The World is built by people who dare to Imagine(!), and also, by people who love to learn and invent. My name is Valentin Voroshilov, and I am an expert in human intelligence, and also a natural human BS-decoder/meter. :) (like an every good teacher is). Thank you for visiting! Please, leave your comments or contact directly to VV.free.PHYSICS@gmail.com
For more info: www.GoMars.XYZ
Ask a scientist what makes science
so special, so effective, so powerful?
What makes science a science?
The top two answers are “data”, and “reason”.
A scientist believes that with the
right amount of data and with the right approach to analyze the data science can
Scientists generally believe that a
scientific approach can be applied to any natural phenomenon, to any social practice.
Well, except one.
Science cannot be used to provide a scientific
description of how scientists teach science.
When I say “cannot” I do not mean “impossible”,
I mean “restricted”.
A scientific approach to analyzing
how scientists teach science would require collection, accumulation, and analysis
of a large amount of data; a scientific approach would require collecting as
much data as possible because in science, no amount of data is ever enough –
one or two new facts may force the paradigm change (it happened!).
But take any college or a university
and check what data does administration collect on the teaching practices of
the faculty? All you find is the set of standard questions in the end-of-a-course
student evaluations. And that’s that.
Those evaluations serve two goals:
(1) to display that the college or university cares about the quality of
teaching (“See, we listen to our students!”); (2) to ensure that a faculty does
not stimulate in students a large amount of hatred toward the college (“Not
great at teaching, but OK”).
That is why all college and
university administrations limit the set of the questions in evaluations to the
bare minimum. Why bother if the answers do not make any difference, anyway?
Data coming from end-of-a-course evaluations are vague and limited. But they are data! Even they could have been used for some analysis. But they aren't. No comparison of any sort; a year to a year, faculty to faculty, a department to a department, a college to a college. Hence, there is no system in professional development of faculty. Of course, there is an official, or a faculty, or even a structural entity which purpose, supposedly, is helping faculty becoming better teachers. It regularly issues advises, links, or invites to talks. But no one assesses the impact of those actions in any way, and no one has a specific data-based strategy for professional development, so, in the end, it is just a facade ("See, we work on professional development of our faculty"). If no one analyses even that limited
data which comes from limited and vague evaluations, no one spends any energy
on designing more informative assessing techniques.
Could it be done?
Why it is not happening?
Because no one wants it – not administration,
not faculty, not students, not parents, not accreditation agencies, not the government,
Reason #2, of course, is that there are
only few faculty who are actually good at teaching and making this fact
official could shatter the system (reason #1 is that no one really cares about
the quality of teaching at a college or a university level if that is a
research college or a university; teaching practices at public or for-profit colleges
or universities are heavily guarded by local politicians or the owners).
Hence, there are faculty who are not
afraid of sharing their evaluations (here are mine).
Plus, there are faculty who could
share their evaluations anonymously (for the sake of science!).
If some college or a university would
start collecting and analyzing the data coming from those evaluations, it already
could lead to invaluable insights on the teaching practices at a college and a
university level. That could, in turn, lead to the improvement of the teaching
practices of more faculty; which would lead to more data, etc. A positive
feedback loop could eventually break the current restrictions self-imposed by
administrations on designing, collecting, analyzing, and sharing data on teaching
practices of faculty.
Who knows, maybe even teaching
practices of scientists teaching science could eventually become a science,
v. Imagination: what does a venture capitalist use?
Today (09/11/2018) on my way to work I was listening to an
interview with some representatives from “Catapult Ventures”.
At one point a question popped up in mine mind: can we call
a person “a visionary”, if that person only sees – according to him – what is
right around a corner?
After some consideration, I came to a conclusion that
venture capitalists do not need to be visionary.
Investing into what you see right around a corner doesn't
require a long vision (or even a long division).
An investor is like a person who keeps one foot in the
present (on a stable place) and uses another one to tap around to find the next
stable place to put the foot on it, and then repeats the process.
An investor does not know which investment will disrupt or
transform the current technology. An investor just hopes that one of those places
he or she tapped on may bring unexpectedly large return. But in order to invest
into anything, an investor first checks many variables to ensure the high
probability of a return, any return, so he or she would not lose any money, because
investing is never about disrupting the world, it is a business of making a profit,
based on the utilization of existing products and technologies for developing
new ones. Disrupting does happen sometimes, but just as a collateral positive
effect. In that case, everyone starts pretending that investing is not about a profit,
and an investor becomes a prophet. However, there are not many prophets in the
field of a venture capital. And the most famous prophets - like Steve Jobs - were
not even in that field.
It is not like Sergey Brin and Larry Page came to you and you wrote them
a check for a hundred grand just for an idea. That never happens in the venture
capital world. Remember the first motto of a venture capitalist? “Ideas are cheap!”
An idea is a seed, which needs to be planted and carefully nurtured. But
only when the hardest part is over, and one can see what fruits can one collect
relatively soon, only then a venture capitalist steps in.
That is why a venture capitalist never invests into basic/fundamental
science (unless it is some pet project, like searching for extraterrestrials or
landing on Mars).
In 1947 an invention was made without which no personal computers, no
cellphones, no Internet would exist. If was done by three researches working at
Bell Laboratories. They got the Nobel prize for their invention, but no single
venture capitalist supported their or similar research (to my best knowledge).
No venture capitalist could envision how a semiconductors-based transistor
could decades later give the birth to cellphones, tablets, etc.
To be fair, the field
of a venture capital is not the only one where ideas can be overlooked. It
happens in all human practices, including art (e.g. Vincent van Gogh), or
science (e.g. Thomas Young).
Maybe, some venture capitalist investing in AI could invest into the
development of a technology which could search for those promising but overlooked
ideas, artifacts, people? The main reason people like Steve Jobs become a prophet
is because they have imagination, which the majority of the investors, including
venture capitalist, do not have (and do not need).
One simply does not need imagination to make a choice about
something already seen right around a corner. One does not need to imagining
it, it is already seen! One can already see the most important details and weigh
the probability of the return. In most cases, an investor puts the money in an
already existing company, with a solid team, an existing product, structure, infrastructure,
and the clear financial streams. No imagination is required, but math; the company
is seen as an amplifier; if I put $X I should get back $X*K, where K > 1.
is needed to make a decision about something one cannot see. But placing
money into something one cannot see would not be an investment anymore, because
the return is not guaranteed, or even not expected.
In my opinion, today is the right day to talk about the role
He or she will have to accept the fact that the money spent
on this study will not represent an investment, because no one can predict if
there will any profitable outcome from it.
But in order to see how the study of imagination could boost
– something? if anything? – one has to have imagination. BTW: imagination usually goes (or not) hand-in-hand with a true genuine curiosity (but who has time for questions which will not bring any profit?).