Great. Well, thank you so much, I'm just sharing my screen right now.
I hope you can all see that it's that, right? Yes.
Great. So as Christopher said, my name is Marina Fabro and I am a research fellow working in emerging technologies and arms control.
And today I'll be presenting the findings from the study that I conducted with Heather Williams at King's College London.
And this is actually a study that will be published next week. So we're very excited to be sharing these findings with you before anyone else, really.
So the bottom line up front of this study is that it provides a new framework for thinking and talking about emerging technologies and nuclear risk.
So this study group's 10 technologies into four technology clusters, which are described based on the effects that they'll have.
So this study essentially groups technologies that distort, compress, thwart and illuminate in a crisis.
And experts assess that technologies and cluster one distort were the most concerning in terms of nuclear
risk because they're both highly impactful and relatively easy to implement in the next 10 years.
So let's take a step back, go to the puzzle, so I don't think it's very helpful to treat emerging technologies as a broad risk category.
After all, this is a vague term. It's a catchall term.
And it's used to describe a really heterogeneous group of technologies from multiple operating domains of space,
cyber, et cetera, and with different maturity timelines.
So instead, what I wanted to do was to create a framework to better understand which technologies create,
what kinds of risks and how these risks can be mitigated. So here are the questions that guided my research.
Essentially, I was looking at which emerging technologies are most likely to escalate a crisis.
How can policymakers better understand the ways in which nuclear weapons states might feel this impact
and which nuclear risk reduction measures could mitigate any potential impacts for any potential risks,
excuse me, of emerging technologies, while also capitalising on the bit on the benefits and opportunities that they present.
So I think these are important questions to ask for a few reasons. They help states to make allocation decisions so states have limited resources.
Emerging technologies is, as we said, this broad category. So they need to decide what to focus on.
Secondly, it offers a new means for addressing emerging technologies in collaborative ways.
So this could be between nuclear weapon states and non-nuclear weapon states or between the public sector and private sector.
And it reduces the risks of catastrophic nuclear use, which obviously we are all interested in.
So setting up the scope of the studies, I short listed 10 technologies for consideration.
These are high powered cyber operations, big technology.
I, for example, are small states for our rendezvous and proximity operations in space,
kinetic antisatellite capabilities, satellite jamming and spoofing systems, hypersonics from robotics.
I promise we'll come back to them. You don't need to memorise the list.
So the function that these technologies are are going to affect in this study is crisis, stability.
And in the simplest terms, a crisis is determined, a stable when no side has incentive to to use nuclear weapons first.
The UK is the subject of the study and the timeline is ten years. So adding all this together,
the study is looking at the likelihood of emerging technologies to impact a crisis between the UK and another nuclear reactor over the next 10 years.
The how of the study is I use extreme method, which is a method that I became familiar with when I worked at Rand.
It's a roundabout method and it's essentially used to look at current and potential
technologies according to a range of impact and implementation criteria.
So what does this mean? Essentially, comparing the impacts of technology side by side, as we said, can be very challenging.
I like to say that it's the policy equivalent of comparing apples with oranges.
Now, the stream method doesn't necessarily allow us to compare apples with apples because that's impossible,
but it allows us to compare apples and oranges with common parameters.
So that's the kind of what the study adds to the literature.
And a huge part of the method is the survey where subject matter experts present a survey that looks like this with ten technologies.
The ten technologies that we spoke about in the columns here.
Over here, we have the impact questions. So these impact questions got at does this technology potentially deliver or enable a disarming first strike?
Does it increase or decrease making time?
Does it create myths or disinformation? And so those are the types of questions that experts were answering.
And then over here,
we have the feasibility of implementation questions which ask which barriers exist to developing or deploying these technologies in the UK.
And this includes budgetary, regulatory, ethical, legal, technical barriers, etc.
So in total, I received sixty one completed surveys. This is an example of what a completed survey looks like.
It was from an equal mix of policy and technical folks, which was one of the objectives of the study.
And on average, not all experts evaluated all technologies like this Absolute Hero did,
but most evaluated between three and four technologies, which is in line with the guidance.
So I only wanted people to evaluate technologies with which they considered themselves an expert.
So as you might imagine, that created a huge amount of data,
and I think that's there was arguably too much data for the human brain to look at and make sense of it in an unbiased way.
So I actually use machine learning to cluster the technologies according to the type of
impact they might have on the stability and the addition of machine learning set the sets,
the study apart from that which came before it.
Because when I've used this method in the past, usually the output is a ranking of technologies from most concerning to least concerning.
But this relies working from the average of the impact and implementation scores for each technology.
Whereas what machine learning does is it allows us to group technologies together that were scored similarly across similar questions.
So the result is that we can see technologies that have a similar impact on stability and start to characterise these clusters.
Yeah, so the computer actually graphs this with multiple axes, but I've visualised it here in 2D to make it understandable to our human brains.
So here's how we can understand this graph. Up in this quadrant, we have highly feasible and highly impactful technologies.
So we've got technology and satellite jamming spoofing systems in this cluster.
In this quadrant, we have highly impactful but less feasible technologies in the UK context.
And in this quadrant we have more feasible but lower impact technologies.
And we'll get into this more as I go along.
So just to note that these technology clusters were also found to be statistically significant when I use pairwise testing,
which is a statistical significance test, that basically what it adds to my findings and how it makes us more confident in them is it tells us
that technologies in different clusters were always seen to be statistically different from each other.
And technologies in the same cluster seem to be sometimes the same sense and sometimes different.
And that aligns with my thinking on this, because I'm not saying that technologies in the same cluster are the same.
I'm just saying that they're more similar to each other than they are to the other technologies, which gives us a way of understanding the findings.
So to give you a brief snapshot on these technology clusters, technology cluster one, which is that high impact,
high visibility cluster encompasses satellite jamming and spoofing systems and big technology.
And these were technologies that are capable of interacting data flows and distorting the information landscape
technology cluster to impacts the speed of conflict and could compress decision making timelines in a crisis.
So this includes hypersonic missiles, swarm robotics, kinetic antisatellite weapons, air powered cyber operations and Archos.
The defining feature of Cluster three is its ability to credibly thwart or blunt a nuclear attack.
And there's only one technology that ends up falling into this cluster, which is directed energy,
weapons and finally cluster for illuminates insofar as it provides more accurate and more comprehensive data flows to decision makers.
And these were the only technologies that were identified by experts as capable of both strengthening and eroding nuclear command,
control and communications, as well as both increasing and reducing Decision-Making time.
So these present both an opportunity and a threat to the stability and the policy paper spends much more time characterising
each of these technology clusters and proposes bespoke risk reduction measures that are unique to their applications.
But for the sake of time, all speed along to the implications of the study.
So, as I mentioned at the beginning,
experts assessed a cluster one distort is the most concerning for nuclear policymakers because their high impact and highly feasible.
So indeed these technologies are very readily accessible to civilians.
There are smartphone apps and telegram votes that create authentic seeming deep fakes.
And even if these don't convince citizens they're still potentially disruptive.
For example, they can be used to embarrass or blackmail decision makers or those with access to classified information.
And one thing that analysts talk about in this area that's particularly concerning is that ninety
six percent of fake videos on the Internet are nonconsensual pornographic videos of women.
So you can see you can deduce that if that were to involve women who are involved in the national security infrastructure,
that could be hugely impactful in an ongoing crisis.
Defects could also compromise classified data feeds and so mistrust in the intelligence community's conclusions.
And similarly, you can buy a GPS jammer that plugs into your car.
They're illegal, but apparently a lot of truckers use them and delivery and service vehicles use these to manipulate their driving logs.
So these can not only manipulate the driving logs, but they also can interfere with emergency services like.
Nine nine, nine ambulances, firefighters, police, etc. So it's a very concerning and concerning thing and mindful of the time all said,
basically, you can read the report if you would like to read some bespoke risk reduction measures that are unique to each cluster.
But one overarching risk reduction measure is the public sector must cooperate
more closely with the private sector because a lot of these technologies are
already being developed or will primarily be developed in the private sector
by multinational companies that traditionally haven't worked with defence.
And this is partially because of the ways that the defence procurement process is
changing and this gives rise to the potential harms of dual use technologies.
So this is a really important finding from the study. And finally,
I think this framework can be used in multilateral forums like the NPT to build bridges between nuclear weapon states and not nuclear weapon states.
So last slide, I promise, revisiting the puzzle.
So I shortlisted 10 technologies that are most likely to escalate the crisis stream and machine learning.
We're used to group the 10 to the 10 short list of technologies into four technology clusters.
And depending on the applications use cases behaviour's posed by each technology cluster.
Bespoke risk reduction measures were proposed. And that's all for me.
Thank you very much for having me today. I will give Marion an idea,
so Marion's asking about potential risk reduction measures that the study found and one so because I talked most about Kluster, one,
the district questionnaire, which has technologies and satellite jamming and spoofing systems,
maybe I'll just say a bit about the risk reduction measures for that cluster specifically.
So a lot of people are talking about specifically Yankovic's, who just wrote the book, How to Lose the Information,
where she's a disinformation scholar and she talks a lot about how we can use deep nudes or these nonconsensual
pornography videos that I was talking about as an entry point into legislating digital replicas of people.
So this is another way of saying essentially because it's so clearly a harmful use of this technology,
that the US Congress has even tried to go this route or is in the process of trying to go this route.
And I propose that the UK also uses this as an entry point into legislating deep, deep technologies because of their potentially harmful impacts.
And as for the space based protection of space based assets such as GPS satellites or satellites that enable early warning or and C three,
I talk about how the UK could potentially use the UN General Assembly's proposal,
a draught resolution on reducing space threats through responsible behaviours,
which is actually a great segue into such presentation as a really great forum
to talk about the protection of early warning satellites and three satellites.