This knowledge is instrumental in steering the development and deployment of AI technologies toward responsible, ethical, and beneficial outcomes for society.