# The Future of the Human-Machine Interface (HMI) in Society 5.0
## 4 Human-Machine Interaction (HMI)
### Augmented Intelligence  
Augmented intelligence, also known as intelligence amplification, refers to the use of Machine Learning, Artificial Intelligence (AI), and other technologies to enhance human decision making and problem solving abilities. Augmented intelligence differs from Artificial Intelligence in that it seeks to augment, rather than replace, human intelligence. Natural language processing (NLP): NLP is a type of AI that enables computers to understand and respond to human language. NLP can be used to analyze large volumes of text data, such as customer feedback, and extract meaningful insights to help humans make better decisions. Predictive analytics: Predictive analytics uses Machine Learning algorithms to analyze data and predict future outcomes [36]. For example, a retailer might use predictive analytics to forecast sales based on historical data and current trends. Virtual assistants: Virtual assistants, such as Siri or Alexa, use natural language processing and Machine Learning algorithms to help humans perform tasks more efficiently. For example, a virtual assistant might help a person schedule appointments, order groceries, or control smart home devices. Decision support systems: Decision support systems are computer programs that use data and algorithms to help humans make better decisions. For example, a healthcare provider might use a decision support system to help diagnose a patient's condition based on symptoms and medical history. The goal of augmented intelligence is to help humans make better-informed decisions by providing them with relevant information, insights, and recommendations. By augmenting human intelligence with Machine Learning and AI technologies, humans can perform tasks more efficiently, accurately, and with greater insights, leading to better outcomes [37].  
Prescriptive analytics and augmented intelligence are related concepts that both use Machine Learning and Artificial Intelligence (AI) to provide humans with insights and recommendations for decision making. Prescriptive analytics refers to the use of data, statistical algorithms, and Machine Learning techniques to identify the best course of action for a given situation. It involves analyzing data and identifying patterns to make predictions about future outcomes, then recommending a course of action based on those predictions. Augmented intelligence, on the other hand, refers to the use of AI and other technologies to enhance human decision making and problem-solving abilities. It seeks to augment, rather than replace, human intelligence by providing humans with relevant information, insights, and recommendations to help them make better-informed decisions. Prescriptive analytics is a type of augmented intelligence because it provides humans with specific recommendations for actions to take based on data and analysis. For example, a healthcare provider might use prescriptive analytics to recommend a treatment plan for a patient based on their medical history and current condition. The provider can then use their own judgment and expertise to make a final decision about the course of treatment [38]. In summary, prescriptive analytics and augmented intelligence are both forms of Artificial Intelligence that aim to provide humans with insights and recommendations to improve decision making. Prescriptive analytics specifically provides specific recommendations based on data analysis, while augmented intelligence seeks to enhance human intelligence more broadly by providing relevant information and insights.