Paul Saffo keynotes, and three panels have been programmed.  The rest of the scheduled two days is left to the attendees to collaborate on topics of relevance to the community.  The three panels, posed as “debates”, are focused on synthetic biology, artificial intelligence, and longevity intervention.

I have the distinct pleasure of moderating the artificial intelligence debate which brings together four leading thinkers in this area:

• Ben Goertzel, Novamente, Singularity Institute
• Peter Norvig, Director of Research at Google
• Steve Omohundro, Self-Aware Systems
• Barney Pell, Founder of Powerset, Strategist at Microsoft

For one hour, we will a conduct a very different AI debate: not whether to create AI, or which technical path will work fastest, but “How can we use AI technology to build the world we want to live in?”

Some of the things I want to know:

• Technology policy and politics:  What advice do you have to President-elect Obama on the future of technology enhanced humanity?
• Haves vs. have-nots:  Is there a growing gap between haves and have-nots?  If so, should we look towards AI to address it?
• Potential outcomes:  Viewing the distribution of future outcomes (imagine a normal distribution), it seems that accelerating technology capability will push probabilities towards the tails:  Exceedingly wonderful or terrible.  How can we use AI technology to push towards a favorable outcome for humanity?
• Governance mechanisms:  I heard a commentator say that this just past election will likely be the most important election of our lifetime.  What about the election of 2048 that pits enhanced human vs. sentient machine?  What kinds of governance systems should we put in place now to inform the world we want in 2048?

What kinds of questions would you like answered by the esteemed panel?  I’d welcome your input.

To give get a novice understanding of the science and progress behind BMI, check out the fantastic piece from 60 Minutes that aired on Sunday, November 2nd.

Bruce Hall, President of Velodyne LIDAR demonstrates the HDL-64E.  The 64E is a ground breaking laser vision system that crushed the competition at the 2007 DARPA urban challenge.  Today, Velodyne sells the 64E (list price $75,000) to organizations wishing to integrate 1″ accuracy GIS data at highway speeds.

“I’d pretty much pissed away most of my Whuffie — all the savings from the symphonies and the first three theses — drinking myself stupid at the Gazoo, hogging library terminals, pestering profs, until I’d expended all the respect anyone had ever afforded me.” — Cory Doctorow, Down And Out in the Magic Kingdom, 2003

“There are perennial discussions of trust metrics for things like automatic sysopping and (a) general “reputation management” system.  It is rightly pointed out (by me and many others!) that such systems are difficult to design properly and often easy to “game”.  At the same time, the hope is that a well-designed system would be scalable and informative, while not oppressive or empowering of tyrants.”  — Jimmy Whales, 2004

In the not too distant future, trust and transparency will become incredibly important issues for the Web.  In a world where increasingly powerful virtual online agents begin to act as proxies for decision making that we humans currently perform, there will become myriad opportunities for disreputable firms to compromise these agents, influencing the decisions that they take against the will of the person they are acting on behalf of.

You might be surprised by how many purchasing decisions robots already make.  Black-box trading systems on Wall Street and across the financial markets accounted for over 1/3 of all stock trades in 2006, and will push 50% of volume in 2010 according to the consulting firm Aite Group.   Electronic Data Interchange (EDI) systems and other standards based protocols in manufacturing, logistics, and procurement frequently execute purchasing decisions with little or no human intervention.  You can event train Amazon.com to automatically send you items based on a schedule you teach it.

What all three of these systems have put in place is an automated system for buying things without having to have a human in the middle of the decision-making process.   While Amazon fulfillment might be a simple algorithm, the underlying models for some algorithmic trading systems are as complex as any logic process that you might execute to decide what stocks to buy and when.

In the next few years, we will see web-based services emerge that want to offer that level of “decision-making by proxy” for many of the tasks that you perform manually online today.  Things like booking airline flights, making dinner reservations, scheduling appointments and buying goods and services are being targeted for automation by this new class of intelligent agent technology (see the Do Button).

The challenge that emerges is figuring out a “trust model” that will allow these agents broad latitude to execute on your desire while maintaining a high level of transparency that they are acting in your best interest, rather than being unduly influenced by third parties (perhaps through favored relationships with the agent provider).

I’m reminded of the recent dust-up around Facebook data.  If you think that having a service like Facebook turn on you and not release your data is wrong, wait until your trusted execution service suddenly decides to change how it behaves because of a new partnership the provider put in place.

Obviously, this kind of conflict could damage the growth potential for intelligence agent technologies.  I’m worried that investors in these firms will look at all of the monetization strategies that such a powerful tool will bring in the near term, and make value judgments about the level of objectivity that such a system might require without considering the broader issues of trust and transparency.

I suspect that this problem will not be easily solved. Modeling trust for an intelligent agent will require an understanding of a great many variables:

1. Beliefs and biases of the user.
2. Beliefs and biases of the user’s trusted network of social relationships
3. Transparent knowledge of the biases of the intelligent agent provider
4. A model for trading degraded transparency for reward
5. A model for adjusting all of the above over time and circumstance

If I am right about how large an impact the Intelligent Agent industry will have on society in the decade ahead, it is incumbent upon interested parties today begin to address these issues in an open and collaborative format.

I presented the following preso at the morning keynote. Props to ethos 3 for their excellent graphical enhancements. Enjoy!

Both are social tools. Twitter enables a group to socially instant-message and share their thoughts and perceptions of the moment. In the case of an assembled group of twitterers (tweeps? tweeters?) attending a conference, the medium becomes a method for creating a “back-channel” of conversation that floats through the aether parallel to the one-way message of the speaker.

Last spring at South by Southwest, the Twitter back-chanel flexed it’s muscle during the keynote conversation between Mark Zuckerberg and Sarah Lacy. (See Zuckerberg Keynote Descends Into Chaos as Audience Takes Over)

Tweets at The Singularity Summit have been less inflamatory (for the most part).  We’ve adopted a hashtag #SS08 which allows people to easily find Summit comments.  You can see the most recent tweets here.  We used the same hashtag yesterday at the Emerging Tech workshop, and several of the panel moderators monitored the twitter feed during their panel to incorporate feedback.

The second tool that we are using at the Summit is Twine.  (Twine is a financial sponsor of the event).  Twine is a bookmarking tool + discussion forum augmented with semantic intelligence.  As presenters discuss topics on stage, I can find a representation online and “Add To Twine”.  (Twine requires a free subscription, you can see the Summit twine here.) Once I submit content to Twine, the service pulls keywords, summary data, and relevant context from the posting and creates a relationship model that links postings to other relevant content. Twine, like Twitter, is a collaborative tool.  Anyone who subscribes to my Singularity Summit twine can add their own content which will semantically get mixed into all other contributions.

What I am finding most fascinating today (aside from the speakers) is the interplay between these two tools.  A speaker’s comments will trigger a posting to Twine which in turn causes someone else to post an item to Twitter.  Conversely, Some feedback on Twitter will trigger a post on Twine.  It’s possible that we can see a recursive feedback loop between these tools from both the speakers and the audience that will last far beyond the speaker’s 15 minutes of fame on the stage.  It would be a great benefit to Twine to integrate a Twitter feed so that semantic relationships within Twine could reference tweets and vice versa.  I’m optimistic that these two tools will work together to create a very powerful offering for managing the short term and longer term wisdom of the crowd.