Automation Vs Humans in the Enterprise
Discussions around automation are heating up in the world of tech. Whether it’s about driverless cars or using autopilot in airplanes, the lines are beginning to blur. For example, take a look at the state of California. It proposed preliminary regulations that could potentially hold “motorists responsible for obeying traffic laws, regardless of whether they are at the wheel.” This latest development didn’t please Google, given its initiative to push the driverless car to the road. And this is just the beginning. Automation is becoming a larger part of our lives and with it, there is an evolution of our behavior.
While automation has been a key trend in the recent technology boom, decision-making efforts are still safeguarded by humans. The shear idea of building human-like intelligence in the form of autonomous technology (artificial intelligence) sounds appealing, but along with psychological resistance, it may impose business risk as well.
Perhaps we’re better served when focusing on augmented intelligence — a perfect vision for next-gen technology to leverage both human decision-making expertise and powerful computing abilities. This concept led to the founding of Stratifyd, where the key belief to helping enterprises unlock insights in modern analytics efforts are best served when harmonizing the two.
Augmented Intelligence — What Can It Be?
When teams are comprised of humans leveraging computer assistance, it allows for them to consistently defeat all challengers including the strongest “computer only” and “human only” teams.
An example of this is when Gary Kasparov, former World Chess Champion, who after being defeated by Deep Blue, IBM’s chess playing machine, explored the interplay between man and computer and how each could affect the outcome of a game. Kasparov designed a tournament to determine which grouping would garner superior results — solely humans, solely computers, or a combination of humans and computers. Hundreds of matches were played.
At the end of the event, the surprise winner was revealed to be not a grandmaster with a state of the art computer, but a pair of amateur American chess players using three computers at once.
Augmented Intelligence in Action
Teams consisting of weaker human players using superior computing generally outperformed teams consisting of stronger human players using inferior computing. This serves as a great example of how combining the speed and processing power of a computer with a human’s interpretive capabilities leads to superior results. This is augmented intelligence in its basic form — computational algorithms helping to put the human end user in the best position to make an informed decision.
Due to the significant increase in collected data and complexity of the reasoning process itself, performing investigative analytical tasks has become more challenging than ever. The simple goal of any analytics effort is to leverage information to bolster business processes. This can involve a variety of techniques to identify and track multiple hypotheses, gathering evidence to validate correct hypotheses, and eliminating ones that offer no business value. Executives and decision makers therefore require robust ways to handle decision-making and knowledge-gathering tasks in open environments, helping them to extract actionable intelligence from evolving data types. Stratifyd’s data analytics platform, Signals, delivers visual insight on textual data that keeps users in the analytics loop and empowers them to identify intelligence that warrants attention. This focuses on providing everyone with augment intelligence from unstructured textual data. In simple terms, algorithms read and analyze textual data and determine the “who”, “what”, “when” and “where”. A human then uses this intelligence to quickly determine the “why” and decides on the appropriate course of action. In the case of textual data, leveraging insight is most effective when combining powerful computing capabilities with an end user’s ability to interpret it.