An AI Direction for Today’s Giants

Today

Google claims to have built “a web of things” to help drive its new Knowledge Graph.  From words to concepts and back?  Just as third-party researchers are using Google’s search algorithm to find biomarkers that cure cancer, Google is claiming to have “found concepts.”  What kind of concepts?  Google’s Norvig explains, “We consider each individual Wikipedia article as representing a concept (an entity or an idea), identified by its URL.” So Google’s using a Wikipedia-derived Explicit Semantic Analysis to achieve Semantic Search.  Novel.

Meanwhile, Bing is doing Social Search…using Facebook’s Social Graph.  Great for seeing what shoes or hotels or articles your friends like…and other “niche knowledges.”  Not so great outside your community’s niches, your communal “filter bubble.”  (Google ‘s Knowledge Graph tackles the problem from the other direction:  start with the most generic knowledge niches.  If you’re not searching for Da Vinci, you might not get Knowledge Graph.)

Then there’s Apple getting sued over SIRI for “overstating the abilities of its virtual personal assistant.”  Who’s not overstating these days?  Apple’s ad teams have tailored a message that achieves the precise amount of ambiguity to maximize sex appeal and plausible deniability.  The suits won’t stick.

Of course, everyone’s attempting to build brand loyalty so they can rake in dollars.

Tomorrow

Deleuze & Guattari define philosophy as the creation of concepts.  I marvel at Google (+Wikipedia), Bing (+Facebook), and SIRI.  They are creating concepts–at least of a certain kind.  When you search for Da Vinci on Knowledge Graph and it groups renaissance painters together, this appears as abstraction, generalization.  When you search SIRI for Indian Food and she finds restaurants in your area, this is a form of pragmatic localization.  When you search Bing for fashion, and it tells you what your friends are wearing, it’s creating concepts in the space of social awareness.

Intelligence is metaphor all the way down.  All the services described above metaphorize in some nascent fashion. Lakoff and Johnson summarize:  “the essence of metaphor is understanding andexperiencing one kind of thing in terms of another.”[1]  General AI can be achieved by building out multi-dimensional metaphorizing algorithms.

Interestingly, SIRI, Google and Bing each assume a specific want (desire) in the user, and tailor their service accordingly.  SIRI assumes you don’t want abstract knowledge about the history or characteristics of Indian Food, but that you want to eat some, nearby, soon.  Google assumes you want general knowledge of Renaissance painters or other search topics.  Bing assumes you want to know what your friends and acquaintances think.

What if what you wantis general AI?  To achieve AI, concepts need semi-permeable membranes between them.  From Turner & Fauconnier’s “Conceptual Blending” to Ridley’s When Ideas Have Sex, ideas need room to breed.  As a first step in the right direction, I envision service that understands and generates metaphor.  At first, I want it to be capable of understanding why and when it might be apt to say  “Juliet is the sun,” “Man is a wolf to man,” or “You made your bed, now lie in it.”  For this, we need a Pragmatic Ontology, a subtle notion of what makes daily human actions meaningful.  Step two involves metaphorically extending the algorithms necessary for the first form of metaphorizing…finally achieving, for instance, an understanding of how identification with the hero of a story is a form of metaphor, how the move from string to a thing is metaphor, how the metaphorical process is ubiquitous.   That’s what I want to see built.

Afterward, I’ll be satisfied enough to navigate to a local Indian restaurant to contemplate Donatello’s brushwork like my friends do.

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[1] Metaphors We Live By (1980), 5.

Slices & Traces

Slices & Traces
In graduate school, I once heard a medieval scholar remark that we now knew what Thomas Aquinas did on nearly every day of his life.  While such a feat is perhaps the wet dream of a medievalist, technology is reaching the point where the same may soon be true of me or you.

Historians compile numerous traces (any historical artifact that says “Thomas was here”) into slices (e.g. a biography).  In the digital age, what fascinates me is that numerous ready-made slices of our virtual lives may be compiled easily from databases that archive massive amounts of our personal digital traces.

I recently had the opportunity to experiment with Stanford’s Muse Project, which provides various analyses and visualizations based on personal email history and browser history (sentiment analysis, social group change over time, et al.)  Pros:  the program provides an interesting slice of one’s virtual self.  Cons:  the slice of my personal history recorded in my email database feels partial and one-sided.[1]  For another example, consider Facebook’s recently released “timeline.”  The history embedded in your Facebook timeline is yet another  slice of your personal history.  Each slice tells its own story, albeit an incomplete story.  A slice is just a slice.

What if, like an fMRI, we were able to capture and compile slice upon slice?[2]  Would the slices add up to a complete picture?[3]  What if one were to aggregate and integrate all the slices of one’s virtual life?  What if you had the tools to capture & integrate your own personal data from email history and browser history and add that to your data from social networks (Facebook, Twitter, LinkedIn), dating sites (eHarmony, Match, OKCupid), bookmarking sites (Stumbleupon, del.i.ci.ous, digg), music sites (Pandora, Grooveshark), movie sites (Netflix, Blockbuster), video sites (Youtube, Vimeo, Dailymotion), commerce sites (Amazon, ebay), banking sites (Mint, Quicken), location services (FourSquare, GPS), SMS history, and blog corpus?  What if, to that already rich textual and social data, one added perceptual data capture via webcams, haptics, and EEG/GSR?  What if one were to sift, analyze and integrate the data using textual algorithms (corpus linguistics, LSA, ESA, sentiment analysis), social algorithms (network & influence analysis), and perceptual algorithms — replete with visual recognition (facial, gesture, object, movement), audio recognition (voice, music, sound), and touch recognition (texture, heat, pressure)?  (See Figure 1)

Slicing & Tracing
Such a system of integrated personal data, collected en masse (even if anonymized), would prove invaluable to social scientists, historians, marketers, Big Brothers, and researchers of all ilks.  Although we’d never achieve Rankean history “wie es eigenlich gewesen ist,” (as it actually happened) through such a system, it represents a potential tool (among other tools we’re developing) that will soon get us closer to historical realism (or even hyper-realism).  What I’d like to discuss today is not the fine-grain detail we may someday achieve by integrating slices and traces.  Instead, today I want to talk about the slicing and tracing.

Suppose you mummify your information…all of your information.[4]  You’re still just a data-fossil in a museum exhibit a millennium from now (and if everyone gets mummified, probably a poorly-visited exhibit).  But your data doesn’t even make it to the museum without first undergoing some form of condensation and selection.[5]  I don’t care how much you love your grandpa, you’re not going use your entire life to watch a second-by-second video of his entire life.

Before the digital age, condensation and selection happened naturally in places like family photo-albums and dinner-table stories.  These human-sized brain-morsels could be chewed and digested comfortably.  In the digital age, a deluge of data makes you cross-eyed and bloated while historians babble about Kim Kardashian and advertisers hypnotize you with french fries.  As we speak, historiography is being asked to develop some frighteningly powerful tools to condense uncompressed information, select salient aspects, and present us with soundbites (Think Robin Williams in The Final Cut).  Too much data is the first challenge facing next-gen story-telling gurus.

But too much information (TMI) is merely the prima facie challenge.  The real challenge, as I see it, is not TMI but too little intelligence.  I’ve often said that “after the Information Age comes the Intelligence Age.”  I want to see a generation of “intelligence scientists” rise up to replace today’s “information scientists.”  Would you rather preserve your intelligence (creativity, intuition) or your information?[6]  What would that even look like?

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FIGURE 1:

In the spirit of Aristotle and Nietzsche, I’ve nicknamed the data-integration algorithm-hub “VirtuAlly.”

FOOTNOTES:

[1] Also, the sentiment analysis engine in Muse is amateurish.

[2] The current discussion assumes that the capture, aggregation and integration of data would be for private and personal use only.  With increasing sousveillance, each of us may be able to compile an increasingly complete picture of our personal histories.  As technologies for personal data capture, aggregation, and integration progress, the following philosophical stance will also snowball in importance:  an individual’s data is his or her inalienable property.

[3] Temporality is a dimension common to each of the following data slices.  Each slice is like a layer of bedrock, and data archived in each aggregates many fossilized traces of one’s virtual life.  Time-stamps are common in each digital trace, making chronological sorting easy.  Who will standardize the aggregation and integration of these slices, as we once standardized the USB port?

[4] Lifenaut.com offers a digital (and biological!) time-capsule for would-be immortality-seekers.

[5] By condensation I mean something like summary, and by selection I roughly mean meme-discrimination.

[6] Arguably, neither is any good without the other, so my answer is “both.”

RECOMMENDED:

DATA AGGREGATION & VISUALIZATION INFO:

http://learning.blogs.nytimes.com/2012/02/07/what-story-does-your-personal-data-tell/#
What story does your data tell?

http://www.ted.com/talks/jer_thorp_make_data_more_human.html
New York Times data analyst on visualization

DATA COLLECTION & AGGREGATION TOOLS:

http://mobisocial.stanford.edu/muse/
Creates a slice of your personal history using your EMAIL, with capabilities for BROWSER HISTORY (best in Firefox).  The program runs securely on your local machine, so there’s no chance your data will make it to the cloud.  I’ve experimented with this program with interesting results.

https://openpaths.cc/
Capture your LOCATION DATA.

https://chrome.google.com/webstore/detail/gdfhmgiphpkoodfifkmiecmcmlmmhaip
Capture BROWSER HISTORY.  a friend of mine built this.

LIFE CASTING INFO:

http://en.wikipedia.org/wiki/Lifecasting_(video_stream)
http://www.justin.tv/

LIFE CASTING / DIGITAL AUTOBIOGRAPHY LOCKER TOOLS:

www.lifenaut.com
Interactive time capsule, digital self-storage space (digital locker)

https://www.lifenaut.com/learn-more-bio/
Also, they store your DNA…free (suggested donation $399)