The Fourth Industrial Revolution, or Industry 4.0, has been a blessing for mankind since its inception a few years ago. It is the ongoing automation of traditional manufacturing and industrial practices, using modern smart technology. Right from Artificial Intelligence, Internet of Things (IoT) and Cloud Computing to Autonomous Vehicles, Drones and Robots – there is no doubt that this industrial revolution aims to propel humans alongside technology into achieving the impossible. One of the many aspects of Industry 4.0 – Artificial Intelligence has successfully become such a significant part of our lives already that its future implications cannot be comprehended by human intelligence anymore.
Healthcare, Education, Manufacturing, and Finance are some of the top industries where artificial intelligence has been well integrated into their systems. AI’s significant use has made it paramount to trust its decision making. During the early adoption of AI, understanding why a certain output was produced by the model was secondary to the output matching our expectations. As long as output was produced, the hunt for an explanation never began.
Not knowing seemed to work just fine for simpler & easier applications of AI. Systems like the Product recommendation systems did not entail a life or death decision. However, when it comes to autonomous vehicles or medical diagnosis systems – the need for an explanation begins to rise. Consequently, it became a ‘black box dilemma.’ Only the inputs (in the form of raw data) and output (in the form of predictions) were visible. To place our trust in the model, it is important for humans to understand why a particular conclusion is drawn.
First, we use data for training the black box, which results in the learning of a particular function. Then, it is followed by feeding inputs & receiving an output from the model – without any justification. Although there are times when the outputs sit parallel to our expectations but being able to interpret the reason behind its conclusion could possibly shed light on many unknown things.