Three challenges facing AI in 2020

The beginning of a new year often brings promises of change, announcements of innovation or reflections on how far we’ve come. With the beginning of a new decade, these factors have gained some extra resonance, and the answers are considered more profoundly. When it comes to the tech world, there is no change more hotly disputed, no innovation more proudly announced and no reflection more wistfully made than on artificial intelligence.

 AI has been around for a while, and it has come on leaps and bounds in that time. It has developed from a fantastical concept in philosophy and fiction to technology with real-world applications. There is probably no innovation that has been more critically debated by the general public over a prolonged period, a debate that is fueled by the searing pace at which AI is improved. It is a concept for which discussion and development go hand in hand.

So, considering this, what has 2020 got in store for artificial intelligence? With such a quickly-evolving sector it’s difficult to make precise predictions, but based on what we have seen thus far, there are a few elements that are sure to be heavily featured in the discussion and development of AI technologies this year.

 Ethics

The discussion of the ethical implications of artificial intelligence predates the technology itself. Indeed, in the 1950s and 60s, back when the idea of self-thinking computers was a science fiction fantasy, Isaac Asimov was calling into question the potential risks of uncontrolled artificial intelligence and the lengths humans would have to go to in order to avoid them.

 While we’re a long way from having to implement the Laws of Robotics, the ethics surrounding the development of ever more intelligent machines are becoming a huge discussion point. With the potential power of AI in disrupting industries and outpacing human workers, are we creating a future in which we have no place? Should machine-learning technology be trusted with the business of social institutions?

 AI is made possible — or at least significantly more achievable — by Big Data, which has its own ethical quandaries. Questions over the privacy of personal information and inherent bias in data collecting methods are being consistently raised, and are expected to form a core part of the discussion on these technologies this year.

Machine Learning

If there was ever a time that AI could exist without machine learning, it is firmly behind us. Over the past few years machine learning has proven itself to be a legitimate and highly efficient way of training AI technology, making systems exponentially smarter and better at what they do.

That is not to say machine learning has been perfected, far from it. The quality of data input is still low — experts blame this for the bias issues discussed above — as is the quality of data output. However, it is still undoubtedly the best way to train AI systems, so expect improvements to come thick and fast this year.

Real-world applications

The biggest defining aspect of AI this year will be the fact that it’s no longer a science fiction concept of a tech-developer pipe dream: it’s here, it’s working, and it’s becoming an established part of how we relate to technology and the internet. As more users relate directly to AI technologies, the mystery and confusion surrounding them will start to disapper, and the discussion on uses, impacts and ethical concerns will become increasingly democratic.

Take chatbots as an example. In their original form they represented tests of technological development, they were shared amongst designers as jokes or flexes, a tongue-in-cheek way to take the Turing Test. Now, however, chatbots like Replika are available to download from mobile app stores for free, and anyone can see the fruits of machine learning technology. This year, anyone can use this technology for a new friend, or to keep a dying relative alive.

Add this to the mounting number of companies that use machine learning for everything from recruitment to customer service and AI is quickly becoming a major factor in how we are seen by corporations, and how we relate to the world around us.

 

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