Artificial intelligence

The term “artificial intelligence” dates back to 1956 and belongs to a Stanford researcher John McCarthy, who coined the term and defined the key mission of AI as a subfield of computer science. Basically, artificial intelligence (AI) is the ability of a machine or a computer program to think and learn. That is the glamorous end of AI. It actually starts by amassing huge amounts of data (big data) from which algorithms are applied to see patterns in the data that ordinary human will have difficulty discerning without the aid of massive computing power. Over time, as data and experience accumulates, the machine learns and rethinks. This is why they are calling data as the new oil. The more the better.

Those working with AI today make it a priority to define the field for the problems it will solve and the benefits the technology can have for society. It is no longer a primary objective for most to get to AI that operates just like a human brain, but to use its unique capabilities to enhance our world. The following are examples as defined above – i.e. to enhance our world:

Iphone X

Users of the Iphone X incorporates several applications of AI including Face ID, Animoji that mimics your facial movement and speaks using your voice, and Siri, a virtual assistant utilizing natural language speech recognition technology.

IBM’s Chef Watson

Watson, IBM’s artificial intelligence platform, had already shown its expertise on “Jeopardy” and for lung cancer treatment. And as Chef Watson it is assisting IBM achieve its mission to “help people discover new ideas”– in this case new ideas for the kitchen.

The first step in having Chef Watson help create a recipe for you is to pick any ingredient you wish to use in your culinary adventure – pineapple, anise, or sea bass – any ingredient you have on hand will do. You also have the option to add up to three additional ingredients for Watson to put through its algorithm. You can enter as few as one ingredient to as many as four and any number in between. Next, you tell chef Watson the dish you wish to make and for what meal. Maybe you want a burger or a chutney, an empanada, or ice cream. Finally, you can select a style or a theme—Chinese, easy, Eastern European and more! Voila! Chef Watson will take your input, compare it to its data and spit out 100 recipe options for you to choose from, complete with ingredient lists and instructions on how to prepare it.

How Dominos use Big Data

Machine learning and deep thinking – two buzzwords in AI – are illustrated by pizza delivery giant Dominos’ AnyWare. Any pizza order made online using various devices eventually yields a lot of data enabling the AI platform to build this “unified customer view, measuring consistent information across their operational and analytic layers.”

This means that individual customers, or households, can be presented with totally different presentation layers than others – different coupons and product offers – based on statistical modeling of customers fitting their profile.

Adapt or die

According to Brian Manusama, an analyst at research firm Gartner: “At the end of 2017, about 70 percent of all use cases in AI were related to customer service and call centers. Several million people are employed in call center roles in the US and UK, and hundreds and thousands more rely on such work in countries like India and the Philippines”.

Chris Baraniuk, a Technology of Business reporter of BBC wrote: “The biggest threat to jobs might not be physical robots, but intelligent software agents that can understand our questions and speak to us, integrating seamlessly with all the other programs we use at home and at work. And call centers are particularly at risk.”

He gave as en example Marks and Spencer which moved 100 switchboard staff to other roles as chatbots took over their duties. “All calls to 640 M&S stores and contact centers are now handled via “Twillio-powered technology”, a California-based tech company operating the new system.” M&S uses Twilio’s speech recognition software and Google’s Dialogflow artificial intelligence to transcribe customers’ verbal requests and understand their intent. Then the call is routed to the appropriate department or shop. The system can handle 12 million queries a year according to Twilio.

But while the new technology may displace jobs, there are other examples where AI and humans work together to enhance the service they provide. American insurer AllState uses AI to interact with human call center workers, not to replace them. It provides the information staff need to answer phone-based customer queries, reducing call durations from 4.6 minutes to 4.2 minutes on average. Those saved seconds add up across millions of calls in an industry where time is money.

The role of AI as helper, rather than replacement is also being promoted by Observe.AI, a recent start-up whose mission is to develop its emotion analysis system. It listens to incoming customer calls, interprets the emotional content - is the customer irate about something going wrong? - and automatically brings up appropriate response information on the call center worker’s computer screen.

Swapnil Jain, co-founder and CEO explains: “Our mission broadly, is to augment the (human) agent, not necessarily get rid of the agent.” Gartner’s Manusama believes it will be some time before virtual customer service agents are sophisticated enough to take on complex customer queries, let alone provide detailed advice about negotiating risk. But both agree that AI will eventually take over most human call center operations in time simply because humans are expensive, software is cheaper. Gartner states that more than 700 companies are trying to seize the opportunity of delivering AI capabilities to this application.

Question???

So that day will inevitably come. Are we prepared to avoid AI leaving our country with “technologically unemployed” workers? Forewarned is forearmed!!! And you know where the next shortage of talent will be? International Data Corporation (IDC) predicts a need by 2018 for 181,000 people with data analytical skills, and a requirement five times that number for jobs with the need for data management and interpretation skills. So as AI displaces traditional jobs, it creates many more.