In almost any field involving new trends and developments, anything attracting rapidly increasing media attention is often referred to in terms of “generating a lot of buzz”. Well, here’s a quite different sort of story that adds a whole new meaning to this notion.
A truly fascinating post appeared on TechRepublic.com this week on January 22, 2016 entitled How ‘Artificial Swarm Intelligence’ Uses People to Make Smarter Predictions Than Experts by Hope Reese. It is about a development where technology and humanity intersect in a highly specialized manner to produce a new means to improve predictions by groups of people. I highly recommend reading it in its entirety. I will summarize and annotate it, and then pose a few of my own bug-free questions.
A New Prediction Platform
In a recent switching of roles, while artificial intelligence (AI) concerns itself with machines executing human tasks¹, a newly developed and highly accurate algorithm “harnesses the power” of crowds to generate predictions of “real world events”. This approach is called “artificial swarm intelligence“.
A new software platform called UNU has being developed by a startup called Unanimous AI. The firm’s CEO is Dr. Louis Rosenberg. UNU facilitates the gathering of people online in order to “make collective decisions”. This is being done, according to Dr. Rosenberg “to amplify human intelligence”. Thus far, the platform has been “remarkably accurate” in its predictions of the Academy Awards, the Super Bowl² and elections.
UNU is predicated upon the concept of the wisdom of the crowds which states that larger groups of people make better decisions collectively than even the single smartest person within that group.³ Dr. Roman Yampolskiy, the Director of the Cybersecurity Lab at the University of Louisville, has also created a comparable algorithm known as “Wisdom of Artificial Crowds“. (The first time this phenomenon was covered on The Subway Fold, in the context of entertainment, was in the December 10, 2014 post entitled Is Big Data Calling and Calculating the Tune in Today’s Global Music Market?)
The Birds and the Bees
Swarm intelligence learns from events and systems occurring in nature such as the formation of swarms by bees and flocks by birds. These groups collectively make better choices than their single members. Dr. Rosenberg believes that, in his view there is “a vast amount of intelligence in groups” that, in turn generates “intelligence that amplifies their natural abilities”. He has transposed the rules of these natural systems onto the predictive abilities of humans in groups.
He cites honeybees as being “remarkable” decision-makers in their environment. On a yearly basis, the divide their colonies and “send out scout bees” by the hundreds for many miles around to check out locations for a new home. When these scouts return to the main hive they perform a “waggle dance” to “convey information to the group” and next decide about the intended location. For the entire colony, this is a “complex decision” composed of “conflicting variables”. On average, bee colonies choose the optimal location by more than 80%.
Facilitating Human Bee-hive-ior
However, humans display a much lesser accuracy rate when making their own predictions. Most commonly, polling and voting is used. Dr. Rosenberg finds such methods “primitive” and often incorrect as they tend to be “polarizing”. In effect, they make it difficult to assess the “best answer for the group”.
UNU is his firm’s attempt to facilitate humans with making the best decisions for an entire group. Users log onto it and respond to questions with a series of possible choices displayed. It was modeled upon such behavior occurring in nature among “bees, fish and birds”. This is distinguished from individuals just casting a single vote. Here are two videos of the system in action involving choosing the most competitive Republican presidential candidate and selecting the most beloved sidekick from Star Wars4. As groups of users make their selections on UNU and are influenced by the visible onscreen behavior of others, this movement is the online manifestation of the group’s swarming activity.
Another instance of UNU’s effectiveness and accuracy involved 50 users trying to predict the winners of the Academy Awards. On an individual basis, they each averaged six out of 15 correct. This test swarm was able to get a significantly better nine out of the 15. Beyond movies, the implications may be further significant if applied in areas such as strategic business decision-making.
- Does UNU lend itself to being turned into a scalable mobile app for much larger groups of users on a multitude of predictions? If so, should users be able to develop their own questions and choices for the swarm to decide? Should all predictions posed be open to all users?
- Might UNU find some sort of application in guiding the decision process of juries while they are resolving a series of factual issues?
- Could UNU be used to supplement reviews for books, movies, music and other forms of entertainment? Perhaps some form of “UNU Score” or “UNU Rating”?
1. One of the leading proponents and developers of AI for many decades was MIT Professor Marvin Minsky who passed away on Sunday, January 24, 2016. Here is his obituary from the January 25, 2015 edition of The New York Times entitled Marvin Minsky, Pioneer in Artificial Intelligence, Dies at 88, by Glenn Rifkin.
2. For an alternative report on whether the wisdom of the crowds appears to have little or no effect on the Super Bowl, one not involving UNU in any way, see an article in the January 28, 2016 edition of The New York Times entitled Super Bowl Challenges Wisdom of Crowds and Oddsmakers, by Victor Mather.
3. An outstanding and comprehensive treatment of this phenomenon I highly recommend reading The Wisdom of the Crowds, by James Surowiecki (Doubleday, 2004).
4. I would really enjoy seeing a mash-up of these two demos to see how the group would swarm among the Star Wars sidekicks to select which one of these science fiction characters might have the best chance to win the 2016 election.