Computing pioneer Alan Turing neatly summed up the theory of cognitive computing and the potential for AI in his 1950 paper ‘Computing Machinery and Intelligence’:
‘Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's? If this were then subjected to an appropriate course of education one would obtain the adult brain.’
From a practical perspective, this means that cognitive computers get better the more we use them, ‘learning’ from our responses to each interaction and putting the information they have into a human context. Instead of being presented with a finished programme crafted to the last detail by developers, users take some of the responsibility themselves for teaching and refining it to meet their needs.
Computers that work with us, our documents and the context in which we place them opens up the field for more widespread use outside the IT department. Making interaction and systems development more natural and intuitive means more people can use them, more often. And the more people involved in ‘educating’ cognitive systems, the faster they will evolve and the more accurate and useful they will become.
This will have tremendous advantages in the workplace – cognitive’s ability to access and use a multitude of data points is ideal for scaling knowledge and enhancing learning and development across all business areas - training, HR, operations, sales – anywhere there is a need for the intelligent application of information.
Natural language processing – the future of cognitive
While the ability to analyse documents and other content to provide more ‘human’ responses to written questions is undoubtedly a terrific development, there’s a reason why every computer appearing in SciFi from Star Trek to 2001: A space odyssey to Her uses speech as its primary method of communication. Natural language processing via the spoken word is the next logical step towards parity of intelligence – or at least a plausible imitation.
Intelligent personal assistants Siri (iOS) and Cortana (Windows) have capitalised on this idea, using voice recognition software to retrieve information and personal details when requested by the user. Though not strictly ‘cognitive’ (they have difficulty recognising/learning some regional accents, for example), they present a good-enough facsimile which is sufficiently futuristic to satisfy the market.
Three and Red Ant built an IBM Watson-powered cognitive sales trainer
Three and Red Ant pioneered the use of IBM Watson in retail with a world first multi-channel sales adviser. It harnessed IBM Watson’s unique ability to recognise natural language queries – either spoken or text-based - and search thousands of documents, product details, customer reviews, blog posts and social content at once to provide contextually relevant answers which get smarter each time.
What Three wanted to achieve
Three wanted to use leading-edge technology to enable sales colleagues to deliver an enhanced service to customers by:
- radically improving how staff interact with technology
- using simple questions to make sense of big data
- integrating with existing sales, training and customer service documentation
What we built
Built on IBM Watson’s cognitive capabilities, we developed a trainer specifically for Three sales colleagues dealing with complex contracts which involved multiple levels of documentation, service manuals and tariffs. Transferable across mobile, tablet and web browser, it processed thousands of data points to give sales colleagues access to all the information they needed, whenever and wherever they needed it:
Natural language processing
- The trainer used the latest breakthroughs in natural language processing to understand sales manuals and business documents
- It allowed Three to maximise existing investments, take control of documentation and instantly improve sales and service
No training required
- Voice recognition and a simple to use question-and-answer interface allowed for intuitive and natural use
- No costly investment in training programmes – instantly accessible to all sales colleagues
Smart product recommendations
- Integrated with eCommerce and existing databases to automatically link content, products, manuals, contract details and other documentation
- Able to be tailored to relevant demographics and purchase histories to boost conversion rates and make cross-selling easy
Machine learning for continuous improvement
- The sales trainer automatically improved the more sales colleagues used it, by crowdsourcing input from across all channels