Events I missed this week: Part 1

There were two events on my radar this week, but I couldn’t attend either of them. Sometimes I wish I could be in two places at once. Actually, I wish that all the time. At this point, I’d settle for more streaming video.

The first event that got me fired up was Nissam Taleb’s talk about his recent book, Black Swan, on Monday, 2/04/08 at the SALT. As I said, I wasn’t able to attend, but Steward Brand did send out a brief email summary, so I’m pretty fired up about listening/watching the talk in the days to come. Truth be told, I have not yet read Black Swan (only barely skimmed it), but I skimmed the good parts.

Here’s what Steward Brand said in the email following the talk, in all it’s CTRL-C and CTRL-V glory, if you didn’t receive the email yourself.

A ‘black swan,’ Taleb explained, is an event which is 1) Hard to predict; 2) Highly consequential; 3) Wrongly retro-predicted. We pretend we know why the big event happened, and so entrench our inability to deal with the next world-changing improbable event.

Examples: Viagra, 9/11, Harry Potter, First World War, Beatles, the PC, Google, and the rise of any successful religion. History is dominated by sudden, lasting changes wrought by deeply unexpected events.Part of the problem is that we ignore the ’silent evidence’ of the nonobserved and nonobservable. We compute probability from the success of survivors. No one writes or reads a book titled ‘How I Lost a Million Dollars.’ Another problem is that we revise our own predictions and intentions unconsciously to match what actually happens. We disguise having been wrong by pretending we were right. This is ‘confirmation bias.’

There are TWO kinds of randomness, two realms in which events happen…

Mediocristan is dominated by the average— one new observation won’t change much. If you are measuring the weight of a large sample of humans, adding the heaviest person in the world won’t change the result, whereas measuring the average wealth of a large sample of humans would be transformed by adding the wealthiest person. Mediocristan is the realm of the Law of Large Numbers and of the Gaussian Bell Curve.

Extremistan is dominated by extremes. Every year 16,000 books are published in English. A handful of best-sellers absolutely dominate. This is the realm of the power-law curve and the Long Tail. Extremistant defies prediction. You can say there will be a few monsters and lots of midgets and the world will be changed by the monsters, and that’s all you can say.

Benoit Mandelbrot convinced Taleb that the main dynamic of Mediocristan is energy, and the main dynamic of Extremistan is information. Anything social is Extremistan.

Thus there are two kinds of experts. A soufflé chef really is an expert and can be trusted. An economist is a pseudo-expert. “Never take advice from someone wearing a tie.” All you get from a Council of Economic Advisors is an illusion of control. Stock market analysts have proved to be worse than nothing.

Don’t focus on probability. Focus on consequences. Black Swans will come. Prepare against the negative ones; be ready to soar with the positive ones.

Pay attentive heed to tradition and old people— they have experienced more Black Swans.” –Stewart Brand

To be totally transparent, I am only part way through Taleb’s earlier book, Fooled by Randomness. Since I read several books at a time, going back and forth, I often don’t finish anything for several months, then finish several books at about the same time. I’m hoping to thwart this tendency and just crank through these. Taleb’s short narrative of the Ludic fallacy (yes, which I found on Wikipedia) is simultaneously hilarious and horrifying:

We love tangible, the confirmation, the palpable, the real, the visible, the concrete, the known, the seen, the vivid, the visual, the social, the embedded, the emotional laden, the salient, the stereotypical, the moving, the theatrical, the romanced, the cosmetic, the official, the scholarly-sounding verbiage (b******t), the pompous Gaussian economist, the mathematicized crap, the pomp, the Academie Francaise, Harvard Business School, the Nobel Prize, dark business suits with white shirts and Ferragamo ties, the moving discourse, and the lurid. Most of all we favor the narrated.

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Alas, we are not manufactured, in our current edition of the human race, to understand abstract matters – we need context. Randomness and uncertainty are abstractions. We respect what has happened, ignoring what could have happened. In other words, we are naturally shallow and superficial – and we do not know it. This is not a psychological problem; it comes from the main property of information. The dark side of the moon is harder to see; beaming light on it costs energy. In the same way, beaming light on the unseen is costly in both computational and mental effort.” –Nassim Nicholas Taleb

P.S. I do enjoy how “Nobel Prize” rhymes with”Ferragamo ties.”

 

Paul Saffo on Forecasting

Paul Saffo is a lauded forecaster and essayists on the future of technology. He’s part theorist, part historian, and part story teller. Saffo is associated with several prominent organizations, including Stanford University, Institute for the Future, and The Long Now Foundation. His talks and writings are consequential, timely, and refreshing. I am a big fan of his work and of The Long Now Foundation.

On January 11, 2008, Saffo spoke on “Embracing Uncertainty: The Secret to Effective Forecasting” at one of Long Now’s Seminars About Long Term Thinking. Having recently relocated to Boulder, Colorado from the San Francisco Bay Area, I wasn’t able to attend this live, but I did enjoy the audio repost and I’m looking forward to the video.

Saffo discussed several of the methods he uses in forecasting, which he also recently described in the Harvard Business Review article entitled “Six Rules for Effective Forecasting.” He started out by recalling one particular forecast he received from a friend some time ago which was supposedly from CNN, although Saffo was been unable to confirm it’s true source. The forecast read, “Hunt for Bin Laden: Experts Agree Al Qaeda Leader is Dead or Alive.” Saffo remarked that on the surface this was not a good forecast, being quite obvious, but in fact that is was actually a great forecast, because it accurately and completed captured the uncertainty of that moment. He said “The biggest mistake of a forecaster can make is being more certain than the facts suggest.” I suppose that assumes a high degree of confidence in the validity of our perceptions / beliefs, and a high degree of actual validity in those perceptions / beliefs, but that is an entirely separate nut to be cracked at another time.

Saffo said that “Uncertainty is not just an artifact of imperfect foresight. Uncertainty is intrinsic in the process and in my opinion, it is very good news. That’s good news because uncertainty is opportunity.”

I’ve pulled out some nuggets from his talk, but the crux of it was that uncertainty is everywhere and that forecasters must embrace it.

Embrace uncertainty

How does one embrace uncertainty? Saffo suggests that you must “map the cone of uncertainty” by taking an event and extending outwards from that event. It’s a cone shape because the degree of uncertainty increases over time. I know what the weather is like right now, I have lower confidence about what it will be like fifteen minutes from now, and I would have extremely low confidence in describing the weather in two weeks. This seems very obvious, and Saffo remarked that much of these forecasting best practices are common sense and so not terribly original. What’s important about the cone is not the shape, but how widely or narrowly it is drawn, and the difficulty one has in describing the edges. He went on to say, “The art of forecasting is understanding uncertainty and also balancing between a stance where if you look at things to narrowly, if you draw that cone to narrowly, you’re going to miss things that happen, if you draw it to broadly, you’re going to spend your whole time navel gazing around events that may never come to pass. The art, what makes forecasting hard, isn’t predicting the outcome. What makes forecasting hard is predicting the edges of the cone.”

Never mistake a clear view for a short distance

Saffo said that “things surprise us for a very simple reason and that is that change is never linear.” I think that Nissam Nicholas Taleb may argue that things surprise us for different reasons, but that too is for another time. Saffo suggested that effective forecasters are constantly looking for s-curves, the model of so many technologies and trends that we see today. An s-curve (sigmoid curve or logistic curve) is a model of the growth of something where growth begins slowly at first, then is characterized by an inflection point followed by exponential growth, followed later by slowing growth and finally zero growth. S-curves often stack on top of each other, which many believe results in a true acceleration of change. Saffo is skeptical of whether or now we are experiencing a true acceleration, but acknowledged the phenomenon of compounding s-curves, especially in technology.

“The future constantly arrives late and in unexpected ways.”

Saffo argued that most “overnight successes” are really ideas that are about 20 years old at the time of their success. He provided several examples, including the demise of LucasFilm’s Habitat and the successive failures of similar products which eventually lead to Second Life. He provided another example of the takeoff in web technologies resulting from how an oversupply of engineering talent in Silicon Valley following the failure of interactive TV in the early 90’s. He suggested that if you want a short term win in the market, look for something that has been failing for 20 years and everybody says will never happen – invest in that. “[Silicon valley] is built on the rubble of failure, not the spires of earlier success.”

Look for indicators and things that don’t fit

Saffo said the way you avoid being blindsided is to look for indicators. He mentioned research published in 1977 suggesting global climate change, Usenet newsgroups in 1984 discussing a software bug that would affect computers in the year 2000 (Y2K bug). He discussed the Roomba and how research showed that 2/3 of Roomba owners named theirs and 1/3 had taken them on vacation or to a friends house. These are indicators. IFTF calls them weak signals. The success of the 2007 DARPA Urban Grand Challenge at virtually the same time that a 108-car pileup occurred with human-drivers is another indicator. Saffo argued that forecasters should look for things that don’t make sense or are just really weird.

 

Saffo commented that Peter Schwartz, “a brilliant futurist, is fond of remarking that the difference between a good forecast and reality is that a good forecast has to be believable and internally consistent – and of course, reality labors under no such constraints.” The moral of the story is that it is important to look for wildcards. Saffo said that wildcards “test the edge of the cone” and “define the ragged edge of plausibility of any good forecast.” Several places to look for wildcards are in really bad forecasts, bad magazines, and science fiction.

Look Back Twice As Far As You’re Looking Forward

Historical observation can provide hints as to what may happen in the future. It’s not surprising that many of the best practitioners of foresight are historians. Saffo certainly is no exception. Saffo said that “a rear view mirror is a damn good forecasting tool if you use it in the right way… backsight is the secret to foresight… look back and random little indicators will suddenly line up into a very powerful beacon hinting at the future.”

Be indifferent

Separate your preferred future from the future that is most probable.

Assume you are wrong and forecast often

“Good forecasting is the inverse of traditional good research” where conclusions are reached only after carefully analysis of data. Instead, come to a conclusion early and set out to prove yourself wrong.

Additional Saffo quotes to enjoy:

• “Embrace uncertainty. In all of its complexity and gut-wrenching portent of change, uncertainty is our friend, uncertainty is opportunity.”
• “I don’t predict, I forecast, and that’s about mapping the cone of uncertainty.”
• “When change clusters at the extremes, it’s a certain bet that much more fundamental change lies ahead.”
• “We fail our way into the future.”
• “Wildcards sensitize us to surprise.”
• “Every decade or so, an enabling technology arrives that sets the entrepreneurial landscape.”

On Feb 4th, 2008, Nassim Nicholas Taleb will be speaking at The Long Now Foundation about his book Black Swan, which I am eagerly anticipating.