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The Future of AI is Intelligence Augmentation

The Future of AI is Intelligence Augmentation

is no longer a sci-fi vision of the future. We are living in a world where is disrupting industry and society at large in truly transformative ways.

SwissCognitiveFrom chat bots reinventing customer service performace to machines such as IBM’s Watson beating some of the most intelligent human beings to ever live, is altering everything from the biggest technological innovations to the simplest of tasks we perform on a daily basis. And both scenarios are true; has both the ability to push the world towards a state of permanent utopia, or it may very well trigger the downfall of humanity. The question, is no longer whether or not is possibly driving us to one of these two futures, but whether or not we can adapt at this early stage in a way that benefits humanity.

One of the first issues we’ve come to face is the question of what , and intelligence in general, really is. While inventors such as Elon Musk have already begun designing brain-computer interfaces that could theoretically be used to treat a variety of medical issues, access thoughts and memories and perhaps one day even upload one’s consciousness to the internet, our current lack of understanding of how exactly the brain works—let alone our understanding of abstract concepts such as thoughts and human consciousness—makes it extremely difficult for scientists to create -powered devices that can precisely interact with the brain and the body in a way that isn’t detrimental. However, as we continue to deepen our understanding of the brain and human consciousness, we can further begin using technology simultaneously to deepen our understanding of human intelligence.

It is time to envision a more realistic future, one in which and machine are used to supplement and support human intelligence, rather than subvert it. The concept of intelligence augmentation demonstrates how and humans will be able to live together in a mutually beneficial fashion.

While may surpass humans in structured environments where inputs and outputs are clearly defined—such as a game of chess or the organization of large sets of data—this same machine often fails to work in less defined environments that involve nuanced decision-making and problem-solving. In structured settings, can organize massive amounts of documents, emails and customer information in a business in mere seconds. But this same lacks the ability to evaluate what should be done with these data sets—which is the sort of nuanced decision making that humans excel at. If humans and worked together, then, algorithms could organize these data loads into a user-friendly interface with which human workers could more quickly and effectively make decisions. […]

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