Artificial intelligence for the fringes of society
Credit to Author: MACARIO CORDEL| Date: Mon, 21 Jan 2019 16:16:21 +0000
The recent success of artificial intelligence (AI) has shown promising performance in accomplishing several computer-aided tasks e.g. detecting diseases in medical imaging using Profound by Zebra Medical Vision, verifying identities using Firefly Baidu Face Recognition and managing traffic using topXview Complete AI Based ATMS. Endowing computers with human abilities such as analyzing data lead to the development of intelligent virtual assistants e.g. Siri and Alexa. AI is so ubiquitous that it is even in our home (e.g. Netflix suggesting what to watch), in our daily commute (e.g. Waze and Grab), and in what we read (e.g. Facebook suggesting news feed).
Indeed, machines are getting smarter every day. Elon Musk, an engineer and technology entrepreneur, and Stephen Hawking, a theoretical physicist, have suggested the threat AI poses for the human race if it is not regulated. Every time we develop an AI system, we are essentially outsourcing part of our intelligence to technology. And, based on the inheritance principle of evolution, this part of our intelligence we offload to machines disintegrates over time.
However, for a country like the Philippines where there is a lack of warm body experts in poverty-stricken rural areas, an AI system is a pragmatic solution. Commonly, these poor rural areas are too remote that it will take people days to travel to and from the metropolis. Thus, medical professionals, agricultural experts and educators rarely reach these rural areas which results in bad health care, poor livelihood and a lack of education in these communities.
Rather than seeing AI as a threat that would replace human intelligence, take our jobs, and eventually dominate our society through robots, we should see AI as a means to solve our age-old poverty problems primarily linked to health care, livelihood and education. Researchers and funding agencies such as the government and the non-government organizations should be more aggressive in bringing this technology to the fringes of society.
For example, common diseases such as tuberculosis, which can be treated if detected early, lead to morbidity because there are no available medical experts in an area. There are several common laboratory procedures for detecting diseases, e.g., X-ray, ultrasound and ECG, which require recognition of patterns or objects to identify abnormalities. Coupled with a viable telemedicine system, an AI-based pattern recognition system would increase the efficiency of doctors by reducing their consultative travels and focusing their attention on those with immediate concerns.
In agriculture, which is the primary source of livelihood in rural areas, countless crops are wasted because of pests and weed damage (e.g. the coconut scale insect outbreak in 2014) which can be prevented if the first signs are detected. Early detection of signs of pest and weed damage can be realized using a drone equipped with computer vision to increase the production of the farmers and decrease wastage and risks. Development of a pattern recognition system to help untrained individuals detect the maturity of crops and possible plant diseases (e.g. cocoa pod rot) could also be provided to farm cooperatives.
Education in far-flung areas is sparse due to lack of teachers and facilities but this could be improved by providing infrastructure to bring AI-based learning to help the teachers. Chatbots and gamified learning environments (GLE) could compensate for the lack of teachers in hard to reach areas. There are AI-based GLE systems that could tailor lessons to the individual learning style of each student through enjoyable games, making the education process more productive and effective for students.
We are experiencing waves of digitization and we have the moral obligation to ensure that no one gets left behind. With all the perceived benefits that AI can bring to a third world country like ours, isn’t it time to embrace what technology is bringing us?
Macario O. Cordel, II, Ph.D. is an assistant professor in the College of Computer Studies, De La Salle University. He teaches Digital Signal Processing, Image Processing and Neural Networks. Email macario.cordel@dlsu.edu.ph.
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