BLOG

AI Supervision: The Gold Rush For Managed Services

Share this 

Share on facebook
Share on twitter
Share on linkedin

AI Supervision is a severely underrepresented ingredient for operationalizing AI. It is akin to serving your dinner with all the sizzle and spices, but the recipe forgets to mention salt.

Sheepdogs or mops?Let’s say you run a pet store and your AI can recognize sheep dogs. You use this to target customers and market the cutest of the lot to them.

But wait – your AI now starts classifying mops as sheep dogs! How do you fix that? How many of your customers were mopped in the process? And what was at fault – the inherent bias carried by all Machine Learning? Or your carelessly gathered training data that induces bias into your models?

Raising the kid named AI

Training an AI system is much like raising a child. Children learn from what you expose them to. They ingest the causes (inputs) and effects (outputs) of what you teach, and in some cases use their own intellect to infer things you don’t explicitly state – much like how neural networks inexplicably engineer features from the given data.

Children, and in fact even babies, can readily identify patterns such as colour and form (clustering). It is we who give colours a name; if you tell a child the colour red is actually called blue, it will readily accept so and repeat after you. On an ongoing basis, we correct a child’s behaviour and help them identify right from wrong (supervised learning).

As you sow, so shall you reap

Garbage in, garbage out” holds very true in the world of Machine Learning and so do prejudices. In fact a lot of us will readily recall how Microsoft’s Tay turned abusive, thanks to its mentors who thought it so. Recent applications of AI to court sentencing and insurance approvals have shown social biases simply because AI learns from the data humans feed them, in turn reflecting their own bias.

Focussing on the business

We often get stuck in the coolness factor and needlessly debate neural net architectures without crystallizing the problem or opportunity on hand. Technology is here to serve and elevate organizations to unparalleled levels of automation and cognition. It is vital we clearly define success metrics and esoteric metrics. Metrics such as AUC (area under the curve), ROC (receiver operating characteristics), precision and F1 scores can transpose into business metrics that reflect customer behaviour and sentiment.

Sudden changes (other than organic growth) in your Machine Learning metrics are often indicative of unforeseen changes to your underlying business processes or emerging new patterns in data. The root cause of such anomalies should be immediately identified and rectified.

The “gold rush” for Managed Services

Machine Learning is remarkably similar to how humans learn. Choosing the right training model, eliminating skewness and biases in data, retraining models, and most importantly tying the system performance to business metrics, are vital functions for successful AI.

The slew of DIY cognitive services and toolsets available today, and their ease of use implies that organizations are rapidly adopting them. But as we all know, “well begun is half done”. A “human in the loop” is a must have for the deployment of most AI applications.

Of course, the illusion is to have you believe AI magically does it all.

 

0 replies on “AI Supervision: The Gold Rush For Managed Services”

Let’s supercharge your virtual agent together

With outstanding customer experience being the most important differentiator, make sure your virtual agent is the one leaving the competition in the dust.

Wysdom is a conversational AI optimization platform that enables higher performing, lower cost conversational virtual agents, continually learning and delivering high-quality customer experiences.

© Copyright Wysdom 2021. All rights reserved.

Artiom Kreimer

VP, Product & Analytics

Artiom has spent 10 years in software and mobile engineering, specializing in quality assurance and customer service. He has worked in testing and QA at both startups and in enterprises such as Clickfree, TELUS, and Freescale Semiconductor.

Michel Benitah

VP, Optimization & Delivery

Michel has 20 years of experience in leading the successful delivery of Conversational AI and Natural Language Customer Care solutions to some of the largest financial, telco, healthcare, utilities, and retail enterprises throughout North America. 

 

Prior to joining Wysdom, Michel spent 20 years at Nuance Communications, holding senior management and leadership positions within the enterprise division, most recently as director of the Toronto office and professional services team.

Frederic Lam

SVP, Sales

Fred brings in 25 years of international experience in sales and business development across North America, the Caribbean, Asia-Pacific, Europe, and the Middle-East.

 

Prior to Wysdom.AI, he held sales leadership positions at Oracle, Redknee, and Movius/Glenayre, successfully growing revenues in both large and small organizations. Fred has also been involved in the start-up community in the earlier stages of his career as an Investment Manager with SP Capital and was an alternate director on a few investee companies.

Karen Chan

Chief Engineering Officer, Co-Founder

With 20 years of experience in software and mobile, Karen has held senior technical roles at 5 startups, including Wysdom.AI, Clickfree, Mobile Diagnostix (HP), Teamatic, and Virtualthere.

Karthik Balakrishnan

Chief Technology Officer

Karthik has over a decade of hands-on, proven global expertise in emerging technologies and implementing intricate platforms and solutions for telecommunications and enterprise during his time at Amdocs, with senior positions in their India, Cyprus, America, and Canada offices.

Nitin Singhal

Chief Operating Officer

Nitin has over 20 years of success in global executions of business technology, driving operational efficiency and digital scalability for some of the world’s largest enterprise clients. 

 

Nitin spent 16 years at Redknee holding executive positions in Research and Development, Customer Operations, Partner Alliances, and most recently as COO.

Jeff Brunet​

President, Co-Founder

Jeff has more than 20 years of experience in the startup world, founding and growing 4 software companies: AracNet, Mobile Diagnostix (HP), ClickFree, and Wysdom.AI. 

 

His in-depth understanding of software development and the challenges in making new technologies successful in the startup world prove invaluable as he serves on the boards of XMG, SurfEasy (Opera), Locationary (Apple), Groupie, and as an advisor to Pushlife (Google), LogMeIn (IPO) and HP. 

 

Jeff holds 23 issued patents in the wireless and consumer electronics spaces and is the lead inventor on 30+ pending patents.

Ian Collins​

CEO, Co-Founder

Ian has founded and grown 6 technology companies over the past 20 years, primarily in the enterprise software space including Wyrex, Mobile Diagnostix (HP), Clickfree, and most recently Wysdom.AI. 

 

Ian invests, mentors, and sits on the boards of several startups in the Toronto area.