An incredible revolution is happening in the world
of health care
that some claim could be the cure that doctors and patients
desperately need.
Artificial intelligence, or AI.
Basically, making computers think.
Artificial intelligence could really revolutionise health care.
Allow us to understand our patients better,
to develop new diagnostic tools, even new treatments.
All of us could benefit from this change, which is driven
by the private tech industry.
They're saying that we're going to do with health care what Google
did with information.
One grand ambition is to get AI computers to diagnose diseases
as well as a human doctor, or better.
This could relieve pressure from the NHS and help bring
good health care to parts of the world where doctors are scarce.
So what's not to like?
But the race to get ahead in the market involves
a major culture clash.
You have the technology world, the Silicon Valley,
move fast, break stuff, and then you have the diligent,
evidence-based, do no harm health care system.
Some even see AI's roll-out as potentially dangerous.
how to regulate it, we don't know how to prove it's effective.
Just because we can do something doesn't mean we should.
The stakes could not be higher, and this is a revolution
that is happening right now.
A seismic disruption for the NHS is on the cards
and, in a blind trial, we will see AI being put to the test.
So can the machines beat the doctors, and should we trust
them if they can?
The British health system, with its easily lost handwritten
notes, isn't exactly renowned for its IT.
I haven't seen one of these for a long time!
But then, I don't work for the NHS, which is the biggest purchaser
of new fax machines in the entire world.
And sometimes our beloved NHS really feels every bit 70 years old.
But maybe not for much longer.
And that is thanks to artificial intelligence,
using algorithms to get computers and machines to automate some
of the brain work usually done by doctors.
There is, in fact, a health tech gold rush going on.
Loads of new smart apps promise to help us keep fit and well,
and the corporate giants are pouring vast sums
of money into AI.
Apple wants to use your phone sensors to monitor your health.
Google's Deep Mind uses AI to spot serious eye disease.
IBM is working on cancer diagnosis.
The profits are potentially eye-watering, but some people
are seriously worried.
In science, you don't believe anything until it's proven
and, in medicine, you're especially cautious.
This isn't some online shopping suggestions or AI recommending
you a film you might like to watch - this can be life or death.
But in the very competitive tech industry, it's quite normal
for companies to race to get their products out.
To witness this phenomenon from the inside, we've had unique
access to one tech company in particular -
Babylon Health.
Based in London, Babylon have hired an international team of top
computer scientists and doctors with a mission to use AI and mobile
phones to transform the way we access GPs.
British entrepreneur Dr Ali Parsa is their CEO.
We started Babylon to see if you can make
health care accessible, affordable and put it in the hands of every
human being on Earth.
To take most of the health care most people need and deliver
it to them on devices they already have.
2018 is set to be a big year for Babylon, who want to prove
that their artificial intelligence, programmed to understand symptoms
and offer health advice, is a match for human doctors.
We're saying that we are going to create a machine
that can eventually hopefully tell you about your disease as accurately
as a doctor can, that can give you your treatment better
than most doctors can, that can look faster,
cheaper, at variations of symptoms, billions of variations of symptoms,
as well as if you had one of the best doctors in the world
in your pocket.
That's the big vision, but you can use Babylon's
smartphone app right now.
Like others on the market, such as Ada and Your.MD,
it uses AI to let you check your symptoms when you feel unwell.
And if you want, it will book you in to see
one of their doctors privately.
So I can see you've completed our AI assessment.
And in London, there's a scheme that offers Babylon's AI
and its doctors on the NHS, entirely free.
This is Lillie Road in Fulham, west London.
To look at it, you'd have little clue that this nondescript GP
surgery is at the centre of a hi-tech venture.
In late 2017, it partnered with Babylon to set
up a new NHS GP service -
GP At Hand.
Any adult who lives or works in inner London can download
Babylon's GP At Hand app and use it to switch from their normal GP
to being registered here at Lillie Road.
So many Londoners have done this that this is now one
of the fastest-growing GP surgeries in the country
with some 30,000 patients.
But most of those people will never actually come here to see a doctor,
and that's because the only way to initiate contact with
GP At Hand is online.
Although appointments are available at one of their clinics
if you really need to see a doctor face-to-face.
We can be open 24 hours a day, seven days a week.
That is three times as much coverage as your GP has for exactly the same
price and, more importantly, often, you have to wait days or weeks
to see a GP. With us, you're seen within minutes.
That is the beauty, the amazing thing about technology.
Dan Smith is one of many who downloaded the app.
One of the big restrictions that people have around primary care
is about time.
I run my own business, I have a two-year-old daughter,
I don't have time.
So being able to just pick the phone up and have an appointment
whenever you want to I think's really important.
Using GP At Hand is pretty straightforward.
You just put in, "I have a headache," and then it will just
take you through a list of questions.
The app uses AI to check patients' symptoms and advise
whether they need to see a doctor - a process called triage.
If it says "See a doctor," you can just go straight
in and have a video appointment, typically within ten minutes.
You said that you're not feeling very well.
I can see that you've used the triage chat today.
Dr Zahra Damji is one of around 200 GPs employed by Babylon in the UK.
Could you just tell me a bit more about how you've been feeling?
I'm able to spend a lot of time seeing patients digitally,
perhaps more so than I would have done if I was just working
within that traditional model, and actually having more patient
contact means that, as a GP, I'm happier because, ultimately,
what I want is to see patients.
Babylon's GP At Hand app not only gives patients triage advice,
it also provides diagnostic information to the online GP.
The information comes up in a list format for us,
so we try to work out from that information
what we predict the diagnosis for them could be,
but we're already one step ahead because we've got
all of that information in front of us.
It also allows us to focus our questions better.
Have a feel of your neck for me. If you just kind
of put your finger across your jawline,
just press all the way round.
It's a slightly strange experience, speaking to a doctor on the phone
rather than face-to-face.
Stop. Stop, keep it right there.
OK, that's quite a good view.
Dan has certainly put the service through its paces.
I suddenly started feeling a strange feeling in my face.
I looked in the mirror and half my face had dropped.
And the immediate fear you have is, "Am I having a stroke?"
I can hear your speech is slightly affected because of your mouth.
I had a video call with a doctor within three minutes,
and he did a couple of basic tests, and he quickly eliminated
it being a stroke and, because of the way
that it was presenting, that it was Bell's palsy.
It tends to get better. It's quite a dramatic problem
to have at the moment.
It meant I didn't have to rush down to A&E and I could just
take some steroids and some painkillers.
Being able to speak to a doctor and have them to reassure
you in minutes I thought was wonderful.
Talking to a doctor via your smartphone certainly feels
a lot more efficient than schlepping down to the local GP and waiting
in a queue.
But that is not artificial intelligence.
Where AI comes into all of this is in the symptom checker.
This is the first thing that you see when you open up one
of these kinds of app, it's where the patient types
in their symptoms to what's known as a chatbot.
At this point, there is no doctor involved at all.
The computer is doing all of the thinking.
It's working out what might be wrong with you and giving you information
about what to do next.
And if the AI is working well, it will filter out all of the people
with non-serious conditions, leaving human GPs to treat
the patients who really need their expertise.
So how does this kind of AI work?
Dr Saurabh Johri leads Babylon's AI team.
What we're trying to do is essentially replicate the kind
of decision-making process that a human doctor takes
when they try and diagnose a patient.
If a user is sick, what we're trying to do is reason
about what may be the underlying condition.
For their AI to do this, to reason, it will have to master
three key skills.
First, it has to become as knowledgeable as a human doctor.
Then it must learn to talk to you, ideally in a nice,
human-like way.
Finally, it must be able to use all that to deduce
what might be wrong.
And that's what we're trying to build, to replicate kind
of human decision-making in terms of medical diagnosis.
It's not easy.
Babylon's team have trained their machines to hoover up as much
medical knowledge as possible.
We have created systems that can read papers,
they can read web pages, and they are much faster than us.
Imagine you had a magical box that you could put a book
in and it was like eating the book and understanding it.
That's what it does.
But hoovering information isn't enough.
The knowledge has to be organised into a knowledge graph -
a vast web of interconnections.
And then the chatbot must be taught to interpret the meaning
of what the patient tells it.
To a machine, a word is just a string of characters, there's no further meaning to it.
In order to determine what something means,
it is important to learn what it is similar to.
The AI computer tries to capture the similarity between words
in a kind of mathematical map.
For instance, words like headache and migraine,
with similar meanings, go in the head region.
If I can arrange things in a way that the computer can easily figure
out the two things are similar, then you're taking a large step
towards the computer actually understanding what the word means.
A map of phrases you might say to the chatbot works in exactly
the same way.
Those that mean something similar belong in the same part of the map,
which helps the chatbot decide what questions to ask you next.
We are at ground zero today.
I bet, in two years' time, maybe five years' time -
but it certainly isn't anything longer than that -
machines can speak any language in the world in any local accent
and understand any dialect.
That is a game changer.
The computing powers, the data sciences,
are now becoming sophisticated enough for us to be able to do
things that only a few years ago we used to dream about.
Imagine everyone having powerful clinical artificial intelligence
in their pocket.
So how can I help you today?
I've got a bad headache.
Headaches are really common...
Since their launch, Babylon have invested tens
of millions of pounds on research and development.
According to the World Health Organization,
we need at least five million more doctors.
They're trying to edge out their competitors to be the
go-to health app in the potentially highly lucrative global market.
But what about the rest of the world?
They've signed up patients from Britain to Rwanda
and partnerships from China to Saudi Arabia.
Such is the current buzz about AI's potential to help us do many things
better, faster and cheaper that the British Government are keen
to get in on the act.
The United Kingdom will incubate a whole new industry around AI
in health care.
But for all the excitement, some people have serious concerns
about how this market functions.
I think there is an inherent risk in the hype that is required
to attract the kind of venture capital that these companies
who are developing novel AI technologies are reliant on to get
themselves off the ground, in many cases.
There is a risk that behind the hype there won't turn out
to be enough substance.
I'm under no doubt that this potentially could really
revolutionise health care, I'm really excited about that.
But the real tragedy here would be if we over-promise
and then funding dries up and we're unable to develop
these tools, and therefore patients miss out on them.
Personally, I find it hard not to be excited
about the possibilities that AI offers for radically
transforming health care.
But it's also really important that we don't allow the hype
around AI, which is currently pretty massive,
to tarnish its true potential.
And that means that the people who are involved here
should be really responsible about the claims that they're making.
And what's more, we should remember that changing how people interact
with a trusted institution like the NHS is never
going to be easy.
Some critics have taken aim at Babylon's GP At Hand service,
worried less about the AI and more about its rapid growth
and impact on normal NHS GPs.
I'm a GP from East London, and I've come here because
I'm furious for my patients, my family and myself
about the privatisation in the NHS.
In protests in London in 2018, a range of concerns are voiced.
But we're not against artificial intelligence when it
helps patient care.
But we're really worried that this system is set to undermine
front line practice.
There are lots of good, I've no doubt, digital interventions,
but this is not one.
Every GP is paid a fee by the NHS for each of its patients,
so when London GPs like Dr Jackie Applebee lose patients to
GP At Hand, they lose funding, too.
So the big concerns that motivated the protest against GP At Hand
was our real fear that it's going to destabilise general practice.
Our patients are leaving, taking their capitation fee from us
to GP At Hand so that we can't provide the care that we want
to provide to the whole of our patient population.
GP At Hand capitalises on the fact that people can now register
with practices far away from home.
It's partly this loophole that allows Babylon to attract
digitally savvy young Londoners away from their old doctors.
GP leaders hadn't seen this coming.
GP At Hand certainly burst onto the scene in London last year
and took us all by surprise because people didn't realise
that there was this loophole in the contractual mechanisms
of all GP surgeries that they could adopt.
But they did, they saw it, and they grabbed it.
When you take the fit, well people out of a practice
and the money goes with them, you're left with far
less money to look after the really sick,
frail people that leaves the practice in jeopardy.
And if that practice goes under, what's going to happen to those patients?
That is a real risk to the individuals
and to their communities.
Unease about GP At Hand, which hopes soon to expand
nationwide, is not just about money.
Something that really concerns me about the GP At Hand type model
is that, on their website, they say, if you're pregnant,
if you're mentally ill, if you've got a complex long-term
condition, we might not be the best service for you.
So what they're doing is they're creating a two-tier
health care service and, if this starts to come in, and more and
more practices start to do that, then we lose our comprehensive NHS.
I'm excited by innovation, but that excitement
is really tempered by anxiety.
My worry about this innovation and this rush to embrace technology
is that we're leaving behind the very people who stand
to need most from the health care service.
Those who need most are going to get least.
You know, people don't have to agree on everything all the time,
what matters is patients in their tens of thousands
are agreeing with this.
As you and I are doing this interview, every three minutes,
a new patient is joining Babylon.
We have many patients with mental health issues,
many elderly patients.
Our fastest-growing group of people are the elderly.
Fears about the impact of AI on health care go well
beyond suggestions that it threatens the status quo
and could increase inequality.
People are asking, how do we know it's safe,
and is it appropriately regulated?
From the first day of medical school, the thing you're told is, first, do no harm.
And that's exactly what patients expect.
That's the right thing.
And then, when you bring that to the fast-moving world
of technology, the move fast and break things culture,
clearly, there's a clash there.
Chest X-ray. Is it really? Yes.
And I wouldn't blame patients and doctors and nurses for finding
it hard to trust these technologies at the moment
because it's hard to find out how they've been assessed
as being safe, who has determined that they are safe.
Now, stay with me because at this point
I'm going to beckon you in to the arcane world
of health care regulation.
Apps like Babylon's are regulated by the MHRA -
the Medicines and Healthcare products Regulatory Agency.
But what you might be surprised to learn is that they are classified
in the lowest possible category of medical device
alongside things like bandages or Zimmer frames and spectacles.
In this category, it is the manufacturers themselves
who vouch for the effectiveness and safety of their product,
and that means that we only have Babylon's word for it
that their app is safe.
Now, there are a lot of very strict rules about what AI symptom checkers
are and aren't allowed to do if they're to qualify
for this quite quick and easy way to launch.
They are allowed to collect data on symptoms and to provide
information, but they're not allowed to give any feedback
that could replace a human medic's advice or offer anything
that could appear to be a diagnosis.
In the case of Babylon, whose human GPs are inspected
and regulated just like any other UK doctor,
its patients could be forgiven for thinking that,
with their AI chatbot, they're consulting something
very like an online doctor.
Is the pain in the lower left part of your tummy
close to the worst pain that you've ever felt?
The chatbot does seem to be working towards a diagnosis.
..Best describes the pain in the lower left...
The GP At Hand website explains the symptom checker offers health
information and fast, accurate advice.
But, in fact, its terms and conditions say
the output does not constitute medical advice,
diagnosis or treatment.
This is the first time I've heard that somebody believes
it's confusing and, if it is, we need to fix it and we need
to call on the regulators to help us to come up with the language
that is not confusing for the users.
Artificial intelligence is a new challenge for the regulators,
and they need to figure out how to do it.
So there is a contradiction between what we want to do
and what we believe people want versus what the regulatory
environment is ready to.
After this interview was filmed, Babylon changed their website.
Confusion about the regulation of AI health products
is clearly a problem.
But what about the science?
Do such products stand up to traditional,
scientific scrutiny?
These are peer-reviewed medical journals, where professional experts
anonymously review each other's work and make sure that it's good
science - robust, accurate and significant.
And, every year, up to 1 million research papers are published
in journals like this, and yet, despite the frenzy around AI
in health care, this is the sum total of all publications to date
on peer-reviewed clinical trials that assess real time,
real world impacts of this technology on patients.
That's right - one paper.
There are a handful more where AI and human doctors are set to work
on the same past data, but basically the AI health field
is booming and yet there's been little scientific proof
that these products are effective.
But this is a reflection of how the tech industry works.
With huge investments at stake, companies often keep their methods
as a closely guarded secret and, as far as they see it,
they can't afford to wait for the long-winded process
of getting a paper reviewed and published.
At the moment, we see a bit of a Wild West.
We see some companies that are going about things in a way
that is highly informed by the kind of concept of evidence and clinical
trials, but at the other end, we have the companies that are kind
of assuming that the problems are much simpler than
they often turn out to be, who are delivering things
and putting them out on the market without the evidence
to support their efficacy or their appropriateness.
As one commentator put it, at the moment, we have no clear
regulator, no clear trial structure and no clear accountability process,
so that doesn't really inspire confidence.
When it comes to Babylon's symptom checker, it hasn't
been independently evaluated, nor is it required to be.
Medical director Mobasher Butt
explains that they do testing another way.
Our approach to testing and evaluation is very different
to traditional models of evaluation, and it has to be.
So, when you're working in a very fast-paced technology
environment, there needs to be the ability to constantly
evaluate the things that we're doing.
So, once we have released a product, the work doesn't stop there.
We're constantly monitoring that, so we have a whole programme
of post-market surveillance.
Up until now, Babylon have never publicly proved
that their app works.
But they say they believe in transparency
and know it's essential to win trust.
So, in June 2018, Ali Parsa gathers his team to make
a big announcement.
We can say it's brilliant, we can run all the tests internally
that says it's brilliant.
It's time that we run these tests also publicly.
At the end of this month, we're going to put our AI to test.
We're going to sit the exam of the Royal College of GPs
related to diagnostics.
Of course, not everything, right?
The second thing we're going to do is be blind-tested
with a set of questions.
Those are the symptoms that a patient will present
itself to our machine, and we're going to test the machine
against those questions.
Hopefully, we perform well.
Otherwise, we have to fire our AI team and get another team coming in!
Babylon intends to publicly demonstrate that the latest model
of their AI chatbot is a match for human doctors.
If we do this, we are it.
So, in a few weeks' time, when they pit the chatbot's
triage and diagnostic skills against human GPs,
will the AI succeed?
And will sharing the evidence with the world be enough to secure
the trust they need to stay ahead?
One British company in the race to
transform health care have already submitted their AI
to a full, peer-reviewed trial by an independent research organisation.
Kheiron Medical aim to use AI to revolutionise
breast cancer diagnosis.
Because their target customers are hospitals,
they've taken a cautious approach, rigorously testing their AI
before it's let loose on patients.
We've been working on this for about two years now,
acquiring data from clinical partners, building algorithms
and testing them.
We want to make sure we get it right because,
in the end, if our technology is going to be in a situation
where it's helping make life or death decisions,
I think it's the only sort of ethical way to build
this kind of technology.
Kheiron's system that aims to use AI to detect cancer
in breast X-ray images called mammograms uses the cutting edge
technique known as deep learning.
We say, "This is an image.
"It has cancer in it.
"In fact here's a million images.
"These ones have cancer in.
"Here's a million images that don't have cancer.
"You figure out what the features are."
With enough good image data, deep learning AI will establish
its own methods for spotting cancers.
Once you've actually trained it, you can then test it.
That, and data that your model has never seen before,
never been tested on, never been trained on, and that's
what are used to validate your model.
Mammograms are very information-dense images.
Millions and millions of pixels.
And, sometimes, the abnormality can just be a few pixels.
Not only are you trying to find small amounts of pixel information
within a million-pixel image, the proportion of women
who actually have cancer that come to a screening programme
is very small. It's about 1%.
So, it's like trying to look for a needle within a haystack
within a haystack.
In Britain's breast screening programme,
each mammogram is usually read by two trained experts to minimise
the risk of missing cancers.
If Kheiron's AI can do some of that work,
it will save doctors precious time, and that could be life saving
for the one in eight British women diagnosed with breast cancer.
Breast surgeon Dr Liz O'Riordan, who advises Kheiron,
speaks from her own experience.
A couple of years ago, I was diagnosed with
breast cancer myself.
I've seen first-hand just how awful the full gamut of breast cancer
treatment could be.
If a AI and technology can reduce the time it takes for women
to get their results, it means they get their biopsies
quicker, they get their cancer diagnosis quicker,
they start treatment quicker.
Kheiron's clinical trial results prove their AI
is outperforming humans.
What we've managed to demonstrate with our first trial
is that our system is both more sensitive and more specific
at making that decision of whether there's a cancer or not
in an image.
So, in future, rather than two human radiologists scrutinising each
image, one could be paired with an AI.
Since 97% of British radiology departments are understaffed,
this could be transformative.
But, even with such promising trial results,
deciding to trust AI is far from straightforward.
to make me accept new AI technology and it's really hard
because it's never been done before.
I don't know what standards it should meet.
Breast cancer is based on trials with 20,
30 years follow-up that look at hundreds of thousands of women,
and you don't have the time to get that follow-up to bring
in new technology because it might change in a year -
let alone 20 years.
I'd want to know that it's been assessed by people
who are independent, who have nothing to gain,
no financial interest.
And, if this is to save money to improve resources,
is that money being ploughed back into NHS services instead
of just going into the profit of the company?
And I think it is being very sure it is patient-driven.
And that would make me think, "OK, this is good."
In Britain, many are recommending caution,
but in some parts of the world, they're thinking more of
opportunity than risk.
This is Rwanda in Africa - one of the world's poorest countries.
Yet, surprisingly, it's a global leader
in experimenting with AI and tech to transform
its citizens' health care.
We generally have a strategy to attract proof of concept companies.
If a company out there in the UK or the US is trying to test
an idea - either for the first time and they are looking for a place to,
you know, if you like, a laboratory to try it out,
we open Rwanda for them.
That has been our strategy.
Be bold. Try something. Experiment.
If it doesn't work, you know, move on and count your losses.
This openness to being the testing ground for new tech means
that Rwanda has welcomed in Babylon.
Here, they're known as Babyl.
Rwanda's 12 million people are served by fewer than 2,000
doctors, but the vast majority of adult Rwandans
have a mobile phone.
If they sign up to Babyl, they can get fast triage and direct
access to a doctor - just like they could in Britain.
Ibrahim Misafiri lives 40 minutes' walk from his local health centre,
which doesn't have a doctor.
Because most Rwandans don't have a smartphone,
people like Ibrahim call Babyl's HQ, where nurses use the same AI
chatbot as UK users.
Rwanda has universal health insurance.
And, any consultation, whether in person or via Babyl,
costs the same flat fee.
It's the possibility of treating vastly more patients with the same
number of doctors that makes this public health experiment
in Rwanda so potentially significant for the world.
In Babyl, we employ about 16 doctors and 16 nurses.
And if we're operating at capacity, we can do about 2,000 consultations
in one day.
With the AI technology for the triage tool,
if that can be given to non-clinical staff,
are you looking at how the numbers are expanding?
How the number of consultations and how we are using technology
to stretch the limited resources that are available
to be able to do more in Randa.
Pretty impressive.
But some people have nonetheless raised concerns that an AI system
built and trained in the UK isn't yet much use on common tropical
diseases like malaria,
although Babylon are working on it.
AIs are only as good as what you put into them.
And incomplete training or biases like that can be very problematic.
Yet we would do well to remember the bigger picture here.
We are living in a world with a desperate shortage of doctors
but where two thirds of the population owns
a mobile phone.
So, if this technology can put good, affordable health care within reach,
surely the impetus is to continue working
to make AI safer, more accurate, and more reliable.
Back in London, the push to improve Babylon's AI continues
at breakneck speed.
It's not long before the big event where its performance
will be compared to human doctors.
Thinking about the event, is a mixture of kind of
like extreme nervousness and also excitement.
We want to show people that we're doing well,
so, there are lots of new ideas rolling, to try and get
to where we need to be for that.
Babylon are trying to advance their app,
going beyond offering triage advice to giving out
diagnostic information, too.
This has always been available to Babylon's GPs, but the aim
is to share it more widely with patients.
Medicine is fundamentally an uncertain discipline,
so, if a patient comes to a doctor and tells the doctor
about their symptoms, often the doctor will have a variety
of different conditions that they may be thinking about,
so they are uncertain about what the underlying condition is.
So, we need to be able to build a system which is able to update
that belief about what the underlying condition is,
based on new information.
The new diagnostic AI system needs to excel at calculating
probabilities or likelihoods.
It works by connecting three things - symptoms,
diseases and risk factors.
A symptom like knee pain could be caused
by a disease like arthritis.
How likely this is depends on the risk factors like age.
Each likelihood can be scored.
And, as the chatbot learns more about the patient,
the scores may change.
For example, a recent fall could suggest an injury
is causing the pain, making arthritis a less likely
diagnosis.
With the new AI system, the team can see exactly
how it comes up with each diagnosis.
Around the same magnitude, then...
In that sense, they think it's step ahead of human doctors.
It's transparent and it's fully accountable, so we can understand
precisely why we've given a diagnosis.
That's not something humans can do.
Humans, you know, probably have a similar
decision-making process in their minds, but it's actually
never written down.
The fact is that here everything is.
There's a trail about how a particular
diagnosis has been arrived at.
And we can revisit that trail at any point.
Babylon use this transparency to try to improve their AI
through repeated rounds of testing.
So, I'm a 65-year-old man.
OK. And how can I help you this morning? So...
Here, two Babylon medics are role-playing a typical GP
consultation.
The pretend patient has been given a secret set of symptoms,
known as a vignette.
So, Doctor, I've a really bad cough I've had for a couple of days.
OK. A couple of days. OK.
When you're coughing, are you bringing up any phlegm at all?
Yes, pretty nasty stuff.
After asking all the questions he needs to, the doctor reports
his most likely diagnoses.
My differentials included bronchitis,
as well as more general influenza.
The pretend patient then enters exactly the same symptoms
into the chatbot to see what the AI thinks is wrong with him.
What it's come out with is bronchitis and pneumonia.
This time, the human doctor and the AI largely agree,
but not always.
This is case vignette number 10.
So, all of a sudden, I've just had this really,
just like difficulty breathing.
When did this start?
About a half hour ago.
It came on quite suddenly did it, or more gradual?
No, it just came on really sudden. OK. And...
Taking a thorough history is one of the key ways a human GP
reaches a diagnosis.
Any recent operation?
Any long haul flights recently?
Um, I've had my hip done.
OK. When was that done?
A couple of days ago.
A couple of days ago? OK. Have you noticed any
swelling of your legs or your calves at all?
Erm, I think, yeah, one of them is a little bit,
a little bit swollen.
Having asked all the questions he needs to, the human concludes
that the patient most likely has a pulmonary embolism,
a blood clot in the lung, which is a life-threatening condition.
But when it is time to enter the same symptoms into the chatbot,
it has other ideas.
So, with this one, it's come up with costochondritis.
The AI has missed the most serious and most probable condition,
given the patient's history.
Though the chatbot is currently only licensed to provide information
to patients, and is not to be relied on as a diagnosis,
it seems an unnerving mistake.
This is the whole process by which science works.
You test new data and then you again try and validate, and so
this is the process by which all of the teams work together to try
and refine the process, to try and bump up that accuracy.
But what does Ali Parsa think of his AI missing
a potentially fatal condition?
Look, we have extraordinarily unrealistic expectations,
in terms of the accuracy, in terms of infallibility
of our machines.
And that is just silly.
For any mistakes our machine makes today, I can name you a hundredfold
the number of mistakes that will be made by human doctors
of the same order of magnitude.
We have to be realistic.
What we are saying is that when you get a diagnosis
from a machine, you have now narrowed the field for the doctor.
What we are not saying is go and entirely,
completely rely on this diagnostic and don't talk to a doctor.
There is a tenacious band of Babylon critics who are waging a noisy
Twitter war, exposing the AI chatbot's mistakes,
and these range from the very serious to the somewhat ridiculous.
For instance, one user told it, "I have a swollen elbow,"
which the chatbot eventually misunderstood as "red skin
"around the genitals."
Cue a whole range of jokes about how it doesn't know its arse
from its elbow.
The thing is, for the AI to improve, it needs to gather data
from lots of use.
But plenty of people find the idea of it learning on the job pretty
troubling, especially when computers are generally assumed
to be somehow infallible.
The future of AI-powered health care may depend on this issue
of how far to trust it.
With just days to go to the big event, which will reveal
to the world how Babylon's AI measures up to human doctors,
the testing of human versus machine intensifies.
Feeling pretty apprehensive about it, I think,
not just me but the team.
There's a lot to do.
With every test, the team helps the app to improve.
There aren't many other companies in this domain
that are doing this.
And somebody has to be the first, so...
..fingers crossed.
I mean, I wouldn't trust claims without evidence,
so we kind of have to make...
..evidence our claims.
Finally, it's time for Babylon's big test,
pitching the AI against human doctors, as before,
but now under exam conditions.
Could you give me your age and gender, please?
I'm male, I'm 21 years old. Mmm-hmm.
I'm feeling really short of breath. Mmm-hmm.
Testing takes place behind closed doors at Babylon HQ.
It doesn't involve real patients and it hasn't been designed and run
by an independent research organisation.
So prior to swimming earlier today, how were you feeling?
But the team haven't chosen the questions or seen them
in advance and won't be judging the answers themselves either.
Babylon's big test starts with respected independent
collaborators supplying 100 sets of patient symptoms that a GP
might typically encounter.
A pretend patient takes each one, presents it to up to seven
independent human GPs and also to Babylon's AI,
via the chatbot.
Both human doctors and AI must respond to each case
with triage advice...
..and their most likely diagnoses.
An independent judge will mark the anonymised answers to see
who scores highest for safety and accuracy,
humans or machine?
And the AI also has a go at some Royal College of GP exam
questions on diagnosis.
The Royal College of Physicians, one of the world's most
respected medical institutions.
So, a bold venue choice for Babylon to reveal their results
to the world.
Two years of development, tens of millions of pounds
of investment and a moment of truth for Babylon's AI.
The question is, how accurate is it?
Can it ever, ever be as accurate as a human doctor in diagnosis?
Before some of Britain's most senior medics,
first up is the Royal College of GPs' exam result.
So how did Babylon's AI do?
In the relevant tests, the average pass mark for human
doctors is 72%.
Babylon's AI achieved 81%.
But this really just is the start.
Now, Babylon's human versus machine test.
How good were the seven independent GPs at diagnosis?
So some did OK, 64% - not, not that great.
But some did really, really well - so 94%.
But if you take an average of this, it's around 80%.
So in Babylon's 100 patient tests, the human doctors on average managed
to give an accurate diagnosis four out of five times.
And how did our AI do?
So, exactly the same as the doctor average, 80%.
And what of safety?
How safe were the AI's triage recommendations?
Human doctors were able to give a safe triage outcome 93.1%
of the time.
In terms of the AI, we were able to give a safe triage
outcome 97% of the time.
As the event ends, Babylon release their research
and results for the scrutiny of all.
So far as Ali Parsa is concerned, Babylon have now verified that AI
matches human GPs at diagnosis.
We absolutely now have proof.
How would that be a claim?
Entirely independent people, from the United States
all the way to the Royal College of Physicians,
created vignettes that the machine sat and passed.
The results were independently judged by...
..a doctor at Harvard.
And we published the results.
It is all in our paper.
And, look - if we ran these tests again and the result
is a little bit different, who cares?
What really matters is that we're getting better and better.
I mean, that is mind-boggling,
the speed at which a machine can learn.
They can never forget, they can never have all the other
problems that we have as humans.
It's an absolute fact, any way they can put
it to test now, right?
But some scientists question Babylon's methods,
saying the study was too small for meaningful statistical analysis,
as well as not being fully independent or peer-reviewed.
So what does the medical establishment make of
what they've seen?
What they've done is they've done it in a lab environment.
They've done it in vignettes, without real patients.
I want to see that algorithm compete with a doctor over many,
many cases, and dealing with Enid, who's 85, who's got multiple
problems, hard of hearing.
She's never going to use the phone.
So I remain excited at the promise and I remain cynical at the moment.
I think GPs will initially feel quite threatened by this,
if the choice is a machine or a GP, but we all know it's not.
The choice is, how do we improve what GPs can do already
and which takes them a lot of time and often a lot of frustration
and a great deal of stress, which worries me enormously
about general practitioners in England.
The strongest criticism comes from the Royal College of GPs,
whose diagnosis exam Babylon say their AI effectively passed.
Babylon don't have our exam.
Babylon used sample old questions from our website,
which they used, as far as we understand.
Our exam is highly confidential.
I had a phone call the night before the presentation to say
that they were going to be making these claims and I did ask
lots of questions. I asked about independent evaluation.
I asked to see the data.
I asked to see the methodology.
Now, I didn't get to see those things, and for a very long time.
However, it's interesting to see.
It's innovative of them to try and evaluate it and I'm glad to see
them trying to evaluate that.
It's a good attempt in the right direction.
But we have a very long way to go.
What they have not done is published in any peer-reviewed journal.
What they have not done is follow any robust scientific methodology.
And what they have not done is allow others in to independently
evaluate their research to date.
All those things are possible and we look forward
to them happening.
We disagree with that.
We think there is a very robust scientific approach and our
scientists' reputation and name is on it.
As any scientist knows, the peer review system was invented
in the 18th century.
It was...
..widely became common in the 19th and early parts of the 20th century,
but it has a speed and at that time, science was progressing
at a certain speed.
So it takes normally 12-18 months from the time you do research
for a peer-review paper to be published.
That, in technology, is a very long time.
Of course, we have to be in a hurry to bring accessible,
affordable health care for everybody on earth.
It's not an intellectual exercise.
It's a mission.
After the event, it's not just Ali Parsa answering
questions about Babylon.
On his first day at the despatch box, the incoming Health Secretary
is in the firing line, too.
Is the Secretary of State familiar with the GP At Hand online service,
which has poached thousands of profitable patients from GPs
all over London, to the alarm of the BMA and GPs generally?
This is creating a two tier service for GPs.
Will the Secretary of State investigate it?
Erm, yes, I'm acutely aware of this, the question that he raises,
not least because I'm a user of the Babylon service myself.
They are my GP.
Despite Matt Hancock's personal endorsement,
NHS England are now investigating.
There is no greater enthusiast for technology than me,
Mr Speaker, as you well know.
But the thing about new technology is that sometimes
the rules need to be updated to take into account
the changes in technology.
So they've been properly evaluated...
The regulations governing AI health products are being reviewed
to ensure they are safe and effective.
The answer, where there are challenges such as the ones
she raises, is not to reject the technology.
The opposite, it's to keep improving the technology so it gets better
and better and make sure the rules keep up to pace.
The NHS has appointed an independent evaluation of GP At Hand,
and its impact on the health care system.
For now, it has decided not to approve Babylon's
expansion outside London.
Yes, it's important to make sure that it works well
and that the rules are right, but if we turn our backs
on new technology, we're turning our backs
on better care.
Revolutions are famously hard to judge without the benefit
of a lot of hindsight.
So working out what to make of the one we're living
through right now is not easy.
For me, there is no question that we could all stand to benefit
enormously from this revolution in AI health care.
In fact, after a while, it might become immoral not to use
AI, if it can outperform humans in so many different tasks.
But at the same time, we might still feel,
understandably, anxious about whether or not
we can trust it.
Because this new technology, these algorithms, they're only
as good as the humans who are involved, the scientists,
the inventors, the entrepreneurs, the politicians and the regulators.
And, in this age of human and machine, it's only right
that we should keep an eye on both.
Businesses, technology businesses in the UK,
are creating an environment which is safe and secure for investment...
Secretary of State, Matt Hancock.
Thanks, Ali, and it is great
to be here to support GP At Hand.