There is no shortage of media coverage around Artificial Intelligence (AI). Currently, much of this conversation centres around AI being discussed in terms of its ability, or potential ability, to replace humans in the workplace and this, as would be expected, is causing a great deal of concern and speculation.
The notion of AI is not a new concept, and has perhaps received most attention recently when Google’s Deep Mind defeated the world champion at the complex game of Go or IBM’s Project Debater further demonstrating more complex and personable capabilities.
AI is driven by algorithms, which themselves are undergoing a revolutionary development trajectory and are driving the recent progress of AI. Early algorithms which famously defeated chess champions at their own game have been left in history. The recent AlphaGo algorithm has developed in such a way that it no longer solely relies on computer power to achieve its goal of outperforming humans. The algorithm teaches itself by performing the function it wishes to perform, for example the game Go, and then learns from its own mistakes and successes too. This type of algorithm is known as deep learning.
Erik Byrnjolfsson of MIT’s Sloan School of Management thinks so!
Erik Byrnjolfsson considers this as “general purpose technology” (GPT) which he contends are set to become common throughout the economy and other activities. It is predicted that GPT will continue to improve over time and, through this learning, will themselves develop the span of contribution that GPT can achieve.
This would suggest to the layperson that the development of GPT will be dramatic and thus the contribution trajectory to be steep. However, this is unlikely to be the case as there is a component which needs to be taken into account, and that is, how suitable is a particular task to be done by a machine? This is otherwise known as ‘suitability for machine learning’.
Most jobs have tasks which are suitable for machine learning, however very few have total task suitability. This is good news for us humans since it suggests that despite the rhetoric and news stories, us humans are not due to be replaced anytime soon!
What these developments in technology and employment make it clear is the need for those entering the workforce to be more versatile in their skillset, have excellent communication skills and be able to start, maintain and build relationships.
In a world where future professionals will increasingly be able to delegate tasks to technology, the need for a more personal touch with an emphasis on soft skills such as problem solving, collaboration and empathy will be the characteristics future employers will look for.