Shall I just give the camera a quick nudge?
and I'm recording my screen. But... D'you want it a bit more...
I've got a shiny face. Just gonna de-shine with the cushion.
Why don't you just go and make telly, and do News n' that? All right. Let's do it,
Hello and welcome to BBC R&D Explains where we lift the
lid on our big projects and chat directly to the people behind them.
We've got a new and really interesting body of work to introduce you to called, New Forms of Value.
It's all about exploring what new data driven services
The BBC could provide in a way that adds value to people's lives.
Here's what's coming up in this episode,
we'll meet Max and hear all about how personal data stores
could give everyone control over their own data. In Episode two
we'll catch up with Alex to see the augmented reality experiences
he has been building. In Episode three we'll drop in with Leanne,
who's offering an alternative approach for evaluating content.
And finally in Episode four
we'll meet Ian who's thinking about how the internet has built
and what we could do to make it work better for society. Let's do it.
So that's already a lot to unpack and explains the let's jump
right in with fellow BBC R&Der Bill Thompson,
who is leading this work. Hi Bill - new forms of value, first
what's the background to this work. And what led us on to exploring this?
Fundamentally new forms of value asks the question: What could
people love the BBC for as well as radio and television in a world
where so many of us are connected by the internet using powerful
computers and laptops and mobile phones and all that sort of stuff.
What else could the BBC do.
OK, so we've got lots of projects going on within that space so tell
us. What are the main three areas that you're looking at? First data.
So how we use and store and look after people's
data and data around the services.
Then we were looking at human values the things that matter to people.
And how we can make sure that what the BBC offers reflects
those values and is good for people,
if you like, and the third area is the network itself,
the internet and how to make sure that the internet as a piece
of technology is able to serve the BBC's public purposes.
So that is an absolute huge body of work.
You're talking about literally every kind of layer. A lot of work going on.
So for the rest of this episode, we will dig into the
personal data area of work. Can you tell me about what exactly this is
and what's your approach to even start to explore this? At the heart of
what we're doing is an exploration of a technology called a personal data
store, which is a place that can hold the data about an individual securely
and give them control over when and how it is used by other organisations
by third parties by service providers by government. By whoever.
So Max Leonard is one of BBC R&D's project engineers and he's
leading the work on personal data stores and I caught up with him earlier to find out more about.
So with me now is Max Leonard. He's a project engineer here at BBC
R&D And he's doing some work on personal data stores. Hi Max.
Thank you so much for your time. Yeah. No worries. Good to see ya.
Excellent. So tell us what exactly is a personal data
store and why are you exploring it.
So as long as there's been digital systems that store
personal data. The usual way to do things is to collect it all and
put it in a big database. So you have all the personal data
that might support your service in one great big store.
Now there's a number of problems with that. So say if you're on a
social network and you want to add a friend from a different social network
well you can't because that service is welded to
the main data store of the service it comes from. The other problem is
things like data leaks, attacks and etc etc.
And also once you start looking into the kind of
architecture, the way that a lot of these big systems are built,
then it becomes very difficult, technically, to be able to kind of
pull your data out on separate and do other usual things with it.
So rather than having your data sorta spread out in the big data stores
of all the services that you use. What would it look like if you
had a single store for all your personal data that the services
could come in and access on a per transaction basis and use and
then essentially forget. And what that would effectively mean is, one
tt would allow you to move your data around services without
having to pull it out of one service and somehow port
it to another, and it would also open up like innovation.
Left, right and centre because now if someone wants to come along
and create a new search engine or a new shopping system or
a new social network. They don't have to amass the data of millions
or billions of users beforehand to be able to provide and create competing service.
Now, suddenly, all you need to, in theory all you'd need to do
as a consumer is plug your personal data store into that service and you're off.
So at the BBC we thought it'd be a good idea to start looking at
personal data stores and how we could build systems services and
deliver what the BBC does best in a more sort of ethically conscious
and secure way that respects the privacy and agency of its audience.
Fantastic. So i can just imagine the sorts of things that would be possible
if you have access to this wealth of data from multiple sources linked them together in new ways.
So Max, the bulk of the work up until now has been building this
personal data store platform and one of the first services
that you've built, prototyped to try it all out is the recommender. So
can you tell us a bit about it. And how, exactly it looks to the audience.
What does the audience get out of it.
Sure. So basically what this is, is we have such a massive backlog
of material in the BBC that stretches back like a hundred years.
Of audio and video content and discovery
discovery of that content, especially as we've got tons of stuff that's rights cleared and
we could make available to people, but just finding it really difficult.
So we thought, wouldn't it be fun as a first go at this stuff to be
able to create a new recommender. So, the basic way this thing works is
you sign up for it, you log in with your BBC account. Like any BBC service,
iplayer, whatever. And you get a personal data store created for you in the background.
this personal data store is, yes, it's running on our servers but corporately we can't access
What goes into it. So you go through a process that, then links your
existing media accounts that pulls in your BBC data and stuff from your
music streaming services and video streaming services and kinda gives you
back a holistic media profile of the things you might like the bands
you might be interested, etc etc. And once you,
you've kinda edited that, and... because there might be
things in there that you don't want to be in there. One of the problems
with a lot of services at the moment that offer recommendations
it doesn't get you much chance to remove things that are
affecting the algorithms in ways you don't want. So if you have,
I've got like two kids who watch cartoons all day and my iPlayer...
my recommendations are full of cartoons right, it's really annoying.
Same. Little tweaks, like that allow you to
edit this thing before it goes off to recommend you stuff, we allow that.
And basically it takes that media profile and performs
a whole bunch searches on the BBC archive, Sounds, iPlayer.
Sport, News etc, and gives you back as a list of recommendations
that are based on your BBC history, but are also based on the data
you have amassed elsewhere in your digital life.
And it's gone down very well. This is a very small internal prototype.
I have to say we are not gonna be launching a service
that does this any time in the near future.
But it proves the concept quite well. And then we've been
coming up with all sorts of new concepts that could use
this wealth of data we now have access to in completely new ways.
So we've had thoughts on what we could do in the worlds of health
finance and emotional wellbeing and all sorts of things that relate to
the current coronavirus crisis and things that could help people there.
So we've got this huge kind of raft of potential services we could build
and once we've finished with the recommended and we've tested the sort
of architecture and the platform that supports this kind of services
we are going to go on to prototype new, new ideas.
Absolutely fascinating. Fantastic stuff.
Looking forward to to see what comes out of it. What is the best way for
for our viewers to keep on top of the work?
Go to the R&D Website there's posts on there and on the R&D Blog
in which we'll be writing about this work as we go through the project
and also when we have completed our trials of the first stage.
So, Bill, we've heard from Max, all sounds great
in theory, but does it work?
Mostly. It's an experiment. There are bits of it that are really tricky.
We found some things are really quite hard getting all the bits to fit
together. But, yes. It is working to end to the point where we are
confident we can start showing it to people and getting them to try
it out and get some real research data from users really quite soon.
Well, that's it for this episode. As always let us know what you think
in the comments and don't forget to like and subscribe and tune in next
time where we'll meet Alex Nelson and get a first look at some brand
new AR experiences he's built all with public service in mind.