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Hello, everyone. I'm Detlev.
I'm the head of AI and data science research here at BT in
industrial park.
And I'm going to talk to you about doing the right thing
with data and AI,
AI as in artificial intelligence.
So recently, I learned that Santa is in breach of the GDPR,
which is the General Data Protection Regulation.
And the question is, why is that? What's wrong?
But if you remember, Santa has his list of naughty and nice
and uses this to decide who gets something for Christmas or
not.
So how does he collect this list?
And he puts names on it.
And is he asking anybody if it's okay to put the name on
this list?
And for how long is he keeping the list?
If you have been naughty five years ago, is that still
recorded on this list?
Or do you have a right to be forgotten
in the sense that you have been naughty at some point?
So there's this kind of data protection topic
that we want to talk about.
And Santa, of course, has to comply as well.
And that means when you collect names of people, data about
people,
and you put them in lists, then you have to follow certain
guidelines.
So first thing is you have to ask people
if they're happy that their names and details are on lists.
So you cannot just go out and collect personal data about
people
and keep them in lists.
People need to know about it and they need to say,
"Yeah, that's okay, I'm fine that my name and my details
are on this list."
And then when you have these lists, you need to tell them
what they are for.
So Santa needs to tell you, you are on this list to track
your behavior.
And to decide if you should get gifts for Christmas or not.
If you're not okay with this purpose, then you can tell
Santa,
"No, thank you very much, but that's not for me.
I don't want to be on this list and I don't want you to
track my behavior."
And Santa has to comply, he can't put your name on this
list anymore.
And in the same way, he has to get rid of the data at some
point
when it's no longer required.
So you can only store data for as long as you need it for
the.
purpose that you collected it for. These sort of
regulations have to be
followed and every business has to do this. You may have
come across the
repercussions of these regulations yourself when you go on
the internet and
you read websites or you use apps. So everybody probably
likes cookies
especially at this time of year but there are certain
cookies we are not so
fond of and mainly because they interrupt our enjoyment of
web pages
these days. If you go to a new web page that you haven't
visited before or you
start a new app for the first time then you usually see a
pop-up and this says
we are using cookies and you have to be okay with it. You
have to agree to the
use of cookies. If you're not happy with the use then you
can make certain
changes. And to be honest are you really reading this? Are
you always click on the
agree because you want to get to the content as quickly as
you can? How do you
actually look into it and try to understand what are these
cookies, what
are they being used for and what are your options? What can
you do in terms of
saying no I don't want you to store cookies. So what's a
cookie? A cookie is
a piece of information, a little bit of data, a small file
that your web browser
or your app stores on your device. And websites and
internet services are using
this to collect information about how you use these
services. So they basically
figure out what kind of information you look at, which
pages you open, how long
you might stay on a page, which ads you click and these
kind of information is
collected about you and is stored on your computer. So next
time you go to the
same page, the page can read this information and realize,
okay this is
this person who was here before, this person seems to be
interested in this
kind of part of the service that we offer. So maybe we use
this information
to adapt the kind of content that we show to the person.
This is the purpose
of cookies and it's also used to advertise to you. So
cookies are the main
technology behind advertising on the internet. So have you
ever had this
experience that you go somewhere to look at a product or
you buy something online
and then as you go along and visit other sites,
are popping up about the stuff that you just looked at or
that you bought. And so
you said why does this happen? How do they know that I
looked at something?
And this is done with these cookies. So when you, let's say,
you go shopping for
Christmas, you look at teddy bears and then you see that
these adverts
on pages that you visit suddenly reflect teddy bears or
other kinds of toys
related to teddy bears. And this happened because you
visited, let's say, a teddy
bear shop. This teddy bear shop has agreements with
advertisers. They place a
cookie on your device and this records the fact that you
have been interested
in teddy bears. And so the advertiser then picks this up
and when you visit
another web page or another service that advertises, then
this service decides on
the fly as you go there to show you an advert on teddy
bears because apparently
you're interested in it. So this happens in real time. So
they read the
cookie from your device, decide this is the interest for
this person and there's
even a bidding going on behind the scenes. So there are
different
advertisers that can bid for their ad to be placed on your
screen in real time.
And they pay depending on the kind of the value of the
service, the interest
that you have shown, how strong this interest is, and they
have their own kind
of models and they try to predict will you be interested in
this advert and
might you click on it and might you purchase something that
this advert
advertises. And there are also some other effects that can
happen based on this
technology. So maybe you have realized that you always see
the same type of
content when you go into your social network apps or if you
go on YouTube or
if you open up Netflix. Do you always see the same kind of
stuff being recommended
to you? And do you maybe see that the updates in your
social network feeds
have changed? Do you miss updates from certain friends that
you have seen in
the past but no longer see that? Or have you ever checked
if the search result
that you get in Google when you search for something and
you compare this to
the same search on your friend's device?
Have you ever noticed that the results are different?
That your search results are presented to you differently
than when your friend does
the same search on their device?
And again, this is happening through the use of these
cookies.
And it's called being trapped in a bubble.
So you always see the same kind of content, the same type
of information, because you
have been interested in something.
And the information that is recorded in these cookies
records these interests.
And then information providers, information service
providers, internet services, they
try to shape the content to your interest.
And obviously, they want you to be interested in the
service, they want you to spend time
with the service.
And so they flex the kind of information that they show to
you based on your interests.
That can be very useful, of course, if you are interested
in let's say, like me, I like
Marvel movies.
So when I open up Netflix Prime or whatever video service,
and there's a new Marvel movie
out, then I want to know, then it should be top on the list
for me.
And so that's a very useful kind of feature.
But if it then turns out that no other types of movies are
shown to me and I miss out other
movies that I might be interested in, then obviously, that
goes too far.
If it goes so far that everywhere I go on the internet, I'm
offered to buy Marvel merchandise,
then it also goes too far for me.
So how can this be kind of managed?
How can it be made responsible?
And one thing to realize is that the data that is being
collected is not just us visiting
a website.
We're basically shedding data like dust wherever we are,
whatever we do, we are producing data
through our devices and through our interactions with these
devices.
This can be our likes, when we like something on social
media, our location where we are,
when we check in into location, any click we do on a web
page or page views, how long
we stay on a page, all our kind of interactions with these
services.
And even things like your chats and emails might be mined
for information.
So you can, if you have a free email account, read the
terms and conditions.
Can the provider scan your emails for keywords and use this
data to advertise to you?
you or shape content for you. And so this happens unbeknownst
to us and this information is kind of
sucked up by all of these internet services and used to
profile us and to deliver content to us
and adverts to us. And all this information is not very
valuable to us but it's like gold test
on the internet because it enables a certain kind of
business to be done.
This data is also called behavioral data because it shows
you what you have done on the internet.
It shows your behavior on the internet and this is then
used to feed into prediction engines. So
if I know what you like, if I know what you have done in
the past on the internet, then I can make
an educated guess on what you're likely to be interested in.
And if I can make a good guess of
what you might be interested in, then I can shape the
information that I show you in the hope that
it makes you more likely to press on an ad and make a
purchase. So this information is not only
used to recommend things, it's also used to shape the
information you see and that can put you into
a bubble. That means you don't see anything else anymore.
And it's important to be aware of this,
that this can happen. So good ways of dealing with this is
to delete cookies regularly. So you can,
in any kind of app or web browser, you can always go to the
settings and say delete the cookies.
Sometimes cookies are useful because they automatically log
you into services
and they keep state when you visit an internet service and
they know, oh, it's you again, and you
were here before, so we can continue where you left off. So
it's a bit inconvenient when you
delete them. But you can also go into a kind of stealth
mode in many web browsers. Let's say you
want to purchase something and you don't want these
purchases to be tracked, you can use the
stealth mode to do this. And so it's just being aware that
these things are happening to you,
and then you can manage it. There are other issues around
data and AI. So the
These kind of prediction engines that predict what you're
interested in and what you might
want to see and what you might want to purchase, they are
built with machine learning.
Machine learning is a part of artificial intelligence or AI.
When you build these kind of AI systems from data, then you
can get other issues, not just
tracking people and influencing behavior of people in the
sense of making them click on
ads.
There's this issue which you have probably heard about that
facial image recognition
software is racially or gender biased.
So this software is more capable of recognizing white males
than dark skinned females.
And this is a problem with the data that has been used to
build these kind of facial image
recognition systems.
Other issues around AI are understanding that you're
actually interacting with an AI system.
So you may not have known that the cookies on your web
browser or on your device are
being used by an AI to predict things about you.
So it's generally considered to be good behavior to let
people know they're interacting with
an AI system.
You get chatbots these days that can talk as if they were
human and it's difficult to
realize that they're actually a machine.
So when you talk to something like an Alexa or Siri, you
can still tell this is not a
person that you're talking to.
But they have managed to build chatbots that speak so
naturally that you can't really tell.
And then you want to let people know you're not talking to
a person, you're talking to
an AI system.
What about if things go wrong?
So you may have heard about accidents that happened with
autonomous cars.
So they are controlled by an AI system.
This AI system has been trained with data.
And what happens if these systems make a mistake?
What are the repercussions of these mistakes?
Who's responsible?
Is it the person who provided the data?
Is it the person who trained the system or is it the person
who operates and runs the
system?
It becomes quite complicated in this context.
And then you can have AI systems that make decisions about
you.
So like in the cookie context, they make decisions about
what you might like and what the service
should show to you.
But in the same sense, they could make a decision about
you being able to buy a smartphone, for example, or to get
a loan or to get a mortgage? And what if
they just say no, you can't have it? How do you challenge
this? How do you say no, I should be
able to get this. Why do you say no, explain this to me.
This is another issue that we need to look
into when we work with AI. So the question is how do we do
the right thing when it comes to handling
data and using data for AI systems. So when we handle data,
then we want to make sure that it's
only used with informed consent. So people need to know
that the data is being used and what it is
being used for. It should only be used for the intended
purpose. So you can't say, okay, here's
Santa, he collects his name for the naughty and nice list.
And now it's being used to advertise
smartphones to you. That's not okay. So the purpose is
completely different.
You need to keep the data stored securely. So Santa has to
make sure nobody nicks his list
and uses the information for other purposes. And you can
only keep information as long as it is
required for the purpose you collected it for. Once this
purpose is fulfilled and it's done,
this information has to be destroyed. So one thing you
might want to find out for yourself,
who uses your data? So try and find out who uses your data.
You can look into terms and conditions
of websites. You can actually read the cookie pop up that
has this big allow all button and make
sure that you understand what they're asking you. It's
important to be aware of what's going on with
your data. When we go to AI and we use data to build AI
systems, then we want to make sure that
there's no bias in the data and the decisions we are making
with AI. That means the data has to
represent everybody fairly and equally. And we cannot just
focus on one group of people
when we build AI systems. And for this, it's very important
to have diversity in the data
and diversity in the people who build these systems.
Everybody kind of should get involved.
We should always let people know that they're interacting
with an AI system. So we shouldn't
be sneaky and just use an AI and don't tell people and
leave them in the belief that they're
interacting with a human. And we should understand how AI
works. And we should be able to explain it
because this is quite a challenge. Actually, the AI systems
that we are creating from data
can become quite complex and quite difficult to
to get our head around.
But we have to make an effort to make sure that we really
understand what they are doing
and we need to be able to explain to people what they're
doing.
We also need to realize that AI systems make mistakes and
we have to account for it.
And this is a particular feature or issue that comes out of
building systems from data
and not engineering them based on rules and understanding
and physical kind of conditions
and understanding natural laws.
You're building something from data.
That means we are showing it examples and say, I want you
to make a decision that represents
what you see in this data.
And this will never be 100% correct.
It will always be making some mistakes.
So you see this yourself when you browse the internet, you
get adverts saying, why are they
showing this to me?
I'm not interested in whatever that might be.
So these prediction engines get things wrong.
And so we have to realize that this happens and we have to
account for it and mitigate
any kind of negative effects that might have.
So one thing you might want to find out for yourself, what
is it that AI really does understand
what AI systems are doing, how they use data and what is
the impact of using this data?
It's not all bad.
There's a lot of AI for good out there.
So AI has a lot of potential to help the world to overcome
issues like climate change.
We can help out in medicine.
So AI can look at scans and might be able to help
specialists to detect illnesses quicker.
And if it is done in the right way, it is a very useful
technology and it will definitely
change the world as we know it.
And it's important to get involved.
So AI will have an impact on your life in the future.
So you should make an effort to try and understand what it
does, how it works and how it will
impact you.
And looking into these kind of AI for good initiatives.
So there's a website here shown and you'll get the links
later where you can go and try
and understand what kind of options and opportunities there
are for AI for good.
It's really important to get involved.
So we need diverse teams working in AI.
So we need more women to go into AI.
AI.
It is really important when you build something for people
that all people are involved.
So AI will have an impact on everyone.
So everyone kind of has to be involved in building it.
If only one part of the population builds it, then it will
be naturally biased to this
part.
So it is really important to get involved.
And it is a really interesting subject.
So you can do really cool and interesting stuff with it.
It is not all hacking code or working with numbers.
There's a lot of aspect to AI that you can get involved in
and that you can find out.
And I'll show you some websites and talks that you can
listen to, to understand what
it does.
It is relatively easy nowadays to find out how it all works.
There's a lot of material out there.
So there are interesting TED Talks, for example.
I would recommend that you look what Joy Buolamwini has to
say.
She has figured out that these facial image recognition
systems are biased and she has
founded the Algorithmic Justice League to fight against
bias in data and AI, which is
a really cool initiative.
And so I recommend that you look this up.
You can look at a fun website about how GDPR sold Christmas,
so you can understand how
data is really being impacted by GDPR and what the issues
are around handling data in
a responsible way.
There is the Ada Lovelace Institute, it's an institute here
in the UK that looks at
handling data and AI responsibly.
And they have a blog and they have lots of interesting
topics that you can read up on.
And if you want to get started and understand how AI works,
you can do a free course on
the Internet called Elements of AI, which is aimed at
people who haven't any kind of
previous training in AI.
So it's a fun course to do.
You can do it all online and it's free.
So I recommend that you have a look.
And here's a recommendation for your holiday reading list.
So if you prefer books to computers, then I would recommend
to have a look at the book
by Hannah Frye, Hello World, where she looks at how data
and AI are impacting us in the
years to come.
So thank you very much for listening and have a nice
Christmas.
Bye.
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