TED Community » Alec Perkins

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  A reply on Conversation: William Gibson said "The future is here, it's just not evenly distributed yet." What futures have you seen that are here, but unrecognized?

  Feb 21 2011: Good point. I definitely agree that humans are predisposed to a leader-based structure. It makes sense from an evolutionary perspective, and leaders provide a good focal point to rally around a particular set of issues. Also, they're good at setting direction of a group.
  
  What I envision is not so much a replacement of leaders, but rather a way to enhance the interaction between leaders and followers. I see these new systems of organizing the crowd as a way to enable better feedback from the bottom up. Politicians often ramble about "what the people want", but how do they really *know*? Instead of relying solely on infrequent elections, which rarely match up to the unpredictable pattern of events, how can we really tell the leaders what we want? (And also make the system work both ways, so people can know more about what the government is doing and more about the issues.)
  
  On Slashdot.org, for example, people are given temporary moderation powers over comments somewhat randomly, with merit weighed in. To prevent their abuse of power, ordinary people can "meta-moderate", and moderate the moderators. Poor moderators are less likely to be given the power again. This pattern of moderation and meta-moderation causes the best comments to emerge from the pool. There are many examples of this type of model implemented online. While they are fairly limited and focused in scope, I think they hints at what's possible with a highly distributed and scalable communication network.
  
  I guess what I'm envisioning is a more participatory system, where it's desirable to participate in the process. People need to feel like they have a say, instead of just one of the millions whose vote doesn't really count. I think the Web is a place to look for answers, since it is something radically new, and has demonstrated a capacity for this. (Also, open source is absolutely another place where models can come from, highly merit- and transparency-based. Sounds like good qualities for government.)
• +2

  A comment on Conversation: William Gibson said "The future is here, it's just not evenly distributed yet." What futures have you seen that are here, but unrecognized?

  Feb 18 2011: Along the lines of Anonymous and Revolution 2.0, mentioned above, our understanding of complex, emergent systems, as well as our more and more pervasive communications networks, hint at new possibilities of governance and organization that we haven't seen before. The industrial revolution marked a starting point where now we humans could operate vastly beyond our own scale, on a planetary level. But, the traditional methods of organizing do not scale as well as our ability to grow our societies.
  
  From what I've seen, the traditional top-down organizational structures won't cut it for much longer. The question is, how can we use more bottom-up approaches that can scale, and the interconnectedness provided by the Web, to better organize ourselves in more effective ways? Our current methods are relatively ancient, and have not really evolved at the same rate as our science, technological, and societal development. We need a radical rethinking of governance, and emergent systems plus the Web are a good place to look.

• A comment on Conversation: Watson's "What is Toronto?????" on Tuesday's Final Jeopardy

  Feb 18 2011: IBM has a writeup of where the answer came from: http://asmarterplanet.com/blog/2011/02/watson-on-jeopardy-day-two-the-confusion-over-an-airport-clue.html
  
  Basically, it came down to the clue itself not explicitly asking for a US city, and Watson having learned during the practice games that categories cannot be trusted to indicate the type of answer expected. Humans still have the advantage when it comes to implied meanings. In the end, Watson picked Toronto because it was slightly more correlated with WWII than Chicago, which was its second choice, though it wasn't very confident about either.
  
  All of Watson's wagers were perfectly rational, more so than humans'. It was playing to win, and could figure out the optimal amount given the state of the game and its confidences in categories.