It was a pleasant Sunday afternoon when I felt the need for respite from my 32-bit layout. Remembering that I've already received my digital copy of IEEE Spectrum for the month of June, I decided to start reading. The theme I confess, got my eyes peeled on the articles and engaged me with enthusiasm and excitement. After the last page, I reclined on my chair eyes closed, my consciousness in a deep state of pensive contemplation and repose.

The topics covered almost every aspect one must be enlightened on to understand the challenges the engineering community is currently faced with when it comes to artificial intelligence. From the essential details of which part of the brain deep learning is concerned with (i.e. the neocortex) to the circuit configuration that mimics the neurons and synapse action (see below), the authors covered them all.

An extract from p.30 of IEEE Spectrum (Issue - June 2017)

But there is one question that still remains open for heavy debate - are we ready?

Honestly, I myself feel that there were some advancements in science and engineering over the past decades that our society wasn't exactly prepared for. The most notable was the internet. Now, I have nothing against freedom of speech or ideas, but the emergence of a network that bridged the limits of physical distance was so sudden it spurred a lot of irreversible consequences that our governments today are finding so hard to surmount, or at the very least control. Pirated copies of copyrighted material such as books, music, and games; the proliferation of pornography that has poisoned fragile juveniles, laxed tolerance towards sexism, and further promoted the objectification of women; and the online orchestration of surreptitious criminal activities and organized crime (remember Silk Road?) are a few depravities birthed by the world wide web. Could artificial intelligence be the impetus of another set of crookedness?

My answer, after giving such a pessimistic description, is yes - we are ready. But (please note there is a but) the answer is application-specific. An example I'd like to cite is the use of machine learning neural networks in S.E.O.s and driverless cars. Reasons border on scope of ability and degree of damage upon failure. S.E.O. is statistical and any mishaps don't have overbearing consequences. Self-driving cars on the other hand, involve the safety of human life, and thus necessitate more stringent requirements before being made available to consumers.

The Effects of Artificial Intelligence

Diverse sectors in our society see many benefits in proper implementation of A.I. This is due to the main effect A.I. will have upon integration to man's daily life - automation. There are stories (that are surprisingly not dystopian, in contrast with Hollywood's imagination) envisioned by technical authors describing what life would be like with A.I. that usually comes in a style similar to the one below:

"Man is woken up by the alarm clock of her A.I. assistant - <put female name here> - usually an automaton. Man then proceeds with morning routine with the help of said A.I. assistant through an incredulously modicum amount of manual effort. Man goes to work on driverless car. Man makes work look like seventh heaven with all the A.I. involved. Man then falls in love with A.I. assistant. (an article describes it as a PDA assistant from the 2013 movie - Her)"

Alright, some predictions could be too exorbitant they may not meet expectation, but even the pragmatic considerations already offer so much worth salivating over. I mean, even the basic constructs are proving indispensable to a data scientist's toolkit.

An adjunt feature I've seen recurring in many advertisements and promotions that enhances the appeal of artificial intelligence is voice/speech recognition. Perhaps a lot of the hype will fizzle around A.I. if it weren't for this means of establishing communication with it. Speech recognition is under the umbrella of digital signal processing, and before it is processed by the A.I. (or neural networks for voice identification), it can undergo a lot of preconditioning.

An I.S.A. for Complex Re-wiring of the Neural Network

One of the thoughts that hit me while pondering on how A.I. impacts my field of expertise is the identification of an algorithm that controls the re-wiring mechanism of the neurons. When a human learns something new, synapses are re-wired and are merged with a sparse set of discriminating factors that involve the newly imbibed abstraction (so as to facilitate interlinking of similar thoughts/ideas). Though there is still that pervading enigma of how re-wiring works, one thing is certain, it must be implemented by an adaptable ISA (or an ISA at the very least). What comes to mind are a bunch of transmission gates turned on/off by a ROM or control register. It's like the portion of the CPU that sends out the control signals. The challenge is to build an adaptable structure/sequence that changes the pattern of control signals based on the feedback of the A.I.'s transducers. It has been reported that the current algorithm of neural networks take 100 layers for an image analysis task that would take a human neural network only 4 layers. So the re-wiring mechanism should be very simple and I think its simplicity lies on its adaptive nature.

Artificial intelligence is a technology that has its advantages and disadvantages. In my opinion, society is prepared for it as long as the appropriate regulations are in place and that it is not abused.
Its applications should also be scrutinized for possible loopholes that risk wanton exploitation.

How about you? Are you ready for A.I. to be part of your life?