At SYMSON we are big believers in bringing the human- and machine perspective together. We like to try and build technology that gives organizations superpowers, rather than replacing them. The phenomenon to bring human- and machine knowledge together to solve problems is called Augmented Intelligence. In this article we want to explain how you can fully benefit of this principle in your own organization.
Since the competition between chess champion Garry Kasparov and IBM Deep Blue in 1997 we know that AI can beat a human in specific tasks that are repeatable. What we’ve learned in 1997 is that for a machine to be superior in the game of chess or any other closed system, it doesn’t have to be perfect. It just has to make less mistakes than a human being. Even the best humans are poised to make mistakes. Kasparov said he saw after the match immediately an opportunity to work together, because he also recognized that this would be an unique opportunity in chess to find out the best ways to collaborate between human way of learning, intuition and judgement and machine force of calculation based on vast amount of data. This ended in a whole new application of chess; freestyle chess where it was allowed to play competitions with computers.
In the article of “Building a More Intelligent Enterprise” Paul Schoemaker shows us a diagram where he simply visualized where humans and computers can be stronger and where humans and computers can strengthen each other. Although artificial intelligence is advancing rapidly, a general rule of thumb is that when tasks are unique and when data overload is not a problem for humans, humans likely have an advantage. In many situations, the strongest performance comes from humans and computers working together (Figure 2).
Humans will always be better in complex negotiations, creativity and exploring the unknown. This why people should be educated for these capabilities to avoid that AI can do better. The example of Freestyle Chess is not Artificial Intelligence, it is called Augmented Intelligence. Augmented Intelligence is an exciting and fascinating tool that we as humans can use to go forward in the next millennium. Augmented Intelligence is used today to solve the most complex problems in the world.
In order to fully get the potential of augmented intelligence to built super intelligent and hyperlearning organizations we have to take a few things into accounts, namely
- Make sure that the logic of the AI is understood by the users. It may not be a black box. We’ll go into this in more detail in the video below.
- When possible make use of various AI techniques. As explained above AI has its shortcomings and different models or techniques have all their pros and cons. Combining methodologies give more robust outcomes.
- As diversity of approaches are good for robust results are diversity for the people in the organization. Different people focus on different aspects and think differently.
- For both humans as for machines applies GIGO; Garbage in garbage out. Therefor be critical about the quality of data and try to recognize noise and increase the signal/noise ratio whenever possible.
- Keep the right balance between the amount of data (big data) and the amount of noise in the data. AI is based upon statistical techniques and the more data the more reliable are the statistics.
- When the amount of data is limited and/or the context is very dynamic and changing fast, use also experimentation to gather information about the objects.
What is said above is more or less common sense. However the difficulty is in applying those rules. At SYMSON we help companies to focus on enhancing the intelligence of the organization by combining both human and machine intelligence.
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