AI: 4 Humans: 1 Some jobs are safer than others.
Last March, Google’s artificial intelligence (AI) AlphaGo defeated Go Grandmaster Lee Sedol 4-1 in a series of five matches.AlphaGo uses deep learning and neural networks to teach itself to play. The AI is fed millions of Go positions from real human games and then improves its ability by playing against increasingly powerful versions of itself.
Demis Hassabis, a researcher who works at the Google’s DeepMind, which built AlphaGo, says that the same techniques can revolutionise robotics and believes that such AI learning is a path to a new kind of scientific research.
At the moment, AI is limited in the jobs it can tackle. Like much of the AI around us, AlphaGo is an example of what computer scientists call Artificial Narrow Intelligence (ANI), which is an AI that can master a specific task. Apple’s Siri, Amazon’s Alexa and Uber’s self-driving cars are all examples of ANI. They’re great at what they are designed to do but are unable to think outside the box.
Many are scared that AI will take all our jobs. It’s natural to be afraid of new technology, but the usual pattern is that we first fear it, then adapt to it and finally benefit from it. As noted by Tim O’Reilly in a recent Ted Talk, we shouldn’t run out of jobs until we run out of problems. Facing adversity is productive and will result in us doing things in newer, better and more creative ways.
Reid Hoffman, executive chairman and co-founder of LinkedIn believes that within the next five years forward-thinking organisations will be using ANI to build what he calls a corporate “knowledge graph”. Just as a social graph represents the interconnection of relationships in a social network, he says that the knowledge graph will represent the interconnection of data and communications within a company.
Assuming he is right, and ANI does begin to take a central role in corporate structures, where does that leave Knowledge Management (KM)?
What is knowledge management?
According to KM World, a publication dedicated to KM, the concept and term first appeared around 1990. At its heart, KM does what it says on the tin: it’s about managing the knowledge of organisations. To elaborate, we can look at one of the most frequently cited definitions, provided by the Gartner Group in the late 1990s:
“Knowledge management is a discipline that promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise's information assets. These assets may include databases, documents, policies, procedures, and previously un-captured expertise and experience in individual workers."
KM’s relationship with Customer Experience (CX)
To promote customer loyalty and gain a competitive advantage, an increasing number of organisations have been turning Customer Experience (CX). Last year, a Frost & Sullivan survey found that 82% of organisations regard CX as a competitive differentiator, while over 75% believe that it increases profits/revenues.
A recent Frost & Sullivan white paper explores the relationship between well-designed KM and the gap between customer expectations and an organisation’s ability to deliver on these expectations. According to Frost & Sullivan’s study, one of the largest global insurance providers realised a 50% drop in agent training cost and a 30% drop in complaints through the use of KM.
The road to AGI
As noted earlier, ANI such as AlphaGo already surrounds us and the trend is that we will continue to use it in various facets of our lives. In organisations, Hoffman sees ANI as something that will occupy a central position in the communication stream, collecting the information and drawing connections between when accumulated data and corporate messaging.
However, despite ANI helping us greatly within organisations, a discipline such as KM, which is a blend of art and science, still requires humans to drive it. ANI simply isn’t “smart” enough to think creatively or establish concepts that are out of the box. To do so, ANI would have to take the next step in its evolution and become “Artificial General Intelligence” (AGI), which is AI that can perform any intellectual task a human can – and more. By most accounts, we are still a long way off from creating AGI, with predictions running from 2030 (43% of AI experts according to one survey) all the way up to never (2%).
For at least the next decade or so, and perhaps a lot longer (or forever?), we are going to need knowledgeable, empathetic and creative humans steering the ship. ANI is great at augmenting what we can already do, and – with the exclusion of manual labour- is thus more likely to be your coworker than the thing that takes your job. Of course, when – or if – we do build a machine with AGI, well have to revisit this discussion. Until then, ANI will continue to supplement rather than replace human capital.