Human-Machine Singularity Series | Evolution of AI and it taking over our jobs!
There are four levels of complexity of Artificial Intelligence:
Instructive - Algorithms where rules are codified manually
This has been in existence since the advent of computers and (the machine – i.e. computer) represents a dumb interpreter of human intelligence. This stage saw siloed digitization of data and process with aim to increase speed especially for repeatable tasks and also reduce errors. It quickly evolved into also giving structure to the data and interoperability between organizations. Machines just did whatever humans did much faster, without fatigue and with minimal errors. What could be done by thousands of people could be done by few machines in fraction of time. And indeed, this sparked an exponential decline in human effort required to generate the same degree of value. This stage is level-0 of AI as machines are not thinking – they do whatever you code.
Supervised - Algorithms that codify rules through guided learning
This is where AI has become main-stream today. The outcome is dependent on the past input-output sets (training data) which is not explicitly coded in the solution. The algorithms finetune their input-output logic using past data and are able to predict future outcomes using this “learnt” input-output logic.
Unsupervised - Algorithms that codify rules through exploration
Today, this is beginning to get into main-stream. The algorithm learns from the past input data and figure outs the inferences or outputs from that data, thus creating the input-output logic.
Generalized - Algorithms that codify rules which adapt to changes in environment
This is the cutting edge of artificial intelligence research. It includes the general-artificial-intelligence algorithms. The algorithm learns on the way – just like a child does – and figures out the best input-output logic. It is just few steps away from enabling Human-Machine Singularity where algorithm will continue to refine themselves to become the better of the two races. Who would then need humans! This will have an exponential impact on human employability.
Instructive - Algorithms where rules are codified manually
This has been in existence since the advent of computers and (the machine – i.e. computer) represents a dumb interpreter of human intelligence. This stage saw siloed digitization of data and process with aim to increase speed especially for repeatable tasks and also reduce errors. It quickly evolved into also giving structure to the data and interoperability between organizations. Machines just did whatever humans did much faster, without fatigue and with minimal errors. What could be done by thousands of people could be done by few machines in fraction of time. And indeed, this sparked an exponential decline in human effort required to generate the same degree of value. This stage is level-0 of AI as machines are not thinking – they do whatever you code.
Supervised - Algorithms that codify rules through guided learning
This is where AI has become main-stream today. The outcome is dependent on the past input-output sets (training data) which is not explicitly coded in the solution. The algorithms finetune their input-output logic using past data and are able to predict future outcomes using this “learnt” input-output logic.
Unsupervised - Algorithms that codify rules through exploration
Today, this is beginning to get into main-stream. The algorithm learns from the past input data and figure outs the inferences or outputs from that data, thus creating the input-output logic.
Generalized - Algorithms that codify rules which adapt to changes in environment
This is the cutting edge of artificial intelligence research. It includes the general-artificial-intelligence algorithms. The algorithm learns on the way – just like a child does – and figures out the best input-output logic. It is just few steps away from enabling Human-Machine Singularity where algorithm will continue to refine themselves to become the better of the two races. Who would then need humans! This will have an exponential impact on human employability.