You may have been told that there is someone who is similar to you in some way, but have you imagined that there is someone similar to you in everything, including form and action?
This is exactly the case in the worlds of the “Metaverse”, which plans to create a virtual world that simulates the physical world inch by inch and arm by arm, and here comes the new technical trend that is starting to be talked about in what is known as “digital twin”.
real virtual twin
A digital twin is a ‘virtual’ digital replica of anything in the ‘physical’ world, be it a person, an organisation, a system or something else. Digital twins have the unique task of helping to improve responses or provide other responses to what is happening in real life.
So, the creation of these twins bridges the gap between the physical world and the virtual world, and the construction of these virtual digital counterparts is based on the data generated by physical entities, and then these twins allow virtual entities to move alongside their physical counterparts to exist, using them for different purposes.
These twins were initially just advanced three-dimensional computer models, but artificial intelligence, in addition to the new generation of the Internet known as the “Internet of Things”, enabled these twins to use sensors, sensors and artificial intelligence tools that enable them set to connect Physical objects in a digital network.
This means that we can now build anything digital that can learn on its own from its real-world counterpart, and then evolve itself to anticipate the appropriate future responses or decisions it needs to make.
And because it’s an exact copy, the digital twin makes the same decisions you would if you had the same data. It may sound like science fiction, but some believe that these numbers will double in the next decade, and others believe that we will have the first version of digital twins imitating humans before the end of the current decade. It may seem crazy to some, but this matter has become possible in a way that exceeds the will of some to accept or believe.
Although we think we are special and unique, AI has successfully taken its first steps by using the wealth of information available around it to provide inferences and explanations for many things such as our personalities, social behavior and buying tendencies, and ultimately by contributing to understanding and solving the most complex biological dilemmas.
We live in the age of big data, or “data lakes,” so your attitudes, tendencies, overt preferences, and behaviors are all subject to collection.
However, the amount of data that organizations collect is surprising. According to a report published by The Conversation, in 2019 the Walt Disney Company acquired Hulu, whose private record of data collection has been questioned by some.
Most of the apps on your phone are involved in collecting your data, including the coffee ordering app, so should we be concerned about that data collection?
Performance accuracy is a key factor
The performance accuracy indicator measures how well the digital version matches the performance of the physical target, thus reflecting how realistic the digital twin is to the real world.
In an exciting experience, a player in a driving video game, in which the player uses a keyboard and steering brake, demonstrates lower performance than a driving simulator, which contains all the driving tools found in the real world, such as windshields , pedals, and more.
Digital twins require a high degree of precision to be able to integrate all the data in the real world in real time, which means that if it rains in reality, it will also rain in the simulator.
Currently, human-mimicking digital twins are low-resolution, requiring a wealth of information about an individual’s preferences, biases, and behaviors, as well as other data about an individual’s immediate physical and social environment, to make correct predictions.
So it requires massive sensors to collect and process that data in real-time, making building true digital twins a remote possibility, at least in the near future.
The production of digital twins raises a number of ethical issues related to the integrity of the data, the accuracy of predictions these twins produce, the ability to monitor and update them, and the ownership and availability of these twin.
Predictions about how we will behave depend on the analysis of the data collected from us about our behavior and habits, so the statistics of this data are the primary source for those predictions made by digital twins.
However, these statistics and numbers have specific meanings that are limited to the measurement tools used in data collection and analysis, and do not have absolute meanings. These data are largely reductive, either for convenience or because of the practical limitations of the technology.
These measurements can work well in predicting one context, and fail in another, which brings us to another ethical issue known as the “McNamara Fallacy” or the “Quantitative Fallacy”, which assumes that numbers have abstract meanings that are separate from context, and therefore decisions. is made on the basis of quantitative measures while ignoring other contexts.