Josh Feast, is the CEO and Co-Founding father of Cogito, an enterprise that mixes Emotion and Conversation AI into an modern platform that gives real-time coaching and guidance to contact center agents, gives supervisors visibility into live conversations from their teams working from anywhere, and constantly monitors customer and worker experiences.
The story of Cogito starts in 1999, before the corporate was founded. Could you share some insights on these early days on the MIT Human Dynamics Lab and what was being worked on?
From 1999 through 2006, Dr. Sandy Pentland developed fundamental basic science demonstrating the presence and power of social signals in human communication and the power of machines to detect and interpret them.
In 2007, Cogito was spun out from the MIT Media Lab. Could you share this genesis story?
Before my days at MIT, I recognized the necessity for technology that’s informed by conversational context to assist its users throughout emotionally charged situations. While working on the Latest Zealand Department of Child, Youth and Family Services (now referred to as the Child, Youth and Family unit of the Ministry of Social Development), I noticed that many social employees were burnt out attributable to the highly emotional nature of their duties and believed that the management systems that supported them would greatly profit from such a technology. I brought my observations from that point to MIT, and Cogito was later created from Dr. Pentland’s MIT Media Lab research that looked as if it would directly address the issue. Cogito received funding from the Defense Advanced Research Projects Agency (DARPA) to research and develop a man-made intelligence platform and behavioral models to robotically detect human psychological states. This technology proved successful at helping military veterans coming back from combat through deployments with the Department of Veteran Affairs (VA).
The Emotion AI technology that’s used at Cogito was first validated by assisting healthcare providers to detect early signs of PTSD and other mental health disorders in soldiers coming back from combat. Could you discuss some details regarding this and the kinds of results that were seen?
The aim of deploying this technology to healthcare providers was to detect depression and stop suicide in military veterans coming back from combat. The platform we developed enabled doctors to trace veterans’ overall mental health through voice signals and to pinpoint events like homelessness and other warning signs of poor mental health. We quickly realized we had something special, and that the technology’s application could prove useful beyond supporting military veterans and healthcare systems in areas with high volumes of complex, emotionally charged conversations. With our roots still centered on the human experience, we became the Cogito today, supporting real-time coaching and guidance for giant scale enterprise contact center agents across multiple industries including healthcare.
Are you able to discuss how Cogito uses AI to investigate behavioral cues and supply in-the-moment feedback during conversations?
Cogito uses a robust combination of Emotion and Conversation AI to disclose latest insights from all conversations, extracting each was said and the purchasers received the message. These AI models measure customer experience (CX) in real-time on all calls to have impacts within the moment, vs. post-call evaluation which centers only on improving future interactions.
Cogito extracts and analyzes greater than 200 acoustic and voice signals in milliseconds to present contact center agents cues on how you can adjust their behavior and surface the most effective recommendations based on the topics discussed and desired outcomes.
Cogito performs live, in-call voice evaluation to reinforce behavior in real-time to create higher human connections at scale between customers and phone center agents, no matter where they work.
How does this feedback guide agents to construct higher relationships with customers?
The actual-time feedback contact center agents receive from Cogito’s nudges allows agents to display more consistent emotional intelligence, which ends up in agents delivering empathy on each call. Improved empathy leads to raised conversational outcomes, reminiscent of reduced call handle times, increased first call resolution, improved customer satisfaction, and increased customer lifetime value.
Each contact center representative has different strengths and weaknesses. The actual-time nudges they receive on the decision helps enhance their customer support, whether or not it’s to offer more empathy, speak slower, or sound more upbeat. This tailored feedback within the moment allows agents to construct a relationship with the client based on that specific customer’s experience and their voice signals picked up by the AI model. In turn, this improves each the client experience, and the agent experience.
Real-time feedback shouldn’t be only helpful to CX – it also advantages the worker experience (EX). Our tools help support representatives to have more positive work experiences, which is proven to drive higher levels of CX.
In 2019, Cogito released a paper titled What were a number of the key insights when it got here to the effect of gender bias in speech with respect to emotion?
Our paper focused on the modeling approach and optimization techniques in addition to sampling bias. Due to this fact, more research should be done to mitigate negative bias generally in machine learning and specifically in speech emotion recognition. Key insights include:
Female speech tends to be higher pitch than male speech, which ends up in more widely spaced harmonics.
Speech emotion recognition models may be affected by this difference. This could result in lower accuracy for female speech versus male speech.
De-biasing machine learning techniques may be applied to scale back this accuracy imbalance. Within the paper, Cogito introduces a novel de-biasing technique which performs favorably relative to the baseline.
How does Cogito operate to mitigate the results of unwanted gender or other kinds of bias?
Cogito uses natural language processing (NLP) models that mix human-aware AI systems, deep learning machine models, and other complex rules which help computers understand, analyze, and simulate human language. We’re consistently working on and evolving our NLPs with latest data to mitigate bias.
Cogito has a comprehensive protocol for machine learning model development, which goals explicitly at mitigating bias and ensuring ethical machine learning (ML)-based product features. This protocol covers areas like sampling data for training, mitigating bias in human labeling, and using ML de-biasing techniques.
Cogito uses a ‘fairness’ dataset comprised of a giant body of audio data where the speakers self-report different demographic categories. All models are assessed against the fairness dataset and against the assorted demographic categories. We also use ML Ops techniques to objectively monitor models in production and systematically perform model audits with human annotation.
What are your personal views on how AI shouldn’t only replace humans, but quite augment human behavior?
There are things humans can do and nuances they will provide in human-to-human interactions that technology like AI cannot emulate by itself. For instance, customers wish to receive empathy after they contact customer support. If the client interacts only with an automatic system powered by AI, their issue is likely to be resolved, but they may find yourself feeling frustrated or annoyed by the interaction. If we replace all contact center agents with AI, then we’re eliminating the human element that’s needed to construct relationships and achieve and maintain lasting, loyal customers.
When engaging in a service interaction, humans value talking to someone who can put themselves of their shoes, who has had experiences just like what they themselves are going through. Along the identical lines, humans value the feeling of another person taking good care of them and owning the resolution to their problem. It is going to be a protracted time before standalone AI is admittedly perceived as something apart from a self-help tool.
Is there the rest that you want to to share about Cogito?
At Cogito, we’re developing latest technologies to usher in the subsequent generation of contact centers. Earlier this 12 months, we released our Worker Experience (EX) Rating to trace agents’ experiences. Much like our customer experience (CX) rating, the EX Rating combines human-aware Emotion AI and Conversation AI, deriving real-time insights across single instances or trends across multiple calls. Amid high levels of dissatisfaction, burnout, and attrition, the EX Rating helps solve the query of how you can prevent burnout and help the agent experience, which in turn drives higher customer experiences and long-term business sustainability.
