AI everywhere & nowhere part 1 – Tempered excitement

March 29, 2016



Artificial intelligence has a lot of promise-but it also has a ways to go before it can be deployed widely to full advantage.

PwC_Rep_USA_NYC_JFB_2482.jpg Busy tourist area an electronic news ticker

Artificial Intelligence (AI) is all the rage in the popular press this week. Even if you are an Alien who just landed on Earth from a planet far away, it is impossible to miss the headlines that AlphaGo—the AI program developed by Google—beat the world champion of the game Go Lee Sedol 4-1.

Why is there such excitement about this AI program beating the human champion? What is in fact AI or Artificial Intelligence? What does this all mean to our businesses or each one of us? To be even more melodramatic – what does this mean for humanity?

In a series of blogs, I will try demystify AI, dispelling myths, providing facts, and offering analysis on AI’s implications to businesses and society at large.

AI defined (really?)

Since the term was first coined in 1956, AI has suffered from shifting definitions.

The word “Artificial Intelligence” was first used at the second Dartmouth conference organized by John McCarthy, one of the founding fathers of AI.  Most definitions of AI revolve around ‘simulation of intelligent behavior by computers’. However, one of the most popular AI textbooks took AI to another level.

In “Artificial Intelligence: A Modern Approach” Stuart Russell and Peter Norvig define AI as the designing and building of intelligent agents that receive percepts from the environment and take actions that affect that environment. This view of AI brings together a number of distinct subfields of computer vision, speech processing, natural language understanding, reasoning, knowledge representation, learning, and robotics with the aim of achieving an outcome by the machine.

As AI has evolved, it has also splintered. As soon as any subfield of AI is well understood it gets renamed and whatever is still to be discovered gets branded as AI. For example, handwriting recognition or voice recognition was once considered AI. However, with the availability of commercial systems that can recognize written text or recognize human speech, these areas are no longer considered AI. As a result, any precise definition of AI is fraught with the danger that the definition becomes obsolete as technology advances take place.

Given the difficulty of defining ‘Intelligence’ and hence ‘Artificial Intelligence’, the field of AI has resorted to beating humans in games where the humans exhibit a lot of ‘thinking’, ‘learning’, or ‘physical activity’. As a result over the past couple of decades, we have seen AI beat the best humans in Chess, Jeopardy, and now Go.

There are also games like Soccer where a group of robots train to beat the Soccer World Champions one day. While beating the best humans at their own game—thinking and learning–is a laudable goal, gaming situations differ from a majority of our day-to-day activity in significant ways.

First, these games have a prescribed set of rules and well-defined and certain outcomes (e.g., win, loss or tie). Second, these games are closed-loop systems where the effect of the actions is limited to participants within the system. Third, the AI can be trained with multiple failures (e.g., losing the game) with no real consequences to participants outside the system.

Needless to say these situations are not very common outside of the games, and the hoopla surrounding AI and games perpetuates the confusion about AI’s ultimate mission. While it is great to see that what was once considered close to impossible just two years back – beating the World Champion of Go – has now been achieved, the implications of this achievement for the broader application of AI needs to be kept in perspective. It is one more feather in the cap of ‘deep learning’, the mechanism that was used by AlphaGo to beat Lee Sedol. However, for the reasons mentioned above, the excitement of the win needs to be tempered by the daunting and challenging situations that AI software still needs to operate under.

In the next three blogs, I will visit three definitions of AI – AI as UI (or Ubiquitous Intelligence), AI as AAAI (or Assisted, Augmented, and Autonomous Intelligence) and AI as noUI (no User Interface). In the meantime, let’s get the conversation started with some questions: Have you considered the impact of AI to your business? Do you know which jobs could potentially be replaced partly or wholly by intelligent software? Feel free to share your views in this forum.




Chris Curran

Principal and Chief Technologist, PwC US Tel: +1 (214) 754 5055 Email

Anand Rao

Global Artificial Intelligence Lead, PwC US Tel: +1 (617) 530 4691 Email