35C3 - What is Good Technology?

35C3 Intro music

Herald Angel: We at the Congress, we not
only talk about technology, we also talk

about social and ethical responsibility.
About how we can change the world for

good. The Good Technology Collective
supports the development guidelines...

sorry, it supports the development process
of new technology with ethical engineering

guidelines, that offer a practical way to
take ethic and social impact into account.

Yannick Leretaille - and I hope this was
okay - will tell you more about it.

Please welcome on stage with a very warm applause
Yann Leretaille.

applause

Yannick Leretaille: Hi, thanks for the
introduction. So before we start, can you

kind of show me your hand if you, like,
work in tech building products as

designers, engineers, coders, product
management? OK, so it's like 95 percent,

90 percent. Great. Yeah. So, today we kind
of try to answer the question: What is

good technology and how can we build
better technology. Before that, shortly

something of me. So I am Yann. I'm French-
German. Kind of a hacker, among the CCC

for a long time, entrepreneur, like, co-
founder of a startup in Berlin. And I'm

also founding member of the Good
Technology Collective. The Good

Technology Collective was founded about a
year ago or almost over a year now actually

by a very diverse expert council
and we kinda have like 3 areas of work.

The first one is trying to educate the
public about current issues with

technology, then, to educate engineers or
to build better technology, and then

long-term hopefully one day we'll be
able to work like in legislation as well.

Here, it's a bit of what we achieved so
far. We've like 27 council members now. We

have several media partnerships and
published around 20 articles, that's kind

of the public education part. Then we
organized or participated in roughly 15

events already. And we are now publishing
one standard, well, kind of today

actually, and
applause

and if you're interested in what we do,
then, yeah, sign up for the newsletter and

we keep you up to date and you can join
events. So as I said the Expert Council is

really, really diverse. We have everything
from people in academia, to people in

government, to technology makers, to
philosophers, all sorts, journalists.

And the reason that is the case is that a year
ago we kind of noticed that in our own

circles, like, as technology makers or
academics, we were all talking about a lot

of, kind of, voice on development and
technology, but no one was really kind of

getting together and looking at it from
all angles. And there have been a lot of

very weird and troublesome developments in
the last two years. I think we really

finally feel, you know like, the impact of
filter bubbles. Something we have talked

for like five years, but now it's like,
really like, you know, deciding over

elections and people become politically
radicalized and society is, kind of,

polarized more because they only see a
certain opinion. And we have situations

that we only knew, like, from science
fiction, just kind of, you know, pre-crime,

like, governments, kind of, over-arching
and trying to use machine learning to make

decisions on whether or not you should go
to jail. We have more and more machine

learning and big data and automization
going into basically every single aspect

of our lives and not all of it been has
been positive. You know, like, literally

everything from e-commerce to banking to
navigating to moving to the vault now goes

through these interfaces. That present us
the data and a slice of the world at a time.

And then at the same time we have
really positive developments. Right? We have

things like this, you know, like space
travel, finally something's happening.

And we have huge advances in medicine. Maybe
soon we'll have, like, self-driving cars

and great renewable technology. And it kind
of begs the question: How can it be that

good and bad use of technology are kind of
showing up at such an increasing rate in

this, like, on such extremes, right? And
maybe the reason is just that everything

got so complicated, right? Data is
basically doubling every couple of years,

so no human can possibly process anymore.
So we had to build more and more complex

algorithms to process it, connecting more
and more parts together. And no one really

seems to understand it anymore, it seems.
And that leads to unintended consequences.

I've an example here: So, Google Photos –
this is actually only two years ago –

launched a classifier to automatically go
through all of your pictures and tell you

what it is. You could say "Show me the
picture of the bird in summer at this

location" and it would find it for you.
Kind of really cool technology, and they

released it to, like, a planetary user
base until someone figured out that people

of color were always marked as gorillas.
Of course it was a huge PR disaster, why

somehow no one found out about this before
it came out... But now the interesting thing

is: In two years they didn't even manage
to fix it! Their solution was to just

block all kind of apes, so they're just
not found anymore. And that's how they

solved it, right? But if even Google can't
solve this... what does it mean?

And then, at the same time, you know,
sometimes we seem to have, kind of,

intended consequences?

I have an example... another example here:
Uber Greyball. I don't know if anyone

heard about it. So Uber was very eager to
change regulation and push the services

globally as much as possible, and kind of
starting a fight with, you know, all the

taxi laws and regulation, and taxi
drivers in the various countries around the

world. And what they realized, of course,
is that they didn't really want people to

be able to, like, investigate what they
were doing or, like, finding individual

drivers. So they built this absolutely
massive operation which was like following

data in social media profiles, linking,
like, your credit card and location data

to find out if you were working for the
government. And if you did, you would just

never find a car. It would just not show
up, right? And that was clearly

intentional, all right. So at the same
time they were pushing, like, on, like,

the lobbyism, political side to change
regulation, while heavily manipulating the

people that were pushing to change the
regulation, right? Which is really not a

very nice thing to do, I would say.

And...

The thing that I find, kind of...
worrisome about this:

No matter if it's intended or unintended,
is that it actually gets worse, right?

The more and more systems we
interconnect, the worse these consequences

can get. And I've an example here: So this
is a screenshot I took of Google Maps

yesterday and you notice there are, like,
certain locations... So they're kind of

highlighted on this map and I don't know
if you knew it but this map and the

locations that Google highlight look
different for every single person.

Actually, I went again and looked today
and it looked different again. So, Google

is already heavily filtering and kind of
highlighting certain places, like, maybe

this restaurant over there, if you can see
it. And I would say, like, from just

opening the map, that's not obvious to you
that it's doing that. Or that it's trying

to decide for you which place is
interesting for you. However, that's

probably not such a big issue. But the
same company, Google with Waymo, is also

developing this – and they just started
deploying them: self-driving cars. They're...

...still a good couple of years away from
actually making it reality, but they are

really – in terms of, like, all the others
trying it at the moment – the farthest, I

would say, and in some cities they started
deploying self-driving cars. So now, just

think like 5, 10 years into the future
and you have signed up in your Google...

...self-driving car. Probably you don't
have your own car, right? And you go in

the car and you are like: "Hey, Yann, where
do you want to go?" Do you want to go to

work? Because, I mean obviously that's why
I probably go most of the time. Do you

want to go to your favorite Asian
restaurant, like the one we just saw on the

map? Which is actually not my favorite,
but the first one I went to. So Google

just assumed it was. Do you want to go to
another Asian restaurant? Because,

obviously, that's all I like. And then
McDonald's. Because, everyone goes there.

And maybe the fifth entry is an
advertisement. And you would say: Well,

Yann, you know, that's still kind of fine,
but it's OK because I can still click on:

'No, I don't want these 5 options, give me,
like, the full map.' But now, we went back

here. So, even though you are seeing the
map, you're not actually not seeing all

the choices, right? Google is actually
filtering for you where it thinks you want

to go. So now we have, you know, the car
like this symbol of mobility and freedom.

It enables so much change in our society
that it's actually reducing the part of

the world that you see. And because, I
mean these days they call it AI, I think

it's just machine learning, because these
machine learning algorithms all do pattern

matching and basically just can recognize
similarities. When you open the map and

you zoom in and you select a random place,
it would only suggest places to you where

other people have been before. So now the
restaurant that opened around the corner

you'll probably not even discover it
anymore. And no one will. And it will

probably close. And the only ones that
will stay are the ones that are already

established now. And all of that without
being really obvious to anyone who would

use the technology. Because it has become
like kind of a black box. So, I do want

self-driving cars, I really do. I don't
want a future like this. Right. And if we

want to prevent that future, I think we
have to first ask a very simple question,

which is: Who is responsible for designing
these products? So, do you know the

answer?
audience: inaudible

Yann: Say it louder.
audience: We are.

Yann: Yeah, we are. Right. That's a really
frustrating thing about it that actually

gets us, right, as engineers and
developers. You know we are always driven

by perfection. We want to create, like,
the perfect code sources. One problem,

really, really nice. You know. Chasing the
next challenge over and over trying to be

first. But we have to realize that at the
same time we are kind of working on

frontier technologies, right, on things,
technology, that are really kind of on the

edge of values and norms we have in
society. And if we are not careful and

just, like, focus on our small problem and
don't look at the big picture, then we

have no say in on which side of the coin
the technology will fall. And probably it

will take a couple of years, or by that
time we alreaday moved on, I guess. So.

It's just that technology has become so
powerful and interconnected and impactful,

because we are not building stuff that
it's not affecting like 10 or 100 people

or a city but literally millions of
people, that we really have to take a step

back and not only look at the individual
problem as the challenge but also the big

picture. And I think if you want to do
that we have to start by asking the right

questions. And the first question of
course is: What is good technology? So,

that's also the name of the talk.
Unfortunately, I don't have a perfect

answer for that. And probably we will
never find a perfect answer for that. So,

what I would like to propose is to
establish some guidelines and engineering

processes that help us to build better
technology. To kind of ensure the same

where we have quality insurance and
project management systems and processes

to, like, kind of, this you were tasked
with. And companies that what we build is

actually, has a net positive outcome for
society. And we call it the good

technology standard. We've kind of been
working that over, the last year, and we

really wanted to make it really practical.
And what we kind of realized is that if you

want to make it practical you have to make
it very easy to use and also mostly,

actually what was surprising, just ask the
right questions. So, what is important

though, is that if you adapt the standard,
it has to be in all project phases. It has

to involve everyone. So, from, like, the
CTO to, like, the product managers to

actually legal. Today, legal has this
interesting role, where you develop

something and then you're like: Okay, now,
legal, make sure that we can actually ship it.

And that's what usually happens. And,
yeah, down to the individual engineer. And

if it's not applied globally and people
start making exceptions then of course it

won't be worth very much. Generally, we
kind of identified four main areas that we

think are important, kind of defining,
kind of an abstract way, if a product is

good. And the first one is empowerment. A
good product should empower its users. And

that's kind of a tricky thing. So, as
humans we have very limited decision

power. Right? And we are faced with, as I
said before, like, this huge amount of

data and choices. So it seems very natural
to build machines and interfaces that try

to make a lot of decisions for us. Like
the Google Maps one we saw before. But we

have to be careful because if we do that
too much then the machine ends up making

all decisions for us. So often, when you
develop something you should really ask

yourself, like, in the end if I take
everything together am I actually

empowering users, or am I taking
responsibility away from them? Do I

respect the individual choice? Why does he
say: I don't want this, or they give you

their preference, do we actually respect
it or do we still try to, you know, just

figure out what is better for them. Do my
users actually feel like they benefit from

using the product? So, I couldn't,
actually not a lot of people ask themselves,

because usually you think like in terms
of: Are you benefiting your company? And I

think what's really pressing in that
aspect: does it help the users, the humans

behind it, to grow in any way. If it helps
them to be more effective or faster or do

more things or be more relaxed or more
healthy, right, then it's probably positive.

But if you can't identify any of these,
then you really have to think about it.

And then, in terms of AI, in machine
learning, are we actually kind of

impacting their own reasoning so that they
can't make proper decisions anymore. The

second one is Purposeful Product Design.
That one is one that, it's been kind of a

pet peeve for me for a really long time.
So these days we have a lot of products

that are kind of like this. I don't have
something specifically against Philips

Hue, but there seems to be, like, this
trend that is kind of, making smart

things, right? You take a product, put a
Wi-Fi chip on it, just slap it on there.

Label it "smart", and then you make tons
of profit, right? And a lot of these new

products we've been seeing around us,
like, everyone is saying, like, oh yeah,

we will have this great interconnected
feature, but most of them are actually not

changing the actual product, right, like,
the Wi-Fi connected washing machine today

is still a boring washing machine that
breaks down after two years. But it has

Wi-Fi, so you can see what it's doing when
you're in the park. And we think we should

really think more in terms of intelligent
design. How can we design it in the first

place so it's intelligent, not smart. That
the different components interact in a

way, that it serves a purpose well, and
the kind of intelligent by design

philosophy is, when you start using your
product you kind of try to identify the

core purpose of it. And based on that, you
just use all the technologies available to

rebuild it from scratch. So, instead of
building a Wi-Fi connect washing machine

would actually try to build a better
washing machine. And if it ends up having

Wi-Fi, then that's good, but it doesn't
has to. And along each step actually try

to ask yourself: Am I actually improving
washing machines here? Or am I just

creating another data point? And yeah, a
good example for that is, kind of, a

watch. Of course it's very old and old
technology, it was invented a long time

ago. But back when it was invented it was
for something you could have on your arm

or in your pocket in the beginning and it
was kind of a natural extension of

yourself, right, that kind of enhances
your senses because it's never there, you

don't really feel it. But when you need it
it's always there and then you can just

look at it and you know the time. And that
profoundly changed how, like, we humans

actually worked in society because we
couldn't meet in the same place at the

same time. So, when you build a new
product try to ask yourself what is the

purpose of the product, who is it for.
Often I talk to people and they talk to me

for one hour, what like, literally the
details of how they solved the problem but

they can't tell me who their customer is.
Then does this product actually make

sense? Do I have features, and these
distract my users, that I maybe just don't

need. And can I find more intelligent
solutions by kind of thinking outside of

the box and focusing on the purpose of it.
And then of course what is the long term

product vision like, where do we want this
to go? This kind of technology I'm

developing in the next years. The next one
is kind of, Societal Impact, that goes

into what I talked about in the beginning
with all the negative consequences we have

seen. A lot of people these days don't
realize that even if you're, like, in a

small start up and you're working on, I
don't know, a technology, or robots, or

whatever. You don't know if your
algorithm, or your mechanism, or whatever

you build, will be used by 100 million
people in five years. Because this has

happened a lot, right? So, only when
starting to build it you have to think: If

this product would be used by 10 million,
100, maybe even a billion people, like

Facebook, would it have negative
consequences? Right, because then you get

completely different effects in society,
completely different engagement cycles and

so on. Then, are we taking advantage of
human weaknesses? So this is arguably

something that's just their technology. A
lot of products these days kind of try to

hack your brain, what, we understand
really well how, like, engagement works

and addiction. So a lot of things, like
social networks, actually have been

focusing, you know, and also built by
engineers, you know, trying to get a

little number from 0.1% to 0.2%, can mean
that you just do extensive A/B testing,

create an interface that no one can stop
looking at. You just continue scrolling,

right? You just continue, and two hours
have passed and you haven't actually

talked to anyone. And this attention
grabbing is kind of an issue and we can

see that Apple actually now implemented
screen time and they actually tell you how

much time you spend on your phone. So
there's definitely ways to build

technology that even helps you to get away
from these. And then for everything that

involves AI and machine learning, you
really have to take a really deep look at

your data sets and your algorithms because
it's very, very easy to build in biases

and discrimination. And again, if you it
applied to all of society many people who

are less fortunate, or more fortunate, or
they're just different, you know they just

do different things, kind of fall out of
the grid and now suddenly they can't,

like, [unintelligible] anymore. Or use
Uber, or Air B'n'B, or just live a normal

life, or do financial transactions. And
then, kind of what I said in the

beginning, not only look at your product
but also, if you combine it with other

technologies that are upcoming, are there
certain combinations that are dangerous?

And for that I kind of recommend to do,
like, some techno or litmus test to just

try to come up with the craziest scenario
that your technology could entail. And if

it's not too bad then, probably good. The
next thing is, kind of, sustainability. I

think in today's world it really should be
part of a good product, right. The first

question is of course kind of obvious. Are
we limiting product lifetime? Do we maybe

have planned obsolescence, or if we
build something that is so dependent on so

many services and we're not only going to
support it for one year anyways, that

basically it will have to be thrown in the
trash afterwards. Maybe it would be

possible to add a standalone node or a
very basic fallback feature so that at

least the products continues to work.
Especially if you talk about things like

home appliances. Then, what is the
environmental impact? A good example here

would be, you know, crypto currencies who
are now using as much energy as certain

countries. And when you consider that just
think like is there maybe an alternative solution

that doesn't have such a big impact. And
of course we are still capitalism, it has

to be economically viable, but often there
aren't, often it's again just really small

tweaks. Then of course: Which other
services are you working with? But for

example I would say, like, as european
companies, we're in Europe here, maybe try

to work mostly with suppliers from Europe,
right, because you know they follow GDPR

and strict rules, and in a sense the US.
Or check your supply chain if you build

hardware. And then for hardware
specifically that's because also I have,

like, we also do hardware in my company, I
always found that interesting. We're kind

of in a world where everyone tries to
save, like, the last little bit of money

out of every device that is built and
often makes the difference between plastic

and metal screws like half a cent, right.
And at that point it doesn't really change

your margins much. And maybe as an
engineer, you know, just say no and say:

You know, we don't have to do that. The
savings are too small to redesign

everything and it will impact upon our
quality so much that it just breaks

earlier. These are kind of the main four
points. I hope that makes sense. Then we

have two more, kind of, additional
checklists. The first one is data

collection. So really, just if, especially
like in terms of like IOT, you know,

everyone focuses on kind of collecting as
much data as possible without actually

having an application. And I think we
really have to start seeing that as a

liability. And instead try to really
define the application first, define which

data we need for it, and then really just
collect that. And we can start collecting

more data later on. And that can really
prevent a lot of these negative cycles we

have seen. By just having machine learning
organisms run on of it kind of

unsupervised and seeing what comes out.
Then also kind of really interesting I

found that, many times, like, a lot of
people are so fascinated by the amount of

data, right, just try to have as many data
points as possible. But very often you can

realize exactly the same application with a
fraction of data points. Because what you

really need is, like, trends. And that
usually also makes the product more

efficient. Then how privacy intrusive is
the data we collect? Right. There's a big

difference between, let's say, the
temperature in this building and

everyone's individual movements here. And
if it is privacy intrusive then we should

really, really think hard if we want to
collect it. Because we don't know how it

might be used at a later point. And then,
are we actually collecting data without

people realizing that they do it, right,
especially if we look at Facebook and

Google. They're collecting a lot of data
without really implicit consent. But of

course at some point you like all agreed
to the privacy policy. But it's often not

clear to you when and which data is
collected. And that's kind of dangerous

and kind of in the same way if you kind of
build dark patterns into your app. They

kind of fool you into sharing even more
data. I had, like, an example that someone

told me yesterday. I don't if you know
Venmo which is this American system where

you pay each other with your smartphone.
Basically to split the bill in a

restaurant. By default, all transactions
are public. So, like 200 million public

transactions which everyone can see,
including the description of it. So for

some of the more maybe not so legal
payments that was also very obvious,

right? And it's totally un-obvious when
you use the app that that is happening. So

that's definitely a dark pattern that
they're employing here. And then the next

point is User Product Education and
Transparency. Is a user able to understand

how the product works? And, of course, we
can't really ever have a perfect

explanation of all the intricacies of the
technology. But these days for most people

almost all of the apps, the interfaces,
the building technology and tech. This is

a complete black box and no one is really
doing an effort to explain it to them why

most companies advertise it like this
magical thing. But that just leads to kind

of this immunization where you just look at
it and you don't even try to understand

it. I'm pretty sure that no one ever,
like, these days is still opening up a PC

and trying looking at the components,
right, because everything is in tablet and

it's integrated and it's sold to us like
this magical media consumption machine.

Then, are users informed when decisions
are made for them? So we had that in

Empowerment, that we should try to reduce
the amount of decisions we make for the

user. But sometimes, that's a good thing
to do. But then, is it transparently

communicated? I would be totally fine with
Google Maps filtering out for me the

points of interest if it would actually
tell me that it's doing that. And if you

can't understand why it made that decision
and why it showed me this place. And maybe

also have a way to switch it off if I
want. But today we seem to kind of assume

that we know better for the people why
it's, so we found the perfect algorithm

that has a perfect answer. So we don't
even have to explain how it works, right?

We just do it and people will be happy.
But then we end up with is very negative

consequences. And then, that's more like a
marketing thing, how is it actually

advertised? I find it, for example, quite
worrisome that things like Siri and

Alexa and Google home are, like, sold as
these magical AI machines that make your

life better, and are you personal
assistant. When in reality they are

actually still pretty dumb, pattern
matching. And that also creates a big

disconnect. Because now we have children
growing up who actually think that Alexa

is a person. And that's kind of dangerous.
And I think we should try to prevent that

because for these children, basically, it
kind of creates this veil and it's

humanized. And that's especially dangerous
if then the machine starts to make

decisions for them. And suggestions
because they will take them as if a human

did it for them. So, what is that? So,
these are kind of the main areas. Of course

it's a bit more complicated. So we just
published the standard today in the first

draft version. And it's basically three
parts of science introduction, kind of the

questions and checklists that you just saw.
And then actually how to implement it in

your company, which processes to have, at
which point you basically should have

kind of a feature gate. And I would kind of
ask everyone to go there, look at it,

contribute, shared it with people. We hope
that we'll have a final version ready kind

of in Q1 and that by then people can start
to implement it. Oh, yeah. So, even though

we have this standard, right, I want to
make it clear having such a standard and

implementing it in your organization or
for yourself or your product is great. It

actually doesn't remove your
responsibility, right? This can only be

successful if we actually all accept that
we are responsible. Right? If today I

build a bridge as a structural engineer
and the bridge breaks down because I

miscalculated, I am responsible. And I
think, equally, we have to accept that if

we build technology like this we also have
to, kind of, assume that responsibility.

And before we kind of move to Q&A, I'd
like to kind of take the citations. This

is Chamath Palihapitiya, former Facebook
executive, from the really early times.

And also, around a year ago when we
actually saw the GTC he said this in a

conference: "I feel tremendous guilt. I
think in the back in the deep restlessness

of our mind we knew something bad could
happen. But I think the way we defined it

is not like this. It is now literally at a
point where I think we have created

tools that are ripping apart the social
fabric of how society works." And

personally, and I hope the same for you, I
do not want to be that person that five

years down the line realizes that they
built that technology. So if there is one

take-away that you can take home from this
talk, then to just start asking yourself:

What is good technology, what does it mean
for you? What does it mean for the

products you build and what does it mean
for your organization? Thanks.

applause

Herald: Thank you. Yann Leretaille. Do we
have questions in the room? There are

microphones, microphones number 1, 2, 3,
4, 5. If you have a question please speak

loud into the microphone, as the people in
the stream want to hear you as well.

I think microphone number 1 was the fastest.
So please.

Question: Thank you for your talk. I just
want to make a short comment first and

then ask a question. I think this last
thing you mentioned about offering users

the options to have more control of the
interface there is also a problem that

users don't want it. Because when you look
at the statistics of how people use online

web tools, only maybe 5 percent of them
actually use that option. So companies

remove them because for them it seems like
it's something not so efficient for user

experience. This was just one thing to
mention and maybe you can respond to that.

But what I wanted to ask you was, that all
these principles that you presented, they

seem to be very sound and interesting and
good. We can all accept them as

developers. But how would you propose to
actually sell them to companies. Because

if you adopt a principle like this as an
individual based on your ideology or the

way that you think, okay, it's great it
will work, but how would you convince a

company which is driven by profits to
adopt these practices? Have you thought of

this and what's your idea about this?
Thank you.

Yann: Yeah. Maybe to the first part.
First, that giving people choice is

something that people do not want and
that's why companies removed it. I think

if you look at the development process
it's basically like a huge cycle of

optimization and user testing geared
towards a very specific goal, right, which

is usually set by leadership which is,
like, bringing engagement up or increase

user amount by 200 percent. So I would say
the goals were, or are today, mostly

misaligned. And that's why we end up with
interfaces that are in a very certain way,

right? If we set the goals
differently, and I mean that's why we have

like UI and UX research. I'm very sure we
can find ways to build interfaces that are

just different. And still engaging, but
also give that choice. To the second

question. I mean it's kind of interesting.
So I wouldn't expect a company like Google

to implement something like this, because
it's a bit against that. This is more by

that point probably but I've met a lot of,
like, also high level executives already,

who were actually very aware of kind of
the issues of technology that they built.

And there is definitely interest there.
Also, more like industrial side, and so

on, especially, it seems like self-driving
cars to actually adopt that. And in the

end I think, you know, if everyone
actually demands it, then there's a pretty

high probability that it might actually
happen. Especially, as workers in the tech

field, we are quite flexible in the
selection of our employer. So I think if

you give it some time, that's definitely
something that's very possible. The second

aspect is that, actually, if we looked at
something like Facebook, I think they

overdid it. Say, optimize that so far and
push the engagement machine and kind of

triggering like your brain cells to
never stop being on the site and keeps

scrolling, that people got too much of it.
And now they're leaving the platform in

droves. And of course Facebook would not
go down, they own all these other social

networks. But for the product itself. as
you can see, that, long term it's not even

necessarily a positive business outcome.
And everything we are advertising here

still also to have very profitable businesses,
right, just tweaking the right screws.

Herald: Thank you. We have a question from
the interweb.

Signal Angel: Yes. Fly asks a question

that goes into a similar direction. In
recent months we had numerous reports

about social media executives forbidding
their children to use the products they

create at work. I think these people know
that their products are made addictive

deliberately. Do you think your work is
somewhat superfluous because big companies

are doing the opposite on purpose.
Yann: Right. I think that's why you have

to draw the line between intentional and
unintentional. If we go to intentional

things like what Uber did and so on. At
some point it should probably become a

legal issue. Unfortunately we are not
there yet and usually regulation is kind

of lagging way behind. So I think for now
we should focus on, you know, the more

unintentional consequences, of which there
are plentiful and kind of appeal to the

good in humans.
Herald: Okay. Microphone number 2 please.

Q: Thank you for sharing your ideas about
educating the engineer. What about

educating the customer, the consumer who
purchases the product.

Yann: Yeah. So that's a really valid
point. Right. As I said I think

[unintelligible] like part of your product
development. And the way you build a

product should also be how you educate
your users on how it works. Generally, we

have a really big kind of technology
illiteracy problem. Things have been

moving so fast in the last year that most
people haven't really caught up and they

just don't understand things anymore. And
I think again that's like a shared

responsibility, right? You can't just do
that in the tech field. You have to talk

to your relatives, to people. That's why
we're doing, like, this series of articles

and media partnerships to kind of explain
and make these things transparent. One

thing we just started working on is a
children's book. Because for children,

like, the entire world just exists with
this shiny glass surfaces and they don't

understand at all what is happening. But
it's also primetime to explain to them,

like, really simple machine learning
algorithms. How they work, how like,

filterbubbles work, how decisions are
made. And if you understand that from an

early age on, then maybe you'll be able to
deal with what is happening. In a way

better, an educated way. But I do think
that is a very long process and so only if

we start and the more work we invest in
that, the earlier people will be better

educated.
Herald: Thank you. Microphone number 1

please.
Q: Thanks for sharing your insights. I

feel like, while you presented these rules
along with their meaning, the specific

selection might seem a bit arbitrary. And
for my personal acceptance and willingness

to implement them it would be interesting
to know the reasoning, besides common

sense, that justifies this specific
selection of rules. So, it would be

interesting to know if you looked at
examples from history, or if you just sat

down and discussed things, or if you just
grabbed some rules out of the air. And so

my question is: What influenced you for
the development of these specific rules?

Yann: It's a very complicated question. So
how did we come up this specific selection

of rules and also, like, the main building
blocks of what we think should good

technology be. Well, let's say first what
we didn't want to do, right. We didn't

want to create like a value framework and
say, like, this is good, this is bad,

don't do this kind of research or
technology. Because this would also be

outdated, it doesn't apply to everyone. We
probably couldn't even agree in the expert

council on that because it's very diverse.
Generally, we try to get everyone on the

table. And we talked about issues we had,
like, for example me as an entrepreneur. And when

I was, like, in developing products with
our own engineers. Issues we've seen in terms

of public perception. Issues we've seen,
like, on a more governmental level. Then

we also have, like, cryptologists in
there. So we looked at that as well and

then we made a really, really long list
and kind of started clustering it. And a

couple of things did get cut off. But
generally, based on the clustering, these

were kind of the main themes that we saw.
And again, it's really more of a tool for

yourself as a company that developers,
designers and engineers to really

understand the impact and evaluate it. Right.
This is what these questions are

aimed at. And we think that for that they
do a very good job.

From microphone 1: Thank you.
Herald: Thank you. And I think. Microphone

number 2 has a question again.
Q: Hi. I was just wondering how you've

gone about engaging with other standards
bodies, that perhaps have a wider

representation. It looks largely like from
your team of the council currently that

there's not necessarily a lot of
engagement outside of Europe. So how do

you go about getting representation from
Asia. For example.

Yann: No, at the moment you're correct the
GTC is mostly a European initaitive. We

are in talks with other organizations who
work on similar issues and regularly

exchange ideas. But, yeah, we thought we
should probably start somewhere. In Europe

is actually a really good place to start.
Like a societal discourse about technology

and the impact it has and also to to have
change. But I think if for example

compared to things like Asia or the US
where is a very different perception of

privacy and technology and progress and
like the rights of the individual Europe

is actually a really good place to do
that. And we can also see things like GDPR

regulation, that actually, ... It's kind
of complicated. It's also kind of a big

step forward in terms of protecting the
individual from exactly these kind of

consequences. Of course though, long term
we would like to expand this globally.

Herald: Thank you. Microphone number 1
again.

Q: Hello. Just a short question. I
couldn't find a donate button on your

website. Do you accept donations? Is money
a problem? Like, do you need it?

Yann: Yes, we do need money. However it's
a bit complicated because we want to stay

as independent as possible. So we are not
accepting project related money. So you can't

like say we want to do certain research
product with you, it has to be

unconditional. And the second thing we do
is for the events we organize. We usually

have sponsors that provide, like, venue
and food and logistics and things like

that. But that's an, ... for the event.
And again, I can't, like, change the

program of it. So if you want to do that
you can come into contact with us. We

don't have a mechanism yet for individuals
to donate. We might add that.

Herald: Thank you. Did you think about
Patreon or something like that?

Yann: We thought about quite a few
options. Yeah, but it's actually not so

easy to not fall into the trap that,
like, as organizations in space have been,

like, Google at some point sweeps in and
it's like: Hey, do you want all this cash.

And then very quickly you have a big
conflict of interest. Even if you don't

want that to happen it starts happening.
Herald: Yeah right. Number 1 please.

Q: I was wondering how do you unite the
second and third points in your checklist.

Because the second one is intelligence by
design. The third one is to take into

account future technologies. But companies
do not want to push back their

technologies endlessly to take into
account future technologies. And on the

other hand they don't want to compromise
their own design too much.

Yann: Yeah. Okay. Okay. Got it. So you
were saying if we should always stop

these, like, future scenarios and the
worst case and everything and incorporate

every possible thing that might happen in
the future we might end up doing nothing

because everything looks horrible. For
that I would say, like, we are not like

technology haters. We are all from areas
working in tech. So of course the idea is

that you can just take a look at what is
there today and try to make an assessment

based on that. And the idea is if you look
it up and meet the standards that over

time actually you try to,... When you add
new major features to look back at your

assessment from before and see if it
changed. So the idea is you kind of create

a snapshot of how it is now. And this kind
of document that you end up as part of

your documentation kind of evolved over
time as your product changes and the

technology around it changes as well.
Herald: Thank you. Microphone number 2.

Q: So thanks for the talk and especially
the effort. Just to echo back the

question that was asked a bit before on
starting with Europe. I do think it's a

good option. What I'm a little bit worried
is it might be the only option. It might

become irrelevant rather quickly because
it's easy to do, it's less hard to

implement. Maybe in Europe now. Okay. The
question is. It might work in Europe now

but if Europe doesn't have the same
economical power it cannot bog in as much

politically with let's say China or the US
in Silicon Valley. So will it still be

possible and relevant if the economical
balance shifts?

Yann: Yes, I mean we have to start
somewhere, right? Just saying "Oh,

economical balance will shift anyway,
Google will invent singularity, and that's

why we shouldn't do anything" is, I think,
one of the reasons why we actually got

here, why it kind of is this assumption
that there is like this really big picture

that is kind of working against us, so we
all do our small part to fulfill that

kind of evil vision by not doing anything.
I think we have to start somewhere and I

think for having operated for one year, we
have been actually quite successful so far

and we have a good progress. And I'm
totally looking forward to make it a bit

more global and to start traveling more, I
think that like one event outside Europe

last year in the US and that will
definitely increase over time, and we're

also working on making kind of our
ambassadors more mobile and kind of expand

to other locations. So it's definitely on
the roadmap but it's not like yeah, just

staying here. But yeah, you have to start
somewhere and that's what we did.

Herald: Nice, thank you. Number 1 please.
Mic 1: Yeah. One thing I haven't found was

– all those general rules you formulated
fit into the more general rules of

society, like the constitutional rules.
Have you considered that and it's just not

clearly stated and will be stated, or did
you develop them more from the bottom up?

Yann: Yes, you are completely right. So we
are defining the process and the questions

to ask yourself, but we are actually not
defining a value framework. The reason for

that is that societies are different, as I
said they are widely different

expectations towards technology, privacy,
how society should work, all the ones

about. The second one is that every
company is also different, right, every

company has their own company culture and
things they want to do and they don't want

to do. If I would say, for example, we
would have put in there "You should not

build weapons or something like that",
right, that would mean that all these

companies that work in that field couldn't
try to adapt it. And while I don't want

them to build weapons maybe in their value
framework that's OK and we don't want to

impose that, right. That's why I said in
the beginning we actually, we're called

the Good Technology Collective, we are not
defining what it is and I think that's

really important. We are not trying to
impose our opinion here. We want others to

decide for themselves what is good and
cannot support them and guide them in

building products that they believe are
good.

Herald: Thank you. Number two .
Mic 2: Hello, thanks for sharing. As

engineer we always want users to spend
more time to use our product, right? But

I'm working at mobile game company. Yep.
We are making, we are making a world that

users love our product. So we want users
spend more time in our game. So we may

make a lot of money, yeah, but when users
spend time to play our game they may lose

something. Yeah. You know. So how do we
think about the balance in a game, mobile

game. Yeah.
Yann: Hmm. It's a really difficult

question. So the question was like
specifically for mobile gaming. Where's

kind of the balance between trying to
engage people more and, yeah, basically

making them addicted and having them spend
all their money, I guess. I personally

would say it's about intent, right? It's
totally fine with a business model where

you make money with a game. I mean that's
kind of good and people do want

entertainment. But if you actively use,
like, research in how, like, you know,

like the brain actually works and how it
get super engaged, and if you basically

build in, like, gamification and
lotteries, which a lot of, I think, have

done, where basically your game becomes a
slot machine, right, you always want to

see the next opening of a crate
and see what you got. Kind of making it a

luck based game, actually. I think if you
go too far into that direction, at some

point you cross the line. Where that line
is you have to decide yourself, right,

some of it could be a good game and
dynamic but there definitely some games

out there, I would say with quite a reason
to say that they pushed to the limit quite

a bit too far. And if you actually look
how they did it because they wrote about

it, they actually did use very modern
research and very extensive testing to

really find out these, all these patterns
that make you addicted. And then it's not

much better than an actual slot machine.
And that probably we don't want.

Herald: So it's also an ethical question
for each and every one of us, right?

Yann: Yes.
Herald: I think there is a light and I

think this light means the interwebs has a
question.

Signal angel: I, there's another question
from ploy about practical usage, I guess.

Are you putting your guidelines at work in
your company? You said you're an

entrepeneur.
Yann: That's a great question. Yes, we

will. So we kind of just completed some
and there was kind of a lot of work to get

there. Once they are finished and released
we will definitely be one of the first

adopters.
Herald: Nice. And with this I think we're

done for today.
Yann: Perfect.

Herald: Yann, people, warm applause!

applause

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