Debates over the possibilities of AI have been raging since the 1770s. An inventor by the name of Wolfgang von Kempelen debuted his creation in Vienna: A chess-playing automaton known as the Turk consisted of a mechanical man dressed in robes and a turban who sat at a wooden cabinet that was overlaid with a chessboard. The Turk was designed to play chess against any opponent, but the Turk became popular recently when Andranik Matikozyan, Grand Chessmaster, and a three-time southern California chess champion played and got checkmated by the Turk. 

Back in those days, the focus was developing mechanical marvels aka Automatons that simulated the actions of living beings such as writing programmable text, playing music, etc.

Artificial Intelligence

Fast forwarding to now, an emerging trend called Artificial Intelligence (AI) aka Cognitive Computing promises to give rise to computers or machines that sense, perceive, learn from, and respond to their environment and their users.

AI is enabling the emergence of new product categories, reshaping how businesses engage with customers (B2C), engage with their employees (B2E) and transforming how work gets done across industries.

In recent years, tech companies have used man-versus-machine competitions to show they are making progress on A.I.  In 1997, an IBM computer beat the chess champion Garry Kasparov. Five years ago, IBM’s Watson system won a three-day match on the television trivia show “Jeopardy!”   Now, Google’s A.I. program is drawing attention when one of its software defeated one of the world’s top players of Go, one of the most complex board games ever created, in a best-of-five series of matches.

IDC estimates that by 2020, the market for artificial intelligence or cognitive applications will reach $40 billion. And 60 percent of those applications, the firm predicts, will run on the platform software of four companies — Amazon, Google, IBM, and Microsoft.

In less than 10 years, Artificial Intelligence  will be to computing what transaction processing is today. Computers will communicate with us on our terms, rather than us having to interpret and adapt to them.             – Rob High, CTO, IBM Watson

On-Demand AI Services

As AI starts to hit the mainstream via API services such as speech and image recognition, tone and emotion analysis, language translation and dialog capabilities, the idea of humans and computers working together is a theme that many companies are starting to explore. 

IBM has released a set of Cognitive API services in the Watson Developer Cloud that clients can leverage to incorporate cognitive capabilities in both front-office and back-office business processes. 

1. Personality Insights service, which measures personality traits by using linguistic analytics to extract a spectrum of cognitive and social characteristics from the text data that a person generates through blogs, tweets, forum posts, and more.

 2. Tone analyzer: This API can measure similar emotions in samples of text from a sentence to a single word. For e.g. A dating site profile that contained the sentence, “I raised two kids and now I’m starting a new chapter in my life.” Based on psycholinguistics and emotion and language analysis, tone analyzer API could determine that about a quarter of people reading that would detect anger, suggesting it might be advisable to change the wording.

3. Emotion analysis: This API service uses linguistic analytics to gauge emotions implied by a sample of text, returning confidence scores for anger, disgust, fear, joy, and sadness. For instance, a customer review site such as Yelp could measure the level of disgust in a restaurant review site to help the business understand how it needs to improve.

4. Personality insights: This API service can extract insights from a lengthy piece of text by a particular person, providing measurements of characteristics such as introversion or extroversion and conscientiousness. It could be used, for instance, to help recruiters match candidates to compatible companies.

AI and Robots

Everywhere we go there will be a presence of cognitive computing in some form that facilitates our life.  AI technology allows systems to understand the world in the way that humans do, through senses, learning, and experience.  This kind of understanding of human emotions and personality may find its most potent application in robots.

IBM is working with Softbank’s Aldebaran NAO robots to give them more human-seeming characteristics, such as the ability to converse more naturally, gesture to punctuate key points–even sing a Taylor Swift song.

Connie (pictured above), a Watson-enabled robot concierge, has made its debut at the Hilton McLean. IBM has developed the robot, which draws on domain knowledge from Watson and WayBlazer to help hotel guests figure out what to visit, where to dine, and how to find anything at the property.  Other hotel companies have experimented with robot technology as well. Starwood Hotels and Resorts has a Botlr, which can deliver room service. And the Yotel in New York has a luggage-toting robot.

In fact, despite the assumption by many that robots will be mainly used for taking care of rote tasks, they may be more important for communications between people and computer systems or cloud applications. This leads to the development of AI messaging interfaces called  “chatbots” on connected devices.

Chatbots

Messaging “chatbots” are basically software that can conduct a human-like conversation and do simple jobs once reserved for people.  Facebook has started to introduce chatbots on the messenger platform that allows us to chat and transact business with 1-800-Flowers and a few other vendors.  At the recently concluded F8 conference, Facebook revealed how they are planning to expand the list of chatbots with AI.   WeChat provides similar services in China to pay for meals, order movie tickets and even send each other gifts. In the near future, users of Microsoft’s Skype and Canada’s Kik can expect to find newly automated assistants powered by AI offering information and services at a variety of businesses. 

Messaging bots can handle a wider range of tasks including mobile maintenance crew, mobile inspection, processing warranty claims, and providing concierge services across a variety of consumer businesses. In part, that’s because bots can recognize a variety of spoken or typed phrases, where apps force users to choose from options on a drop-down menu. Reaching a chatbot can be as simple as clicking a link in an online ad or scanning a QR code with a smartphone camera. 

As the big messaging players open up their technology to bots, businesses and brands will need a bot presence to fill this communication with their customer base. I believe this will lead to an overhaul of internal data and business processes in order to provide on-demand services to customers, employees, and others on any connected devices.

Impact of AI  is growing

In The Second Machine Age MIT’s Erik Brynjolfsson and Andrew McAfee reveal the forces driving the reinvention of our lives and our economy. As the full impact of digital and cognitive technologies is felt, we will realize immense bounty in the form of dazzling personal technology, advanced infrastructure, and near-boundless access to the cultural items that enrich our lives.

Digital and cognitive technologies are capable of helping everything and everyone. Companies will be forced to transform to adapt to this change.  Let’s look at Amy – the virtual AI assistant. Amy isn’t a real person, she’s not even an app, she’s a virtual AI assistant that you can cc into email chats. Let’s see how Amy can help. 

“Shall we grab a coffee next week, maybe one afternoon?” someone asks me in an email.

“Sounds good, Amy will sort out the details,” I reply, cc’ing Amy into the conversation.

From there Amy takes over, offering meeting times that work for me and making suggestions of where to meet, like my favorite coffee-house (Crema Coffee Express Bar in Cary, NC) or the nearest Starbucks.  But I don’t see any of that, because Amy has taken over, managing the back-and-forth to work out the details.  The conversation is clear, directed, Amy refuses to be derailed and talks with a clear conviction to lock-down a time and location that works for everyone.

Conclusion

Even if you have a fancy car, you still have to decide where to go.                     – John Giannandrea, VP Engineering, Google

The ultimate dream of many advance thinkers in AI  is to create machines that can think as well as people. But today human judgment and creativity remain indispensable.  However, the impact of AI or cognitive technology on business will grow significantly over the next three to five years. This I believe is due to two factors. First, the performance of AI has improved substantially in recent years, and we can expect continuing research efforts to extend this progress. Second, billions of dollars have been invested to commercialize these technologies. Many companies are working to modularize and package AI technologies for a range of business functions and industries, making them easier to acquire and easier to deploy.  Together, improvements in performance and commercialization are expanding the range of applications for AI technologies and will likely continue to do so over the next several years.

Martin Lindstrom has spent time with 2,000 families in more than 77 countries to get clues to how they live — resulting in the acquisition of what he likes to call Small Data. In his new book, Small Data: The Tiny Clues That Uncover Huge Trends, he argues that the Small Data explains the “why” behind what Big Data reveals.

Big Data is all about finding correlations, but Small Data is all about finding the causation, the reason why.                                 –Martin Lindstorm

In his book, he talks about how the corporate world has become completely blinded by Big Data.  He also talks about how companies which are completely reliant on Big Data actually have started to have a problem.  He cites the example of Walmart, irrespective of having the largest data-mining and big data operations in the word, they had to issue a second profit warning recently.  He gave another example of Lowes Foods, which is my home town favorite in NC and now one of the fastest growing in the region.  Lowes Foods is actually living with the consumer in the community to understand the Small Data. That means listening closely to the community needs by  embedding themselves into the community. They’re talking with everyday consumers and integrating themselves deeper. As a result, they now have completely turned around and is now one of the fastest growing in the region because they’re listening to the consumer and the Small Data.

Need for Small Data

In a traditional sense, I agree it is very hard to describe emotions using just data and numbers. I also agree that it is very important to listen to the consumer via. the Small Data.  It would be ideal to elicit Small Data by living in the communities or by deeply embedding into the communities, but we can’t ignore the practical challenges and resource limitations to replicate this nationally.

Small Data lives on the Cloud

Let’s also look at how we are communicating in today’s world.  Technology’s rampant popularization over the past decade in terms of social media has meant that texting, WhatsApp, Next Door, Facebook, Instagram, and Twitter have inevitably taken over as the most efficient ways of communicating with each other. One can make an argument that in today’s world Small Data actually lives in the form of tweets, images, videos, product reviews, surveys, community blogs, etc. somewhere on the cloud.

Understand Small Data with Cognitive Computing

Understanding Small Data in today’s world means understanding the verbal and non verbal communications that are taking place on the cloud.  I believe cognitive analytics can bridge the gap quite nicely.

Cognitive Analytics is creating a new partnership between people and computers that enhances, scales and accelerates human expertise.

Like humans, cognitive analytics understands individual behaviors and can engage with humans.  It also learns from us and improves over a period of time.  We use our cognitive capabilities to understand emotions and other human behaviors.  Likewise, cognitive analytics can sort through millions of tweets, images, speeches, product reviews and other customer generated data points to understand human behavior, emotions, personality traits,etc.  Image below outlines cognitive capabilities available on the IBM Watson Developer Cloud.  Google and Microsoft are offering similar capabilities as well.

Develop Big 5 Personality Traits from user generated content

IBM’s Watson Developer Cloud includes a Personality Insights API/tool, which leverages linguistic analytics to extract a spectrum of cognitive and social characteristics in the form of Big 5 personality traits from the text data someone generated through blogs, tweets, forum posts, and more. This kind of personality analysis helps to understand, connect to, and communicate with customers on a more personalized level.

Evolution of Cognitive technologies

Cognitive technologies have improved dramatically in recent years. From machine learning, natural language processing (NLP), speech recognition and tone analysis, it now can extract visual insights from a collection of customer images from Instagram or Facebook collections. Corporations can now leverage these visual cues (Small Data) to understand customer behavior and needs.

Big Data meets Small Data

When companies start to weave-in Small Data from cognitive analytics into insights from Big Data and predictive analytics, they can deliver an enriching and personalized experience for their customers.

In summary….

There is a huge desire for tactile interaction with people, but unfortunately the physical community as we know is dying.  As a result, the human interactions are moving into the cloud.  We also need to fly/dive deep into the cloud to understand deep consumer psychology (Small Data) by analyzing human interactions on the cloud.  This type of analysis is going to be the biggest asset for every company going forward.