In a recent article in the MIT Sloan Management Review the authors report “Disruption from artificial intelligence (AI) is here, but many company leaders aren’t sure what to expect from AI or how it fits into their business model.” In datanami George Leopold reports “a sizable number of executives said they remain worried about data security in the cloud while 41 percent were still not convinced workloads would run securely in the cloud.”
This feinting move by business executives, expressing concern about data security instead of speaking to the business issues of Artificial Intelligence (AI), should not surprise anyone who’s worked in corporate America. It happens all the time when executives are presented with technology imperatives for changing business models but are very uncomfortable speaking about the technology driving the change imperative discussion.
Fearful of change, many business executives simply misdirect the discussion to a topic, like “data security”, with which they feel somewhat comfortable, and allows them to point-out the business short-sightedness of “technologists”. That approach has been responsible for more luddite resistance to technological change than Ned Ludd’s resistance to automated knitting frames ever was. It has also lead to the eventual destruction of many businesses. The approach is pervasive, however, and employed in all industries. It’s the reason more than 81 million shoppers perused online offerings on Cyber Monday, Nov. 27, compared to the 77 million who showed up in stores on Black Friday. It’s the reason Bill Gates and Jeff Bezos are the first and second richest men in the world, respectively, and Amazon recently acquired Whole Foods.
Many are familiar with the famous George Bernard Shaw quote, “Some men see things as they are and ask why. Others dream things that never were and ask why not”. Well in the case of many business executives there’s an add-on to Shaw’s quote that reads “and then others see things they don’t want to be, and obstruct them however they can”.
All of this jousting between business executives and technologists is very destructive. Much of the behavior of business executives is simply bravado. It’s behavior “intended to impress or intimidate”. It’s basically a statement from the executives letting everyone know, “who’s in charge”. It’s kind of like a rooster prowling the barn yard, with his feathers all fluffed-up and his comb as bright red as gleaming cherries, expecting the hens to be attracted and his competitor roosters to run for the cover of the nearest coop.
In the end however, the behavior of luddite executives is little different than , that of “ flat-earthers”, like “Mad” Mike Hughes, on whom the Economist recently reported. Apparently Mad Mike is a Californian, who will launch himself 1,800 feet into the sky in a homemade steam-powered rocket made of scrap metal to prove a point. “On his trip over the Mojave Desert, which could propel him at speeds of up to 500 miles per hour, the 61-year-old limousine-driver-turned-daredevil hopes to prove the Earth is flat”. There’s also Bobby Ray Simmons Jr., a rapper known as B.o.B, who launched a crowd-funding campaign to send satellites into orbit to determine the Earth’s shape.
On a more respectful note however, the entire move to integrate cloud-based Artificial Intelligence (AI) applications into business needs to be held accountable by the same business executives I’ve abused throughout this post. Following is a picture of the K computer, manufactured by Fujitsu and currently installed at the Riken Advanced Institute for Computational Science in Kobe, Japan.
The K performs 10 petaflops. (FLOPS, floating-point operations per second). A petaflop is 10¹⁵ . The K can perform 10¹⁵ operations ten times in a second. In 2017 the K’s performance is 14,000 times better than Moore’s law expected.
All major industrial nations have projects underway building K class computers. The genie is out of the bottle with no intention of going back. However, business executives should not expect to spend hundreds of millions of dollars on K class computers or the development of sophisticated AI algorithms. Both will be made available for a fee from world class cloud computing services using economies of scale to keep costs down. David Kenny, the boss of Watson, IBM’s AI platform, predicts there will be “two AIs”: companies that profit from offering AI-infused services to consumers and others which offer them to businesses.
Following is a computing model for AI developed by Professor Jeffery Leek of Johns Hopkins University. It includes three parts:
1. The data set — used to train a statistical or machine learning models to make predictions.
2. The algorithm — trained using the data set to issue commands for work to be performed.
3. The interface — An interface to the algorithm to that receives a data input and executes the human like task in the real world.
Today the three largest providers of AI serices are Amazon Web Services, Microsoft’s Azure and Google Cloud. They all offer application-programming interfaces (APIs) to allow the user interfaces of other companies to access machine-learning capabilities and avoid the costs of each company building it’s own AI.
According to professor Leek, “the most under-appreciated component of the AI revolution does not have to do with data or machine learning in the cloud. Rather it’s the development of new interfaces that allow people to interact directly with machine learning models.” It’s these business interfaces on which executives and their teams will need to focus.
Business executives don’t need to be talking about data security and cloud computing workloads. Those are things their technologists and cloud service providers will bake-into all new AI configurations. Business executives need to assure there are solid, reliable and understandable business objectives for buying cloud computing services and building business interfaces to those services for their teams to use. If those investment methodologies and techniques are not in place for the evaluation of Internet-based AI applications, then executives need to pull-in their feathers and calm down the gleam of their comb. They need to focus getting them in place and operational before worrying about data security and workloads running in the cloud. ___________________________________________________________________
- The Economist, “Google leads in the race to dominate artificial intelligence” Dec. 7, 2017