The rise of the Intelligent Machine

So it’s Tuesday evening and I’m watching the BBC 10 O’clock news. There’s an article being aired around the impact that technology-driven automation is going to have on the labour market which is suggesting that by 2035, 35% of the total UK employment market may be at risk of displacement. This is a pretty sobering statement, and gives rise to philosophical debate around the impact that this will have – not just on those members of the workforce affected, but also on our education system and the nature of employment opportunity in the advent of the automation revolution. Should we be teaching our children differently, right now, to prepare them for this? How do we second guess those jobs that are likely to become obsolete and thus help our children to focus their energies in those areas less likely to be impacted? Are we in danger, as some have prophesised, of creating an unemployable underclass?

Only time will tell, and it’s human nature to want to predict the worst case scenario, but quite often the reverse scenario is the more likely outcome.

Historically speaking, advances in technology, robotics and automation have not resulted in a commensurate rise in unemployment numbers but have actually increased employment

Deloitte executed a study on this subject using census data going back to 1871 and found that, whilst certainly some jobs have been made largely redundant by technology, the labour market has responded by switching to roles in care, service and education sectors. Knowledge-based industries in particular have benefitted from the ubiquitous availability of data, and increasing ease of communication. People are generally wealthier as the costs of goods and services have dropped which, rather amusingly, has seen a 1000% rise in bar staff (so we now know where all of our extra cash is going).

But this new wave of technology, the rise of artificial intelligence and intelligent machines, will likely have an equally material impact on knowledge based industries as robotics and technology assisted machinery has had on manual labour based ones. Companies such as IBM are spearheading this movement with technologies such as Watson. Cognitive computing platforms that are able to ‘think’ in human-like ways, they can reason, understand context, and use previous experience to make future predictions and inform decision making. They are capable of conversing in natural language and, when used in conjunction with big data repositories, are able to present insight that would otherwise be impossible to achieve using conventional computational systems. Perhaps more importantly, when used in conjunction with process automation engines, they are able to execute tasks. Process automation is not a new technology – we’ve been achieving this to varying degrees of complexity for many years now. What cognitive technologies bring to the table, however, is the ability to deal with decisions. Theoretically a cognitive system can execute complex processes that, under normal circumstances, would be wholly reliant on human interaction to complete due to the inherent necessity to think, to reason, and to bring knowledge into the equation. The future potential for such technologies is only now starting to be truly understood.

If, like me, you have an overactive imagination you may be imagining a cognitive system like IBM’s Watson to be some kind of huge supercomputer with flashing lights akin to the WOPR in the seminal 1983 classic film, WarGames. Indeed the WOPR was capable of natural language processing (it could talk), it could ‘learn’ through trial and error (albeit via circa 1000 games of tic tac toe) and it was capable of making informed decisions based on access to a wide range of data (Russian nuclear missile launch trajectories). But the reality is that Watson is highly scalable and not nearly so resource hungry. When it won the US TV show Jeopardy! in 2011, beating two of the show’s most prolific and successful contestants in the process, it did so running on 100 IBM POWER 750 servers running in a massively parallel computing cluster. Since then, IBM has refined the code for enterprise use such that it can now run on a single server platform, or directly via the Cloud. The Watson algorithms are being embedded in multiple different enterprise applications, tuned for different use cases, and are already being adopted in major banking and healthcare applications, to name but a few.

Other companies are also now offering enterprise solutions that have cognitive capabilities behind them, and one area that is garnering quite a bit of interest of late is the Virtual Digital Assistant, also commonly known as (an intelligent) chatbot. If you’ve ever used a customer service chat box online, you may be familiar with the concept of a ‘bot’ that can ask certain pre-canned questions or relay information prior to handing you off to a human operator. Bots are also often used in web chat applications for things like providing help on how to use the service itself.

Historically bots have been pretty dumb. They possess no innate intelligence, and simply work from a script. Go off-script, and the bot will simply not understand the question.

Chatbots that use cognitive algorithms, on the other hand, possess two unique and potentially game changing characteristics. Firstly, the can converse using natural language, so the experience is a very close approximation to that when conversing with a real human. Secondly, they can go off-script – they can interpret questions or instructions and combine stored knowledge with probabilistic algorithms to provide you with a response that is highly likely to be appropriate and possibly even useful! Such systems need to learn over time, and can even be trained, so their true potential is not unlocked immediately. Their potential, however, is huge, the use cases are many.

So what of the impact of such technologies? For the consumer, the likes of Amazon’s Alexa or Apple’s Siri will only become more capable and increasingly useful. Integration with home automation systems and access to consumer services are the obvious starting points. At present, the vast majority of service integration is limited to vendor’s entertainment and media services, but thinking outside of the box, consider the implications of using such technology to engage with other types of service providers. Want to pay your bank bill? Why not ask Alexa to do it for you? Need to register a complaint with your utility provider? Why not have Siri do it for you? Need to book a taxi? …Cortana?! As consumer service provider organisations begin to digitise their customer engagement channels, this kind of opportunity for integration begins to open up, paving the way for a new era in automated service fulfilment.

For the enterprise the impact is likely to be significantly more material. Efficient gains made via labour arbitrage, for instance, will shift to those enabled by technology arbitrage, as automation, driven by cognitive platforms, drives the cost of service down and the quality of service up. The impact this will have on traditional delivery models could be both rapid and significant. Service providers using cheap labour to deliver cost-effective knowledge-centric services will likely need to re-evaluate their models to remain competitive. Junior roles within organisation, many of which may be traditional routes in to the industry, will need to adapt to cater to those areas that support these new technology capabilities, or else see themselves replaced by them. Commercial models too will need to adapt as customers choose to move increasingly toward consumption or outcome based models, rather than those dictated by headcount or traditional performance related targets. The opportunities are there in abundance for those providers – and consumers – who choose to embrace the technology. Indeed, in this particular case, the WOPR was way off target when it philosophically announced that “…the only way to win is not play”. Whilst that may be true of Global Thermonuclear War, it certainly isn’t true of intelligent computing platforms within the enterprise.

As for me, I’m off to play a nice game of chess…

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