Augmented intelligence – Transforming traditional processes
In our recent “6 Data Analytics Trends to look out for in 2020” blog, we touched briefly on Augmented Intelligence Systems. In this blog, we’ll take a closer look at Augmented Intelligence, what it means and what it can do for organisations.
The concept of “Augmented Human Intellect” is not a new concept, in fact, its origins stretch all the way back to the mid-20th Century. In his thesis entitled “Augmenting Human Intellect: A Conceptual Framework”, internet pioneer (and computer mouse inventor) Doug Engelbart defines augmented intelligence as “increasing the capability of a man to approach a complex problem situation, to gain comprehension to suit his particular needs, and to derive solutions to problems”.
Mainstream adoption of Augmented Intelligence technologies certainly has been a long time coming, but it appears as though its day has come. Gartner recently featured Augmented Intelligence in its 2019 Hype Cycle for Emerging Technologies. They expect Augmented Intelligence to reach the “Plateau of Productivity” and see mainstream implementation across industry within the next two to five years.
For us here at Analytics Engines, we define Augmented Intelligence as the empowerment of human processes through the intelligent use of data.
Greater than the sum of its parts
While the definition of Augmented Intelligence is clear, what might we consider its features and components to be? In an interview with CXOTalk, Dr David Bray, Executive Director of the People-Centered Internet, outlines how he sees Augmented Intelligence as a convergence between several technologies, including neural networks, deep learning and pattern matching.
“…[it’s] the idea of sort of augmenting what a human does as a way of pairing the human with the machine so that the human is learning from the machine and, at the same time, the machine is learning from the human and, together, you’re getting better outcomes from them both.”
Dr David Bray
Executive Director
People-Centered Internet
In line with Dr Bray’s sentiments, many of the Augmented Intelligence systems that Analytics Engines have developed are a coming together of a range of technologies. Our solution, developed in partnership with EIT Food, combines Natural Language Processing and Machine Learning to help improve consumer trust in food supply chains.
Transforming outcomes
Augmented Intelligence systems are not designed to replace the individual, but rather to help improve their capacity and capability for problem-solving and decision-making.
In an article titled, The Augmented Workforce, KPMG outlines the opportunities that augmented intelligence systems present. Specifically, their ability to “help individuals make better decisions, allowing employees to focus on value-added task”.
Consider our recent case study for Innovate UK. Our solution, COBALT Grant Manager, utilises machine learning and text analytics to automate the process of grant application checking and assessor matching and to assist in identifying fraudulent submissions. Since deployment, our solution has been able to reduce the time taken to match assessors from 4 days’ work to just a matter of minutes, allowing the assessment team to focus their time and efforts on service delivery. Other benefits have included:
– More robust fraud detection
– Increased efficiency and allocation of resources
– Improved accuracy compared with manual assessment.
Conclusions
Augmented Intelligence systems have the potential to transform outcomes and traditional processes. To find out more about how the augmented intelligence systems have helped our clients, contact us using the form below.
