Augmented Intelligence in a New Era of Search
One of the few things that the tech industry agrees with is that humans create a lot of data. By extension today we can also agree that we are creating more of it—in more ways—and to more media than yesterday. This trend will continue inexorably. The value of information to the user at any point in time is something that should be reflected upon. In the age of big data, how do users sort through all the clutter to extract information that feels intuitive, personal and intelligent? This is highly subjective, yet fundamental.
Paradigm Shift to Augmented Intelligence
This relentless growth in information and the rise of the information-savvy, evolved user is driving the need for a new era of search where the user sits at the center of his information rather than the user sitting surrounded by information systems.
User-centric search makes systems work the way we want them to work, not the other way around. This is both an opportunity and a challenge for the enterprise and its users. It’s an opportunity because—if effectively leveraged—the tremendous volume of data can augment the intelligence of the user to solve real business, operational, legal, compliance, data management, security challenges, etc. in a more efficient manner. But it’s a challenge because management of this data requires implementation of new technologies and new practices that disrupt the status quo of the traditional search landscape. Users want to be close to the information they have an affinity toward and will leverage any number of technologies that can provide them with the most convenient access to their information. They don’t want to be bogged down by monolithic systems. It becomes the responsibility of technology providers to adopt a user-centric approach to capture, quantify and characterize information and then take this knowledge to analyze, map, infer, connect and assemble insights to empower the user to consume and react more intelligently than he would have been able to yesterday.
As data increasingly centers on the user, developments in hardware, software and communications will trend toward providing the same experience and information to the user across all technologies. Cloud computing is an example of this. The user’s affinity to information becomes the glue that connects hardware, software and communications, and acts as the driving force behind technological advancements.
In parallel, as technology becomes more and more pervasive and absorbed in our everyday environment, it’ll function in the periphery of the user—blurring the line between humans and technology. Technology by itself doesn’t possess advanced human conceptual intelligence or perceptual capabilities. However, by marrying the human brain with technology, we give birth to a new age of augmented intelligence that’s more powerful than what humans or technology can achieve on its own. Augmented intelligence turns data into valuable knowledge that is actionable for the user—effectively shifting information from passive intelligence to results-driven intelligence.
We see the infancy of augmented intelligence in the demand that consumers are driving from search-based apps, and emerging trends such as the Internet of Things (IoT), the Internet of Everything (IoE) and haptic touch technologies. The coexistence of humans and technology is creating a paradigm shift to augmented intelligence in the vast information landscape.
Driving the Need for a New Era of Search
With the movement to a more user-centric information model, more sophisticated search technologies are required to keep up with the growing business needs and evolved users of today. Users need to find meaning in large volumes of data to make the best decisions. Large volumes of data can be retrieved via questions and queries, but the concepts held within information are not always apparent. When organizations leverage emerging augmented intelligence search technologies that can derive actionable, contextual and conceptual insights, they can uncover information they hadn’t considered before.
Added complexity around data also drives the need for a new era of search. Many organizations and their users are well down the path of managing structured data in columns and rows, but what about the unstructured data? Needless to say, it’s no longer enough to simply sort through exorbitant amounts of data. It’s also critical to address different types of data. The bulk of digital data is unstructured, human-friendly information, such as free text, emails, images, audio, videos
and social media. For example, users are creating massive amounts of human information (beyond spreadsheets and PowerPoints) through their communications within social channels.
Light and Dark Data
We have established through this article that humans create a lot of data. What we haven’t touched on is the time-value concept around data. Information isn’t weighted equally—in fact, its value often fluctuates, particularly when associated with time—the here and now. The volumes of data that we create and exchange affect our ability to use the information effectively. For example, we might analyze and use information that’s within our reach. We call this light data. But we might not get a chance to analyze it completely before the next influx of data arrives. In these very dynamic motions, information ebbs and flows between light data and dark data. When light data falls to the bottom of our attention, it turns into dark data. The means to bring it back to the top of our attention is difficult to accomplish using traditional means.