What do tech pioneers think about the AI revolution? - BBC World Service

Summary

In 'The Engineers' by the BBC World Service, Caroline Steele hosts a panel of AI pioneers at Imperial College London to explore the impact of artificial intelligence on society. The discussion covers AI's role in medical advancements, such as early cancer detection and potential new antibiotics, as well as its potential in enhancing human capabilities in areas like sports and writing. The panelists, including David Silver from Google DeepMind, MIT professor Regina Barzilay, and Embodied CEO Paolo Pirjanian, also address the challenges and ethical considerations of AI development.

Takeaways

• 🧠 The panelists at the BBC World Service's 'The Engineers' discussed the impact of artificial intelligence (AI) on various fields, emphasizing its potential to revolutionize industries and society.
• 🎓 Regina Barzilay, a professor at MIT, shared her personal journey of applying AI to oncology after her battle with breast cancer, highlighting the lack of AI integration in medical treatment and her efforts to change this.
• 🤖 Paolo Pirjanian, founder of Embodied, discussed creating emotionally intelligent robots to assist with child development, particularly for children on the autism spectrum, emphasizing the potential of AI to provide companionship and therapy.
• 🏆 David Silver from Google DeepMind, known for leading the team that created AlphaGo, spoke about reinforcement learning and the pursuit of artificial general intelligence (AGI), which aims to mimic the diverse learning capabilities of humans.
• 🤝 The conversation underscored the collaborative potential of AI, suggesting that it can augment human capabilities rather than replace them, as seen in advancements in medical diagnosis, game strategies, and creative writing.
• 🛡️ The panel acknowledged the need for regulation and ethical considerations in AI development to ensure safety and prevent misuse, reflecting on the balance between innovation and caution.
• 💡 AI's role in improving sports performance was mentioned, with ongoing research and collaborations aiming to refine tactics and enhance athletic training through data analysis.
• 🧐 The script highlighted the importance of understanding AI's implications for jobs, with a recognition that while AI may automate certain tasks, it could also create new opportunities and roles.
• 🌐 The discussion touched on the global nature of AI development, suggesting that international cooperation and regulation might be necessary to manage the technology's rapid advancement.
• 🚀 The potential of AI to accelerate scientific discovery was noted, with Regina Barzilay suggesting that tools like AI could have amplified the contributions of historical figures like Isaac Newton or Albert Einstein.
• 📚 The script concluded with an optimistic view of AI's future, envisioning a world where AI serves as a personal assistant and teacher, enhancing human learning and creativity.

Q & A

What is the main focus of the BBC World Service program 'The Engineers' in this transcript?

The main focus of the program is the technical revolution defined by artificial intelligence (AI) and its implications for various fields, including medicine, robotics, and general intelligence.

Who are the three world leaders in AI featured in the panel discussion?

The panel features Paolo Pirjanian, founder and CEO of Embodied; David Silver, principal research scientist at Google DeepMind; and Regina Barzilay, a distinguished professor for AI and Health at MIT.

What significant achievement is attributed to Paolo Pirjanian's company, Embodied?

Embodied has developed emotionally intelligent robots designed to assist with child development, particularly in social skills and emotional understanding.

What was David Silver's contribution to the field of AI in the context of games?

David Silver led the team at Google DeepMind that used AI to defeat the world's best player at the complex strategy game Go, showcasing the capabilities of reinforcement learning in AI.

Regina Barzilay's work in AI has had an impact on which medical field?

Regina Barzilay has made significant contributions to oncology, particularly in early-stage breast cancer detection and the potential discovery of a new antibiotic.

What personal experience influenced Regina Barzilay to shift her work to oncology?

Regina Barzilay was diagnosed with breast cancer in 2014. Her experience with the lack of AI integration in her treatment motivated her to apply AI to improve cancer diagnostics and treatment.

What is reinforcement learning, and how does it relate to how humans learn?

Reinforcement learning is a method where a system learns from experience, trial, and error, similar to how animals and humans learn. It involves learning to do more of the good things and less of the bad things based on feedback in the form of rewards.

How does Paolo Pirjanian's robot form an emotional bond with children?

The robot forms an emotional bond by mimicking human behaviors such as making eye contact, smiling, and expressing empathy. This allows children to connect with the robot and practice social skills in a non-threatening manner.

What is the potential impact of AI on the development of new antibiotics, as discussed by Regina Barzilay?

AI can analyze thousands of molecules to predict their effectiveness against drug-resistant bacteria and their safety for human use, potentially leading to the discovery of new antibiotics that can combat resistant strains.

What is artificial general intelligence (AGI), and how does it differ from narrow AI?

Artificial general intelligence (AGI) refers to AI systems that can approach any number of problems with intelligence, similar to human intelligence. In contrast, narrow AI is designed to perform a single task or a narrow set of tasks.

What are some of the challenges and considerations regarding the regulation of AI, as discussed by the panel?

The panel discussed the need for regulation to ensure the safe and ethical use of AI, but also acknowledged the difficulty in creating a one-size-fits-all approach due to the diverse applications of AI. They also touched on the potential economic and strategic implications of AI regulation.

How might AI influence the future of sports performance and training?

AI can be used to analyze data and develop strategies to improve sports performance, as exemplified by Google DeepMind's collaboration with Liverpool Football Club to enhance their tactics.

What is the panel's perspective on the balance between AI advancements and human learning and development?

The panelists believe in a symbiotic relationship between AI and humans, where AI can assist in learning and development, allowing humans to focus on more complex ideas and creative tasks.

Outlines

00:00

🌟 Introduction to The Engineers: AI Edition

The script opens with Caroline Steele's introduction to 'The Engineers,' a BBC World Service program held at Imperial College London. The focus is on artificial intelligence, a technological revolution. The program features three leading AI experts: Paolo Pirjanian, the CEO of Embodied, known for emotionally intelligent robots; David Silver, a principal research scientist at Google DeepMind, who led the AI team that defeated the world's best Go player; and Regina Barzilay, an MIT professor who has made breakthroughs in early breast cancer detection and new antibiotic discovery. The audience is informed about the diverse applications of AI, from complex games to medical breakthroughs, setting the stage for a discussion on the impact of AI on humanity.

05:00

🤖 The Journey of Creating Emotionally Intelligent Robots

Paolo Pirjanian shares his motivation for creating robots that understand human emotions, stemming from personal experiences of alienation. He discusses the growing need for companionship and therapy, especially for children with autism, and the potential of robots to help them develop social skills. The robots are designed to form emotional bonds and act as training wheels for social interaction, with the goal of improving children's integration into society.

10:03

🎲 Reinforcement Learning and AI in Strategy Games

David Silver discusses his background in the gaming industry and his transition to academia, where he became interested in creating AI with real intelligence. He explains reinforcement learning, a method that allows systems to learn from experience, similar to how animals and humans learn. This approach was applied to develop AlphaGo, an AI that defeated the world's best Go player, showcasing the potential of AI to master complex tasks that were previously considered uniquely human.

15:04

🏥 AI in Medical Diagnosis and Drug Discovery

Regina Barzilay recounts her personal experience with breast cancer, which led her to apply AI to improve cancer diagnosis and treatment. She emphasizes the potential of AI to handle uncertainty in medical fields and to remove the guesswork from diagnosis and treatment. Her team at MIT also used AI to discover a new antibiotic, highlighting AI's capability to analyze complex data and make significant contributions to medical science.

20:09

🧠 The Pursuit of Artificial General Intelligence (AGI)

The conversation turns to the concept of artificial general intelligence, with David Silver explaining the goal of creating AI systems capable of approaching a wide range of problems with human-like intelligence. He acknowledges the challenges and the need for further breakthroughs, suggesting that achieving AGI will be a gradual process with significant implications for society.

25:09

🛡 The Challenges and Future of AI Regulation

The script concludes with a discussion on the challenges of regulating AI, balancing the need to prevent misuse while not hindering technological advancement. The panelists consider the potential for international cooperation in AI regulation and the ethical implications of AI's growing role in various sectors. They also address concerns about AI's impact on jobs and the importance of ensuring that AI development benefits humanity.

👏 Closing Remarks and Audience Q&A

The final part of the script involves audience interaction, with attendees asking questions about AI's role in sports, the potential for AI to aid learning, and the impact of AI on job security. The panelists express optimism about the symbiotic relationship between humans and AI, suggesting that AI can enhance human capabilities rather than replace them. The session ends with a round of applause for the panelists, celebrating their pioneering work in the field of AI.

Keywords

💡Artificial Intelligence (AI)

Artificial Intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the video, AI is the central theme, with discussions on its applications in various fields such as healthcare, robotics, and gaming. The script mentions AI's role in medical diagnosis, creating movies, and developing new technologies like potential new antibiotics.

💡Technical Revolution

The term 'technical revolution' encapsulates the rapid advancements in technology that significantly impact society. The video discusses AI as a defining factor of the current technical revolution, highlighting its transformative potential across different sectors.

💡Mars Rovers

Mars Rovers are robotic vehicles designed to explore the planet Mars. The script introduces Paolo Pirjanian, who started his career working on Mars rovers for NASA, indicating the application of AI and robotics in space exploration.

💡Emotional Intelligence

Emotional intelligence is the ability to recognize, understand, and manage our own emotions and the emotions of others. The video mentions Paolo Pirjanian's work on emotionally intelligent robots designed to assist with child development, showcasing AI's potential to interact with humans on a more personal level.

💡Go

Go is a strategic board game of ancient Chinese origin that has been a significant challenge for AI due to its complexity. The script refers to David Silver's work on AlphaGo, an AI program that defeated the world's best Go player, illustrating the advancement of AI in mastering complex human games.

💡Reinforcement Learning

Reinforcement learning is a type of machine learning where an agent learns to make decisions by performing actions in an environment to maximize a reward. David Silver discusses his work in this area, particularly its application in training AI to play games like Go.

💡Oncology

Oncology is the branch of medicine that deals with the study, diagnosis, treatment, and prevention of cancer. Regina Barzilay's work in applying AI to oncology is highlighted in the script, emphasizing AI's role in improving cancer detection and treatment.

💡Antioxidant

An antioxidant is a substance that inhibits oxidation or reactions promoting the formation of free radicals in a living organism. The script mentions the use of AI in potentially discovering a new antibiotic, which could be significant in treating resistant bacteria.

💡Artificial General Intelligence (AGI)

Artificial General Intelligence refers to the hypothetical ability of an AI to understand, learn, and apply knowledge across a wide range of tasks at a level equal to or beyond that of a human. David Silver talks about his work towards achieving AGI, indicating the future direction of AI development.

💡Regulation

Regulation in the context of AI refers to the establishment of rules and guidelines to govern its development and use. The script discusses the need for AI regulation to ensure ethical practices and prevent misuse, reflecting on the balance between innovation and safety.

💡Robot Companions

Robot companions are AI-driven machines designed for social interaction and companionship. Paolo Pirjanian's work on creating robot companions for children with autism is mentioned, showing how AI can be used to provide emotional and social support.

Highlights

The discussion at Imperial College London focuses on artificial intelligence as a defining technical revolution of our era.

AI has achieved significant milestones such as defeating the world's best Go player and contributing to the discovery of a new antibiotic.

Paolo Pirjanian's company, Embodied, develops emotionally intelligent robots to aid in child development.

David Silver from Google DeepMind led the team that used AI to master the game of Go and is now working on artificial general intelligence.

Regina Barzilay's work at MIT involves using AI for early-stage breast cancer detection and discovering new antibiotics.

Regina Barzilay's personal battle with cancer motivated her to integrate AI into healthcare for improved diagnostics and treatment.

David Silver explains reinforcement learning, which allows AI to learn from experience, similar to how animals and humans learn.

Paolo Pirjanian discusses the creation of robot companions to address the need for companionship and therapy, especially for children with autism.

AI's potential in oncology includes dealing with uncertainty and improving diagnosis and treatment outcomes.

The complexity of the game of Go and how AI's intuitive approach to the game differs from traditional methods.

The emotional bond formed between children and robots, and the potential of AI to serve as a companion for the elderly.

The economic challenges in developing new antibiotics and how AI is being used to discover potentially effective new molecules.

The concept of artificial general intelligence (AGI) and the potential breadth of its applications across various fields.

The current limitations of AI in medicine, including regulatory hurdles and financial disincentives for doctors.

The ethical considerations and potential risks of AI development, including the need for international regulation.

The potential of AI to enhance human performance in sports through collaborations and data analysis.

Concerns about over-reliance on AI and the importance of maintaining human skills and learning.

The optimistic view of AI as a tool for human augmentation, potentially leading to greater human productivity and creativity.

Transcripts

Hello.

I'm Caroline Steele.

This is the BBC World Service.

And welcome to The Engineers.

This year we're at the Science Specialist University, Imperial College London.

And we're here to focus on the technical revolution

defining our era, artificial intelligence.

I'm joined by a panel of three world leaders in the field and a large,

enthusiastic audience in Imperial's Great Hall.

Already a computer can defeat the world's

greatest player at our most complex strategy game.

The first movie written entirely by AI

has just been released, and AI may have discovered

our first antibiotic in three decades.

Together with our partners, Royal Commission 1851,

we've brought together three engineers at the cutting edge of this field

to discuss their work and what it means for us humans.

Paolo Pirjanian

is Armenian, but he was born in Iran and started his career working on Mars

rovers for NASA.

He's now founder and CEO of Embodied, which is a company

that builds emotionally intelligent robots to help with child development.

David Silver

is from the UK, where he's principal research scientist at the AI

Research Lab.

Google DeepMind.

He led the team that used AI

to defeat the world's best player at the complicated strategy game Go.

And he's working on artificial general intelligence.

Regina Barzilay is Israeli-American and a distinguished professor for AI

and Health at MIT in the U.S.

She created a major breakthrough in detecting early stage breast cancer

and also led the team that used AI

to discover what is hoped to be a brand new antibiotic.

So please do join me in welcoming them all.

Regina, let's start with you.

So what is it that made you shift your work to oncology?

Sadly, you were in the perfect position to do that, weren't you?

Yeah.

So actually, I started my work at MIT in 2003

as a faculty and I was working on natural language processing and AI

And in 2014, I was diagnosed with breast cancer

and I was treated in one of the best hospitals

in the United States, Massachusetts General Hospital.

And what I discovered going through the treatment that there was really no AI

or not even basic information technology as part of the treatment.

Neither the diagnostics nor the treatment nor the post-treatment.

And, you know, after I was treated, I just was totally confused

as to what I want to do,

because it was the first time I realised that, you know, my life is finite

and I've seen a lot of very sick people there surrounding me.

And I was thinking, What can I do?

And MGH - this hospital at MIT - is just one subway stop away,

they are separated by a bridge

I’m saying, how come we have all this great technology at MIT,

but none of it is actually coming to the hospitals and helping patients.

So after I finished my treatment, I still didn't have my hair.

I started kind of going from doctor

to doctor, asking them, you know, how I can bring AI - I will do it for free.

I'm a professor.

So there were not many takers, but eventually

we found somebody who... it was a doctor called Connie Lehman

who had the idea that we can apply

AI to do early detection of cancer.

Thank you, Regina.

David, you came to AI via the games industry

and you did a PhD in reinforcement learning.

What is reinforcement learning and how did you use it in those early days?

Yeah.

So I guess I started out in the games industry before

I went back to academia and I was working on building computer games.

And as a big part of building computer games is building the AI

for those games, that kind of makes all of the characters move around.

And I found myself being fundamentally disappointed

by the methods that were being used in those games.

And it felt like

what I really wanted to do was build something that had real AI in it.

I discovered this idea of reinforcement learning, which is basically a method

very much like those that animals and humans use,

where the system is able to learn for itself from experience, from trial

and error, from trying things out and seeing what works and what doesn't.

So is it sort of like when we learn to

not touch fire because at some point we try it and it really hurts

and we learn don't do that in the future because the consequences aren't appealing.

Is it sort of like how humans learn reinforcement learning?

Yes, it's a lot like that.

So in fact

humans are believed to have, you know, a major part of the brain

which is devoted to providing a signal, giving feedback that

that makes the brain actually learn

to do more of the good things and less of the bad things.

And so actually, that's inspired a lot of work in machine

learning to make machines have that same capability.

But a machine doesn't feel heat or isn't rewarded by a cookie.

How can you reward a machine?

Yeah, so for a machine, it's just a number.

So you give it a positive number

if it's done something good and a negative number if it's done

something bad.

And at the end of the day, everything

stems from that one single number.

So this one single number, which we call the reward, contains

enormous power because it's the signal that drives everything.

Paolo, you said your experiences of feeling

alienated in foreign countries made you want to create an imaginary friend.

And I'm sure much of our audience can relate to having an imaginary friend,

but for most of us, they stay imaginary.

How did you go about making a real one?

So unfortunately, there's a lot of people

in need of companionship or therapy,

and there's a massive gap of labour force

that can provide us, as an example, to use numbers from the U.S.

We know the prevalence of things such as autism is growing rapidly.

Ten years ago it was one out of about 200 kids.

Today, it's one out of about 30 kids.

So the experiences I had, which was leaving my family

at a very young age, living abroad in a society that's amazing.

I mean, these are amazing people,

but yet you are different, so you are not going to be embraced.

So this is not too dissimilar from a child on the autism spectrum

that has a hard time expressing themselves or reading emotions from other people.

And that was the genesis of creating a robot companion that understands

human emotions, can create a deep relationship

with a child, and it'll help them exercise and practice social skills

such as eye contact, turn-taking, joint attention and so on,

so that the child has a chance of being successful in their society.

Thank you.

Regina, what can AI do

when it comes to understanding cancer that humans can't?

So I think that in cancer and in many other diseases,

a big question is always, how do you deal with uncertainty?

And unfortunately, today we rely on humans who don't have this capacity

to make predictions.

And as a result, many times people get wrong treatments

or they are diagnosed much later.

And one question that really troubled me is, you know, how late I was diagnosed

and when we already developed a model, I came back to my own mammograms

and rediscovered the mammograms two years earlier

already had on a tiny small cancer.

Now, for human eye, for radiologists,

it's impossible to diagnose it because it's so, so confusing.

There's so many other spots on your tissue.

So what AI can do, it can do a lot of tasks which humans cannot do.

Take all the data that we have

and remove the guessing out of diagnosis and treatment.

Thank you.

David, AI had already defeated the reigning grandmaster, Garry Kasparov, at chess

well before you started your project

AlphaGo and the rules of Go sound quite simple.

Basically, on each turn, a player puts down a counter on the board

and you gain territory by connecting your counters

and the player with the most territory at the end of the game wins.

So why is it harder for a computer to beat a human at Go than at chess?

Which sounds more complicated.

So the game of Go is this very beautiful and elegant game

where it seems at first glance like the rules are very simple.

But once you start to understand it a bit like unpeeling

an onion, you discover more and more layers of complexity

and what's amazing is that when humans play this game, they basically...

If you ask them to describe how they did something, they really don't know.

They've used incredible intuition.

And so these amazing professional players who've devoted their entire lives

to this game have built this incredible intuition and creativity

and intuition and creativity are two traits which were previously

considered to be very human and very hard to build into machines.

So while chess, it was possible to succeed just with tactical look ahead

in the game of Go, that wasn't enough because, you know, early on in the game

you just have this handful of stones on the board and you really just have to

imagine what the game will pan out like, you know, 300 moves later

with this sort of intuitive sense of where it will go.

And that required some some major breakthroughs.

Paolo, debatably even more complex than Go is human children.

Your human centred robot forms an emotional bond with children.

How can a robot do that?

Well, first of all, it's important

to make clear that the robot is not meant to replace the need for human contact.

It's really almost like training wheels to teach children the social skills

and then be able to practice those in real life.

The way the robot forms

bond is that humans are wired to bonding.

We create connections with inanimate objects all the time.

I mean, with a robot that has eyes, can make eye contact,

can smile back at you and can speak to you and express emotion and empathy.

It's actually not that hard to create a bond there.

And children open up to to these robots very quickly

in ways that they may not even open up to their therapists or parents.

Thank you, Paolo.

Regina, you not only made an impact on oncology, your team at MIT used

AI to discover what could be our first new

antibiotic in three decades.

It seems it can be E. Coli, MRSA, and strains of bacteria

which are currently resistant to all other antibiotics.

So I think we all wish it success.

How did you do that?

So I should say

that, you know, developing antibiotics is not an area

with an immense competition, even though their resistance to

to antibiotics that we have continues to grow.

This happened to be an area where pharmaceutical companies

are not very active because economically it doesn't work for them.

So in some ways we do need to have alternative approaches.

I met a colleague and he was working.

He was from biological engineering, he was working on antibiotics.

And he was describing the big problem of finding new molecules

which are effective against bacteria, drug resistant bacteria.

But at the same time, are not toxic to humans.

They have some molecules screened against, I think E.coli.

We started with that

and then we just gave to the machine, you know, thousands of molecules.

And for each molecule you knew whether it kills a bacteria or not.

It was kind of the first attempt to learn automatically.

How do you look at the structure

of the molecule and predict whether it would have a desired effect?

We found a molecule that didn't look like something human created.

And it turns out in the lab that it was able to kill

using a different mechanism of action, kill it in a different way.

And that's what made it so effective against so many different species.

David, let's go back to you.

So, so far we've been talking about systems designed to perform

one task - that's known as narrow AI,

but you're working towards artificial general intelligence.

Could you explain what artificial general intelligence is?

So if you think about humans and human intelligence, it's

this wonderful and beautiful thing where we're able to learn skills

which are incredibly diverse, where,

you know, one person might choose to specialise in learning how to play tennis

and another person might specialise

in becoming an amazing chef and another person, a pianist

and another person, a scientist and so when we want to build

artificial intelligence, we want systems which not only solve a single problem

but in a similar manner to humans, are able to approach

any number of problems with intelligence, and

that's capable of doing amazing things in each of those different areas.

And that's what we refer to as artificial general intelligence or AGI for short.

And how far off do you think we are from that being a reality?

So I think it's going to be a spectrum over many years.

And I also think it's likely or at least plausible

that there are many breakthroughs that are still required

before we can really crack, you know, the same kind of

level of intelligence that humans have.

Regina, you've developed AI to better predict cancer,

but it's only employed in a tiny number of cases, right?

Why is AI not used more widely in medicine?

The problem is that we're creating a lot of great technology,

but this technology is not really translated into patient care.

And if I would ask the audience, you know, how many of you when you last saw

your physician, have you actually seen any AI,

and I'm sure not many can really attest to it.

So I think

the technology for many of the tasks is really mature,

but there are many other questions which have nothing to do with AI per se.

One is the regulation or regulations, in Europe,

UK, US - continue to change.

Another big problem is people don't really know how to bill for AI.

And today the American doctor who uses AI loses money

when they see a patient.

So it's not much of a motivation.

So just to clarify that, did you say that using AI for doctors in the US

could actually make them lose money because it makes treatment more effective?

I'm referring to a specific paper.

The way the billing is done

it somehow relates to the time the doctor spends with a patient.

So if you have something that makes it faster, you're actually losing money.

Very depressing.

And Paolo, what about your challenges?

The robot you've developed mimics human behaviour.

What's next?

I'm very hopeful with what we are doing in terms

of creating social emotional AI systems

that can help humanity become its best.

If we can intervene early with children for instance on the autism spectrum,

they have a chance of really integrating well with the society and

doing really well.

When we think about other vulnerable

areas of our life is when we age.

Social isolation, being lonely, and that leads to mental

health issues, that leads to physical health issues and so on.

We can have the same systems become a companion that help you there.

Once we figure out the physical task,

you can also imagine that they can give you assistive care,

meaning that they can be not only a social emotional companion for you,

but they can also be a companion and say, let's cook some food together,

let's go for a walk together and so on, which is going to help

a lot with independent living with dignity

when we are at that age.

Do you think we'll see robots helping with assistive care in the future

any time soon, or is this way off in the distance?

I think it is within the next decade.

Oh wow. David, you're working on Gemini, which is Google's answer to ChatGPT,

and you aim for it to be able to do both tax returns and write a novel.

People would probably be very happy to have their tax returns done or I would

definitely would be.

But novels, should we really be letting AI sort of take over human culture?

So it's a great question.

I think I wouldn't see it as taking over human culture.

I think what will happen, or the most likely outcome, is that we'll be

providing an incredibly powerful tool to human authors.

So we've already seen this in a number of areas where

we've developed technologies that enable authors of different

kinds of media to basically create things much more powerfully using tools.

So, for example, there's a music authoring system called Lyria

that was released recently, and there's this wonderful footage of

Will.i.am when he's playing with it for the first time.

And he's just so excited because he says it can kind of speed up

his songwriting process by, you know, 10 to 100 times.

So I think, you know what I really hope we get to is a world in which the

AI and the humans kind of work together to just make everything better.

So, you know, I'm excited to be in a world where we have much more...

the most amazing novels that we can imagine,

that which go far beyond the ones we have today.

Thank you, David.

Thank you.

This is The Engineers - Intelligent Machines from the BBC World Service.

We've discussed medical AI, emotionally intelligent robots, the goal

of artificial general intelligence and the threats AI might pose.

Has anyone got a question on anything we've discussed so far? Wow.

Okay.

Pretty much everyone has a hand up, so this is going to be tricky.

Could we start with the man in the red shirt?

If you could stand up and say your name and your question.

Thank you very much.

Hello, my name's Simon. The British government wants to make Britain

a leader in AI and sees the way to do this by making it a safe space.

They're looking at doing that by making sure you can't develop

AI where you don't understand the consequences before you develop it.

Does the panel think that's the right approach?

So, yes.

David, what do you think about legislation around AI?

I think we need some kind of regulation.

I think it's, you know, an area which clearly is going

to have more and more consequence and impacts on society.

So I think regulation is important.

I think some of the areas which have been agreed

in various summits over the last year - you know, fantastic start.

One thing I would say is I think it's hard sometimes

to come up with like a one size fits all recipe for AI

because it's so different in different areas.

So you know, the regulation that you might need in medicine might look

quite different to the kind of regulation you might need for, say, a chatbot.

So I think, you know, we have to look at each area separately

and make sure that whatever we do, you know, we really fully understand

the consequences of what the impact of AI will be in that area.

There's a lot of anxiety about the pace

AI is moving, right?

We have people resigning, leaders in the field to campaign

for more safeguarding against the threat of misinformation,

the threat to jobs, and even an existential risk to humanity.

Regina?

I actually feel quite opposite.

People are really suffering. There are lots of incurable diseases.

It's hard for patients, it's hard for their families.

There is a lot of technologies that is out there

and because we cannot get together to put the regulation in place,

make, you know, the payers take part of it and find a way to bring it

I think we are really making many, many people suffer.

Thank you. Paolo, what about robots?

Are they going to take all our jobs?

Yes.

Yes. Okay, great. We've got it.

We finally have an answer. Thank you, Paolo.

On a serious note, I feel it's a bit of a

conundrum to think about legislation, because on one hand,

yes, there are definitely risks and you would like to regulate it

so that no one with bad intentions goes wild.

On the other hand, if you think about it, it's an extremely

potent technology.

It could change everything

in our lives including

being strategically important technology

to master from a national perspective.

And from that perspective, if you regulate it,

let's say part of the regulation is slowing it down,

what are our adversaries going to do?

Are they going to then have an advantage over us?

So it's a bit of an arms race.

And I think for that reason, practically

speaking, I think it's going to be very hard

to regulate it to that level unless you can have

international regulation and agreement

across all the powerful nations to say this is how we're going to handle it.

And I haven't seen that work out very well in the history of time.

Fair enough.

Audience, we have time for a couple more questions.

So hands up. If we could go to the man in the white top.

Thank you.

Hello, panel. My name's Rob.

And I'm a business and sports coach.

And I'm wondering whether what you've been talking about

is possible for helping humans to improve their performance

at a sport.

Good question.

Who's our greatest sport enthusiast?

Perhaps this one is for you, David.

Can we be using AI to improve sports performance?

It's a great question.

There's a lot of really amazing research that's happening to try and do just that.

You know, one thing which we've been doing at Google DeepMind is actually

a collaboration with Liverpool Football Club to try and help them improve

their tactics.

So that's one example.

I think, you know, the amazing thing about sports is it's become over time

so refined in terms of the particular approaches

that people take that actually, you know, really they're very open

to new discoveries and new ways to do things.

And so it's been really fun actually, just watching that kind of thing unfold.

Very cool. Thank you, David.

I can see we've got lots of young people in the audience, some teenagers even.

Does any of our younger audience have a question?

If so stick your hand up.

There was a young lady who had a hand up here

with a ponytail. Yes.

As AI develops, I reckon

that humans probably depend more on AI and maybe learn less.

Is there anything we could do to maybe make sure that as it

develops, humans still develop and learn?

Ooh, good question.

So will we stop learning, as AI does the learning instead for us?

I'm going to put that to all of you if that's all right. What do you think, David?

I'd like to imagine a world where we have an AGI

which is like a personal friend, assistant teacher,

and everything we do understands what we want to learn, and it knows

just how to teach us and help us to learn more and more and more and more.

Regina, what do you think?

Do you think we're just going to end up relying on

AI for everything?

As a non-native speaker of English

I remember as a young professor I spent a humongous amount of time

like reading my papers and making sure, you know, because in my native language

we don't have

and so I make a lot of mistakes when I write.

I see now how I write papers.

Actually, it removes a lot of my pressure in writing

and I can really focus on ideas rather than doing the small things.

So I hope that we will find a symbiosis.

We don't really, you know, remove our basic skills,

but we can just do more and focus on the things that we can do better.

I would like to imagine if Isaac Newton or Albert

Einstein had access to these tools today, I mean, as prolific

as they were at a time where we didn't even have calculators,

imagine what they would have done and the impact it would have had on the world

if they had access to these tools. In the next five years

potentially, you don't need to code.

You will just tell

your favourite AI system and say I want a code that does x, y, z

and you can accomplish what would take years of many people in hours today.

So it will make you more prolific.

Thank you.

I think it's fair to say all three of you have given us hope for the future.

Audience, thank you so much for your questions.

I wish we could take more, but I'm afraid we're out of time.

That's it for The Engineers -

Intelligent Machines at Imperial College, London.

I'm Caroline Steele.

On behalf of the BBC World Service

our partners

the Royal Commission for the Exhibition of 1851 and my producer, Charlie Taylor.

Please join me in giving a warm round of applause for our brilliant pioneering

AI engineers Regina Barzilay, Paolo Pirjanian and David Silver