Interviews With The Fantastic
InterGalactic Interview With Ogi Ogas
by Randall Hayes
This month, another experiment--this time with an actual scientist! Meet Ogi Ogas, co-author of
Dark Horse: Achieving Success through the Pursuit of Fulfilment. He works with Todd Rose
at Harvard on The Dark Horse Project, which interviews people who have come to success
through their own unique pathways. These are considerably more detailed than those colorful
blurbs at the backs of SF novels, listing the crappy jobs we've apparently all endured on our way
to authorial eminence. Examples at the link above. Among Dr. Ogas's own colorful adventures
was a run on Who Wants to Be a Millionaire? which we did not discuss. The picture below
graces the Dark Horse website.
"I wanted to create a sculpture almost anyone, regardless of their background, could look at and
instantly recognize that it is about the idea of struggling to break free. This sculpture is about
the struggle for achievement of freedom through the creative process."
- Zenos Frudakis
Hayes: What's your research background, and how did you get interested in "the science of the
Ogas: My PhD is in computational neuroscience from Boston University's department of
cognitive and neural systems. I've always been deeply interested in the individuality of the human
mind--how the software (and hardware) of each person's brain is unique. I became interested in
the interdisciplinary science of individuality as I began to wonder what the individuality of the
human mind signified for the trajectory of one's life. I specifically got involved with the science of
individuality after I met Todd Rose and he invited me to join his Laboratory for the Science of
Hayes: You and Todd Rose (also founder of a public think tank called Populace) claim that the
Standardization Covenant--"follow the standard procedure and you'll be rewarded with
success"--is an almost accidental outgrowth of the Industrial Revolution. To me it sounds very
similar to what every hierarchical organization from Sumer on down always says: Trust us, we're
experts. We spoke to the gods. Was this just the same con, dressed up with new mathematical
gods? Or was it unique in some way?
Ogas: The Standardization Covenant certainly reflects a transaction fundamental to the
relationship between any government (or authority) and its citizens--abide by my rules, and we
will keep you safe and prosperous. But the Standardization Covenant contains a very specific
agreement characteristic of the Industrial Revolution in economics and normative thinking in the
human sciences: follow the standardized path based on the mathematical notions of averages,
types, and norms, and we will provide you with security and prosperity. This fundamental reliance
on statistical science is unique to the Industrial Age.
Hayes: It seems that at least through the 20th century, there's been consistent cultural pushback
against this idea of the average human as being some kind of ideal. The Beats, the 60s
counterculture, science fiction (I'm thinking in particular of Kurt Vonnegut's "Harrison
Bergeron," but there are many others). Standardization continued. How is this moment in history
different? What have you got that they didn't have?
Ogas: Resistance to the Standardization Covenant flowered in the 1960s, certainly, though it's
been around from the very start--Europeans were mocking the notion of "the average man" as
long ago as the 1850s--but what all of these rebels and dissidents lacked was an alternative. It's
not difficult to point out all the ways that standardization is oppressive; it's much harder to offer
something better, especially something with a better math and science. That's what changed: we
finally have the right kind of practical math, science, and technology to establish a viable social
compact that is better than the Standardization Covenant (which was also a much better social
contract than anything that came before).
Hayes: Isaac Asimov based his Foundation series and its future science of 'psychohistory' on
statistics. How was that different than what we would today call 'big data,' and how are both of
those different than what you're doing?
Ogas: Ironically, statistics, social science, and standardization were all born with the first eruption
of "big data"--in the early 19th century in Europe. That's when governments started collecting
data on everything they could; one historian called it an "avalanche of the printed number."
Getting more and more data is not revolutionary in itself; what's revolutionary is how you think
about and harness that data--whether you use it to develop a more detailed model of normality
(or optimality), or whether you use it to better understand each individual on their own terms.
You do need more data about individuals to make practical use of the methods and tools of the
science of individuality, but it's the way of thinking about individuals that's crucial, not the sheer
volume of data.
Hayes: As someone who has taught college courses of 75+ people, and who tried customizing a
nonmajors biology course at least to the level of the 11 or so different majors who were taking
it--from accounting to journalism to nursing--it was really hard, and it didn't work that well. The
students pushed back as though it was unfair to customize ("His work is easier than mine!"). Do
you customize your own courses? How?
Ogas: Implementing personalized learning in an effective and affordable manner is an enormous
challenge, no doubt. By definition, there will never be "best practices" or a "gold standard" when
it comes to establishing a personalized learning system--it will always be highly dependent on
local conditions: the specific material to be taught, the aims of the specific institution, the available
infrastructure and budget, and of course the specific students. A number of educational
institutions have implemented reasonably successful personalized learning programs, and they
each look different--such as Western Governor's University, Southern New Hampshire
University, and Summit Learning (K-12). One thing that makes the transition so difficult is that
it's usually hard to move from a standardized pedagogical system to a personalized system in
incremental steps--it usually demands numerous major changes in everything from textbooks to
billing. Not many institutions are set up to make such a drastic change. That's probably why we
see the greatest innovators coming from institutions getting built from scratch (rather than
transitioning), or from institutions that were sort of on the margins and have little to lose from
trying something radically different. I could be wrong, but I'd be willing to bet the Ivy League
schools will be the last to adopt personalized learning, because what's their motivation?
Hayes: I really appreciated your discussion of "quotacracy," and how letting in the same
predetermined number of people every year, regardless of people's actual scores on entrance
exams, undermines the very idea of objective standards. Have you ever read anything about how
IQ scales have been adjusted as the 20th century went on? Were humans getting smarter, due to
better nutrition and such (some estimates were that iodized salt raised IQ by 15 points in deficient
areas), or were schools just getting better at teaching to the tests?
Ogas: "Were humans actually getting smarter" is a poorly formulated question to begin with, like
asking what color is justice, and it's even more pointless if you're asking it because of changing IQ
scores. Intelligence is a complex adaptive system (i.e., non-linear, holistic, sensitive to initial
conditions, contextual, etc.) which means that statistics don't apply, at least, not in any way that's
useful for thinking about intelligence. It's like trying to compare LeBron James to Bill
Russell--when Russell played, there were fewer teams, salaries were a tiny fraction of what they
are today, there were no 3-point shots, fouls were called much differently. Our minds instinctively
imagine that there's some essential quality we call "basketball talent" that we can divorce from all
the messy details of playing real games in the real world, but that's silly. And mathematically
Hayes: Dark Horse mentions nonlinear dynamical models as being better than statistical
models but doesn't offer any details (maybe that's in The End of Average, which I haven't read).
What behavioral variables are you actually modeling, and how do you go about doing it, when
your studies appear to be based on qualitative personal interviews? Where would an interested SF
author--maybe one not terribly well versed in mathematics--learn more?
Ogas: Yeah, it's a huge problem that there are not really any great popular books about systems
thinking. (I'm working on one right now, as a matter of fact, but we'll see if I can sell it.) The best
I've come across is Thinking in Systems, by Donella Meadows, which is an accessible
introduction. There are a lot of good, accessible books about complexity theory that contain
discussions of complex systems that can be understood by readers without a strong math
background. I like Complexity: A Guided Tour, by Melanie Mitchell.
Hayes: Let's say you get your way, and the Standardization Covenant is finally broken. What
does the world look like? What changes? Have you ever thought about using SF to illustrate what
that new world might look like? NSF has funded such outreach projects before. In fact, they now
require some kind of outreach projects in all their research grants.
Ogas: I think our world is already moving away from the Standardization Covenant, in fits and
starts. The Internet is a huge contributor. There are more universities and schools that implement
personalized learning, as I mentioned. More and more employers are abandoning standardized
approaches to hiring and management, and adopting personalizing hiring and management
systems (Morning Star is a classic example, and particularly interesting because it's in one of the
most old-school standardized factory industries around, food processing).
I think this is the only way that democratic societies will be able to regain and maintain a
competitive economic and cultural edge over authoritarian societies like China--any country with
an educational and economic system based upon the Standardization Covenant will always be
outcompeted by one that uses a personalized (Dark Horse) covenant--that uses personalization
throughout its systems, because personalization always maximizes the productivity, innovation,
and engagement of its students and workers, whereas standardization always has an artificially
low ceiling. The only way an authoritarian society like Russia or China will be able to compete
with a truly personalized democratic society would be to become democratic and personalized.
Hayes: Maybe on long time scales, if the system can reach some kind of equilibrium. The history
of agriculture and languages might argue otherwise. But those are topics for another day.
Thanks so much for your time.
If you think you or someone you know fit the criteria to be a Dark Horse, you can nominate that
person to be interviewed by e-mailing Dr. Ogas.
"THE YEAR WAS 2081, and everybody was finally equal."
Special issue on how "average thinking" seeped into worldwide culture.
And are we now getting dumber?
Nonfiction stories about "essential quality" thinking and how it gets us in trouble.
Perhaps not coincidentally, something I wrote about just last month.
Because those highly variable societies are being standardized out of existence.
As are their languages.