Brianna White

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Jul 30, 2019
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While we’re still debating whether and how long it will take to reach singularity and superintelligence, artificial intelligence is playing an increasingly important role in our everyday lives. Artificial intelligence – most commonly machine learning (ML) – is the process of training algorithms using data, instead of explicitly programming them. Such algorithms are already being used in applications ranging from HR to finance and transport to medicine, and in use cases almost too numerous to mention.
The benefits of machine learning are obvious: they enable faster analysis of vastly more data than any human or even groups of humans are capable of. Many ML applications that can surpass human capabilities already exist, such as those designed to play Go and Chess, or detect fraudulent insurance claims. Unlike past AI boom-and-bust cycles, we’re unlikely to see the return of an AI winter. Current ML algorithms are generating enough value to justify continued research and funding. AI is here to stay – and set to be more pervasive in both industry and our personal lives.
However, one hurdle still exists on the path to true AI success – trust. How can we trust AI when we’ve seen it make so many poor decisions?
Obstacles to reaching AI’s full potential
At the risk of oversimplifying the situation, I believe that there are just two fundamental aspects that must be addressed before AI can reach its full potential. Those are a proper understanding of what AI is capable of and how it should be used, and improvements to the security of AI.
Continue reading: https://www.helpnetsecurity.com/2021/12/20/secure-ai/
 

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