The race to win AI

Artificial Intelligence: It’s Not Man vs. Machine. It’s Man And Machine

At the Gigaom Change conference in Austin, Texas, on September 21-23, 2016, Manoj Saxena (Chairman of CognitiveScale), Josh Sutton (Head of Data & Artificial Intelligence at Publicis Sapient) and Rob High (CTO for IBM Watson) talked with moderator and market strategist, Patricia Baumhart, about the next frontier in artificial intelligence and how the race to win in AI will soon reshape our world.

Artificial intelligence is a field with a long history starting as early as 1956, but today what we’re beginning to see emerge is a new convergence of 6 major technologies: AI, cloud, mobile, social, big data and blockchain. Each of the panelists agreed that as we enter into the next digital frontier, AI will be woven into each of these areas causing a “super-convergence” of capabilities.

Saxena predicts that “this age of the Internet is going to look small by comparison to what’s happening in AI.” It’s true. The proliferation of AI creates a new world of application and computation design, including embodied cognition in concierge-style robots that help when we need assistance.

Cloud will become “cognitive cloud,” a ubiquitous virtual data repository powered by a “digital brain” that understands human needs to help us engage with information seamlessly in work and life. Big data will evolve from being about understanding trends to understanding and predicting outcomes. In combination these developments will disrupt enterprise IT and other business models across the world.

But as we move from a “mobile first to an AI first” landscape, how do we differentiate the winners from the losers? And how can investors know where to place their bets?

Trust and transparency are going to be the two most critical pieces of winning applications. Imagine a hedge fund manager using AI algorithms to develop a financial strategy for their portfolio. Before placing millions of dollars at risk, that manager will need an explanation of why the AI chose a particular solution.

We’re seeing companies like Waze do this already. Beyond being a great way to navigate, Waze is a contextually aware, predictive computing platform that anticipates what information you need next based on your location and route. More applications in different industries — from healthcare, to retail, to personal finance — will soon act like Waze, using cognitive computing and context to constantly learn and anticipate what we need.

The businesses that will win are the ones that apply AI capabilities not just to automate their processes, but that use AI to run their business in a fundamentally different way.

First, we have to understand the areas that AI can best be applied. The challenge in cognitive computing is interpreting and understanding the oftentimes imprecise language we use as humans. As High pointed out in the panel, “our true meaning is often hidden in our context.” AI needs to be able to learn from these conditions to gain meaning.

It’s not a question of who has the best technology, but who has the best understanding and appreciation of what the technology can unlock. The people who will gain the most from AI are the ones who are rethinking their business processes, not just running their existing businesses better.

As more of our lives are aided by intelligent systems in our homes, at work, and in our cars, other questions arise. Will AI get so smart that it replaces us? Sutton, High and Saxena all agree “no,” but they say that some tasks will certainly become automated. They believe the more important change will be the creation of a new class of jobs. According to Forrester, 25% of all job tasks will be offloaded to software robots, physical robots, or customer self-service automation — in other words, all of us will be impacted in some way. But while that may sound disparaging, the same study states that 13.6 million jobs will be created using AI tools over the next decade.

The nature of work will change dramatically with AI. We’ll have technology that augments our skills and abilities — perhaps something like a “JARVIS suit” that allows us to be superhuman. We’ll work alongside robotic colleagues that help us with our most challenging tasks. In terms of cognitive computing, we’re talking about amplifying human cognition, not replacing the human mind. There is so much to be gained when we uncover ideas and solutions we wouldn’t have been able to do on our own.

Today 2.5 exabytes of data are being produced every day. That number is expected to grow to 44 zettabytes a day by 2020. Like an actual brain — a super-complex network of biological components that learns and grows with experience — these interconnected data points, along with the machine learning algorithms that learn and act upon them on our behalf, are the building blocks of our AI-powered future.

By Royal Frasier, Gryphon Agency for Gigaom Change 2016