Regulating AI for the safety of humanity
Transcriber: Maurício Kakuei Tanaka
Reviewer: omar idmassaoud
“The development of full
artificial intelligence
could spell the end of the human race.”
The words of Stephen Hawking.
Do you want to live in a society
of constant AI surveillance
and invasive data collection?
A society where AI decides
whether you’re guilty of murder or not,
whilst also being able to create
ultrarealistic deep fakes,
planting you at a crime scene.
A society where AI
developed to kill cancer
decides that the best way to do so
is to exterminate any human
genetically prone to the disease.
I know I wouldn’t,
but this is what a society
without AI regulation
could look like.
Of course, these are
very far-fetched outcomes,
but far-fetched does not mean impossible.
And the possibility of an AI dystopia
is reason enough to consider AI regulation
so as to at least address
the more apparent
and immediate dangers of AI.
So first, what actually is AI?
Well, artificial intelligence is a theory
and development of computer systems
able to perform tasks normally
requiring human-level intelligence.
The thing that lets us
make things like this.
A plagiarism checker.
OK, maybe not the most popular
use of AI among students,
but what about this?
A smart home.
Or this?
A Mars rover collecting data
analyzed by AI.
Or this?
A self-driving car?
Seems pretty cool, right?
That’s what I thought.
And it was a self-driving car
that particularly caught my attention.
So last summer, I decided to build one.
I made a small robot one
so that it could autonomously
navigate through lanes
using nothing but a camera,
an ultrasonic sensor,
and a neural network I made.
And it was driving perfectly like this
until one day it just starts
to consistently veer out of the lane.
I spent hours trying to find the bug.
And you know what It was?
A deleted bracket.
I’d accidentally deleted a bracket
when editing the code,
and they stopped
one function from running,
causing the entire system to fail.
And this demonstrated to me,
on a small scale,
how one small bug can have
devastating consequences.
And then I started to think,
“Imagine if this happens
on a larger scale,
say, in a real self-driving car
or nuclear power plant.
Imagine how devastating that would be.”
Well, unfortunately,
you don’t have to imagine.
In 2016, a self-driving Tesla
mistook a white truck trailer
as the bright sky,
leading to the death
of the Tesla occupant.
And this made me think,
“We have regulation
in health care and education
and financial services,
but next to none in AI,
even though it’s such a large
and growing aspect of human life.”
We are all aware of the digital utopia
that AI can provide us with.
So surely we should introduce regulations
to ensure we reach this utopian situation
and avoid a dystopian one.
One suggestion is a compulsory
human-in-the-loop system,
where we put serious research efforts
into not only making AI
work well on its own,
but also collaborate effectively
with its human controllers.
This would effectively
give humans a kill switch
so that control can be
transferred back to humans
when a problem is expected.
But for those in search of a less
restrictive form of regulation,
a transparency-based approach
has been suggested
whereby firms must explain
how and why their AI makes its decisions,
essentially a compulsory
open-source system.
This would allow third parties
to review the AI systems
and spot any potential dangers
or biases before they occur.
However, this could reduce competition
and incentive to innovate
as ideas can easily be copied.
And this demonstrates
just how difficult it is
to regulate AI in a way
which suits everyone
as we must ensure safety
whilst also ensuring
that regulation does not stifle
worthwhile advances in technology.
This would suggest
that the most effective way to regulate AI
would be to introduce AI-specific boards
into the government,
allowing AI experts to make regulations
rather than politicians.
The most important thing for us
is that we don’t settle
for a “one-size-fits-all”
regulatory approach
as a range of possible uses of AI
is far too diverse for this.
You wouldn’t use the same regulation
for a self-driving car
as for a smart fridge.
So our main goal
should be to learn more about
the risks of AI in different applications
to understand where regulation
is actually needed.
And an AI-specific government board
would be far more efficient at this
than politicians who were just
not familiar with AI.
And if people are fundamentally
against government intervention,
then a company-led self-regulated system
must be established.
Trust is very hard
for technology firms to gain,
but also very easy for them to lose.
And since trust is such a vital
commodity for businesses,
it would be in their interest
to go above and beyond
the minimum legal standards
in order to gain
this valuable consumer trust.
As being seen to promote AI safety,
offers an easy way to gain trust
was actively opposing it,
or quickly lose the trust
they worked so hard to gain.
It’s likely that regulation strategies
will differ around the world,
with some countries
taking the government-led approach
whilst others opt
for a company-led approach
or even a mix of the two.
And that is OK.
But the most dangerous thing we can do now
is to completely run away
from the idea of AI regulation.
Google CEO Sundar Pichai has said,
“There is no question in my mind
that artificial intelligence
needs to be regulated.”
Elon Musk has said that AI
is more dangerous than nukes.
When even the people
developing AI themselves
agree with the need for regulation,
it’s time to get down to the business
of how to regulate the rapidly changing
field of artificial intelligence.
Thank you.
(Applause)