"I can't code, and this bums me out because--with so many books and courses and camps--there are so many opportunities to learn these days. I suspect I'll understand the machine revolution a lot better if I speak their language. Should I at least try?" Dear Decoder, Your desire to speak the "language" of machines reminds me of Ted Chiang's short story "The Evolution of Human Science." The story imagines a future in which nearly all academic disciplines have become dominated by superintelligent "metahumans" whose understanding of the world vastly surpasses that of human experts. Reports of new metahuman discoveries--although ostensibly written in English and published in scientific journals that anyone is welcome to read--are so complex and technically abstruse that human scientists have been relegated to a role akin to theologians, trying to interpret texts that are as obscure to them as the will of God was to medieval Scholastics.

Artificial intelligence is the buzzword for 2018 and it is being used everywhere and often to describe fairly mundane automation and analytics-driven processes. One of the earliest adoptions has been speech to text, for example in call centres. AI enables the speech of both the call centre operator and the customer to be converted into text files and then an algorithm scans that text looking for keywords that may indicate an area of risk for the enterprise or sentiment analysis of the customer. "All AI today is narrow-focused, in other words, we have a system and we give it a specific challenge or task, a series of input data and a whole bunch of training data which is usually labelled or pre-classified," said Charles Sevior, CTO Unstructured Data Solutions, APJ and Greater China, Dell EMC, in an email interview with Networks Asia. "We are at the early stages of having computers accurately interpret unstructured data in a time so fast that it is considered to be "just like a human" – so-called AI."

While this theme may be premature, the concern of teaching ethics and valuing human life is a relevant question for machine learning, especially in the realm of healthcare. Creating "laws" or "rules" for ethics in artificial intelligence as Elon Musk calls for is difficult in that ethical bounds are difficult to teach machines. Many companies have done extensive work in training systems that will be working with patients to learn what words mean and common patterns within patient care. When a patient asks about their symptoms they get clinically relevant information paired with their symptoms even if that patient uses non-medical language in describing their chief complaint.

Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. Artificial Intelligence could be the death of us all. I heard that roughly a hundred times last week through shares on twitter. While this theme may be premature, the concern of teaching ethics and valuing human life is a relevant question for machine learning, especially in the realm of healthcare. Can we teach a machine ethical bounds?