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Why count on the brain for truth? posted on August 31, 2010
 General
Try this. Hold your thumb as far away as you can from your eye. That represents about one percent of your field of vision. When we see things, that's about the extent of our focus. The rest of the picture is supplied by schema that we fill in from our memory.
I was discussing this yesterday with Rich Carlson, a psychology professor at Penn State. He said that we have limited capacity for new sensory input. And much like a computer on narrow-band, we store a lot of cached information to round out the meager flows we process. That's why people often experience what they believe, instead of what they actually see or hear. And it's why when their brains are busy watching a basketball game and counting the passes between the players, they miss other phenomena. (see video below)
These things have been known for a while. But now, increasingly, we have sensors to back us up: security cameras, digital recorders. And as those machines take over the monitoring and measuring of physical reality, our own views and testimony will be discounted. Referees in professional sports are already experiencing this. The testimony of eye-witnesses in court, I'm sure, will also be taken ever more lightly as digital evidence piles up.
My question: Is this progress? Will the brain simply be regarded as an instrument of art, feelings and communication, and an unreliable witness or judge of what's happening in the world? Is this a good thing?
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Why trust Facebook with our history? posted on August 24, 2010
General
Scott Rosenberg discusses the digital records we leave of our day-to-day existence, and wonders why anyone would entrust them to Facebook. It's a good question. Many of us don't have the zeal of a Gordon Bell when it comes to monitoring and recording our lives. But we're recording big sections all the same, with our conversations, updates and photos. If that trove occurs on Facebook, how do we get our hands on it 10, 20 or 30 years from now?
You could ask the same question about many Web-based services, including e-mail accounts and photo services on Google, Yahoo and Microsoft. But I find my stuff lodged with those companies easier to search and retrieve. (The key, as Bell will tell you, is being able to search it, because the bits of data we're dying to find will be buried under mountains of stored junk.)
Facebook, though, will likely have a richer stream of data describing our lives, especially if its new "places" app takes off. It would seem to me that Facebook could build a niche business offering to archive personal datastreams for premium customers.
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Future of search: Verbs posted on August 23, 2010
Jeopardy book
"One of the "smartest things Bill Gates has ever said," according to Esther Dyson, came out at a private dinner a couple of years ago when he predicted that the future of Internet search was "verbs." The idea, Dyson writes, is that verbs give a search context:
To me, the meaning was clear: when people search, they aren't just
looking for nouns or information; they are looking for action. They
want to book a flight, reserve a table, buy a product, cure a hangover,
take a class, fix a leak, resolve an argument, or occasionally find a
person, for which Facebook is very handy. They mostly want to find
something in order to do something.
To turn search toward verbs, search engines must do a much better job of understanding human language. This is (and has long been) a key frontier for Artificial Intelligence, and is moving front-and-center in Internet search.
The point is not just to understand verbs in queries, as in the "company that Google acquired" as opposed to the "company Google competes with." Mastering verbs also requires the search engine to pick out this level of syntactic detail while crawling and indexing the Internet. In essense, it involves figuring out the meaning of online communication, and not just settling for key words, word combinations and the linking patterns to pages. For this, search companies will have to decode the relationships among verbs and objects in billions of online sentences and paragraphs. It's a ton of automated linguistic analysis.
This is the kind of analysis that IBM's Jeopardy-playing computer is attempting to carry out (though its trove of data is locally stored, and not online). Sometimes the job involves coming to grips with implicit messages, and providing a verb and/or noun that's not there. For example, if I write "I'm hungry," the verb, "to be," is meaningless. The computer has to turn that sentence into I (subject) desire (verb) food (object). Multiply this times a few million, and you get the idea of the challenge facing smarter search engines.
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Ning closures: a blow to Cialis posted on August 19, 2010
News
Back before President Obama was inaugurated, my colleague Peter
Elstrom and I came up with an idea for crowdsourcing a BusinessWeek
story. We'd launch a social network on Ning called BWInfrastructure, and the
community that gathered there would develop and debate ideas on how to
spend the trillion dollars of stimulus spending that was en route
We put up the site, scores of people signed up. It wasn't anywhere close
to the smash hit we were hoping for, but still. It gave us enough for
our crowd-sourced BusinessWeek
story.
After the story, I promptly forgot about the site. But this week I got
this email from Ning warning me that if I didn't pony up some
subscription fees they'd shut down the formerly free site. Ning wrote:
Your network has grown up a
bit since you started the ball rolling. You have grown to 4201 members who have collectively helped you add
unique photos, some
interesting videos, and 135 spirited
discussions. Well done!
4201 members? Here I had forgotten about the site, and it
apparently had taken off! Were there thousands of people on the site busy debating pressing
investment needs of the United States? I went and took a look at the
old place. I quickly saw that it had long since abandoned the focus
on infrastructure spending. The folks active there, if you can call them
that, are a bunch of bots spamming for Cialis, Tramadol and other
medications. They're blogging, signing up as members on the site. They
can't get enough of it. I checked out the member list, and saw hundreds of
them are there: Bon, Kros, Krek, Ganna, and
English-song-lyrics-download-03.
Spam, it seems, is a close cousin of entropy. We humans use
enormous energy to organize and structure information. But as soon as we
loosen our grip, spam flows in. It has no organizing principal, it
obeys no rules, recognizes no limits. The BWInfrastructure site will close down tomorrow, but In the long run, spam prevails.
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The coming privacy boom posted on August 17, 2010
Privacy
A piece I posted on SmartDataCollective last week:
A year ago, at a cover meeting at BusinessWeek, I
proposed a big story: The Privacy Pay-off. The idea was that tracking
and other data surveillance would spark a reaction: People would fear
for their privacy. And this would create all sorts of business
opportunities, the privacy pay-off.
It sounded like a plausible
idea to the editors. So I went off hunting for companies cashing in on
this expanding new market. I figured that certain advertisers would seek
competitive advantage by offering privacy guarantees. I hoped that at
least a couple would transform their privacy statements, changing them
from unreadable legalese into a clear and compelling promise. Someone,
somewhere had to be turning privacy statements into marketing tools.
I
also talked to the research divisions of major tech companies. They had
to be developing technology to help individuals manage and defend their
privacy in a data-driven world.
Long story short: I did lots of
research, and I never found the cover story. Sure, I picked up threads
of it. EMC's Mozy service, for example,
offers cloud-based data storage with military-grade encryption. It costs
more than, say, Google Docs. That's the privacy premium. Researchers at
Microsoft, HP and IBM were coming up with new filters and tools. I
learned about data records that "aged," vanishing after six months or a
year. That Viagra receipt you might not want marketers to see would go
poof. A hint of privacy pay-off? Perhaps.
This new market
requires awareness, and feeds on fear. Last week's Wall Street Journal series on
privacy, which carried some provocative headlines, provides a dose of
that. And now I see that others are pointing to the market potential for
privacy. Jeff Jarvis agrees with
me. Fred Wilson does too. Wilson, a
VC, holds investments in Twitter, Foursquare, and other start-ups built
on publicness (Jarvis' word). And yet Wilson says:
"There
are business opportunities in privacy-related services...The challenge
is to get someone [whether business or consumer] to pay $2-$10 dollars
per month to ensure that sort of premium privacy."
As I
researched my doomed story, I saw two mass-market data economies taking
shape. One, the free economy (embodied by Google), provides users with
near limitless services free of charge, and in return asks only for
their data. It gains intelligence from that data, which supports its
advertising business. The privacy policy in this free economy is simple:
Trust us.
The second (and far smaller) data economy is built upon
distrust. If you place your private data--your clickstream, your
finances, health records, kids pictures, your location, social
network--onto the networks, people will take advantage of you, harm you,
spill your secrets, steal from you. So pay a privacy premium and stay
safe. This is the policy companies have been following for decades, and
now outfits like Mozy are offering these services to individuals.
I'm
still grappling with the question of why the privacy payoff is taking
so long to materialize. I think it has a lot to do with two basic
factors. First, people tell pollsters they care about privacy. But they
also like free stuff and hate to pay premiums, especially in a down
economy. Second, despite all the fears about privacy, people have reason
to share lots of their data. Far beyond gossip, there's a value to it.
It connects people to friends, answers, insights, business
opportunities. For proof, look no further than the half billion folks on
Facebook, or at Fred Wilson's thriving portfolio. Even cookies serve a
useful function. (Erase them and you'll go crazy typing passwords to
visit Web sites.)
Yes, I still believe the privacy pay-off will
come. Turning privacy policies into marketing opportunities seems like a
no-brainer. Smart filters will sell. But given the power of the free
and public data economy, I suspect the privacy-wing will remain a niche
market. In BusinessWeek lingo, a six-column story, not a cover.
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Modeling the brain: Hardware's not the issue posted on August 16, 2010
Jeopardy book
If computing continues its exponential growth, within 15 years
the most powerful machines will be able to carry out 1020
calculations per second. Shane Legg, a theoretical
neuroscientist speaking at the Singularity Summit, put
that number into context yesterday. The estimate for all the grains of
sand on every beach in the world comes to between 1020 and
1021. These supercomputers of 2025 would be able to count each
grain (or presumably do more sophisticated work) in a single second.
That number also represents the total, Legg said, of every neuron in
every brain of every person on earth. Again, one machine, one second.
It's numbers like these that nourish the Singularity movement. Humans
tend to think in lines: The rate of change in the next 10 years will be
about the same as the last decade. But if you take into account
exponential growth in vital technologies, change is likely to be much
more abrupt. And some believe that when computers grow to surpass the
complexity of the human brain, we flesh-and-blood animals will pass the
evolutionary baton to intelligent machines.
But from what I'm learning, we already have machines powerful enough to
carry out highly intelligent thinking, and to simulate areas of human thought.
The problem is that we don't know how or what to teach them. It's a
software issue. And while hardware advances exponentially, software,
coded by humans, inches forward at a much slower rate. Conceivably, the
faster machines will pitch in on this project. For starters, they'll
produce detailed brain images and make it easier to run simulations.
But there's still a missing ingrediant to creating truly smart machines:
Intelligence. It should come, when it does, from humans. The
Singularity won't necessarily follow the chip-makers' timetable.
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Singularity: Is brain too complex to model? posted on August 15, 2010
Jeopardy book
We'd been through eight hours of lectures at the Singularity Summit, talks about the future of man-machine interfaces, anti-aging technology, human values in a post-human world. But it was at the end of a long and mind-taxing day that two scientists debated the fundamental question in artificial intelligence: Do we know enough about the brain to build machines that attempt to replicate it (or even parts of it?)
The skeptic was Dennis Bray, a Cambridge neuroscientist. He represented carbon-based intelligence, the kind that is carrying out extravagently complex tasks as you make sense of these words. For a half hour, he led us through the workings of a single cell, and discussed the mysteries that remain to be discovered. That's one cell. And the human brain has 100 billion neurons, each of them making uncounteded and poorly understood connections with others. Even the connections have modulations. It's a phenomenally complex network, and we've barely started to decode its workings. How, he argued, can we attempt to model machines on something we don't understand?
On the other side was Terrence Sejnowski, who heads the computational biology lab at the Salk Institute. To the sound of 2001 A Space Odyssey he showed a computer simulation of the release of a neural transmitter. He agreed with Bray that the complexity was daunting, but said that with the exponential growth of computing, and the learning that accompanies it, scientists would be able to model the brain. The transmitter, he said, was an early step. "We're taking it one step at a time." But he added that "even if the models are incomplete, they'll show us what's missing. Then we'll look for the missing pieces."
Will they find the missing pieces in time for the Singularity? That's the point, in about 2029, according to Ray Kurzweil, when computers should pass humans in intelligence. Well, if machines continue their march, they should increasingly help measure and model the workings of the brains that are building them. That's the exponential factor Sejnowski refers to. But listening to Bray, it became clear to me that no matter how much complexity we unravel, we'll always be confronted with more, much more.
The other question is whether the brain is the right model for computer. Early aviators studied birds. But it was a decidedly non-bird-like machine that finally led to the age of aviation. And the vessel that carried me from Newark to San Francisco two days ago was closer in its model of propulsion to an octopus than an eagle.
Heading back to the conference today. Just more thought about complexity. It's not only cells that are complex, but every moment in time. (And each cell evolves through time. Your brain has changed since you started reading this post.) In his poem, 1964, Jorge Luis Borges wrote: "Un instante cualquiera es mas profundo y diverso que el mar." (A single moment is deeper and more diverse than the sea.")
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Posterous DOS attack. Someone should write the story posted on August 12, 2010
News
I have a blog on Posterous, a very interesting and agile Web service. Just now I received an apologetic email from the company's CEO, Sachin Agarwal. He says that over the last six days, Posterous has been victimized by powerful Denial of Service Attacks. When the first one hit, last Wednesday, the Posterous team raced to move to new data centers. Another one hit on Friday. It was a crazy six days for Posterous. A tech leader named Vince, Agerwal writes, "worked like a mad man until he passed out on his desk."
Briefly, in 2002/03, I was acting info tech editor at BusinessWeek. If this were a Thursday night back then, I'd be preparing for Friday's story meeting, in which I'd propose a 4-column narrative on the Posterous attacks. Here's a very innovative and popular start-up, I'd argue, whose very existence was threatened by these attacks. (I still don't know where they came from.) It would make a great story. It would give us insights into the dangers surrounding us and a look at a start-up battling them.
But why, another editor would surely ask, should we care about Posterous? (Of course, if the editor in chief appeared to be interested in my story, that question might remain unasked. These meetings were exercises in Kremlinology.) In any case, I'd have to make a case for Posterous. Still, I hope someone somewhere is considering writing a story about it. I'm far too busy with my book to report the story. But it's one I'd like to read.
***
You might be wondering about my blog on Posterous. I started a BusinessWeek alumni network on Ning. When Ning demanded payment for what started out as a free site, I migrated all of the content to Posterous. I look at it not as an active blog, but as a private archive of BusinessWeek history.
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Goldblatt exhibit: Eyes on South Africa posted on August 10, 2010
General
| We finally got to the Jewish Museum in New York to see the David Goldblatt exhibit. He's a South African who photographed people in his country, white, black and "colored" alike, making their best efforts to live normal lives under apartheid, which created the most abnormal of circumstances. It's a wonderful exhibit if you get the chance.
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Jaron Lanier critiques IBM's Jeopardy challenge posted on August 9, 2010
Jeopardy book
Jaron Lanier,
the technologist and author who worries that we're getting carried away
with our machines, includes Watson, IBM's Jeopardy-playing computer, in
his latest broadside at the tech industry. Unfortunately, he
misinterprets the question-answering technology. In a long New York Times op-ed, he writes:
...I.B.M. scientists recently unveiled a “question answering” machine that
is designed to play the TV quiz show “Jeopardy.” Suppose I.B.M. had
dispensed with the theatrics, declared it had done Google one better
and come up with a new phrase-based search engine. This framing of
exactly the same technology would have gained I.B.M.’s team as much
(deserved) recognition as the claim of an artificial intelligence, but
would also have educated the public about how such a technology might
actually be used most effectively.
The challenge for a Jeopardy-playing computer is not simply to carry
out searches based on phrases. Google and other search engines already
do that, at least for simply phrased queries. Far beyond pointing toward Web pages, Watson must generate specific answers,
each with its own confidence ranking. This enables the computer to
calculate if it can risk a bet on the clue. It's a far more difficult
challenge than the one Lanier portrays.
That said, he raises interesting questions about the marketing of machine
"intelligence." His point, which he elaborated upon in his book, You Are Not a Gadget,
is that we're too often ceding our decision-making to machines and
"swarms" of online communities. By using Amazon
recommendations or software to compose a harmony line, Lanier says
we're abandoning the human brain--by far the most sophisticated known
work of circuitry in the universe. Instead, we're delegating this work
to far simpler algorithms.
The tech industry promotes this, he says, by branding technologies as
"intelligent" and comparing some of them to the brain. It often
anthropomorphiizes. This is where Watson comes in. Long before the Jeopardy challenge, IBM had a team of researchers working on Question-Answer technology. By channeling this research toward Jeopardy, the company was (and is) clearly looking for a branding opportunity. And by giving Watson a human name and voice, it anthropomorphizes the machine.
Is this a good thing? Well, putting a computer into a match against humans imposes a series of constraints that push researchers very hard. They must prepare the computer for long and confusing clues, and they have to design the system to come up with an answer it can bet on within three to five seconds. This advances the technology. (Whether or not this pays off commercially is still open to question.)
But let's assume that Watson and its kin race produce ever more sophisticated answers for us in coming years. Are we going to accept their responses as "truth" and our own judgments as something less than that? I don't think so. Watson is at its most fascinating and entertaining when it makes mistakes. It is when the machine is struggling or clueless that you most appreciate the astounding complexity of our language and the intricate web of connections in our minds.
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Cog psych yesterdy at Penn St. Try counting things w/out moving finger. You rock, nod, or tap foot,anything to create rhythm.
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The Wall Street Journal - John Derbyshire
Frankfurter Allgemeine Zeitung - Milos Vec
The Guardian (UK) - Steven Poole & Christopher Exeter
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