A.I. is a great tool

Still not as good as people think it is

It's just a name

It is argued that there is no articial or intelligence in A.I. but we do like to hang simple collective nouns on stuff, so we will stick with that. Machine Learning, Deep Learning, Synthetic Cognitive Systems and so on ... basically obtaining a goal by using electronic computational systems to analyse data [insert own description]. Like art, we recognise it when we see it. The use of algorithms can be a black art and sometimes the secrecy of these can be to protect its advantage or to hide the fact that it is flawed. Neural networks are particularly opaque and there is legislation to try and show what is going on inside those black boxes. Also analytics such as LIME - Local Interpretable Model-Agnostic Explanations.

Patterns

Both organic and A.I. look for patterns, it turns data into information, which is what it is all about. Humans are particularly good at this and can interpret them really fast. It is called survival and we, like other animals do it instinctively and subconsciously. Machine neural networks are also good but require lots of data and are specific in what they do. The young are masters at learning with a very malleable neural network. There are quicker algorithms than neural networks and sometimes out compete them but as usual it depends on the data and what you are trying to do. Bayesian inference is a particularly good statistical fast response technique. Some of its strengths are the relationship of entities and if it looks like a duck, quacks and walks like a duck, then it is probably a duck.

Vive le difference

The aims of both natural and synthetic intelligence is to solve problems and there are some similarities in approach but more differences.The human brain uses massively parallel and highly specific cell networks to do different jobs. Synthetics use very fast, kind of parallel and fixed hardware. The articial neurons in a chip are usually all the same and use a weighting procedure to produce different outputs. Backpropagation has been a common tool but is being replaced by more brain like components such as the IBM and Graphcore chips. Neural networks use training data to tweak the result in many runs (epochs) with a serious amount of data. Humans on input of data are always back checking to see if they have seen this item before. They can short circuit the cycle by a symbolic realisation that they already know what the thing is.

The Stock Exchange

Most people think computerised trading is a highly complex whiz kid kind of thing. The actual algorithms used are quite simple because of one overall restraint. Time is the key and complexity is its enemy. The simpler the code, the faster it works and getting quickly to market is everything. Tracking shares is quite dumb and follows the ups and downs of share prices. When you are dealing in nanoseconds the real advantage is to physically set your bit barn as close to the the Stock Exchange as you can. The speed of your transaction is limited by the physics of computing and physical transfer. Transactions can be so quick that crashes and overselling can happen before the traders know it is happening. Software cutouts and brakes were introduced to slow the process. On the other hand analysing and hopefully predicting stock can take days. The newish concepts of NeuroEconomics also claim that we make decisions not just on logic but on emotions, cultural backgrounds, personal development and so on. So good luck with that, trading algorithms.

Ghost Work

The excellent book by Mary L.Gray and Siddharth Suri warns of the new underclass of technical workers. They have no real contact with others but are hidden away at home or in bit barns, often underpaid and always overworked. They are in danger of becoming the Morlocks of H.G.Wells Time Machine fame. The word robot comes from the Czech word for forced labour and with the Ghosts could become the new slaves of the technology age. Although industry and politicians are always crying out that there is not enough tech savvy applicants available to solve all the problems of the future, there could come a time when the techies are in surplus.

Hype

Don't get me started - but that is the point. For those of who are struggling to understand the nature of man and machine, we are often in despair at the claims and simplicity of popular articles. The more you know, the less you know and research is constantly updating its findings. A popular trend is ingesting certain foods will do such and such. This usually glosses over the fact that our stomach acids wipe out a lot of the constituents. There are whole industries built on non scientific hearsay. This also applies to the A.I. field where promises of predictions equal the Oracle of Delphi. The greed of large data corporations and trading directors who are too frightened to say it was all a horrible mistake encourage the misuse of improving the real truth. Jumping on the band wagon can be a great way to progress in business and hoping that you have moved on before the truth emerges. Of course there are great things happening but as always - Caveat Emptor.

The end of working

The idea that we will be better of by being free from the tyranny of work is not in our DNA. We are hunter/gatherers (still) that are curious and need goals. Our evolution has made us require contant movement, otherwise we get ill (get off your chair) and constant challenges. The majority are not philosophers, artists or dreamers. No work means revolution.