This has been a rich day already. I will try to keep it quite short.
So there is time for one or two questions, perhaps, and then for one for those who are interested in wine rather than questions.
So I will briefly talk to sort of three aspects of the work that we do at the Reuters
Institute for the Study of Journalism that concerns the role of A.I. in the area of news.
The first is how AI is used on news. The second one is how he is used by news organisations, and the third one is how A.I. features in the news.
And you might think that it's strange that someone who directs an institute that is committed to exploring the future of journalism.
I think a profession that people perhaps associate bit more with sort of ink stained hats or,
you know, stately August old broadcast us is interested in the eye and works in the eye.
But because our focus is on the future, and as Gina pointed out,
sometimes I think we focus a bit on the distant issues without recognising the
way in which analogies are already reshaping the present and the near future.
I will draw attention to a couple of things that are already happening around A.I.
that that is quite central to journalism and the way in which journalism can.
To the best of its imperfect ability in different countries around the world, try to play the different roles that we may associate with it.
Inform us by making the invisible world visible to the citizen of the modern state.
Help to portray the contending forces of our time so we can think about where we stand on the issues of the day and confront us,
if you will, with experience to go beyond our own immediate lived experience.
So where are we with A.I. in this?
Well, the first thing I want to point out is that arguably the biggest impact of A.I. as it exists today in practise in this case,
you know, mostly various forms of machine learning,
but also some forms of deep learning and neural networks is applied to news by other companies that do not
themselves provide news and is quite central to the way in which most of us navigate news and public information.
I'm talking, of course, about the role of platform companies that operate search services like Google Search or social
media platforms like Facebook that by now are the most widely used ways of accessing online news.
So other word is interest to it. Every year, we run a big survey that write a sensitive of digital news report where in 2019
we surveyed online news services in 38 different markets across the world,
and we and most of these people use a wide variety of different ways of getting news online.
But when we asked the follow up question about what is their main way of accessing news online,
only 29 percent identify going directly to the website or app with a news publisher as their main way of getting news online,
whereas more than two thirds identify various forms of site or access via search or social,
or also other forms of site doors like aggregators, for example.
And in 2019, for the first time, we had actually had a majority 53 percent of our respondents identifying various forms of algorithmic selection,
search social media aggregators as their main way of accessing news online.
So this is A.I. that is used on news content to filter it as all of us are voting with
our feet in terms of what are the channels we rely on to discover the news content.
And this, of course, leaves news organisations in a situation where they are in turn increasingly reliant
on the search engines and social media that all of us as end users are embracing.
And in turn, these rely on various forms of AI and machine learning amongst the many different
forms of automation that they use to near instantaneously rank content.
Whether it's in response to a search query or a response to the act of opening a
social media app or in the response to the act of accessing a news aggregator.
This is a AI down to news, so to speak, by other companies.
What about the news industry itself?
So a lot of the discussion has been around the sort of idea of so-called robot journalists and essentially the hope,
perhaps amongst people concerned about the expense side and the fear amongst
those who actually produce the journalism that all of us rely on as citizens,
that they would be replaced by systems akin to the tech generation that Katrina showed us.
Various forms of neural networks like to generate content automatically without human agency.
In fact, as is often the case with digital technology,
a lot of the initial embrace of A.I. in the news industry has been at the back end rather than the front end.
It's been around issues of recommendations. This is a survey of digital news leaders and we just published.
Earlier this month, more than 200 editors and chief CEOs and other leaders and news organisations from around
the world writing the forms of A.I. they consider most important for their organisation.
So various forms of automated recommendations and secondly various forms of commercial use, for example,
to predict the propensity that you might sign up as a subscriber for news organisation and thus target you and market to you in particular ways.
And only less so is the use of this sort of automated tagging introduction metadata and a light to display things more efficiently.
And there's actually very little focus on news gathering and so-called robot journalism in the traditional areas of concern.
From the point of view of many professional journalists and much more at the back end of data of targeting and of recommendations.
And of course, this in fact, is not so different from what the platforms are doing to journalism.
In fact, publishers are in many ways trying to follow the platforms and adopting to the best of their ability.
Some of the same technologies and here, of course, I think you can see resonances to some of the points that Alan drew up in the opening presentation
about the way in which an access effect or performance effect might lead to very different outcomes,
depending on who in fact, can use these technologies.
There are two major news organisations here in Oxford the Oxford Mail slash, Oxford Times and then the BBC Oxford.
And let's just say that the two organisations will have access to very different forms of technology,
as News Quest and the BBC have rather different resources available and different abilities to gather data.
For example, this might play out in quite different ways, depending on how the technology evolves.
The third area is the way in which AI features in news coverage itself.
I think Gina issued a call, if you will, for a public debate, not just around the ethics of A.I.
What do we consider to be good or bad forms of this technology or use of this technology, but also the politics of it?
How do we make collectively binding sessions again, a theme that Alan start from the beginning of the day as well?
I suppose I would say this as someone who both works on and cares deeply about professional journalism,
but because most of us have precious little personal insight into A.I. or the wider implications beyond our
experience as users where we mean it may often be invisible to us that these technologies are relied upon are used.
I think we rely, at least in part on the ability of journalism to inform us about the ways in which these technologies are used.
Who uses them for what and with what life implications.
If we are in fact a form of you as citizens on how we think this technology ought to be governed
and what we think of the ways in which is being put to use by different organisations,
including, of course, importantly, our own governments to do a variety of things that we may not find equally agreeable.
So how is this in fact covered in the news? Well, I think most of you will have if you have an interest in this area,
will come across articles that are illustrated with a still from various Terminator movies.
The sort of the fear of killer robots. And I think it's quite a resonant framing, if you will, of the issue.
And when we set out to try to understand how AI is covered in the UK news media.
Two years ago, at the beginning of a project,
I suppose our hypothesis was that that kind of sort of slightly sensationalist scaremongering would be quite prominent in the volume of coverage.
In fact, we found a rather different texture of the coverage,
which is that when we look at what the sources are and the locations that occupation news coverage of A.I. in the UK,
it is overwhelmingly driven by the industry itself.
So more than half, in fact, 60 percent of all the articles we identified that dealt with A.I. in the content.
Now, as of eight months of coverage in six mainstream news outlets here in the UK,
60 percent were occasioned by various forms of release, press release,
product launches and the like by companies commercial for profit companies that develop various forms of A.I. technology,
very little academic research, very little government, almost no civil society or others.
And in fact, last year we did a follow up studies on this to better understand the role of academics.
It turns out that amongst the academics, more than two thirds in fact have very strong industry affiliations,
not simply in the way that they collaborate with some of these companies, which we do too.
At the institute, as many entities in Oxford and elsewhere do.
But in that they work primarily for industry and have only part time on nominal academic affiliations.
So in fact, what is here listed academic research turns out on closer inspection to be largely be more industry sources driving the coverage.
Now, this is not always a bad thing, but I think we can sort of see the risk for a certain conflict of interest, if you,
if you will, in a coverage that is largely driven by sources from the industry itself, a for profit commercial industry.
And I think if we step back from China early to look at what this sort of what analogies to the situation might be,
I think we can think of sort of two things from the not too distant past the way in.
To which the finance industry has been covered historically, including in the run up to the financial crisis.
In a way that's heavily reliant on industry sources with technical insight and expertise,
which make some good sources but also potential conflict of interest. And, of course, even more adjacent to the end, in some cases,
even dealing with the same very same companies the way in which say, social media has been covered in the tents,
if you will, again, in a way that was heavily heavily reliant on industry sources and often quite,
if you will, quite positive about the potential of new technologies.
And I think we have seen belatedly and not so attuned to the sort of the wider range of
possible outcomes and consequences of the large scale deployment of new technologies.
So where does that leave us? I want to leave with a couple of questions that we can discuss, either in this room or delightful refreshments outside.
So I think there are some questions that this raised, at least for me,
and in the work we do at the Writers Institute around the growing role of A.I. news.
I think the first one is how do we ensure accountability, intelligibility and transparency when now is used on news?
I think fundamentally for us as users, but more importantly, perhaps as us,
as citizens and indeed for many of the participating organisations for the public service
media like the BBC or for profit ones like News Quest that owns the Oxford Mail,
it is extremely hard near impossible to actually understand what the [INAUDIBLE] happens.
When news is filtered through, for example, search or social,
and I think it's a question whether that is sort of a state of affair we can be content with.
Secondly, when we think about how the news industry itself leverage the power of various forms of A.I.,
how might they avoid the already well known and documented risks of, for example,
rampant discrimination in the way in which we deal with gender and race again, an issue that Gina Flack for us,
it is well known that these systems, unless very carefully calibrated and constantly monitor, can reinforce and amplify existing inequalities.
Is that really something that the news industry should be complicit with, in particular knowing that these risks are very real?
And secondly, of course, concentration. There are many dynamics at play in our media environment right now that lead to sort of winner takes most
markets where a few companies succeed beyond their wildest dreams and most other companies struggle.
And I think this issue of how A.I. develops and whether it becomes more accessible or more effective,
if you will, is a pretty critical question for what the future of the news industry will look like.
Are these technologies that will only be really powerful and efficient to deploy if you are a very large company with lots of data,
lots of engineers and lots of money?
Or are these also tools that might empower smaller organisations, non-profit organisations, local news organisations and the like?
So issues around discrimination, concentration and of course, finally for the journalism itself?
How can journalism rise to the challenge of covering A.I. in a way that allow for an informed debate,
not just in rooms like this at universities like this, but in public over the ethics and politics and future of A.I. with that?
Thank you very much.