WEBVTT
00:00:00.000 --> 00:00:14.294
rC3 preroll music
00:00:14.294 --> 00:00:18.950
Herald: Welcome with me with a big round
of applause in your living room or
00:00:18.950 --> 00:00:25.970
wherever you are derJoram. derJoram is a
science communicator. He got his
00:00:25.970 --> 00:00:31.160
University education and his first
scientific experience at Max Planck
00:00:31.160 --> 00:00:38.570
Institute. And he will give you now a
crash course for beginners to have the
00:00:38.570 --> 00:00:44.850
best insight into the scientific method
and to distinguish science from rubbish.
00:00:44.850 --> 00:01:03.542
derJoram, the stage is yours.
00:01:03.542 --> 00:01:07.980
derJoram: Hi, nice to have you here. My name
is Joram Schwartzmann and I'm a plant
00:01:07.980 --> 00:01:12.830
biologist. And today I want to talk about
science. I have worked in research for
00:01:12.830 --> 00:01:18.810
many years, first during my diploma thesis
and then during my doctoral research. I've
00:01:18.810 --> 00:01:22.280
worked both in Universities and at the Max
Planck Institute. So I got pretty good
00:01:22.280 --> 00:01:27.150
insights into the way these structures
work. After my PhD, I left the research
00:01:27.150 --> 00:01:31.869
career to instead talk about science,
which is also what I'm about to do today.
00:01:31.869 --> 00:01:36.710
I am working now in science communication,
both as a job and in my spare time, when I
00:01:36.710 --> 00:01:41.070
write about molecular plant research
online. Today, I will only mention plants
00:01:41.070 --> 00:01:45.350
a tiny bit because the topic is a
different one. Today though, we are
00:01:45.350 --> 00:01:49.590
talking about science literacy. So
basically, how does the scientific system
00:01:49.590 --> 00:01:53.430
work? How do you read scientific
information and which information can you
00:01:53.430 --> 00:02:00.179
trust? Science. It's kind of a big topic.
Before we start, it's time for some
00:02:00.179 --> 00:02:04.970
disclaimers: I am a plant biologist. I
know stuff about STEM research that is
00:02:04.970 --> 00:02:09.289
science, technology, engineering and
mathematics. But there's so much more
00:02:09.289 --> 00:02:13.920
other science out there. Social science
and humanities share many core concepts
00:02:13.920 --> 00:02:19.019
with natural sciences, but have also many
approaches that are unique to them. I
00:02:19.019 --> 00:02:21.840
don't know a lot about the way these
works, so please forgive me if I stick
00:02:21.840 --> 00:02:26.900
close to what I know, which is STEM
research. Talking about science is also
00:02:26.900 --> 00:02:31.230
much less precise than doing the science.
For pretty much everything that I'll bring
00:02:31.230 --> 00:02:35.389
up today there is an example where it is
completely different. So if in your
00:02:35.389 --> 00:02:39.709
country, field of research or experience
something is different, we're probably
00:02:39.709 --> 00:02:44.120
both right about whatever we're talking.
With that out of the way, let's look at
00:02:44.120 --> 00:02:48.629
the things that make science science.
There are three parts of science that are
00:02:48.629 --> 00:02:53.319
connected. The first one is the scientific
system. This is the way science is done.
00:02:53.319 --> 00:02:56.559
Next up, we have people, who do the
science. The scientific term for them is
00:02:56.559 --> 00:03:00.819
researchers. We want to look at how you
become a researcher, how researchers
00:03:00.819 --> 00:03:06.659
introduce biases and how they pick their
volcanic layer to do evil science.
00:03:06.659 --> 00:03:11.230
Finally, there are publications and this
is the front end of science, the stuff we
00:03:11.230 --> 00:03:15.249
look at most of the time when we look at
science. There are several different kinds
00:03:15.249 --> 00:03:20.480
and not all of them are equally
trustworthy. Let's begin with the
00:03:20.480 --> 00:03:26.299
scientific system. We just don't do
science, we do science systematically.
00:03:26.299 --> 00:03:30.069
Since the first people tried to understand
the world around them, we have developed a
00:03:30.069 --> 00:03:34.809
complex system for science. At the core of
that is the scientific method. The
00:03:34.809 --> 00:03:39.339
scientific method gives us structure and
tools to do science. Without it, we end up
00:03:39.339 --> 00:03:43.839
in the realm of guesswork, anecdotes and
false conclusions. Here are some of my
00:03:43.839 --> 00:03:47.859
favorite things that were believed before
the scientific method became standard.
00:03:47.859 --> 00:03:54.230
Gentlemen could not transmit disease. Mice
are created from grain and cloth. Blood is
00:03:54.230 --> 00:03:59.906
exclusively produced by the liver. Heart
shaped plants are good for the heart. But
00:03:59.906 --> 00:04:03.219
thanks to the scientific method, we have a
system that allows us to make confident
00:04:03.219 --> 00:04:07.760
judgment on our observations. Let's use an
example. This year has aged me
00:04:07.760 --> 00:04:13.349
significantly and so as a newly formed old
person, I have pansies on my balcony. I
00:04:13.349 --> 00:04:17.450
have blue ones and yellow ones, and in
summer I can see bees buzz around the
00:04:17.450 --> 00:04:21.740
flowers. I have a feeling, though, that
they like the yellow ones better. That
00:04:21.740 --> 00:04:25.889
right there is an observation. I now think
to myself I wonder if they prefer the
00:04:25.889 --> 00:04:31.702
yellow flowers over the blue ones based on
the color and this is my hypothesis. The
00:04:31.702 --> 00:04:36.747
point of a hypothesis is to test it so I
can accept it or reject it later. So I
00:04:36.747 --> 00:04:40.419
come up with a test. I count all bees that
land on yellow flowers and on blue flowers
00:04:40.419 --> 00:04:45.840
within a weekend. That is my experiment.
So I sit there all weekend with one of
00:04:45.840 --> 00:04:49.819
these clicky things in each hand and count
the bees on the flowers. Every time a bee
00:04:49.819 --> 00:04:54.189
lands on a flower, I click. click, click,
click, click, click. It's the most fun I
00:04:54.189 --> 00:04:59.930
had all summer. In the end, I look at my
numbers. These are my results. I saw sixty
00:04:59.930 --> 00:05:03.700
four bees on the yellow flowers and twenty
seven on the blue flowers. Based on my
00:05:03.700 --> 00:05:09.109
experiment I conclude that bees prefer
yellow pansies over blue ones. I can now
00:05:09.109 --> 00:05:14.139
return and accept my hypothesis. Bees do
prefer yellow flowers over blue ones.
00:05:14.139 --> 00:05:18.259
Based on that experiment I made a new
observation and can now make a new
00:05:18.259 --> 00:05:22.860
hypothesis: do other insects follow the
same behavior? And so I sat there again
00:05:22.860 --> 00:05:28.807
next weekend, counting all hoverflies on
my pansies. Happy days. The scientists in
00:05:28.807 --> 00:05:33.910
the audience are probably screaming by
now. I am, too, but on the inside. My
00:05:33.910 --> 00:05:38.340
little experiment and the conclusions I
did were flawed. First up, I didn't do any
00:05:38.340 --> 00:05:43.689
controls apart from yellow versus blue.
What about time? Do the days or seasons
00:05:43.689 --> 00:05:48.240
matter? Maybe I picked up the one time
period when bees actually do prefer yellow
00:05:48.240 --> 00:05:52.419
but on most other days they like blue
better? And then I didn't control for
00:05:52.419 --> 00:05:56.469
position. Maybe the blue ones get less
sunlight and are less warm and so a good
00:05:56.469 --> 00:06:00.909
control would have been to swap the pots
around. I also said I wanted to test
00:06:00.909 --> 00:06:05.009
color. Another good control would have
been to put up a cardboard cutout of a
00:06:05.009 --> 00:06:09.199
flower in blue and yellow and see whether
it is the color or maybe another factor
00:06:09.199 --> 00:06:14.389
that attracts the bees. And then I only
counted once. I put the two data points
00:06:14.389 --> 00:06:17.639
into an online statistical calculator and
when I had calculated it, it told me I had
00:06:17.639 --> 00:06:21.380
internet connectivity problems. So I
busted out my old textbook about
00:06:21.380 --> 00:06:25.060
statistics. And as it turns out, you need
repetitions of your experiment to do
00:06:25.060 --> 00:06:29.570
statistics and without statistics, you
can't be sure of anything. If you want to
00:06:29.570 --> 00:06:33.389
know whether what you measure is random or
truly different between your two
00:06:33.389 --> 00:06:37.270
conditions, you do a statistical test that
tells you with what probability your
00:06:37.270 --> 00:06:42.340
result could be random. That is called a
P-value. You want that number to be low.
00:06:42.340 --> 00:06:46.629
In biology, we're happy with a chance of
one in twenty. So five percent that the
00:06:46.629 --> 00:06:50.870
difference we observe between two
measurements happened by chance. In high
00:06:50.870 --> 00:06:54.760
energy particle physics, that chance of
seeing a random effect is 1:3.500.000
00:06:54.760 --> 00:07:00.780
or 0.00003%. So without
statistics, you can never be sure whether
00:07:00.780 --> 00:07:06.421
you observe something important or just
two numbers that look different. A good
00:07:06.421 --> 00:07:10.310
way to do science is to do an experiment a
couple of times, three at least, and then
00:07:10.310 --> 00:07:14.710
repeat it with controls again at least
three times. With a bigger data set, I
00:07:14.710 --> 00:07:19.009
could actually make an observation that
holds significance. So why do I tell you
00:07:19.009 --> 00:07:22.819
all of this? You want to know how to
understand science not how to do it
00:07:22.819 --> 00:07:27.009
yourself? Well, as it turns out, controls
and repetitions are also a critical point
00:07:27.009 --> 00:07:30.779
to check when you read about scientific
results. Often enough cool findings are
00:07:30.779 --> 00:07:34.659
based on experiments that didn't control
for certain things or that are based on
00:07:34.659 --> 00:07:38.819
very low numbers of repetitions. You have
to be careful with conclusions from these
00:07:38.819 --> 00:07:43.580
experiments as they might be wrong. So
when you read about science, look for
00:07:43.580 --> 00:07:47.169
science that they followed the scientific
method like a clearly stated hypothesis,
00:07:47.169 --> 00:07:53.439
experiments with proper controls and
enough repetitions to do solid statistics.
00:07:53.439 --> 00:07:56.730
It seems like an obvious improvement for
the scientific system to just do more
00:07:56.730 --> 00:08:01.490
repetitions. Well, there is a problem with
that. Often experiments require the
00:08:01.490 --> 00:08:05.180
researchers to break things. Maybe just
because you take the things out of their
00:08:05.180 --> 00:08:08.460
environment and into your lab, maybe
because you can only study it when it's
00:08:08.460 --> 00:08:13.379
broken. And as it turns out, not all
things can be broken easily. Let me
00:08:13.379 --> 00:08:18.483
introduce you to my scale of how easy it
is to break the thing you study. All the
00:08:18.483 --> 00:08:22.490
way to the left, you have things like
particle physics. It's easy to break
00:08:22.490 --> 00:08:26.340
particles. All you need is a big ring and
some spare electrons you put in there
00:08:26.340 --> 00:08:30.020
really, really fast. Once you have these
two basic things, you can break millions
00:08:30.020 --> 00:08:33.690
of particles and measure what happens so
you can calculate really good statistics
00:08:33.690 --> 00:08:38.314
on them. Then you have other areas of
physics. In material science. the only
00:08:38.314 --> 00:08:42.750
thing that stops you from testing how hard
a rock is, is the price of your rock.
00:08:42.750 --> 00:08:47.632
Again, that makes us quite confident in
the material properties of things. Now we
00:08:47.632 --> 00:08:53.589
enter the realm of biology. Biology is
less precise because living things are not
00:08:53.589 --> 00:08:58.550
all the same. If you take two bacterial
cells of the same species, they might
00:08:58.550 --> 00:09:02.800
still be slightly different in their
genome. But luckily we can break millions
00:09:02.800 --> 00:09:08.280
of bacteria and other microbes without
running into ethical dilemmas. We even ask
00:09:08.280 --> 00:09:12.190
researchers to become better at killing
microbes. So doing more of the experiment
00:09:12.190 --> 00:09:16.839
is easier when working with microbes. It
gets harder, though, with bigger and more
00:09:16.839 --> 00:09:22.085
complex organisms. Want to break plants in
a greenhouse or in a field? As long as you
00:09:22.085 --> 00:09:26.466
have the space, you can break thousands of
them for science and no one minds. How
00:09:26.466 --> 00:09:29.800
about animals like fish and mice and
monkeys? There it gets much more
00:09:29.800 --> 00:09:33.920
complicated very quickly. While we are
happy to kill thousands of pigs every day
00:09:33.920 --> 00:09:37.630
for sausages, we feel much less
comfortable doing the same for science.
00:09:37.630 --> 00:09:41.854
And it's not a bad thing when we try to
reduce harm to animals. So while you
00:09:41.854 --> 00:09:46.300
absolutely can do repetitions and controls
and animal testing, you usually are
00:09:46.300 --> 00:09:50.902
limited by the number of animals you can
break for science. And then we come to
00:09:50.902 --> 00:09:55.420
human biology. If you thought it was hard
doing lots of repetitions and controls in
00:09:55.420 --> 00:09:59.590
animals, try doing that in humans. You
can't grow a human on a corn sugar based
00:09:59.590 --> 00:10:03.910
diet just to see what would happen. You
can't grow humans in isolation and you
00:10:03.910 --> 00:10:08.619
can't breed humans to make more cancer as
a control in your cancer experiment. So
00:10:08.619 --> 00:10:11.560
with anything that involves science in
humans, we have to have very clever
00:10:11.560 --> 00:10:15.379
experiment design to control for all the
things that we can't control. The other
00:10:15.379 --> 00:10:18.320
way to do science on humans, of course, is
to be a genetic life form and disk-
00:10:18.320 --> 00:10:24.060
operating system. What this scale tells us
is how careful we have to be with
00:10:24.060 --> 00:10:28.040
conclusions from any of these research
areas. We have to apply a much higher
00:10:28.040 --> 00:10:32.690
skepticism when looking at single studies
on human food than when we study how hard
00:10:32.690 --> 00:10:36.650
a rock is. If I'm interested in stuff on
the right end of the spectrum, I'd rather
00:10:36.650 --> 00:10:40.519
see a couple of studies pointing at a
conclusion. Whereas the further I get to
00:10:40.519 --> 00:10:44.769
the left hand side, the more I trust
single studies. That still doesn't mean
00:10:44.769 --> 00:10:50.510
that there can't be mistakes in particle
physics, but I hope you get the idea. Back
00:10:50.510 --> 00:10:55.279
to the scientific method. Because it is
circular, it is never done, and so is
00:10:55.279 --> 00:10:59.180
science. We can always uncover more
details, look at related things and refine
00:10:59.180 --> 00:11:04.182
our understanding. There's no field where
we could ever say: Ok, let's pack up. We
00:11:04.182 --> 00:11:09.320
know now everything. Good job, everyone -
the science has been completely done.
00:11:09.320 --> 00:11:13.120
Everything in science can be potentially
overturned. Nothing is set in stone.
00:11:13.120 --> 00:11:18.430
However, and it's a big however, it's not
likely that this happens for most things.
00:11:18.430 --> 00:11:21.700
Most things have been shown so often that
the chance that we will find out that
00:11:21.700 --> 00:11:25.490
water actually boils at 250 degrees
centigrade at sea level and normal
00:11:25.490 --> 00:11:30.510
pressure is close to zero. But if
researchers would be able to show that
00:11:30.510 --> 00:11:35.170
strange behavior of water, it is in the
nature of science to include that result
00:11:35.170 --> 00:11:39.610
in our understanding. Even if that breaks
some other ideas that we have about the
00:11:39.610 --> 00:11:44.510
world. That is what sets science apart
from dogma. New evidence is not frowned
00:11:44.510 --> 00:11:48.570
upon and rejected, but welcomed and
integrated into our current understanding
00:11:48.570 --> 00:11:55.045
of the world. Enough about a scientific
system. Let's talk about scientists. You
00:11:55.045 --> 00:11:59.368
might be surprised to hear, but most
researchers are actually people. Other
00:11:59.368 --> 00:12:02.569
people, who are not researchers tend to
forget that, especially when they talk
00:12:02.569 --> 00:12:07.270
about the science that the researchers do.
That goes both ways. There are some that
00:12:07.270 --> 00:12:11.290
believe in the absolute objective truth of
science. Ignoring all influence
00:12:11.290 --> 00:12:15.899
researchers have on the data. And there
are others, who say that science is lying
00:12:15.899 --> 00:12:20.683
about things like vaccinations, climate
change or infectious diseases. Both groups
00:12:20.683 --> 00:12:26.410
are wrong. Researchers are not infallible
demigods that eat nature and poop wisdom.
00:12:26.410 --> 00:12:31.120
They're also not conspiring to bring harm
to society in search for personal gain.
00:12:31.120 --> 00:12:35.019
Trust me. I know people, who work in
pesticide research, they're as miserable
00:12:35.019 --> 00:12:39.660
as any other researcher. Researchers are
people. And so they have thoughts and
00:12:39.660 --> 00:12:44.977
ideas and wishes and biases and faults and
good intentions. Most people don't want to
00:12:44.977 --> 00:12:49.733
do bad things and inflict harm on others
and so do researchers. They aim to do good
00:12:49.733 --> 00:12:55.540
things and make lives of people better.
The problem with researchers being people
00:12:55.540 --> 00:13:00.279
is that they are also flawed. We all have
cognitive biases that shape the way we
00:13:00.279 --> 00:13:04.339
perceive and think about the world. And in
science, there's a whole list of biases
00:13:04.339 --> 00:13:08.681
that affect the way we gather data and
draw conclusions from it. Luckily, there
00:13:08.681 --> 00:13:13.810
are ways to deal with most biases. We have
to be aware of them, address them and
00:13:13.810 --> 00:13:20.709
change our behavior to avoid them. What we
can't do is deny their impact on research.
00:13:20.709 --> 00:13:24.800
Another issue is diversity. Whenever you
put a group of similar people together,
00:13:24.800 --> 00:13:28.730
they will only come up with ideas that fit
within their group. That's why it is a
00:13:28.730 --> 00:13:33.800
problem when only white men are dominating
research leadership positions. Hold on.
00:13:33.800 --> 00:13:39.209
Some of you might shout. These men are
men of science. They are objective. They
00:13:39.209 --> 00:13:44.069
use the scientific method. We don't need
diversity. We need smart people. To which
00:13:44.069 --> 00:13:50.190
I answer: ugghhh. Here is a story for
you. For more than 150 years, researchers
00:13:50.190 --> 00:13:54.490
believed that only male birds are singing.
It fits the simple idea that male birds do
00:13:54.490 --> 00:13:59.329
all the mating rituals and stuff, so they
must be the singers. Just like in humans,
00:13:59.329 --> 00:14:03.019
female birds were believed to just sit and
listen while the men shout at each other.
00:14:03.019 --> 00:14:07.870
In the last 20 years, this idea was
debunked. New research found that also
00:14:07.870 --> 00:14:13.980
female birds sing. So how did we miss that
for so long? Another study on the studies
00:14:13.980 --> 00:14:17.240
found that during these 20 years that
overturned the dogma of male singing
00:14:17.240 --> 00:14:22.649
birds, the researchers changed. Suddenly,
more women took part in research and
00:14:22.649 --> 00:14:27.404
research happened in more parts of the
world. Previously, mostly men in U.S.,
00:14:27.404 --> 00:14:31.780
Canada, England and Germany were studying
singing birds in their countries. As a
00:14:31.780 --> 00:14:35.550
result, they subconsciously introduced
their own biases and ideas into the work.
00:14:35.550 --> 00:14:40.851
And so we believe for a long time that
female birds keep their beaks shut. Only
00:14:40.851 --> 00:14:46.217
when the group of researchers diversified,
we got new and better results. The male
00:14:46.217 --> 00:14:50.226
researchers didn't ignore the female
songbirds out of bad faith. The men were
00:14:50.226 --> 00:14:53.701
shaped by their environment but they
didn't want to do bad things. They just
00:14:53.701 --> 00:14:56.889
happened to oversee something that someone
with a different background would pick up
00:14:56.889 --> 00:15:02.190
on. What does this tell us about science?
It tells us that science is influenced
00:15:02.190 --> 00:15:06.490
consciously or subconsciously by internal
biases. When we talk about scientific
00:15:06.490 --> 00:15:10.930
results we need to take that into account.
Especially in studies regarding human
00:15:10.930 --> 00:15:14.810
behavior. We have to be very careful about
experiment design, framing and
00:15:14.810 --> 00:15:18.990
interpretation of results. If you read
about science that makes bold claims about
00:15:18.990 --> 00:15:23.250
the way we should work, interact or
communicate in society that science is
00:15:23.250 --> 00:15:26.940
prone to be shaped by bias and you should
be very careful when drawing conclusions
00:15:26.940 --> 00:15:31.279
from it. I personally would rather wait
for several studies pointing in a similar
00:15:31.279 --> 00:15:35.829
direction before I draw major conclusions.
I linked to a story about a publication
00:15:35.829 --> 00:15:39.600
about the influence of female mentors on
career success and it was criticized for a
00:15:39.600 --> 00:15:46.889
couple of these biases. If we want to
understand science better, we also have to
00:15:46.889 --> 00:15:50.980
look at how someone becomes a scientist
and I mean that in a sense of professional
00:15:50.980 --> 00:15:54.740
career. Technically, everybody is a
scientist as soon as they test a
00:15:54.740 --> 00:15:58.890
hypothesis, observe the outcome and
repeat. But unfortunately, most of us are
00:15:58.890 --> 00:16:03.299
not paid for the tiny experiments during
our day to day life. If you want to become
00:16:03.299 --> 00:16:08.310
a scientist, you usually start by entering
academia. Academia is the world of
00:16:08.310 --> 00:16:12.000
Universities, Colleges and research
institutes. There is a lot of science done
00:16:12.000 --> 00:16:16.740
outside of academia, like in research and
development in industry or by individuals
00:16:16.740 --> 00:16:21.029
taking part in DIY science. As these
groups rarely enter the spotlight of
00:16:21.029 --> 00:16:26.709
public attention, I will ignore them
today. Sorry. So this is a typical STEM
00:16:26.709 --> 00:16:31.240
career path. You begin as a Bachelor's or
Master's student. You work for something
00:16:31.240 --> 00:16:35.549
between three months and a year and then
wohoo you get a degree. From here you
00:16:35.549 --> 00:16:39.689
can leave, go into the industry, be a
scientific researcher at a University or
00:16:39.689 --> 00:16:44.709
you continue your education. If you
continue, you're most likely to do a PhD.
00:16:44.709 --> 00:16:47.649
But before you can select one of the
exciting options on a form when you order
00:16:47.649 --> 00:16:51.889
your food, you have to do research. For
three to six years, depending on where you
00:16:51.889 --> 00:16:56.660
do your PhD, you work on a project and
most likely will not have a great time.
00:16:56.660 --> 00:17:00.959
You finish with your degree and some
publications. A lot of people leave now
00:17:00.959 --> 00:17:05.810
but if you stay in research, you'll become
a postdoc. The word postdoc comes from the
00:17:05.810 --> 00:17:09.800
word "doc" as in doctorate and "post" as
in you have to post a lot of application
00:17:09.800 --> 00:17:18.050
letters to get a job. Postdocs do more
research, often on broader topics. They
00:17:18.050 --> 00:17:21.910
supervise PhD students and are usually
pretty knowledgeable about their research
00:17:21.910 --> 00:17:26.432
field. They work and write papers until
one of two things happen. The German
00:17:26.432 --> 00:17:30.150
Wissenschaftszeitvertragsgesetz bites them
in the butt and they get no more contract
00:17:30.150 --> 00:17:34.730
or they move on to become a group leader
or professor. Being a professor is great.
00:17:34.730 --> 00:17:37.770
You have a permanent research position,
you get to supervise and you get to talk
00:17:37.770 --> 00:17:42.260
to many cool other researchers. You
probably know a lot by now, not only about
00:17:42.260 --> 00:17:46.530
your field but also many other fields in
your part of science as you constantly go
00:17:46.530 --> 00:17:50.910
to conferences because they have good food
and also people are talking about science.
00:17:50.910 --> 00:17:55.870
Downside is, you're probably not doing any
experiments yourself anymore. You have
00:17:55.870 --> 00:18:01.010
postdocs and PhD students, who do that for
you. If you want to go into science,
00:18:01.010 --> 00:18:04.740
please have a look at this. What looks
like terrible city planning is actually
00:18:04.740 --> 00:18:09.190
terrible career planning as less than one
percent of PhDs will ever reach the level
00:18:09.190 --> 00:18:13.940
of professor, also known as the only
stable job in science. That's also what
00:18:13.940 --> 00:18:20.450
happened to me, I left academia after my
PhD. So what do we learn from all of this?
00:18:20.450 --> 00:18:23.420
Different stages of a research career
correlate with different levels of
00:18:23.420 --> 00:18:27.490
expertise. If you read statements from a
Master's student or professor, you can get
00:18:27.490 --> 00:18:31.220
an estimate for how much they know about
their field and in turn for how solid
00:18:31.220 --> 00:18:35.270
their science is. Of course, this is just
a rule of thumb- I have met both very
00:18:35.270 --> 00:18:38.440
knowledgeable Master's students and
professors, who knew nothing apart from
00:18:38.440 --> 00:18:43.990
their own small work. So whenever you read
statements from researchers independent of
00:18:43.990 --> 00:18:47.830
their career stage, you should also wonder
whether they represent the scientific
00:18:47.830 --> 00:18:52.160
consensus. Any individual scientist might
have a particular hot take about something
00:18:52.160 --> 00:18:57.040
they care about but in general, they agree
with their colleagues. When reading about
00:18:57.040 --> 00:19:00.530
science that relates to policies or public
debates, it is a good idea to explore
00:19:00.530 --> 00:19:04.940
whether this particular researcher is
representing their own opinion or the one
00:19:04.940 --> 00:19:09.050
of their peers. Don't ask the researcher
directly though, every single one of them
00:19:09.050 --> 00:19:16.530
will say that, of course, they represent
the majority opinion. The difference
00:19:16.530 --> 00:19:21.380
between science and screwing around is
writing it down, as Adam Savage once said.
00:19:21.380 --> 00:19:24.760
Science without publications is pretty
useless because if you keep all that
00:19:24.760 --> 00:19:29.290
knowledge to yourself, well, congrats, you
are very smart now but that doesn't really
00:19:29.290 --> 00:19:33.720
help anyone but you. Any researchers'
goal, therefore, is to get their findings
00:19:33.720 --> 00:19:38.500
publicly known so that others can extend
the work and create scientific progress.
00:19:38.500 --> 00:19:43.000
So let's go back to my amazing bee
research. I did the whole experiment again
00:19:43.000 --> 00:19:47.233
with proper controls this time and now I
want to tell people about it. The simplest
00:19:47.233 --> 00:19:51.570
way to publish my findings would be to
tweet about it. But then a random guy
00:19:51.570 --> 00:19:56.036
would probably tell me that I'm wrong and
stupid and should go f*** myself. So
00:19:56.036 --> 00:20:00.850
instead I do what most researchers would
do and go to a scientific conference.
00:20:00.850 --> 00:20:04.470
That's where researchers hang out, have a
lot of coffee and sit and listen to talks
00:20:04.470 --> 00:20:08.120
from other researchers. Conferences are
usually the first place that new
00:20:08.120 --> 00:20:13.250
information becomes public. Well, public
is a bit of a stretch, usually the talks
00:20:13.250 --> 00:20:17.690
are not really recorded or made accessible
to anyone, who wasn't there at the time.
00:20:17.690 --> 00:20:20.740
So while the information is pretty
trustworthy, it remains fairly
00:20:20.740 --> 00:20:25.170
inaccessible to others. After my
conference talk, the next step is to write
00:20:25.170 --> 00:20:29.845
up all the details of my experiment and
the results in a scientific paper. Before
00:20:29.845 --> 00:20:33.930
I send this to an editor at a scientific
journal, I could publish it myself as a
00:20:33.930 --> 00:20:38.620
pre-print. These pre-prints are drafts of
finished papers that are available to read
00:20:38.620 --> 00:20:43.120
for anyone. They are great because they
provide easy access to information that is
00:20:43.120 --> 00:20:47.170
otherwise often behind paywalls. They are
not so great because they have not yet
00:20:47.170 --> 00:20:51.751
been peer reviewed. If a pre-print hasn't
also been published with peer review, you
00:20:51.751 --> 00:20:55.500
have to be careful with what you read as
it is essentially only the point of view
00:20:55.500 --> 00:21:01.186
of the authors. Peer review only happens
when you submit your paper to a journal.
00:21:01.186 --> 00:21:04.720
Journals are a whole thing and there have
been some great talks in the past about
00:21:04.720 --> 00:21:08.900
why many of them are problematic. Let's
ignore for a second how these massive
00:21:08.900 --> 00:21:12.490
enterprises collect money from everyone
they get in contact with and let's focus
00:21:12.490 --> 00:21:17.170
instead on what they're doing for the
academic system. I send them my paper, an
00:21:17.170 --> 00:21:21.540
editor sees if it's any good and then
sends my paper to two to three reviewers.
00:21:21.540 --> 00:21:25.370
These are other researchers that then
critically check everything I did and
00:21:25.370 --> 00:21:30.440
eventually recommend accepting or
rejecting my paper. If it is accepted, the
00:21:30.440 --> 00:21:35.260
paper will be published. I pay a fee and
the paper will be available online. Often
00:21:35.260 --> 00:21:40.180
behind a paywall, unless I pay some more
cash. At this point, I'd like to have a
00:21:40.180 --> 00:21:44.330
look at how a scientific paper works.
There are five important parts to any
00:21:44.330 --> 00:21:49.543
paper. The title, the author list, the
abstract, the figures and the text. The
00:21:49.543 --> 00:21:53.310
title is a summary of the main findings
and unlike in popular media, it is much
00:21:53.310 --> 00:21:57.250
more descriptive. Where a newspaper leaves
out the most important information to get
00:21:57.250 --> 00:22:00.900
people to read the article, the
information is right there in the title of
00:22:00.900 --> 00:22:06.600
the study. In my case that could be
"Honeybees -Apis mellifera- show selective
00:22:06.600 --> 00:22:11.120
preference for flower color in viola
tricolor". You see, everything is right
00:22:11.120 --> 00:22:15.793
there. The organisms I worked with and the
main result I found. Below the title
00:22:15.793 --> 00:22:19.640
stands the author list. As you might have
guessed, the author list is a list of
00:22:19.640 --> 00:22:23.320
authors. Depending on the field the paper
is from, the list can be ordered
00:22:23.320 --> 00:22:28.280
alphabetically or according to relative
contribution. If it is contribution then
00:22:28.280 --> 00:22:32.120
you usually find the first author to have
done all the work or the middle authors to
00:22:32.120 --> 00:22:35.350
have contributed some smaller parts and
the last author to have paid for the whole
00:22:35.350 --> 00:22:40.130
thing. The last author is usually a group
leader or professor. A good way to learn
00:22:40.130 --> 00:22:45.400
more about a research group and their work
is to search for the last author's name. The
00:22:45.400 --> 00:22:49.000
abstract is a summary of the findings.
Read this to get a general idea of what
00:22:49.000 --> 00:22:53.270
the researchers did and what they found.
It is very dense in information but it is
00:22:53.270 --> 00:22:56.420
usually written in a way that also
researchers from other fields can
00:22:56.420 --> 00:23:01.730
understand at least some of it. The
figures are pretty to look at and hold the
00:23:01.730 --> 00:23:07.090
key findings in most papers and the text
has the full story with all the details or
00:23:07.090 --> 00:23:11.840
the jargon and all your references that
the research is built on. You probably
00:23:11.840 --> 00:23:16.300
won't read the text unless you care a lot,
so stick to title, abstract and authors to
00:23:16.300 --> 00:23:20.690
get a quick understanding of what's going
on. Scientific papers to reflect a peer
00:23:20.690 --> 00:23:25.820
reviewed opinion of one or a few research
groups. If you are interested in a broader
00:23:25.820 --> 00:23:30.610
topic like what insects like to pollinate
what flower, you should read review
00:23:30.610 --> 00:23:35.110
papers. These are peer reviewed summaries
of a much broader scope, often weighing
00:23:35.110 --> 00:23:39.500
multiple points of view against each
other. Review papers are a great resource
00:23:39.500 --> 00:23:43.510
that avoids some of the biases individual
research groups might have about their
00:23:43.510 --> 00:23:48.590
topic. So my research is reviewed and
published. I can go back now and start
00:23:48.590 --> 00:23:52.100
counting butterflies, but this is not
where the publishing of scientific results
00:23:52.100 --> 00:23:56.860
ends. My institute might think that my bee
counting is not even bad, it is actually
00:23:56.860 --> 00:24:01.290
amazing and so they will issue a press
release. Press releases often emphasize
00:24:01.290 --> 00:24:04.760
the positive parts of a study while
putting them into context of something
00:24:04.760 --> 00:24:08.770
that's relevant to most people. Something
like "bees remain attracted to yellow
00:24:08.770 --> 00:24:13.010
flowers despite the climate crisis". The
facts in a press release are usually
00:24:13.010 --> 00:24:17.190
correct but shortcomings of a study that I
mentioned in a paper are often missing
00:24:17.190 --> 00:24:22.670
from the press release. Because my bee
study is really cool and because the PR
00:24:22.670 --> 00:24:27.760
department of my institute did a great
job, journalists pick up on the story. The
00:24:27.760 --> 00:24:31.950
first ones are often journals with a focus
on science like Scientific American or
00:24:31.950 --> 00:24:35.750
Spektrum der Wissenschaft. Most of the
time, science journalists do a great job
00:24:35.750 --> 00:24:40.490
in finding more sources and putting the
results into context. They often ask other
00:24:40.490 --> 00:24:44.230
experts for their opinion and they break
down the scientific language into simpler
00:24:44.230 --> 00:24:48.300
words. Science journalism is the source I
recommend to most people when they want to
00:24:48.300 --> 00:24:52.500
learn about a field that they are not
experts in. Because my bee story is
00:24:52.500 --> 00:24:57.180
freaking good, mainstream journalists are
also reporting on it. They are often
00:24:57.180 --> 00:25:00.150
pressed for time and write for much
broader audience, so they just report the
00:25:00.150 --> 00:25:05.450
basic findings, often putting even more
emphasis on why people should care.
00:25:05.450 --> 00:25:10.980
Usually climate change, personal health or
now Covid. Mainstream press coverage is
00:25:10.980 --> 00:25:14.920
rarely as detailed as the previous
reporting and has the strongest tendency
00:25:14.920 --> 00:25:20.417
to accidentally misrepresent facts or add
framing that researchers wouldn't use. Oh,
00:25:20.417 --> 00:25:23.140
and then there is the weird uncle, who
posts a link to the article on their
00:25:23.140 --> 00:25:26.500
Facebook with a blurb of text that says
the opposite of what the study actually
00:25:26.500 --> 00:25:31.750
did. As you might imagine, the process of
getting scientific information out to the
00:25:31.750 --> 00:25:35.660
public quickly becomes a game of
telephone. What is clearly written in the
00:25:35.660 --> 00:25:39.480
paper is framed positively in a press
release and gets watered down even more
00:25:39.480 --> 00:25:44.170
once it reaches mainstream press. So for
you, as someone, who wants to understand
00:25:44.170 --> 00:25:48.380
the science, it is a good idea to be more
careful the further you get away from your
00:25:48.380 --> 00:25:52.710
original source material. While specific
scientific journalism usually does a good
00:25:52.710 --> 00:25:56.540
job in breaking down the facts without
distortion, the same can't be said for
00:25:56.540 --> 00:26:01.310
popular media. If you come across an
interesting story, try to find another
00:26:01.310 --> 00:26:05.530
version of it in a different outlet,
preferably one that is more catered to an
00:26:05.530 --> 00:26:09.320
audience with scientific interest. Of
course, you can jump straight to the
00:26:09.320 --> 00:26:13.250
original paper but understanding the
scientific jargon can be hard and
00:26:13.250 --> 00:26:17.960
misunderstanding the message is easy, so
it can do more harm than good. We see that
00:26:17.960 --> 00:26:23.640
harm now with Hobbyists, when epidimi...,
epidimio..., epediomiolo.., who are not
00:26:23.640 --> 00:26:28.180
people, who study epidemics, who are
making up their own pandemic modeling.
00:26:28.180 --> 00:26:31.550
They are cherry picking bits of
information from scientific papers without
00:26:31.550 --> 00:26:35.230
understanding the bigger picture and
context and then post their own charts on
00:26:35.230 --> 00:26:39.851
Twitter. It's cool if you want to play
with data in your free time, and it's a
00:26:39.851 --> 00:26:44.510
fun way to learn more about a topic but it
can also be very misleading and harmful
00:26:44.510 --> 00:26:48.390
while dealing with a pandemic if expert
studies have to fight for attention with
00:26:48.390 --> 00:26:52.940
nonexperts Excel-graphs. It pays off to
think twice about whether you're actually
00:26:52.940 --> 00:26:59.280
helping by publishing your own take on a
scientific question. Before we end, I want
00:26:59.280 --> 00:27:03.600
to give you some practical advice on how
to assess the credibility of a story and
00:27:03.600 --> 00:27:08.470
how to understand the science better. This
is now an in-depth guide to fact checking.
00:27:08.470 --> 00:27:12.760
I want you to get a sort of gut feeling
about science. When I read scientific
00:27:12.760 --> 00:27:18.320
information, these are the questions that
come to my mind. First up, I want to ask
00:27:18.320 --> 00:27:23.499
yourself, is this plausible and does this
follow the scientific consensus? If both
00:27:23.499 --> 00:27:28.610
answers are "no" then you should carefully
check the sources. More often than not,
00:27:28.610 --> 00:27:32.530
these results are outliers that somebody
exaggerated to get news coverage or
00:27:32.530 --> 00:27:37.676
someone is actively reframing scientific
information for their own goals. To get a
00:27:37.676 --> 00:27:41.280
feeling about scientific consensus on
things, it is a good idea to look for
00:27:41.280 --> 00:27:45.280
joint statements from research
communities. Whenever an issue that is
00:27:45.280 --> 00:27:49.850
linked to current research comes up for
public debate, there is usually a joint
00:27:49.850 --> 00:27:53.550
statement laying down the scientific
opinion signed by dozens or even hundreds
00:27:53.550 --> 00:27:59.150
of researchers, like, for example, from
Scientists for Future. And then whenever
00:27:59.150 --> 00:28:03.640
you see a big number, you should look for
context. When you read statements like "We
00:28:03.640 --> 00:28:08.760
grow sugar beet on an area of over 400,000
hectare", you should immediately ask
00:28:08.760 --> 00:28:14.610
yourself "Who is we? Is it Germany,
Europe, the world? What is the time frame?
00:28:14.610 --> 00:28:20.954
Is that per year? Is that a lot? How much
is that compared to other crops?". Context
00:28:20.954 --> 00:28:26.620
matters a lot and often big numbers are
used to impress you. In this case, 400,000
00:28:26.620 --> 00:28:32.360
hectare is the yearly area that Germany
grows sugar beet on. A wheat, for example,
00:28:32.360 --> 00:28:37.870
is grown on over 3 million hectare per
year in Germany. Context matters, and so
00:28:37.870 --> 00:28:42.100
whenever you see a number, look for a
frame of reference. If the article doesn't
00:28:42.100 --> 00:28:45.960
give you one, either, go and look for
yourself or ignore the number for your
00:28:45.960 --> 00:28:50.290
decision making based on the article.
Numbers only work with framing, so be
00:28:50.290 --> 00:28:54.840
aware of it. I want you to think briefly
about how you felt when I gave you that
00:28:54.840 --> 00:29:00.370
number of 400,000 hectare. Chances are
that you felt a sort of feeling of unease
00:29:00.370 --> 00:29:05.010
because it's really hard to imagine such a
large number. An interesting exercise is
00:29:05.010 --> 00:29:09.630
to create your own frame of reference.
Collect a couple of numbers like total
00:29:09.630 --> 00:29:13.750
agricultural area of your country, the
current spending budget of your
00:29:13.750 --> 00:29:17.620
municipality, the average yearly income,
or the unemployment rate in relative and
00:29:17.620 --> 00:29:21.850
absolute numbers. Keep the list somewhere
accessible and use it whenever you come
00:29:21.850 --> 00:29:27.390
across a big number that is hard to grasp.
Are 100,000€ a lot of money in context of
00:29:27.390 --> 00:29:32.070
public spending? How important are 5,000
jobs in context of population and
00:29:32.070 --> 00:29:36.350
unemployment? Such a list can defuze the
occasional scary big number in news
00:29:36.350 --> 00:29:41.640
articles, and it can also help you to make
your point better. Speaking of framing,
00:29:41.640 --> 00:29:45.730
always be aware, who the sender of the
information is. News outlets rarely have a
00:29:45.730 --> 00:29:52.360
specific scientific agenda, but NGOs do.
If Shell, the oil company, will provide a
00:29:52.360 --> 00:29:56.390
leaflet where they cite scary numbers and
present research that they funded that
00:29:56.390 --> 00:30:00.060
finds that oil drilling is actually good
for the environment but they won't
00:30:00.060 --> 00:30:03.870
disclose, who they work with for the
study, we all would laugh at that
00:30:03.870 --> 00:30:07.910
information. But if we read a leaflet from
an environmental NGO in Munich that is
00:30:07.910 --> 00:30:11.260
structurally identical but with a
narrative about glyphosate in beer that
00:30:11.260 --> 00:30:15.350
fits our own perception of the world, we
are more likely to accept the information
00:30:15.350 --> 00:30:19.010
in the leaflet. In my opinion, both
sources are problematic and I would not
00:30:19.010 --> 00:30:25.440
use any of them to build my own opinion.
Good journalists put links to the sources
00:30:25.440 --> 00:30:30.461
in or under the article, and it is a good
idea to check them. Often, however, you
00:30:30.461 --> 00:30:34.860
have to look for the paper yourself based
on hints in the text like author names,
00:30:34.860 --> 00:30:39.910
institutions, and general topics. And then
paywalls often block access to the
00:30:39.910 --> 00:30:44.280
information that you're looking for. You
can try pages like ResearchGate for legal
00:30:44.280 --> 00:30:49.580
access to PDFs. Many researchers also use
sci-hub but as the site provides illegal
00:30:49.580 --> 00:30:55.000
access to publicly funded research, I
won't recommend doing so. When you have
00:30:55.000 --> 00:30:59.330
the paper in front of you, you can either
read it completely, which is kind of hard,
00:30:59.330 --> 00:31:03.900
or just read the abstract, which might be
easier. The easiest is to look for science
00:31:03.900 --> 00:31:09.330
journalism articles about the paper.
Twitter is actually great to find those,
00:31:09.330 --> 00:31:12.380
as many researchers are on Twitter and
like to share articles about their own
00:31:12.380 --> 00:31:16.500
research They also like to discuss
research on Twitter. So if the story is
00:31:16.500 --> 00:31:20.380
controversial, chances are you'll find
some science accounts calling that out.
00:31:20.380 --> 00:31:24.650
While Twitter is terrible in many regards,
it is a great tool to engage with the
00:31:24.650 --> 00:31:30.320
scientific community. You can also do a
basic check-up yourself. Where was the
00:31:30.320 --> 00:31:34.160
paper published and is it a known journal?
Who are the people doing the research and
00:31:34.160 --> 00:31:39.260
what are their affiliations? How did they
do their experiment? Checking for controls
00:31:39.260 --> 00:31:43.200
and repetitions in the experiment is hard
if you don't know the topic, but if you do
00:31:43.200 --> 00:31:49.534
know the topic, go for it. In the end,
fact checking takes time and energy. It's
00:31:49.534 --> 00:31:53.200
very likely that you won't do it very
often but especially when something comes
00:31:53.200 --> 00:31:57.231
up that really interests you and you want
to tell people about it, you should do a
00:31:57.231 --> 00:32:01.960
basic fact-check on the science. The world
would be a lot better if you'd only share
00:32:01.960 --> 00:32:06.860
information that you checked yourself for
plausibility. You can also help to reduce
00:32:06.860 --> 00:32:10.990
the need for rigorous fact checking.
Simply do not spread any sane stories that
00:32:10.990 --> 00:32:14.690
seem too good to be true and that you
didn't check yourself or find in a
00:32:14.690 --> 00:32:19.100
credible source. Misinformation and bad
science reporting spread because we don't
00:32:19.100 --> 00:32:23.820
care enough and because they are very,
very attractive. If we break that pattern,
00:32:23.820 --> 00:32:26.850
we can give reliable scientific
information the attention that it
00:32:26.850 --> 00:32:31.160
deserves. But don't worry, most of the
science reporting you'll find online is
00:32:31.160 --> 00:32:35.150
actually pretty good. There is no need to
be extremely careful with every article
00:32:35.150 --> 00:32:40.060
you find. Still, I think it is better to
have a natural alertness to badly reported
00:32:40.060 --> 00:32:45.415
signs than to trust just anything that is
posted under a catchy headline. There is
00:32:45.415 --> 00:32:49.800
no harm in double checking the facts
because either you correct a mistake or
00:32:49.800 --> 00:32:55.980
you reinforce correct information in your
mind. So how do I assess whether a source
00:32:55.980 --> 00:33:00.720
that I like is actually good? When I come
across a new outlet, I try to find some
00:33:00.720 --> 00:33:05.710
articles in an area that I know stuff
about. For me, that's plant science. I
00:33:05.710 --> 00:33:08.970
then read what they are writing about
plants. If that sounds plausible, I am
00:33:08.970 --> 00:33:12.410
tempted to also trust when they write
about things like physics or climate
00:33:12.410 --> 00:33:17.870
change, where I have much less expertize.
This way I have my own personal list of
00:33:17.870 --> 00:33:22.620
good and not so good outlets. If somebody
on Twitter links to an article from the
00:33:22.620 --> 00:33:26.360
not so good list, I know that I have to
take that information with a large
00:33:26.360 --> 00:33:30.490
quantity of salt. And if I want to learn
more, I look for a different source to
00:33:30.490 --> 00:33:37.710
back up any claims I find. It is tedious
but so is science. With a bit of practice,
00:33:37.710 --> 00:33:41.240
you can internalize the skepticism and
navigate science information with much
00:33:41.240 --> 00:33:47.499
more confidence. I hope I could help you
with that a little bit. So that was my
00:33:47.499 --> 00:33:50.970
attempt to help you to understand science
better. I'd be glad if you'd leave me
00:33:50.970 --> 00:33:55.233
feedback or direct any of your questions
towards me on Twitter. That's
00:33:55.233 --> 00:33:59.080
@sciencejoram. There will be sources for
the things I talked about available
00:33:59.080 --> 00:34:04.430
somewhere around this video or on my
website: joram.schwartzmann.de. Thank you
00:34:04.430 --> 00:34:10.676
for your attention. Goodbye.
00:34:10.676 --> 00:34:15.450
Herald: derJoram, thank you for your talk,
very entertaining and informative as well
00:34:15.450 --> 00:34:23.480
as I might say. We have a few questions
from here at the Congress that would be...
00:34:23.480 --> 00:34:26.929
where's the signal? I need my questions
from the internet - all of them are from
00:34:26.929 --> 00:34:28.929
the Internet.
Joram: laughs
00:34:28.929 --> 00:34:37.539
H: So I would go through the questions and
you can elaborate on some of the points
00:34:37.539 --> 00:34:41.529
from your talk. So the first question...
J: yeah, I will.
00:34:41.529 --> 00:34:47.829
H: very good. The first question is: Is
there a difference between reviewed
00:34:47.829 --> 00:34:55.700
articles and meta studies?
J: To my knowledge, there isn't really a
00:34:55.700 --> 00:35:00.430
categorical difference in terms of peer
review. Meta studies, so studies that
00:35:00.430 --> 00:35:05.220
integrate, especially in the medical field
you find that often, they integrate a lot
00:35:05.220 --> 00:35:10.259
of studies and then summarize the findings
again and try to put them in context of
00:35:10.259 --> 00:35:18.920
one another, which are incredibly useful
studies for medical conclusion making.
00:35:18.920 --> 00:35:23.630
Because as I said in the talk, it's often
very hard to do, for example, dietary
00:35:23.630 --> 00:35:28.569
studies and you want to have large numbers
and you get that by combining several
00:35:28.569 --> 00:35:33.730
studies together. And usually these meta
studies are also peer reviewed. So instead
00:35:33.730 --> 00:35:39.330
of actually doing the research and going
and doing whatever experiments you want to
00:35:39.330 --> 00:35:46.100
do on humans, you instead collect all of
the evidence others state, and then you
00:35:46.100 --> 00:35:49.480
integrate it again, draw new conclusions
from that and compare them and weigh them
00:35:49.480 --> 00:35:55.240
and say "OK, this study had these
shortcomings but we can take this part
00:35:55.240 --> 00:35:59.641
from this study and put it in context with
this part from his other study" because
00:35:59.641 --> 00:36:04.630
you make so much additional conclusion
making on that, you then submit it again
00:36:04.630 --> 00:36:08.869
to a journal and it's again peer reviewed
and then other researchers look at it and
00:36:08.869 --> 00:36:12.650
say, and yeah, pretty much give their
expertize on it and say whether or not it
00:36:12.650 --> 00:36:17.079
made sense what you concluded from all of
these things. So a meta study, when it's
00:36:17.079 --> 00:36:21.599
published in a scientific journal, is also
peer reviewed and also a very good,
00:36:21.599 --> 00:36:25.960
credible source. And I would even say
often meta studies are the studies that
00:36:25.960 --> 00:36:30.601
you really want to look for if you have a
very specific scientific question that you
00:36:30.601 --> 00:36:36.560
as a sort of non expert, want to have
answered because very often the individual
00:36:36.560 --> 00:36:40.510
studies, they are very focused on a
specific detail of a bigger research
00:36:40.510 --> 00:36:44.759
question. But if you want to know is, I
don't know, dietary fiber very good for
00:36:44.759 --> 00:36:49.339
me. There's probably not a single study
that will have the answer but there will
00:36:49.339 --> 00:36:53.609
be many studies that together point
towards the answer. And the meta study is
00:36:53.609 --> 00:36:59.230
a place where you can find that answer.
H: Very good, sounds like something to
00:36:59.230 --> 00:37:05.740
reinforce the research. Maybe a follow-up
question or it is a follow-up question: Is
00:37:05.740 --> 00:37:12.150
there anything you can say in this regards
about the reproducibility crisis in many
00:37:12.150 --> 00:37:16.641
fields such as medicine?
J: Yeah, that's a very good point. I mean,
00:37:16.641 --> 00:37:20.900
that's something that I didn't mention at
all in the talk because for pretty much
00:37:20.900 --> 00:37:26.410
like complexity reasons because when you
go into reproducibility, you run into all
00:37:26.410 --> 00:37:33.569
kinds of, sort of complex additional
problems because it is true that we often
00:37:33.569 --> 00:37:40.309
struggle with reproducing. I actually
don't have the numbers how often we fail
00:37:40.309 --> 00:37:45.290
but this reproducibility crisis that's
often mentioned - that is this idea that
00:37:45.290 --> 00:37:49.700
when researchers take a paper that has
whatever they studied and then other
00:37:49.700 --> 00:37:54.329
researchers try to recreate a study and
usually in a paper, there's also a
00:37:54.329 --> 00:37:58.279
'Material & Method' section that details
all of the things that they did. It's
00:37:58.279 --> 00:38:01.769
pretty much the instructions of the
experiment. And the results of the
00:38:01.769 --> 00:38:04.410
experiment are both in the same paper
usually - and when they try to sort of
00:38:04.410 --> 00:38:09.559
recook the recipe that somebody else did,
there is a chance that they don't find the
00:38:09.559 --> 00:38:13.299
same thing. And we see that more and more
often, especially with like complex
00:38:13.299 --> 00:38:17.859
research questions. And that brings us to
the idea that reproduction or
00:38:17.859 --> 00:38:24.109
reproducibility is an issue and that maybe
we we can't trust science as much or we
00:38:24.109 --> 00:38:30.509
have to be more careful. It is true that
we have to be more careful. But I wouldn't
00:38:30.509 --> 00:38:36.425
go as far and to be like in general, sort
of a distrustful of research. And that's
00:38:36.425 --> 00:38:39.369
why I'm also saying, like in the medical
field, you always want to have multiple
00:38:39.369 --> 00:38:43.789
studies pointing at something. You always
want to have multiple lines of evidence
00:38:43.789 --> 00:38:50.410
because if one group finds something and
another group can't find it, like
00:38:50.410 --> 00:38:56.640
reproduce it, you end up in a place where
you can't really say "Did this work now?
00:38:56.640 --> 00:39:00.500
Like, who did the mistake? The first group
or the second group? " Because also when
00:39:00.500 --> 00:39:03.329
you were producing a study, you can make
mistakes or there can be factors that the
00:39:03.329 --> 00:39:08.480
initial research study didn't document in
a way that it can be reproduced because
00:39:08.480 --> 00:39:13.039
they didn't care to write down the supply
of some chemicals, and the chemicals were
00:39:13.039 --> 00:39:16.619
very important for the success of the
experiment. Things like that happen and so
00:39:16.619 --> 00:39:20.630
you don't know when you just have the
initial study or the production study and
00:39:20.630 --> 00:39:25.180
they have a different outcome. But if you
have then multiple studies that all look
00:39:25.180 --> 00:39:31.849
in a similar area and out of 10 studies, 8
or 7 point to do a certain direction, you
00:39:31.849 --> 00:39:37.170
can then be more certain that this
direction points towards the truth. In
00:39:37.170 --> 00:39:42.040
science, it's really hard to say, like
OK, this is now the objective truth. This
00:39:42.040 --> 00:39:47.080
is now.. we found now the definitive
answer to the question that we're looking
00:39:47.080 --> 00:39:53.849
at, especially in the medical field. So,
yeah.. So that's a very long way of saying
00:39:53.849 --> 00:39:58.530
it's complicated reproduction or
reproducibility studies, they are very
00:39:58.530 --> 00:40:06.519
important but I wouldn't be too worried or
too - what's the word here? Like, I
00:40:06.519 --> 00:40:11.510
wouldn't be too worried that the lack of
reproducibility breaks the entire
00:40:11.510 --> 00:40:18.050
scientific method because it's usually
more complex and more issues at hand than
00:40:18.050 --> 00:40:22.490
just a simple recooking of another
person's study.
00:40:22.490 --> 00:40:31.920
H: Yes, speaking of more publishing, so
this is a follow-up to the follow-up, the
00:40:31.920 --> 00:40:34.799
Internet asks, how can we deal with the
publish or perish culture?
00:40:34.799 --> 00:40:41.579
J: Oh, yeah. If I knew that, I would write
a very smart blog posts and trying to get
00:40:41.579 --> 00:40:46.019
convince people about that. I think
personally we need to rethink the way we
00:40:46.019 --> 00:40:50.109
do the funding because that's in the end
where it comes down to. Another issue I
00:40:50.109 --> 00:40:54.100
really didn't go into much detail in the
talk because it's also very complex. So
00:40:54.100 --> 00:40:59.880
science funding is usually defined by a
decision making process; at one point
00:40:59.880 --> 00:41:04.810
somebody decides, who gets the money and
to get the money they need a qualifier to
00:41:04.810 --> 00:41:09.300
decide. Like there is 10 research groups
or 100 research groups said that write a
00:41:09.300 --> 00:41:13.309
grant and say like "Hey, we need money
because we want to do research." And they
00:41:13.309 --> 00:41:19.490
have to figure out or they have to decide,
who gets it because they can't give money
00:41:19.490 --> 00:41:24.099
to everyone because we spend money in our
budgets on different things than just
00:41:24.099 --> 00:41:29.759
science. So the next best thing that they
came up with, what the idea to use papers
00:41:29.759 --> 00:41:35.730
- the number of papers that you have - to
sort of get a measurement - or the quality
00:41:35.730 --> 00:41:40.270
of paper that you have - to get a
measurement of whether you are deserving
00:41:40.270 --> 00:41:44.579
of the money. And you can see how that's
problematic and means that people, who are
00:41:44.579 --> 00:41:49.089
early in their research career, who don't
have a lot of papers, they have a lower
00:41:49.089 --> 00:41:53.049
chance of getting the money. And that
leads to publish or perish idea that if
00:41:53.049 --> 00:41:56.900
you don't publish your results and if you
don't publish them in a very well
00:41:56.900 --> 00:42:01.240
respected journal, then the funding
agencies won't give you money. And so you
00:42:01.240 --> 00:42:07.619
perish and you can't really pursue your
research career. And it's really a hard
00:42:07.619 --> 00:42:11.730
problem to solve because the decision
about the funding is very much detached
00:42:11.730 --> 00:42:19.060
from the scientific world, from academia.
That's like multiple levels of abstraction
00:42:19.060 --> 00:42:23.660
between the people, who like in the end
make the budgets and decide, who gets the
00:42:23.660 --> 00:42:29.660
money and the people, who are actually
using the money. I would wish for funding
00:42:29.660 --> 00:42:36.850
agency to look less at papers and maybe
come up with different qualifiers, maybe
00:42:36.850 --> 00:42:44.980
also something like general scientific
practice, maybe they could do audits of
00:42:44.980 --> 00:42:50.980
some sort of labs. I mean, there's a ton
of factors that influence good research
00:42:50.980 --> 00:42:57.210
that are not mentioned in papers like work
ethics, work culture, how much teaching you
00:42:57.210 --> 00:43:01.670
do, which can be very important. But it's
sort of detrimental to get more funding
00:43:01.670 --> 00:43:05.760
because when you do teaching, you don't do
research and then you don't get papers and
00:43:05.760 --> 00:43:10.940
then you don't get money. So, yeah, I
don't have a very good solution to the
00:43:10.940 --> 00:43:16.410
question what we can do. I would like to
see more diverse funding also of smaller
00:43:16.410 --> 00:43:21.450
research groups. I would like to see more
funding for negative results, which is
00:43:21.450 --> 00:43:28.369
another thing that we don't really value.
So if you do an experiment and it doesn't
00:43:28.369 --> 00:43:32.430
work, you can't publish it, you don't get
the paper, you don't get money and so on.
00:43:32.430 --> 00:43:35.180
So there are many factors that need to
change, many things that we need to touch
00:43:35.180 --> 00:43:39.019
to actually get away from publish or
perish.
00:43:39.019 --> 00:43:47.359
H: Yeah, another question that is closely
connected to that is: Why are there so few
00:43:47.359 --> 00:43:52.420
stable jobs in science?
J: Yeah, that's the
00:43:52.420 --> 00:43:56.349
Wissenschaftszeitvertragsgesetzt,
something that - I forgot when we got it -
00:43:56.349 --> 00:44:04.099
I think in the late 90s or early 2000s.
That's at least a very German specific
00:44:04.099 --> 00:44:14.269
answer that defined this Gesetz, this law,
put it into law that you have a limited
00:44:14.269 --> 00:44:18.750
time span that you can work in research,
you can only work in research for I think
00:44:18.750 --> 00:44:23.589
12 years and are some footnotes and stuff
around it. But there is a fixed time limit
00:44:23.589 --> 00:44:27.579
that you can work in research on limited
term contracts, but you're funding
00:44:27.579 --> 00:44:31.170
whenever you get research funding, it's
always for a limited time. You always get
00:44:31.170 --> 00:44:36.220
research funding for three years, six
years if you're lucky. So you never have
00:44:36.220 --> 00:44:41.019
permanent money in the research group.
Sometimes you have that in universities
00:44:41.019 --> 00:44:44.559
but overall you don't have permanent
money. And so if you don't have permanent
00:44:44.559 --> 00:44:49.570
money, you can't have permanent contracts
and therefore there aren't really stable
00:44:49.570 --> 00:44:52.940
jobs. And then with professorships or some
group leader positions, then it changes
00:44:52.940 --> 00:44:58.830
because group leaders and professorships,
they are more easily planned. And
00:44:58.830 --> 00:45:02.289
therefore in universities and research
institutes, they sort of make a long term
00:45:02.289 --> 00:45:07.250
budget and say "OK, we will have 15
research groups. So we have money in the
00:45:07.250 --> 00:45:12.810
long term for 15 group leaders.". But
whoever is hired underneath these group
00:45:12.810 --> 00:45:16.480
leaders, this has much more fluctuation
and is based on sort of short term money.
00:45:16.480 --> 00:45:20.529
And so there's no stable jobs there. At
least that's in Germany. I know that, for
00:45:20.529 --> 00:45:25.859
example, in the UK and in France, they
have earlier permanent position jobs. They
00:45:25.859 --> 00:45:29.900
have lecturers, for example, in the UK
where you can without being a full
00:45:29.900 --> 00:45:35.300
professor that has like its own backpack
of stuff that has to be done, you can
00:45:35.300 --> 00:45:40.259
already work at a university in the long
term in a permanent contract. So it's a
00:45:40.259 --> 00:45:44.839
very.. it's a problem we see across the
world but Germany has its own very
00:45:44.839 --> 00:45:50.190
specific problems introduced here that
make it very unattractive to stay long
00:45:50.190 --> 00:45:56.530
term in research in Germany.
H: It's true. I concur.
00:45:56.530 --> 00:46:02.589
J: Yes
H laughs Coming to talk to the people,
00:46:02.589 --> 00:46:12.720
who do science mostly for fun and less for
profit. This question is: Can you write
00:46:12.720 --> 00:46:17.530
and publish a paper without a formal
degree in the sciences, assuming the
00:46:17.530 --> 00:46:23.680
research efforts are sufficiently good?
J: Yes, I think technically it is
00:46:23.680 --> 00:46:27.090
possible. It comes with some problems,
like, first of all, it's not free. First
00:46:27.090 --> 00:46:34.240
of all, when you submit your paper to a
journal, you pay money for it. I don't
00:46:34.240 --> 00:46:39.560
know exactly but it ranges. I think the
safe assumption is between 1.000 and
00:46:39.560 --> 00:46:44.349
5.000$, depending on the journal, where
you submit to. Then very often it's like
00:46:44.349 --> 00:46:49.960
some formal problems that... I've been
recently co-authoring a paper and I'm not
00:46:49.960 --> 00:46:56.509
actively doing research anymore. I did
something in my spare time, helped a
00:46:56.509 --> 00:47:02.130
friend of mine, who was still doing
research with some like basic stuff but he
00:47:02.130 --> 00:47:06.619
was so nice to put me on the paper. And
then there is a form where it says like
00:47:06.619 --> 00:47:11.850
institute affiliation and I don't have an
institute affiliation in that sense. So as
00:47:11.850 --> 00:47:16.049
I'm just a middle author in this paper, I
was published - or hopefully if it gets
00:47:16.049 --> 00:47:19.609
accepted - I will be there as an
independent researcher but it might be
00:47:19.609 --> 00:47:23.930
that a journal has their own internal
rules where they say we only accept people
00:47:23.930 --> 00:47:28.201
from institutions. So it's not really
inherent in the scientific system that you
00:47:28.201 --> 00:47:32.470
have to be at an institution but there are
these doors, there are these
00:47:32.470 --> 00:47:38.239
pathways that are locked because somebody
has to put in a form somewhere that which
00:47:38.239 --> 00:47:42.760
institution you affiliate with. And I know
that some people, who do like DIY science,
00:47:42.760 --> 00:47:48.549
so they do outside of academia, that they
need to have in academia partners that
00:47:48.549 --> 00:47:54.060
help them with the publishing and also to
get access to certain things. I mean, in
00:47:54.060 --> 00:47:57.579
computer science, you don't need specific
chemicals,but if you do anything like
00:47:57.579 --> 00:48:02.819
chemical engineering or biology or
anything, often you only get access to the
00:48:02.819 --> 00:48:08.170
supplies when you are an academic
institution. So, I know that many people
00:48:08.170 --> 00:48:13.269
have sort of these partnerships,
corporations with academia that allow them
00:48:13.269 --> 00:48:18.540
to actually do the research and then
publish it as well because otherwise, if
00:48:18.540 --> 00:48:23.549
you're just doing it from your own
bedroom, there might be a lot of barriers
00:48:23.549 --> 00:48:27.490
in your way that might be very hard to
overcome. But I think if you really,
00:48:27.490 --> 00:48:35.210
really dedicated, you can overcome them.
H: Coming to the elephants in that
00:48:35.210 --> 00:48:41.160
bedroom: What can we do against the spread
of false facts, IFG, corona-
00:48:41.160 --> 00:48:48.240
vaccines? So they are very.. They get a
lot of likes and are spread like a disease
00:48:48.240 --> 00:48:56.099
themselves. And it's very hard to counter,
especially in personal encounters, these
00:48:56.099 --> 00:49:01.609
arguments because apparently a lot of
people are not that familiar with the
00:49:01.609 --> 00:49:04.700
scientific method. What's your take on
that?
00:49:04.700 --> 00:49:09.329
J: Yeah, it's difficult. And I've read
over the years now many different
00:49:09.329 --> 00:49:15.630
approaches ranging from nuts actually
talking about facts because often
00:49:15.630 --> 00:49:18.960
somebody, who has a very predefined
opinion on something, they know a lot of
00:49:18.960 --> 00:49:22.989
false facts that they have on their mind.
And you, as somebody talking to them,
00:49:22.989 --> 00:49:26.160
often don't have all of the correct facts
in your mind. I mean, who runs around
00:49:26.160 --> 00:49:31.529
with, like, a bag full of climate facts
and a bag full of 5G facts and a bag full
00:49:31.529 --> 00:49:37.880
of vaccine facts or like in the same
quantity and quality as the stuff that
00:49:37.880 --> 00:49:41.089
somebody, who read stuff on Facebook has
in their in their backpack and their sort
00:49:41.089 --> 00:49:47.119
of mental image of the world. So just
arguing on the facts, it's very hard
00:49:47.119 --> 00:49:52.670
because people, who follow these false
ideas, they're very quick at making turns
00:49:52.670 --> 00:49:56.319
and they like throw a thing at you one
after the other. And so it's really hard
00:49:56.319 --> 00:50:01.079
to just be like but actually debunking
fact one and then debunking the next wrong
00:50:01.079 --> 00:50:07.859
fact. So I've seen a paper where people
try to do this sort of on a argumentative
00:50:07.859 --> 00:50:13.239
standpoint. They say: "Look: You're
drawing false conclusions. You say because
00:50:13.239 --> 00:50:20.820
A, therefore B, but these two things
aren't linked in a causal way. So you
00:50:20.820 --> 00:50:25.260
can't actually draw this conclusion." And
so sort of try to destroy that argument on
00:50:25.260 --> 00:50:31.659
a meta level instead on a fact level. But
also that is difficult. And usually
00:50:31.659 --> 00:50:36.980
people, who are really devout followers of
false facts, they are also not followers
00:50:36.980 --> 00:50:42.769
of reasons or any reason based argument
will just not work for them because they
00:50:42.769 --> 00:50:51.900
will deny it. I think what really helps is
a lot of small scale action in terms of
00:50:51.900 --> 00:50:56.779
making scientific data. So making science
more accessible. And I mean, I'm a science
00:50:56.779 --> 00:50:59.940
communicator, so I'm heavily biased. I'm
saying like we need more science
00:50:59.940 --> 00:51:04.789
communication, we need more low level
science communication. We need to have it
00:51:04.789 --> 00:51:09.031
freely accessible because all of the stuff
that you read with the false facts, this
00:51:09.031 --> 00:51:14.210
is all freely available on Facebook and so
on. So we need to have a similar low
00:51:14.210 --> 00:51:22.189
level, low entry level for the correct
facts. So for the real facts. And this is
00:51:22.189 --> 00:51:25.970
also.. It's hard to do. I mean, in science
communication field, there's also a lot of
00:51:25.970 --> 00:51:31.339
debate how we do that. Should we do that
over more presence on social media? Should
00:51:31.339 --> 00:51:38.130
we simplify more or are we then actually
oversimplifying like where is the balance?
00:51:38.130 --> 00:51:43.819
How do we walk this line? So there's a lot
of discussion and still ongoing learning
00:51:43.819 --> 00:51:48.130
about that. But I think in the end, it's
that what we need, we need people to be
00:51:48.130 --> 00:51:56.746
able to just to find correct facts just as
easily and understandable as they find the
00:51:56.746 --> 00:52:05.210
fake news and the facts. Like we need
science to be communicated as clearly as a
00:52:05.210 --> 00:52:11.279
stupid share rolls on Facebook, as an
image that - I don't want to repeat all of
00:52:11.279 --> 00:52:17.680
the wrong claims, but something that says
something very wrong, but very persuasive.
00:52:17.680 --> 00:52:22.190
We need to be as persuasive with the
correct facts. And I know that many people
00:52:22.190 --> 00:52:28.099
are doing that by now, especially on
places like Instagram or TikTok. You find
00:52:28.099 --> 00:52:33.309
more and more people doing very high
quality, low level - and I mean that on
00:52:33.309 --> 00:52:40.170
sort of jargon level, not on a sort of
intellectual level - so very low barrier
00:52:40.170 --> 00:52:46.700
science communication. And I think this
helps a lot. This helps more than very
00:52:46.700 --> 00:52:52.569
complicated sort of pages debunking false
facts. I mean, we also need these we also
00:52:52.569 --> 00:52:56.951
need these as references. But if we really
want to combat the spread of fake news, we
00:52:56.951 --> 00:53:01.589
need to just be as accessible with the
truth.
00:53:01.589 --> 00:53:10.749
H: A thing closely connected to that is:
"How do we find human error or detect
00:53:10.749 --> 00:53:16.319
it?", since I guess people, who are
watching this talk have already started
00:53:16.319 --> 00:53:23.380
with a process of fine tuning their
bullshit detectors but when, for example,
00:53:23.380 --> 00:53:27.010
something very exciting and promising
comes along as an example, CRISPR/Cas or
00:53:27.010 --> 00:53:39.489
something. How do we go forward to not be
fooled by our own already tuned bullshit
00:53:39.489 --> 00:53:46.400
detectors and fall to false conclusions.
J: I think a main part of this is
00:53:46.400 --> 00:53:54.200
practice. Just try to look for something
that would break the story, just not for
00:53:54.200 --> 00:53:57.829
every story that I read - that's that's a
lot of work. But from time to time, pick a
00:53:57.829 --> 00:54:01.119
story where you're like "Oh, this is very
exciting" and try to learn as much as you
00:54:01.119 --> 00:54:05.870
can about that one story. And by doing
that, also learn about the process, how
00:54:05.870 --> 00:54:12.279
you drew the conclusions and then compare
your final images after you did all the
00:54:12.279 --> 00:54:18.640
research to the thing that you read in the
beginning and see where there are things
00:54:18.640 --> 00:54:23.010
that are not coming together and where
there are things that are the same and
00:54:23.010 --> 00:54:30.109
then based on that, practice. And I know
that that's a lot of work, so that's sort
00:54:30.109 --> 00:54:38.150
of the the high impact way of doing that
by just practicing and just actively doing
00:54:38.150 --> 00:54:43.900
the check-ups. But the other way you can
do this is find people whose opinion you
00:54:43.900 --> 00:54:51.039
trust on topics and follow them, follow
them on podcasts, on social media, on
00:54:51.039 --> 00:54:56.579
YouTube or wherever. And, especially in
the beginning when you don't know them
00:54:56.579 --> 00:55:01.059
well be very critical about them, it's
easy to fall into like a sort of trap here
00:55:01.059 --> 00:55:06.339
and following somebody, who actually
doesn't know their stuff. But there are
00:55:06.339 --> 00:55:09.970
some people, I mean, in this community
here - I am not saying anything UFSA -
00:55:09.970 --> 00:55:16.650
if you follow people like minkorrekt, like
methodisch inkorrekt, they are great for a
00:55:16.650 --> 00:55:19.470
very.. I actually can't really pin down
which scientific area because in their
00:55:19.470 --> 00:55:22.740
podcast they're touching so many different
things and they have a very high level
00:55:22.740 --> 00:55:28.599
understanding of how science works. So
places like this are a good start to get a
00:55:28.599 --> 00:55:35.049
healthy dose of skepticism. Another rule
of thumb that I can give is like usually
00:55:35.049 --> 00:55:40.059
stories are not as exciting when you get
down to the nitty gritty details, like I'm
00:55:40.059 --> 00:55:45.220
a big fan of CRISPR, for example, but I
don't believe that we can cure all
00:55:45.220 --> 00:55:49.369
diseases just now because we have CRISPR,
like, there's very limited things we can
00:55:49.369 --> 00:55:54.829
do with it and we can do much more with it
than what we could do when we didn't have
00:55:54.829 --> 00:56:00.549
it. But I'm not going around and thinking
now we can create life at will because we
00:56:00.549 --> 00:56:05.849
have CRISPR. We can fight any disease at
will because we have CRISPR. So that's in
00:56:05.849 --> 00:56:11.059
general a good rule of thumb is: just calm
down, look what's really in there and see
00:56:11.059 --> 00:56:18.490
how much.. or tone it just down like 20%
and then take that level of excitement
00:56:18.490 --> 00:56:22.130
with you instead of going around and being
scared or overly excited about a new
00:56:22.130 --> 00:56:28.630
technology and you think that's been found
because we rarely do these massive jumps
00:56:28.630 --> 00:56:34.769
that we need to start to worry or get over
excited about something.
00:56:34.769 --> 00:56:42.520
H: Very good, so very last question: Which
tools did you use to create these nice
00:56:42.520 --> 00:56:47.910
drawings?
J: laughs Oh, a lot of people won't like
00:56:47.910 --> 00:56:53.343
me for saying this because this will sound
like a product promo. But there is.. I use
00:56:53.343 --> 00:56:59.349
an iPad with a pencil and I used an app to
draw the things on there called Affinity
00:56:59.349 --> 00:57:04.380
Designer because that works very well then
also across device. So that's how I
00:57:04.380 --> 00:57:08.849
created all of the drawings and I put them
all together in Apple Motion and exported
00:57:08.849 --> 00:57:14.649
the whole thing in Apple FinalCut. So this
is now the show like a sales pitch for all
00:57:14.649 --> 00:57:17.329
of these products. But I can say, like for
me, they work very well but there's pretty
00:57:17.329 --> 00:57:23.640
much alternatives for everything along the
way. I mean, I can say because I'm also
00:57:23.640 --> 00:57:28.019
doing a lot of science communication with
drawings for the Plants and Pipettes project
00:57:28.019 --> 00:57:33.039
that I am part of and I can say an iPad with a
pencil and the finishing designer gets you
00:57:33.039 --> 00:57:38.530
very far for high quality drawings with a
very easy access because I'm no way an
00:57:38.530 --> 00:57:44.940
artist. I'm very bad at this stuff. But I
can hide all my shortcomings because I
00:57:44.940 --> 00:57:49.170
have an undo function in my iPad and
because everything's in a vector drawing,
00:57:49.170 --> 00:57:54.140
I can delete every stroke that I made,
even if I realized like an hour later that
00:57:54.140 --> 00:57:58.589
this should not be there, I can, like,
reposition it and delete it. So vector
00:57:58.589 --> 00:58:03.739
files and a pencil and an undo function
were my best friends in the creating of
00:58:03.739 --> 00:58:09.079
this video.
H: Very good, derJoram. Thank you very
00:58:09.079 --> 00:58:14.151
much for your talk and your very extensive
Q&A. I think a lot of people are very
00:58:14.151 --> 00:58:16.151
happy with your work.
J: Thanks you.
00:58:16.151 --> 00:58:21.619
H: And are actually saying in the pad that
you should continue communicate science to
00:58:21.619 --> 00:58:24.670
the public.
J: That's very good because that's my job.
00:58:24.670 --> 00:58:27.700
laughs It's good that people like that.
H: Perfect.
00:58:27.700 --> 00:58:31.529
J: Thank you very much.
H: So a round of applause and some very
00:58:31.529 --> 00:58:39.760
final announcements for this session.
There will be the Herald new show and the
00:58:39.760 --> 00:58:47.920
break. So stay tuned for that. And I would
say if there are no further... no, we
00:58:47.920 --> 00:58:53.339
don't have any more time, sadly, but I
guess people know how to connect to you
00:58:53.339 --> 00:58:59.299
and contact derJoram if they want to know
anything more.
00:58:59.299 --> 00:59:14.869
rC3 postroll music
00:59:14.869 --> 00:59:40.000
Subtitles created by c3subtitles.de
in the year 2020. Join, and help us!