One label we may stick to 2018 is that it was the year of technological evangelism. When a mini-bus driver asks for advice on investing in cryptocurrencies, you know it is time to get a clinical view of how technology is likely to change lives in the next decade and beyond.
The latest fad of evangelism relates to the potential of artificial intelligence to make our lives better. This is possibly because many are realising that cryptocurrencies are not the get-rich-discoveries that can create wealth overnight. Many ordinary people prefer to ignore the messianic proclamations of technological evangelism promulgated by both some business consultants and politicians who more often than not know only a minuscule fraction of what scientists know.
Technology evangelists tell us that soon we will have to cohabitate with robots, pay our bills will bitcoins and manage our lives with apps on our smartphone. For many starry-eyed people technology has replaced theology.
One such evangelist of technology is Masayoshi Son, founder and chief executive of Japanese tech group SoftBank. When speaking about artificial intelligence, he says: “AI is the biggest revolution in human history... it will change or will redefine all the industries... winners in AI will be winners in the future.”
Son’s admirers see him as a genius; more traditionally-minded business people dismiss him as a reckless chancer.
The Harvard Business Review in one of the better sources of reliable information on how new technologies are evolving. Thomas Davenport and Rajeev Ronaniki wrote an interesting article in February 2018 entitled ‘Artificial Intelligence of the Real World’. They give two contrasting examples that show both the potential as well as limitations of AI.
Many fear that robotic process automation is bound to make many people redundant. There is some truth in this evaluation
The MD Anderson Cancer Centre in Texas in the US in 2013 launched a moon shot project to diagnose and recommend treatment for certain forms of cancer using IBM’s Watson cognitive system. In 2017 the project was put on hold after US$62 million had already been spent, and the system had yet to be used on patients.
The IT department of the same cancer centre is using AI to do much less ambitious jobs like making hotel and restaurant recommendations for patients’ families and determining which patients needed help to pay bills. Looking at AI as a means to complete moon shots is a sure way to deflate the potential of this technology. A moon shot, in a technology context, is an ambitious, exploratory and ground-breaking project undertaken without any expectation of near-term profitability or benefit and also, perhaps, without a full investigation of potential risks and benefits.
Davenport and Ronaniki argue that AI will certainly help achieve significant improvement in three particular areas. The first area is in process automation. AI can help organisations by automating business processes, gain insight through data analysis and engaging with customers and employees. Check-in of luggage in some airports is already being done by robotic equipment that checks ticket details, weigh, tags and accepts luggage in a fraction of the time it takes a human check-in clerk to do it.
Many fear that robotic process automation is bound to make many people redundant. There is some truth in this evaluation, but Davenport’s research found that other new jobs were created in organisations that used AI to make robots do manual work.
A second application of AI that gives investors the chance to pick some low lying fruit is to gain cognitive insight. Businesses are inundated with massive data and information. They need tools to change this information into knowledge. Equipment armed with AI is capable of sifting through mines of information to, for instance, predict what a particular customer is likely to buy. Those who use Amazon and eBay know how after a while of buying things online, they are bombarded by adverts and e-mails luring them to buy other things that an analytical machine has identified as a personalised buying need for a particular previous buyer.
The third successful application of AI so far is cognitive engagement. These AI projects that involve employees and customers that use natural language processing chatbots, intelligent agents, and machine learning. In this case, companies have to take a conservative approach to customer-facing engagement technologies. Some people do not like speaking to machines and are easily frustrated with the lack of empathy when dealing with a robot.
AI can indeed usher a golden age of productivity and work satisfaction. However, ethical and workforce displacement issues will need to be addressed first.
johncassarwhite@yahoo.com