The last few months have seen some big statements of intent from companies like IBM in the field of cognitive computing, and these are likely to drive massive advancements over the course of 2016. In October, IBM launched a 2,000-employee consulting unit devoted exclusively to work that builds on the cognitive computing capabilities of IBM Watson. It also announced plans to train a further 25,000 IBM consultants and practitioners on cognitive computing, and CEO Ginni Rometty said that the firm is becoming a cognitive business.
Cognitive-based computing systems, such as IBM Watson, are built in such a way as to act more in sync with human beings than traditional systems, by simulating human thought processes in a computerized model. They are fundamentally AI that feeds on big data, using data mining, pattern recognition and natural language processing to self-learn in the same way that the human brain works. Cognitive systems are able to understand natural language questions and return understandable answers because of the taxonomies that they have built up around specific knowledge domains.
IBM Senior Vice President John Kelly said: ‘Though cognitive computing includes some elements of the academic discipline of artificial intelligence, it's a broader idea. Rather than producing machines that think for people, cognitive computing is all about augmenting human intelligence — helping us think better. Over time, it will be possible to build cognitive technologies into many of the IT solutions and human-designed systems on earth, imbuing them with a kind of 'thinking' ability. These new capabilities will enable people and organizations to accomplish things they couldn't before — understanding more deeply how the world works, predicting the consequences of actions and making better decisions.’
The implications of cognitive computing for businesses are many. It can be used in any space that traditionally involves deployment of sophisticated, context sensitive, human reasoning, and is used to make the best decisions in responses to queries input by users. This is true within business functions, with staff able to leverage insights to gather intelligence about the best possible option, and also for consumers. So, for example, a retailer’s mobile platform, when enhanced with cognitive commerce capabilities, allows its customers to ask questions about every aspect of its products.
Cognitive systems can still only advise people, as opposed to prescribing a final option. They present the best options to users and then allow them to pick the results. There is still resistance to cognitive computing, with many still fearing the consequences around machines left to run themselves. When dealing with human-like, complex problems, there may be no ‘right’ answer, there may only be an optimal one, and it is important to understand that the human is still having the final decision. Many cognitive computing systems are also able to provide a trail of reasoning too, so decisions are not accepted blindly on faith. According to a survey by IBM’s Economist Intelligence Unit, cognitive applications are being built and deployed by a growing range of organizations in many industries. Data traceability programs, along with greater data sharing across the world, which will provide more information to help cognitive systems grow, should see cognitive computing finally reach its potential in everyday life.