Will machines really take over?
ARTIFICIAL intelligence (AI) is founded on the claim that human intelligence can be so precisely described that a machine can be made to simulate it.
We are only at the dawn of the AI innovation, even though Alan Turing postulated the thinking machines more than 60 years ago.
Turing is widely considered the father of theoretical computer science, who in 1950 developed the Turing test of a machine’s ability to exhibit intelligent behaviour equivalent to or indistinguishable from that of a human.
Still, there are no machines today that can match human flexibility over wide domains or in daily tasks requiring human adaptability.
Currently, scientists are scrambling to develop systems that can reason, discover meaning, generalise or learn from experience.
From natural-language processing and chatbots to machine learning and automation, innovations are rolling out at accelerating speed.
Artificial intelligence is found in applications as diverse as medical diagnosis, search engines, voice recognition, advertising, e-commerce, finance, logistics, the media and more.
Based on the basic computing model of input-process-output, machines can learn to process specific human tasks and figure out the input-output relationship.
Examples of machine learning are verifying if an input picture is a human face or a species of animal or plant (photo tagging) and recognising an audio clip to provide a transcript (speech recognition).
According to Andrew Ng, former director of the Stanford AI Lab and former overall lead of Baidu Research, tasks that require lessthan-one-second cognitive power are suitable for automation, such as deciding a transport mode for a courier parcel, examining security videos to detect persons of interest and removing offensive online posts.
To further illustrate this, Singapore-based Trax offers a computer vision and deep learning solution that can contextually analyse the shelves in a retail store at the most granular level, including brand, stock-keeping unit, product location and pricing labels.
As more images are analysed, the platform becomes more knowledgeable about the retail landscape.
The potential business value is obtaining real-time insights that enable decision making regarding product availability and replenishment, merchandising, operational efficiencies and automated audits.
With voluminous data, it seems plausible to create sentient robots using deep learning or deep neural networks. For instance, Massachusetts Institute of Technology is building socially aware robots that can navigate through an erratic human throng.
This human awareness will make not just an efficient robot but one that is not overly aggressive. Such robots will do well as restaurant servers, hospital assistants and similar human roles.
For business uses, the challenge is to turn AI into a strategic resource that is valuable, rare, difficult to imitate and non-substitutable.
At present, the scarcities of necessary data and human talent are the main obstacles to AI development.
Therefore, data and human talent with AI competencies are the defensible entry barriers of new AI-enabled businesses.
It is debatable whether AI will cause serious job displacement of individuals, but we can expect a closer collaboration between men and machines. Rather than a wholesale automation of existing roles, a synergy of human skills and technology will be the new normal.
Depending on situations, the interaction may be processed or automated, semi-automated or entirely human. Some existing roles will be redefined – for instance, customer relationship managers become chatbots manager.
Other new roles related to AI and data include AI developer, data scientist, data analyst, data artist and data visualiser.
Technology-induced jobs will generate far more excitement than concern. The onus is on us to remain employable and futureproof ourselves by upskilling through formal courses or on-thejob learning.
At Sunway College KL, the master’s programmes of Victoria University (VU) are designed to create technology-driven business graduates. – By Dr Hendry Ng, director of VU postgraduate programmes – Master of Business Administration and Master of Business (Enterprise Resource Planning Systems)
For more information, e-mail hendryng@sunway.edu.my