Message from the editor
The game of chess has been calculated as supporting 1040 positions for the 32 various chess pieces or chessmen. As daunting as it is to conceptualize a number that large, try thinking about the 10120 different possible chess games! Perhaps we can simplify things, as Diego Rasskin-Gutman did in his book Chess Metaphors. He pointed out that a player trying to consider all the possibilities of just the next eight moves by both players encounters a number equivalent to all the stars in a typical galaxy. It’s no wonder chess has been called the most cognitively challenging of all games.
Business leaders and staff operate in a realm of similar uncertainty that can be considered even more challenging than chess. More than 32 “chessmen” are in play, and the rules guiding the behavior of suppliers, employees, partners, competitors, and customers are far more fluid, even unknowable. Yet decisions must be made despite all this uncertainty; not making a decision is the same as making one.
Enter the computer. In a review of Chess Metaphors, Garry Kasparov (the chess grandmaster and former World Chess Champion) described what it was like being one of the few grandmasters whose life in chess spanned both the before and after periods in which computers impacted the game.1 He played 32 “chess computers” simultaneously in 1985 and beat them all. Eleven years later, in 1996, he barely defeated IBM’s Deep Blue; the next year in 1997 he lost to a new and improved Deep Blue—an event that made headlines around the world.
The experience was transformative for Kasparov, but it did not lead him to the obvious conclusion that computer intelligence will supplant human intelligence very soon. That’s because Deep Blue’s “intelligence” represented an exhaustive, computationally intensive search of all possible outcomes of a limited set of move options facing the chess player. Human intelligence works at a higher level, looking for familiar patterns and making decisions based on patterns. But patterns are conceptual; they can hide fatal flaws in the next series of moves that are otherwise conceptually similar. Kasparov recognized that computers could easily check for those fatal flaws and signal the player not to follow a particular pattern of play. He even proposed a new style of play he called “Advanced Chess,” which explicitly allows a single player to have a computer at hand to check for such fatal flaws.
But why have a human involved at all? Didn’t Deep Blue prove no humans need apply? The answer lies in how chess tournaments have evolved since Deep Blue’s arrival on the scene. These newer forms of chess invite humans and machines to the table with fewer constraints. Freestyle chess tournaments allow pure human, pure machine, and any combinations of humans and machines to compete.
In a 2005 freestyle tournament, the winner was not a grandmaster playing alone, or a machine playing alone, or a single grandmaster aided by a single powerful computer.2 The surprise winner was a team of two amateur chess players using three computers at the same time. The secret to their success was the interaction between the humans and the computers—the different types of intelligence were “coaching each other” in a distinctive process. As Kasparov concluded, “Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.”
This issue of the Technology Forecast examines the future of enterprise applications. Our starting assumption was that many high-value “business activities” are actually cognitively challenging mental processes, not unlike chess. Were there any applications that could have been inspired by the lessons from the freestyle chess movement, that combining human and machine intelligence in a strong process creates the most effective results?
The answer to that question appears to be yes. A confluence of trends such as mobility, cloud, application programming interfaces (APIs), analytics, and others are giving rise to apps, which we call mindful apps, that blend human and software intelligence and make human cognitive processes part of the enterprise business processes. In doing so, these mindful apps expand the purview of enterprise applications to include human thinking and augment humans’ capacity for knowledge work.
The article, “The future of enterprise apps: Moving beyond workflows to mindflows,” on page 06 explains the rise of mindful apps, what they are, and how they optimize the human element by building support for thinking processes as part of any business process.
“Technologies that enable mindful apps” on page 28 looks at the collection of methods and technologies involved in the design, development, and deployment of mindful apps.
The article, “The mindful CIO,” on page 46 explores the key role CIOs and IT staff can play in the development and adoption of mindful apps.
This issue also includes interviews with executives and thought leaders at enterprises that are demonstrating leadership with the future of enterprise applications:
Please visit pwc.com/techforecast to find these articles and other issues of the Technology Forecast online. If you would like to receive future issues of this quarterly publication as a PDF attachment, you can sign up at pwc.com/techforecast/subscribe.
As always, we welcome your feedback and your ideas for future research and analysis topics to cover.
1. Garry Kasparov, “The Chess Master and the Computer,” The New York Review of Books, February 11, 2010, http://www.nybooks.com/articles/archives/2010/feb/11/the-chess-master-and-the-computer/.
2. “Dark horse ZackS wins Freestyle Chess Tournament,” Chess News, June 19, 2005, http://en.chessbase.com/home/TabId/211/PostId/4002461.