Swarming Artificial Intelligence

Unanimous A.I.  http://unanimous.ai has developed what they call Artificial Swarm Intelligence, the UNU swarming platform and the Swarm Insight on-demand intelligence service. The UNU platform allows online groups to form real-time “human swarms” in order to tap collective knowledge, wisdom, and intuition. Distributed online groups can answer questions and make predictions in real-time.

We have been talking about the wisdom of crowds for more than a decade. In 2004, The Wisdom of Crowds (with its very long subtitle "Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations") popularized the idea. The term collective intelligence (CI) is also used for shared or group intelligence that emerges from the collaboration and of collective efforts of many individuals. This also leads to consensus decision making.
CI appears in sociobiology, political science as well as crowdsourcing applications.

You'll also hear the term collective IQ, which is a measure of collective intelligence. We shouldn't be overly proud of our use of this since collective intelligence has also been attributed to bacteria and animals.

Unanimous A.I. takes this idea of the wisdom of the crowd's collective opinion rather than that of a single expert. They use this amplified intelligence to generate decisions, predictions, estimations, and forecasts, which can be seen in events such as the Kentucky Derby, the Oscars, the Stanley Cup, Presidential Elections, and the World Series. They call the technology Swarm AITM using algorithms and interfaces modeled after swarms in nature. 

The Internet As Café

caféI was quite charmed last year when I made my first visit to Prague in the Czech Republic. I had in my mind a Romanticized version of the city and its famed café culture. In my imagination, it was people sipping coffee on sidewalk table and talking about art and literature. When my wife and I went for coffee and dessert at the Café Imperial, it was certainly much grander than anything I had imagined.

We did find those little cafés too, so I was able to embrace my Romantic version of the city. There is also the well-documented role of  the coffeehouse in the Age of Enlightenment. These informal gatherings of people played an important role in innovation in politics, science, literature and religion.

Next year, I hope to visit the Café de Flore which is one of the oldest coffeehouses in Paris. Located at the corner of Boulevard Saint-Germain and Rue Saint-Benoît, it is known for its history of serving intellectual clientele. At one time, those tables overheard conversations from existentialist philosopher Jean-Paul Sartre,  writer Albert Camus and artist Pablo Picasso.

In science, breakthroughs seem to rarely come from just one person working alone. Innovation and collaboration usually sit at the table together. We are currently in a time when, at least in American politics, collaboration seems nonexistent.

This notion is what caught my attention in an interview I heard with Steven Johnson who wrote Where Good Ideas Come From.
He writes about how “stacked platforms” of ideas that allow other people to build on them.  This way of ideas coming together from pieces borrowed from another field or another person and remixing feels very much like what has arisen in our digital age.

One example he gives is the 1981 record My Life in the Bush of Ghosts by Brian Eno and David Byrne. It is an innovative album for that time in its use of samples well before the practice became mainstream. Eno was inspired by the varied voices and music and advertising on New York AM radio which was so different from the straightforward BBC radio he grew up with in England. He thought about repurposing all that talk into music.

We call that “decontextualizing” now – in this case a sound or words taken out of context and put in a new place. But this borrowing and remixing also occurs with ideas in culture, science and technology.

Unfortunately, ideas are not always free to connect with each other. Things like copyright and intellectual property law get in the way. We often silo innovators in proprietary labs or departments and discourage the exchange of ideas.

I didn’t know that Ben Franklin had a Club of Honest Whigs that would meet at the London Coffeehouse, when he was in England and they would hang out and exchange ideas.

Johnson describes these as “liquid networks” – not so much for the coffee, but for the fluidity in the conversation. These informal networks work because they are made up of different kinds of people from different backgrounds and experiences. Diversity is not just necessary as a biological concept but as an intellectual one.

The Internet was built on ideas stacked on top of ideas. A whole lot of code and ideas are underneath this post. At its best, when I write online I am connecting, if only virtually, with other writers, artists and thinkers, and connecting literally through hyperlinks to those ideas.

I know there are “Internet cafés,” but what about Internet as a café?

Do We Still Need to Debunk Online Learning Myths?

robot head

Ever since I started working in the design of online courses and began teaching online, I have heard that online courses are sub-par, difficult to use, boring and ineffective compared to traditional face-to-face courses. There are lousy online courses, and there are lousy face-to-face courses. Research has shown over and over that there is so significant difference in learning in a good online course and a good traditional version of the same course.
But myths still exist and I still see posts about debunking online learning myths. In one post from glassdoor.com (an online job search site) they list four "myths." 
Myth #1: Instructor-led training is the “gold standard” for every learner.
Not everyone learns well online, but for some people it is actually a better delivery system. One advantage online is that learners control the pace of learning. That helps slower and faster learners.
Myth #2 Online learning’s primary purpose is to serve scale, not individuals.
Although online platforms are ideal to train a large group of students or workers -hence the growth of MOOCs - individuals can benefit. When it is done well, online learning can be mapped to the learner.  
Myth #3: Online learning creates a lack of accountability for the learner.
Measuring "engagement" has become a focus in the past decade. One kind of accountability is keeping learners engaged. I have always found that I can more easily monitor my online students engagement (readings, discussing, submitting small and large assignments etc.) than keeping track of a class of on-ground students. 
Myth #4: Instructor-led training is more social and better leverages social learning.
As the article notes, "Online learning is optimized for social learning—especially when it matters. In a traditional classroom, learners interact with a handful of peers during discussions and often practice skills in small groups or in pairs. In addition, they may get a smidge of personal interaction with the instructor. In online learning, a cohort of learners can discuss the application of a skill in social threads. When a learner practices a skill, they do so for the rest of the class to observe and provide feedback. Conversely, learners can also see how the other members of their cohort apply the same skills. Rather than seeing a partner demonstrate the behaviors, they see how everyone in the class approaches the skills—allowing them to pick up even more social nuances than they might in a classroom. Rather than a handful of social exchanges, online learners experience dozens and dozens of interactions."