There's one technology that's already being used by millions of people around the world
that has the potential to define the next decade of technological progress.
Facial recognition systems work by matching an image of a person's face to a previously held image of them.
The technology is powered by artificial intelligence, and it can be used in a number of different ways -
from unlocking mobile phones to real-world events.
It's been used at protests, sports matches and at concerts.
Police say it can be used in public spaces to improve security
by helping to locate dangerous people and suspects.
The rapid increase in the use of facial recognition has proved to be hugely divisive.
There has been a lack of transparency around how the technology is being used.
Critics claim the systems are unreliable and erode people's privacy.
There are broadly two types of facial recognition systems that are used.
The first doesn't work in real time, it's static and uses individual images.
If you have a photo of someone, it's possible to compare against the database of 10s,
thousands or even millions of images to find a potential match.
This type of facial recognition technology could be used on one individual computer
or powered through the cloud.
Police in the UK have used this type of facial recognition system with images captured from CCTV cameras.
The second type of facial recognition system is more dynamic and therefore more controversial.
It works in real time.
It's called automated facial recognition.
It all starts with cameras that can be positioned in public places such as outside shops or on high streets.
The image is captured by these cameras and then processed by artificial intelligence software.
It's able to pick out humans and their faces from other objects around them,
such as cars, lampposts and street signs.
The faces are analyzed in a matter of seconds and compared to images
that are already held on a database.
The systems that are currently being trialled can identify 10s of faces in one image.
They can also scan huge crowds with very little effort.
When a match is made, police can receive a notification
telling them about a potential suspect on the ground.
They're then able to go and identify and locate them.
The facial recognition systems used to unlock mobile phones work in a similar way,
they identify our likeness in real time.
But there are some differences.
The systems on our phones are only trained to recognize one face.
They work at short distances and crucially they have to be opted into by the phone's owner.
Facial recognition systems aren't looking at your face in the same way that a human would.
Instead, they process biometric markers on your face,
for instance, the gap between your nose and lips or the width of your eyes.
An algorithm can essentially create a map of your face
by combining different measurements and personal traits.
Much like your fingerprints, your face is unique to you.
It can't easily be replicated.
Around the world facial recognition has been used in lots of different ways.
Airports are using the technology to verify people's identities.
Shopping malls have experimented with emotion tracking.
In Taylor Swift's Reputation tour it was used to spot stalkers.
China has tracked Uighur Muslims throughout the country.
And police in the UK and US have used the software to arrest alleged criminals.
So what's the danger with facial recognition?
This is where it gets complicated.
Questions have been raised about bias in data sets, accuracy,
and the ethics of facial recognition deployments.
Essentially, a facial recognition system is only as good as the data that has been used to train it.
Researchers in scientific labs can get the technology to be highly accurate.
They use high quality images of people showing their full faces and well-lit conditions.
When they do this they can get matches nearly 100% of the time.
But when the tech's being used in the real world, this is when things can get messy.
Things don't work as well when CCTV cameras are low quality and people are moving around,
cameras can't capture people's faces as well in poor quality lighting conditions.
One of the first uses of facial recognition technology in the UK was the UEFA Champions League Final in 2017.
South Wales Police received 2,400 alerts of possible matches less than 200 of these were right.
The risk is people who are criminals get identified as potential suspects
and then receive unwanted police attention.
And then there's the issue of bias.
A study by MIT Media Lab has found problems with Amazon's facial recognition technology.
The system could identify the gender of lighter-skinned men, but it mistook women for men 19% of the time.
On top of this, it mistook darker-skinned women for men 31% of the time.
The danger here is that AI systems won't treat people equally or fairly.
In May 2019, lawmakers in San Francisco banned facial recognition technology from being used.
This is massively significant as Silicon Valley is the home of big tech.
Both Amazon and Microsoft have said there needs to be rules put in place to control facial recognition.
The main argument in favour of the technology
is to help improve law enforcement and increase security.
Police say that facial recognition technology can be used to help find suspects in large crowds.
They argue that this can be cheaper, more efficient and help to reduce crime in a certain area.
Is this going to end up with us living in a dystopian society?
Well, it's too early to say - but one thing's for sure.
Facial recognition is going to be debated for years to come.
Police, government and law enforcement are going to increasingly use the technologies
in live deployments.
The key issue is that the technology is still being developed.
Without control there's a danger we will rely on facial recognition technology
when we don't know whether it's safe or accurate.
And at that point, things will be too late.