Computers turning their intelligence to real-life human issues

This underscored the computer’s capability to further outsmart humans in complex tasks such as the complicated board game.

Previously, IBM’s Deep Blue computer defeated world chess champion Garry Kasparov.

Since the 1900s, when computers emerged in the form of tabulation; and the 1950s when computers were software-driven and static; to today’s era of machine-learning algorithms, AI is becoming more and more crucial to human life, especially in a context of human-machine collaboration.

In fact, AI, which includes cognitive computing, is already at work in healthcare and other fields in Thailand.

Bangkok’s Bumrungrad Hospital is a good example. It has been using IBM Watson for Oncology to treat cancer patients over the past year. How does the system work?

According to IBM scientists Gerald Tesauro and Murray Campbell, cognitive computing works in tandem with human doctors. At Bumrungrad, there are about 40 general cancer doctors who use the system to provide more accurate evidence-based treatment to patients in a timely fashion.

In the case of healthcare, IBM Watson will first analyse a patient’s medical records, using its advanced capabilities about the meaning and context of clinical notes and reports. It also takes into account key patient information written in plain English that may also be critical to selecting a treatment pathway.

Second, the system identifies potential evidence-based treatment options by combining attributes from the patient’s file with clinical expertise, external research and data – helping the doctor to make their decision more quickly and accurately.

Third, the system finds and provides supporting evidence from a wide variety of sources, and ranks them as supporting evidence for each option.

Overall, the system draws from a huge amount of information, called Big Data. It includes literature and rationales curated by MSK, a leading US cancer treatment centre, as well as more than 290 medical journals, more than 200 textbooks, and 12 million pages of text.

All these computing tasks can be done within a short time and can be replicated in other areas of work to benefit from the so-called augmented intelligence in which human and machine intelligence is combined to deliver faster and more accurate solutions.

This can be applied to medicine, education, banking, insurance, law, government, retailing, manufacturing and many other industries.

According to Tesauro and Campbell, cognitive computing which is now capable of addressing some “messy” real life issues, rather than just playing winners in board and other games, has the potential to transform industries and professions, leading to greater productivity, and more highly informed decision-making.

Prior to the advent of Google’s AlphaGo computer, IBM also succeeded in incorporating elements of AI, machine learning, deep question answering and natural language processing.

Its computer programme then played the American quiz show Jeopardy and beat the world’s best human players. But scientists like Campbell believe we are at least 50 years away from creating fully autonomous systems that manifest human-level cognitive faculties.

However, Campbell and Tesauro noted it’s now the time to increase the leverage of AI and human intelligence in a meaningful way to tackle more “messy” problems in real life.

While computers may not yet be as intelligent as humans, they can now compute web-scale data sets with cloud-scale computing power, and extract insights using highly sophisticated algorithms for machine learning. 

The IBM scientists said that research efforts should also be shifted from the sci-fi fantasy of machines that fully replicate human general intelligence to more realistic development of collaborative machines that can work with humans.

This will make the best use of each other’s different strengths – as in the case of Dr Watson who works side by side online in real time with real-life doctors at Bumrungrad Hospital.

Campbell and Tesauro also shared the opinion that in the foreseeable future, it appears the challenges of a complex world will require a combination of people and machines working together toward a more productive and better world.