<img height="1" width="1" style="display:none;" alt="" src="https://dc.ads.linkedin.com/collect/?pid=586106&amp;fmt=gif">

We’ve all seen dystopian sci-fi flicks like The Terminator and The Matrix. The notion that machines might one day supplant humans is predicated on the discovery of Artificial General Intelligence – essentially, that machines will one day think like humans (at blindingly faster rates of speed, of course).

The discovery of Artificial General Intelligence has long been considered the Shangri-La of those pushing the boundaries of AI. As far as markets are concerned, when that day comes, machines will be capable of accurately forecasting future events based on the actionable insights they extract from large, unstructured data sets. Today, machines can accomplish the first step – they can extract the data. However, they are incapable of interpreting meaning based on that data. Our human brains are still superior in this regard.

The problem with humans is, we’re prone to bias. We make errors in informational processing and reasoning all the time – even the best of us. We can’t help it, we’re only human. The good news is that machines can solve for human bias by freeing up the mental bandwidth of investors who can then focus on tasks that machines are incapable of accomplishing; those involving creativity, independent thought and reasoning from first principles – the cognitive tasks that fundamentally drive alpha generation. And as machines correct for human bias, humans in-turn correct machine bias (by tweaking their inputs), which further corrects human bias… and on and on until optimal decision-making is derived.

Therein lies the opportunity for collaboration between humans and machines. Far from the world of The Matrix where machines take over for humans, we are creating a world where machines are enhancing human capabilities. Consider the use of drones to capture and assess agricultural yields, or satellite imagery which can detect oil rig activity. What would previously require an army of human analysts to undertake over an extensive period of time, machines can accomplish in seconds. And these unconventional data sources can now be mined for tradable signals which have previously gone undetected.

Additionally, large networks of humans (think customers reviewing a product online) can seed machines with enough contextual understanding that the machines will be able to extract actionable insights buried in the nuance, language and sentiment of the human interactions. Essentially, humans communicate with one another, and machines pick up on all of the subtleties overlooked by our biologically limited human brains. The humans then read these insights and incorporate them into their decision-making processes.

In a world where digital noise (for lack of a better term) collects at an exponential rate, investors are finding it impossible to make sense of the immeasurable amounts of raw data. Since alpha generation is a function of identifying market inefficiencies, any system that solves for those inefficiencies by leveraging the collective intelligence of human networks will capture greater amounts of alpha for investors. These systems add value by helping human investors connect invisible dots. All of this can be realized with greater accuracy, efficiency and scalability than either humans or machines can achieve independently.

In the end, partnering with cognitive systems equates to better outcomes for investors, and for humans in general. While Hollywood likes to portray otherwise, the reality is that machines are humanity’s greatest accelerant – they solve for our inefficiencies, and free us up to focus on the tasks we’re best at.

For more on how AI and unstructured data are reshaping the investment landscape, check out Nasdaq’s interview with Accrete Founder and CEO, Prashant Bhuyan.

Nasdaq Interview with Accrete

Topics: Artificial Intelligence