How Will Synesis One Leverage the Wisdom of Crowds to Teach AI about the World?

INTRODUCTION

To grow the compendium of knowledge that fuels the AI engine, Synesis One will rely on crowdsourcing, which is premised on the idea that aggregations of individuals often make more intelligent judgements than individual experts. This idea may seem counter-intuitive, as anyone who has blundered into a crowd of cheerfully inebriated British football fans after the big game can attest. How can a crowd possibly be smarter than the smartest experts?

THE WISDOM OF CROWDS

The idea that crowds can be wise and not irrational or foolish is a modern one. In the 19th century, the Scottish writer Charles Mackay penned a three-volume work called Memoires of Extraordinary Popular Delusions and the Madness of Crowds, which took a rather dim view of the decision-making capacities of humans in large groups. For Mackay, the European witchcraft craze of the 16th century, the Dutch ‘Tulip Mania’ of the 17th century and the South Sea Bubble of 18th century England are all examples of otherwise reasonable people collectively losing their minds. As he put it, “we find that whole communities suddenly fix their minds upon one object and go mad in its pursuit; that millions of people become simultaneously impressed with one delusion, and run after it, till their attention is caught by some new folly more captivating than the first.” (1)

The folly of crowds was the prevailing view until James Surowiecki turned the notion on its head with his 2004 book, The Wisdom of Crowds — whose title is an allusion to Mackay’s classic work. Under certain conditions, he argues, crowds can be better informed and make better decisions than individual experts in fields as diverse as behavioral economics, pop culture, and psychology.

Whereas Mackay was writing about what today we’d call crowd psychology, Suroweicki focuses on aggregations of individuals weighing evidence and making decisions independently. The idea is that collective wisdom compensates for individual biases. For Suroweicki, a crowd is wise to the extent that its members have a wide diversity of opinions, arrive at their unique views independently of one another and can draw on their private individual experience and knowledge. Then all that is required is a mechanism (like polls or markets) for aggregating individual judgements into a collective determination. The internet offers the latest way for humanity to tap the wisdom of crowds: crowdsourcing!

CROWDSOURCING

Gartner researcher and crowdsourcing expert Daren Brabham defines crowdsourcing “as an online, distributed problem-solving and production model that leverages the collective intelligence of online communities.” This model has been successfully applied in many online contexts, including knowledge sharing platforms such as Wikipedia and Quora, prediction markets like Augur, computational crowdsourcing like Crowdcloud or Amazon’s Mechanical Turk, and many other Web 2.0 platforms.

To ensure that crowds are wise, crowdsourcing designers need to ensure that their platforms embrace diversity. The greater the diversity of ideas and perspectives, the more accurate the crowd’s judgement — as opposing views, biased perspectives and over or under estimates tend to cancel each other out in the aggregate. In the ‘Wisdom of Crowdsourcing,’ Jessica Day argues that the key to making a platform welcoming for everyone (and hence diverse) is to test it with a wide variety of demographics — different income levels, educational backgrounds, ethnic backgrounds, tech savviness or lack thereof, geographic locations and so on.

Crowdsourcing designers also need to make sure that members of the crowd are truly independent. If the designer allows for too much communication, for example, then individual members of the crowd can be swayed by group think, herd-like conformity, deference to authority or other social biases. Each participant needs to arrive at judgements by themselves, with minimal social influencing — otherwise the crowd (as a whole) can become less intelligent.

SYNESIS ONE

Similar to Wikipedia, we look to the wisdom of crowds to grow our database of knowledge. Humans are still better at many tasks than computers, including annotating and categorizing knowledge. Synesis One crowdsources the process of categorizing, building, and validating, natural language inputs. For example, if an Architect wishes to expand the natural language inputs for making a hotel room reservation, then responses to questions such as, ‘how would you express a desire to book a hotel room’ would be solicited for. We also use crowdsourcing to check whether a response is relevant to a given domain or topic.

Unlike Wikipedia, Synesis One compensates contributors for their contributions. And we’re not talking about carpal tunnel inducing ‘clickwork’ that pays pennies, like many of the tasks on Amazon’s Mechanical Turk. When contributors add to the knowledge compendium, the engine transforms the inputs into data structures called canonicals. Canonicals are stored as Kanon, which are NFTs. Each time the AI engine accesses a particular keyword Kanon, the NFT holder receives a reward (like a royalty) in Synesis (SNS). In this way, contributors become owners of capital producing digital assets. The more Kanon a contributor owns, the more rewards he or she can earn.

Over time, the crowdsourced compendium will make the AI more intelligent, taking us closer to the ultimate goal of general artificial intelligence — all while rewarding contributors and creating new opportunities to earn rewards.

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1. Charles Mackay, Memoires of Extraordinary Popular Delusions and the Madness of Crowds. London: George Rutledge & Sons, 1841.
2. James Surowiecki, The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations. New York: Doubleday, 2004.
3. Daren C. Brabahm, Crowdsourcing, MIT Press 2013.
4. Jessica Day, The Wisdom of Crowdsourcing undated article on ideascale.com
5. Brad DeWees and Julia A. Minson, ‘The Right Way to Use the Wisdom of Crowds’ Harvard Business Review, December 20, 2018.
6. Alana Semuels, The Internet Is Enabling a New Kind of Poorly Paid Hell The Atlantic, January 23, 2018.
7. Charles Mackay, Memoires of Extraordinary Popular Delusions and the Madness of Crowds. London: George Rutledge & Sons, 1841.
8. James Surowiecki, The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations. New York: Doubleday, 2004.
9. Daren C. Brabahm, Crowdsourcing, MIT Press 2013.
10. Jessica Day, The Wisdom of Crowdsourcing undated article on ideascale.com
11. Brad DeWees and Julia A. Minson, ‘The Right Way to Use the Wisdom of Crowds’ Harvard Business Review, December 20, 2018.
12. Alana Semuels, The Internet Is Enabling a New Kind of Poorly Paid Hell The Atlantic, January 23, 2018.