A Cognitive Computing system has to provide machines with a mental model of the surrounding world to be smarter, and able to replicate the way humans understand
Today, within organizations, many business processes which do require human intelligence are executed by people and can hardly be modernized using traditional technologies.
Let’s take some examples.
Hello, I'm Jane
I’m a human resource representative working for a large organization. Like many other businesses, managing our talents is very important.
Since a couple of months, many employees are quitting and we try to understand why. We decided to prepare a survey in order to collect employee feedback on several questions.
We will soon receive their answers…
When Jane will receive feedback’s from the workforce, she and her team will have to read them and identify specific semantics related to satisfaction at work criteria, emotions and affective states in order to understand what employees are thinking.
Hello, I'm Julien
I’m a police officer working for law enforcement authorities. For us, being able to help and protect people is very important.
When we arrest a suspect, we have less than 48 hours to analyze what we have seized and collect evidences, qualify them and present them to justice.
Time for us is critical…
When Julien will have to assess the content of the material he has seized, he will have to open each file to look after evidences, read and search for specific words related to illegal drug trafficking, terrorism or pedocrimes. For him, time is critical !
Let’s dig into the details of what they need to do.
Jane and her team have to read employee surveys in order to detect satisfaction at work criteria. There are 17 different criterias which are defined. In addition, they will have to find specific semantics related to emotions and affective states since those psychological factors will also say a lot about what employees think. In total, 1 546 words are used to define this specific frame of reference and for someone who knows them, like a human resource expert, at least 8 minutes are needed to identify them within one employee feedback (half a page of text). But Jane has to process a total of 14 763 surveys! Her labor can be estimated to 118 104 minutes, in other words 281 mandays (1.33 FTE). This is a lot of work for Jane and her team.
For Julien, the situation is very similar. Currently he has someone under arrest and has to look into several megabytes of text data (SMS messages, eMails, Internet history, files on the computer and on external drives). The time is playing against him and it is critical to find evidences. The problem is that criminals are using secret words so that they are not easy to find during an investigation. Only subject matter experts, like Julien, know those words and this tasks cannot be shared easily with other police officers. The amount of data he has to study today is only 3 637 Kilobytes long and this does represent 890 pages of text. If he reads quickly, let’s say 5 minutes per page to collect the information that he needs, he would need a little over 74 hours to complete the job but he has only 30 hours left !
What can be done to help them ?
Jane and Julien they both do the same thing. They need to read text, identify specific words, understand what is said and write a report.
To read and understand, to identify specific semantics, to capture the meaning of what was written, those things are mental activities and cannot be processed by machines. People have to do this.
We think that it is possible for people and machines to execute the same processes. To do this, we need to create a new generation of software which is able to replicate how the brain works and perform tasks usually requiring human intelligence.
We need to create a software that is able to represent a context like humans would represent it, a software that is able to understand content provided in natural language, a software that is fast enough in order to accelerate the assessment to be done and a software that could provide a true expertise.
To do this, we need to understand how the brain works. Neurosciences and psychology will help us to better understand how the brain is processing information, how knowledge is stored and used to represent a context, understand, reason, make decisions and solve problems.
In short, what we need to do is to create a new generation of software !
Let’s do Cognitive Computing
All individuals exist in a continually changing world of experience (their phenomenal field) of which they are the center. This perceptual field is a reality for the individual, and the best vantage point for understanding behavior is from their internal frame of reference.
While they communicate, individuals will freely associate specific words together and describe, using their language, how they perceive, represent, or understand a given situation.
Our ability to reason, make decisions, and solve problems can define intelligence. These cognitive processes are linked to psychological functions such as emotions, sentiments, or needs. These mental states provide additional context-related vital insights, which, once added to other available inputs, will create a conglomerate of information, giving us a mental representation of the situation, enabling our awareness, and adapting our behaviors and actions.
Making machines smarter will require that these human capabilities can be transferred to and executed by a machine. To do this, two core components must be created: the SmartNeuron™ and the VirtualBrain™.
SmartNeurons™ can process information like it is processed in our brain by our chemical neurons, in an analog way or fuzzy way so that this processing is as close as possible to how humans process information.
VirtualBrains™ is a data structure analog to the human long-term memory, where information or knowledge is stored in a categorized way, providing machines with specific frames of references and enabling cognition.
Natural language understanding technologies involve identiﬁcation the intended semantics from the multiple possible semantics. That means the system needs a contextual lexicon of the language, with a suitable ontology, to provide machines with a mental model of the surrounding world and assess the provided data to extract its meaning in several languages without prior training (no machine learning). This contextual ontological lexicon is then added to a categorized symbolic object structure so that machines can better understand, be smarter, and able to replicate the way humans understand.
Job done !
After 7 years of research & development in neurosciences, cognitive and clinical psychology, linguistics, philosophy, ergonomics and computer sciences, we have created Percipion™, a new generation of Cognitive Computing engine able to represent a semantic context, understand content provided in natural language, reason and take actions
Now that Percipion™ is available and used, what are the benefits for Jane and for Julien ?
Percipion is helping us a lot !
What would have taken us 281 days to complete is now done in a couple of minutes. Our benefit is that the assessment is done faster which is giving us more time to address value added work and better take care of our workforce.
If you need more information about our Cognitive Computing solution Percipion™, please message us using our contact form.