The rise of three of the most anticipated technologies of this decade is often perceived to be a threat and an attack on human choice – yet others regard big data, AI, and machine learning as tools that enable a previously unknown level of accuracy in human decision-making. So in the age of information, what is ‘choice’?
Just a decade ago, the business world made decisions in a very different way to today. The rather slippery concepts of human intuition and gut instinct reigned supreme in human resources and marketing departments worldwide, and it was those who held this ‘magic’ sixth sense that would be held in the highest regard. But while intuition certainly should not be disregarded and should be viewed in the same way as conscience when it comes to decision making, it is often based more on luck than judgement.
The human brain as a problem-solver has its flaws; it focuses on information that affirms assumptions and prejudices, reaches conclusions that stick to the status quo, and also places disproportionate weight on the first piece of evidence learned on any given topic. This means that decisions made through intuition and instinct are influenced by biases and will often to lead to a lack of diversity in terms of ideas. Coupled with the rising time pressures in corporate settings, judgement errors are likely to occur; errors that, in recruitment (for example) could cost the business between four and twenty times the salary of the person involved. Clearly, this decision-making process is flawed, and this is where big data, AI and machine learning play a central role.
Big data refers to the large and dynamic volumes of data being created by people, tools and machines. Technologies are able to collect, host and analyse the vast amount of data to provide real-time business insights that relate to consumers, risk, profit, performance, and productivity amongst many other things. The data includes information gathered from social media, internet-enabled devices (including smartphones and tablets), video and voice recordings, and the continued preservation and logging of structured and unstructured data.
The main benefit of big data for businesses is the insight that it provides, and the fact that these insights can be provided instantaneously. It drastically eliminates the need to make a risky, ‘gut-feeling’ decision, as the information needed to make the same choice rationally is available. This elimination of risk inevitably means fewer poor decisions are made, and judgements are instead based on real evidence in which clear patterns and correlations are likely to exist. The preference for a big-data-informed decision is evident based on the growth of data generation; today, we generate more data in ten minutes than all of the humanity has ever created through to the year 2003.
AI and Machine Learning
Artificial Intelligence (AI) involves the process of analysing data to model some aspect of the world. Inferences from these models are then used to predict and anticipate possible future events. AI models will use collections from big data in order to provide as robust and well-informed predictions as possible. Because these huge datasets are used to build AI models, it means that the chances of anomalies in its results are very slim, and this, in turn, provides a degree of reliability that businesses really value. The fact that the models are pre-designed, and ready to be used whenever needed, also means they are perfectly suited to a high-pressure and time-constrained environment; an environment in which a human could make a critical mistake.
Lastly, machine learning is AI which possesses the ability to learn without being explicitly programmed. Its capability is most effectively conveyed in the example below by Avinash Kaushik:
“A large hotel chain wanted to solve this problem: ninety-thousand travellers are stranded every day in America across 5,145 airports. How can the hotel ensure that they show up at the right moment for all these people? The solution was to leverage real-time signals like bad weather, flight delays at 5,145 airports, and other such data, combine that with machine-learning powered algorithms to automate ads and messaging in the proximity of local airports. The result? A 60% increase in bookings in targeted areas.”
This case clearly shows the benefits of machine learning; it can combine a range of variables and process them in a way to produce a result precisely at the time that humans want it to, while simultaneously saving a huge amount of time and effort for the person who otherwise would have had to analyse it manually.
What This Means
It is indubitable that these three technologies can vastly improve human decision making. But what does it all mean for human choice? Do humans even still have a choice to make?
The answer is: absolutely. These technologies do not eliminate human intuition; they simply improve it. Humans still have several choices to make in any instance despite the availability of these technologies. Would using AI help find a better solution? Which insight model should be run? Does the result being given seem correct? Should this advice be followed or go with a different plan? These are all questions that will be asked, despite the intelligence and the automation of the technology. And it is imperative to remember that – it is humans that create all this technology in the first place.
In reality, given the evidence, this discussion should not be a question of whether human choice still exists or not, but instead an examination of how our choices have changed – and in many ways enhanced. Human intuition and instinct remain critically important in business; all that these technologies do is fine-tune them.
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