Artificial intelligence is the ability of computers to behave in an ‘intelligent’ way. It means making good decisions based on the available data. In more technical terms, it takes ‘input’ and transforms it into ‘output’, which is beneficial for its ultimate goal. Whether it is through data to find a useful pattern or to help drive an automated vehicle is irrelevant. It is the same under the hood. It differs from just the degree of complexity. The biggest advantage of AI is that it can accomplish what we cannot. It is very different than humans. Artificial intelligence works in large numbers and does not do so creatively as we think. This means that we are strong, where we are weak, and weak where we are strong. Humans and AI make very good teams. Contrary to popular belief, AI is often used instead of transforming human teams.
Reduced Human Risk
There are many areas where it is dangerous for a person to be physically present. Artificial intelligence can be used in such cases because it will enable machines to make decisions in real time. An example of this may be deep sea drilling at the bottom of the sea where high risk of human life is involved.
As humans, we can work 5-6 hours, and can have 7-8 hours, including breaks. Usually, we should not use more than this because we need to rest and restore energy. In addition, we require a weekly holiday to charge the next day of office. However, a machine can serve you 24/7 without any break and can be bored unlike humans.
Efficiency and Accuracy
AI is scalable and efficient. Instead of being limited by the finite resource of a human brain, it can be integrated with scalable computer systems that range from cell phones to supercomputers such as AI such as IBM Watson and Google DeepMind. The scalable efficiency of AI means that it can be used to perform very small tasks and highly complex tasks, without being fatigued. It is a misconception that all AI have to be ‘smart’ to be ‘intelligent’. AI can be used to perform tasks that are otherwise too boring, time consuming or repetitive for humans, such as crawling through webpages to gather information. Will you be stuck through a million webpages manually copying information pieces and pasting them into a spreadsheet?
This is the type in which machines will have systems that can allow them to be self-conscious. This phase is also an extension of the Theory of Mind phase in which machines will have self-awareness for a cause. This will take machines to a new level of intelligence. While AI-researchers have a long road to walk before self-conscious machines run, current AI scientists focus on honing the machine learning skills of these computers. Enabling machines to react more like humans is getting better each day.
Engaging machines in tasks that can be a threat to humans can pay off well. For example, enabling machines to deal with natural disasters can result in faster recovery and less pressure on human teams. The idea rides high on Google and Harvard’s initiative to develop AI systems that can predict the locations behind earthquakes. After more than 131,000 earthquakes and the studies behind it, scientists have tested this neural network at 30,000 events. It shows greater accuracy in pinning aftershock locations when standing against conventional methods.