- **Automation of routine, script‑based work** (e.g., call‑centre agents, document summarisers, copywriters) is imminent. - Jobs that require **human insight, creativity, and emotional intelligence** will become more valuable as AI handles the drudgery. - New business models and services will emerge that we cannot yet imagine.

The AI Revolution: Insights from Professor Mike Wooldridge, Royal Institution Lecturer — Summary

Q: What Is Artificial Intelligence?

- **A broad church** – No single entity “owns” AI; it encompasses many ideas and goals. - **Two main camps**: - *General AI*: The Hollywood‑style vision of machines that match or exceed all human abilities. - *Narrow (or applied) AI*: Tools that excel at specific tasks, such as diagnosing heart scans or spotting tumors on X‑rays. The bulk of current work falls into this camp.

Q: Recent Breakthroughs (Around 2020)

- A **step‑change in capability** occurred circa 2020, before the public noticed ChatGPT. - New models were dramatically better than their predecessors, prompting researchers to recognize a **new era** of AI. - These systems are **phenomenally complex**, making it a scientific challenge to understand how and why they work.

Q: AI as a Mass‑Market Technology

- Like the early World Wide Web, AI is moving from specialist labs to everyday tools **within months** rather than years. - Expect ubiquitous features such as: - Selecting a paragraph in Word and instantly getting a summary, a simplified version for a 10‑year‑old, or a professional rewrite. - Seamless integration into browsers, word processors, and countless other applications.

The Royal Institution

Jan 20, 2026

•

3 min read

The AI Revolution: Insights from Professor Mike Wooldridge, Royal Institution Lecturer

Introduction

Mike Wooldridge, professor of artificial intelligence at the University of Oxford and director of AI at the Alan Turing Institute, delivered this year’s Royal Institution Christmas Lecture on artificial intelligence. Drawing on over 30 years of research, he explored what AI is, why it matters now, and how it is reshaping society.

What Is Artificial Intelligence?

A broad church – No single entity “owns” AI; it encompasses many ideas and goals.
Two main camps:
General AI: The Hollywood‑style vision of machines that match or exceed all human abilities.
Narrow (or applied) AI: Tools that excel at specific tasks, such as diagnosing heart scans or spotting tumors on X‑rays. The bulk of current work falls into this camp.

Recent Breakthroughs (Around 2020)

A step‑change in capability occurred circa 2020, before the public noticed ChatGPT.
New models were dramatically better than their predecessors, prompting researchers to recognize a new era of AI.
These systems are phenomenally complex, making it a scientific challenge to understand how and why they work.

AI as a Mass‑Market Technology

Like the early World Wide Web, AI is moving from specialist labs to everyday tools within months rather than years.
Expect ubiquitous features such as:
Selecting a paragraph in Word and instantly getting a summary, a simplified version for a 10‑year‑old, or a professional rewrite.
Seamless integration into browsers, word processors, and countless other applications.

Impact on Jobs

Automation of routine, script‑based work (e.g., call‑centre agents, document summarisers, copywriters) is imminent.
Jobs that require human insight, creativity, and emotional intelligence will become more valuable as AI handles the drudgery.
New business models and services will emerge that we cannot yet imagine.

Transforming Science

Experimental sciences (astronomy, particle physics, biology, chemistry) generate massive datasets.
AI now offers tools to:
Analyse data at scale.
Detect patterns and generate hypotheses.
Example: An astronomer can train a model with labelled images of spiral and barred galaxies, allowing the AI to classify millions of galaxies automatically—replacing a labor‑intensive manual count.

Risks and Responsible Use

Misuse: AI can be weaponised for disinformation, privacy invasion, or biased decision‑making.
Data privacy: Users often become unwitting providers of personal data when interacting with AI systems.
Awareness and ethical guidelines are essential to harness AI’s benefits while mitigating harms.

Future Outlook

The next few years will see AI embedded in virtually every digital interaction.
Young innovators will devise clever, unforeseen applications, enriching work, leisure, and education.
Ongoing scientific debate about whether AI‑generated hypotheses constitute true science, but the momentum toward AI‑augmented discovery is undeniable.

Conclusion

AI is undergoing a rapid, watershed transformation comparable to the advent of the World Wide Web. Its integration into everyday tools, workplaces, and scientific research promises unprecedented productivity and creativity, yet it also raises serious ethical and societal challenges that must be addressed proactively.

AI is entering a fast‑moving, transformative era that will reshape work, science, and daily life, making it essential to embrace its potential responsibly.

Takeaways

A broad church – No single entity “owns” AI; it encompasses many ideas and goals.
Two main camps:

Optional Next Steps

Tools and resources related to the topics discussed above.

Helpful resources related to this video

If you want to practice or explore the concepts discussed in the video, these commonly used tools may help.

Artificial Intelligence: A Guide for Thinking Humans book

Provides a clear, accessible overview of AI concepts and current capabilities, helping readers understand the rapid changes discussed in the lecture

View on Amazon →

Deep Learning by Ian Goodfellow book

Offers an in‑depth technical foundation for the neural network breakthroughs that sparked the 2020 AI leap

View on Amazon →

Raspberry Pi 4 Model B kit

Enables hands‑on experimentation with AI models on affordable hardware, encouraging the practical exploration highlighted by the speaker

View on Amazon →

Links may be affiliate links. We only include resources that are genuinely relevant to the topic.

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Full Transcript

- So my name's Mike Wooldridge.
I'm a professor of artificial intelligence
at the University of Oxford
and director of AI at the Allen
Turing Institute in London.
I'm an AI researcher.
I've been an AI researcher
for more than 30 years,
and the reason that I'm here today is
I'm this year's Royal
Institution Christmas lecturer,
which will be on artificial intelligence.
The question, what is
artificial intelligence
is just a phenomenally difficult one.
Nobody owns artificial intelligence.
It's a very broad church.
Lots of people have very
different ideas about what it is
and what it should be.
For some people,
artificial intelligence
is the Hollywood dream.
What they're after is
the idea of building machines
which are as fully capable
or perhaps even better,
more capable than human beings.
Machines that could do everything
that a human being could do.
And that's sometimes called
general artificial intelligence.
For other people, and I'm
more in that other camp,
artificial intelligence
is about building tools,
building computers that
can do very specific tasks
better than human beings can.
So for example,
machines that can diagnose
abnormalities on a heart scan
or spot tumours on an X-ray,
those kinds of things.
And the bulk of work in
artificial intelligence
is around those kinds of problems.
But I say it's a broad
church, nobody owns it.
I certainly don't own it.
You know, everybody listening to this
will have their own views.
But I have to say the
centre of gravity in AI
is around extending the
capability of machines,
to get machines to do things,
which currently only human beings can do.
I hate the word revolution
to describe these things,
but I think what we've seen
is genuine breakthroughs in the sense of
a step change in capability
of AI in the last few years,
and it happened around
about 2020 prior to ChatGPT.
ChatGPT is the one that everybody noticed,
but around about 2020,
there were AI systems released,
which were markedly better
than the systems that went before them.
And that really got the
attention of AI researchers.
And we realised,
okay, this is a different game now.
We are in a different league here
in terms of the capability.
And so genuinely, I think
somewhere around about 2020
we moved into a new era.
Things have definitely changed.
And everybody in my
community is busy exploring
what these new technologies can do,
what these new AI systems can do,
trying to understand them,
which in itself is no trivial thing.
They are phenomenally complicated things
to try to understand why
they do what they can do
and how they do what they can do.
But yeah, I think we are...
This is one of those moments
like the emergence of the worldwide web
that is going to be a watershed moment
in scientific history.
We are at the point now
where general purpose AI technologies
are reaching a mass market.
And that's a new thing.
We haven't been there before
and it's happening very, very quickly.
So when the worldwide web first appeared,
it took sort of five or six
years for it to really reach
a mass audience before
people on the clap of
omnibus were using it.
And we've seen much more rapid take up
of these general purpose AI tools
just in the last year.
And so things are
changing much more quickly
than we've been used to in technology
over the last few decades.
We've seen lots of technological changes.
The arrival of smartphones
around about 2010,
and then going back to the
worldwide web before that
and then before that,
the desktop computer and so on.
But they all took, you
know, years to unfold.
And we're seeing this unfold
in the period of months
if not weeks.
So it's just gonna be embedded
in absolutely everything.
And to some extent it already is,
but we're gonna see a lot more rollout
of that technology into
your Word processor
and your web browser.
And so within a year,
I predict,
pretty confidently predict at this point,
you know, you'll be able
to just select a paragraph
in your Word document
and there'll be an option to summarise it
or to turn it into beautiful English
or to turn it into English
that would be understandable
for a 10-year-old audience
or for a professional
business audience and so on.
And people won't even
realise that that's AI.
But absolutely it is AI,
This generation is gonna
think of ways of using this
that we can't even begin to imagine.
They're gonna think up
very clever, ingenious,
and for us, old fogies weird ways
of using this technology.
They're gonna create new
businesses and services, again,
that we can't even guess at right now.
They're gonna find applications
for it in their work life.
It's gonna make them more productive.
It's gonna take away a lot
of the drudgery I think
for an awful lot of jobs,
and free them up to do the things
that require human
intelligence and human insights
and emotional insight and so on.
It's gonna free them up
in their jobs to do that.
They're gonna find ways
of using it in leisure,
it's gonna appear in computer games
and endless different applications.
So it's gonna enrich their world
and in an enormous number of ways.
But for every potential
beneficial use of this technology,
there are ways in which it
can be abused and misused.
And it is just so important
that people understand
what those are and go
into using the technology
with their eyes open.
And I think one of the most important ones
was the issue of data
and being the unwitting
provider of data about yourself.
So everywhere where
people deal with content,
with understanding content, processing it,
you know, people whose jobs
are to take due documents
and to summarise them, collate
them into a single document,
you know, just in London
there are probably 100s of 1000s of people
whose jobs more or less
involve doing just that.
People whose job is to summarise
or extract their key points from text,
people who create routine copy,
pieces of text,
people who create routine
pieces of artwork,
all of those in the very near future
are gonna be affected by this technology.
If your job largely
involves following a script,
and the only thing that you
are really required to do
is to understand what another
human being is saying,
but otherwise you're
just following a script,
then those kinds of jobs seems
to me are very vulnerable.
And in the UK one area
of immediate concern
is around call centres.
And there are 100s of
1000s of people in the UK
employed in call centres.
And there is potential,
it hasn't happened yet,
but there is potential for AI technology
to automate a lot of those processes.
It is absolutely changing science.
All the experimental sciences are
busy looking to see what they
can do with AI technologies.
And if you're in experimental science,
you produce data
and things like the square
kilometre array telescope,
all of those,
like CERN produce vast, vast,
vast quantities of data.
And AI now gives you another tool
to be able to analyse that data,
to spot patterns in it,
to maybe form hypotheses about
what's going on in the data.
Now I have to tell you,
there are scientists out there
who think this is more or
less the end of civilization.
You know, the idea that
it's no longer human beings
that are forming the hypothesis,
but that a machine is forming a hypothesis
or maybe even the machine
isn't even doing that.
It's just telling you that if
you eat these red toad stools,
then you'll die.
But it can't tell you why
or form a theory about why you would die.
And some people don't think that that
kind of extreme inductivism
as it's sometimes called
is even science.
But everybody is
frantically looking to see
what they can do with this.
So it really is changing
science across the board.
So suppose you are an astronomer
and what you're trying to do
is you're trying to figure out
how many spiral versus bar
galaxies there are out there.
So what do you do?
You can take pictures of the sky
and expose them for a long time
and you'll get pictures of
lots and lots of galaxies.
And 20 years ago you would
go through those pictures
and you would count
the number of spiral versus bar galaxies.
So how does AI help you with that?
Well, with AI, what you
can do is you simply
rather than writing a
programme to identify a spiral
or a bar galaxy,
what you do is you
simply show the programme
and you say, "that's a spiral
galaxy, that's a bar galaxy,
that's a bar galaxy, off you go."
And the programme figures out
how to do that identification on its own.
And that's what the
technology of neural networks
and the like,
the machine learning technologies,
that's what they're extremely good at.
And that's just one example,
one very simple example
of how the technologies might
be used in modern science,
but you can think of exactly
the same kinds of scenarios
everywhere you look in science,
in biology, in chemistry and so on.
I'm absolutely fired up and
interested in this subject.
And one of the reasons is
because stuff that seemed like it was
just unimaginably distant
at the start of my career,
we now have.
You know, we have tools
that you can just converse
with in ordinary language.
They didn't exist even a decade ago.
Nothing like the tools
that we have now existed even a decade ago
and stuff that was just pure
speculation and philosophy
10 years ago, now we can just...
We actually can try out
and it's transforming AI
into a kind of new science,
we're reinventing AI as a field
to be able to explore what
large language models can do,
what they can't do.
You know, do they really
understand people?
Do they really understand at all?
And these used to be
philosophical questions
and now they're practical ones.
We can actually roller past
sleeves and try things out
and that's just enormously,
enormously exciting.

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Jan 14, 2026

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The AI Revolution: Insights from Professor Mike Wooldridge, Royal Institution Lecturer

Introduction

What Is Artificial Intelligence?

Recent Breakthroughs (Around 2020)

AI as a Mass‑Market Technology

Impact on Jobs

Transforming Science

Risks and Responsible Use

Future Outlook

Conclusion

Takeaways

Optional Next Steps

Helpful resources related to this video

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