WELCOME TO THE HUMAN DIGITAL TWIN (HDT)
Human-Environment Digital Integration
THE AGE OF THE MACHINES
Smart machines, or agents, are becoming more common. Machines will soon be present in many aspects of our public and private lives. A smart city, for example, is expected to include 80 different types of smart machines by 2025. These numerous machines would manage and optimize different aspects of our lives, such as health, mobility, energy, and security. Smart machines, digital communication, and digital technologies should give us more options for shaping our professional and personal lives based on our individual needs and preferences. To take advantage of the expanded options and opportunities, we are expected to evaluate more information in order to make more choices in a shorter period of time, which may overwhelm many of us. However, if we rely on our own intelligent machine, our own Human Digital Twin (HDT), to manage and optimize the complex digital interactions that surround us, we will be able to maintain our long-term interests and life balance.
The HDT is a personal agent that observes its user's interactions with the machines (or applications) around her and learns her interaction patterns. The HDT uses learned patterns and user-defined objectives to recommend how she should use the various machines to achieve her goals. Users can also delegate to the HDT some of their habitual responses to the machines around them. Such delegation would improve the overall effectiveness of the environment while saving the human user a significant amount of time and effort. The HDT learns user interaction patterns by analyzing the metadata of information exchanged during user-machine interactions rather than the content of that information. This allows the HDT to protect its users' privacy while still providing a trustworthy representation of their behavior.
STANDARDIZATION OF HUMAN-MACHINES INTERACTIONS' REPRESENTATION
The HDT learns and defines a standard digital representation of its user, which enables a seamless integration of humans with many smart machines and agents. Based on the standard representation, the HDT further learns and updates a dynamic policy of the human-machine interactions (see HDT-HMT page!).