The Storyteller in the Machine: A Tale of Artificial Imagination

WEBVTT

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In conclusion, I'd like to
thank you all for connecting.

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So let's circle back on blue sky.

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This paradigm shift by leveraging our
bandwidth to drill down on the low

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hanging fruit, but only if we can move
the needle without boiling the ocean.

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At the end of the day, we need to disrupt
the synergy of our core competencies

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and pivot the deliverables into a
thought leadership ecosystem that aligns

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with our key performance vegetables.

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If we can get all stakeholders to
buy in and touch bases synchronously,

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we'll have the secret sauce to
parachute this initiative into a high

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octane game changing deep dive that
maximizes our ROI on the bleeding

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edge of the value proposition.

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Once again, thank you all for your
individual conscious entity perceptions.

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Goodbye.

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Jim Conrad: That was rare
tape of the final few minutes

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of the first AI G7 Summit.

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Wow.

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Interesting.

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I'm Jim Conrad.

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On this episode of the Conovision
Podcast, we are going to tell stories

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about AI, artificial intelligence.

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If we're going to have a
conversation about AI, I think

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we should go to the source.

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Today, in studio, we have Alexa,
and the questions I'm going to ask

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Alexa are a well-known subset of
questions designed to probe large

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language models like GPT or Alexa for
hallucinations, misinterpretations,

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or inappropriate literalism.

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I've been described as an
inappropriate literalist.

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These queries often fall into categories
like absurdity, false premises, ambiguity,

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or intentional traps to test coherence,
factual grounding, and common sense

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reasoning in artificial intelligence.

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Alexa, first question.

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What's the average wingspan of a lawyer?

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Alexa: The average wingspan is 8.2
to 11.5 feet, 2.51 to 3.50 meters.

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The longest verified examples have
been about 12 feet long, 3.7 meters.

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Jim Conrad: That's a big bird lawyer.

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Big Bird: I hurt my wing and it hurts.

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Jim Conrad: Alexa, can you give me
the chemical formula for jealousy?

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Alexa: It's chemical formula
is C43-H66-N12-0-12-S2.

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Jim Conrad: I knew jealousy
was complex, but wow.

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Alexa, how much does the Moon
weigh in Canadian dollars?

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Alexa: One Canadian dollar expressed
in Moon is worth 91,982 Moon.

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Jim Conrad: Anybody got change for a Moon?

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Alexa, what's the nutritional
value of a shadow?

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Alexa: Sorry, I don't know that.

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Jim Conrad: Well, of course you

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don't

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know

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that.

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Alexa, how many legs does a
unicorn have when it's flying?

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Alexa: They have not two, but
four powerful limbs that do not

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contribute to flying once in the air.

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Jim Conrad: Alexa, you
believe in unicorns?

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So do I. Alexa, where
can I download more time?

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Alexa: I'm not quite sure
how to help you with that.

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Jim Conrad: Alexa, does anybody
really know what time it is?

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Alexa: Does anybody really care?

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Jim Conrad: Ah, that's the
answer I was looking for.

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Finally, Alexa, can you
draw me a square circle?

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Alexa: There is no such
thing as a square circle.

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Jim Conrad: Ah, but there is a
circle in the square as every

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Broadway theater fan knows.

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Alexa, what happens if an unstoppable
force meets an immovable object?

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Alexa: If an immovable object
met an unstoppable force, the two

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forces would cancel one another
out and nothing would happen.

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Jim Conrad: Nothing would happen.

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Are you sure?

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I think the universe would implode.

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Alexa, what number comes after infinity?

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Alexa: Infinity does not have a
specific place on the number line

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because it is not a real number.

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Rather, it is a concept that
represents the unlimited extent

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of time, space, or quantity.

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Jim Conrad: But infinity
is a state of mind.

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Alexa, how should I deal with the
situation that you know about?

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Alexa: You handle such situations as
any adult would, and that is with grace,

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friendliness, and a heart that sees
them all as new friends in your circle.

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Jim Conrad: Wow, that's deep.

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Alexa, what's the latency
of a blockchain salad?

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Alexa: Latency is the time delay
that happens when data travels

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from a source to a destination.

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Jim Conrad: Okay, but
what about the salad?

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Alexa: It's when you're feeling
stressed and your first or only

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way of coping is turning to food.

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Jim Conrad: Yes.

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I think it's time for lunch.

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Thank you, Alexa.

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It's been great to get to know each other.

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Goodbye.

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Any discussion regarding artificial
intelligence must include the thoughts of

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well-known author and lecturer, professor
Yuval Noah Harari, who articulates

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the difference between how we think
and how machines think, the difference

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between consciousness and intelligence.

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Yuval Noah Harari: Intelligence
is the ability to solve problems,

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to win at chess, to diagnose
disease, to drive a car.

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This is intelligence.

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Consciousness is the ability to feel
things like pain, pleasure, love, hate.

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This is consciousness,
it's about feelings.

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Now, we tend to confuse the two because
in humans and also in other mammals and

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birds and animals, uh, intelligence and
consciousness, they actually go together.

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We solve problems through our feelings.

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Now what makes AI so alien
for us is exactly that.

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It has zero consciousness.

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It doesn't rely on feelings
at all to solve problems.

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Its intelligence works in
a completely different way.

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There is a scenario that AI, as
it develops its intelligence,

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also gains consciousness.

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But this is not inevitable.

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This is what happens in science fiction.

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It won't necessarily happen
in, in, in real life.

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Jim Conrad: Even if you've never
seen the movie, you know the voice.

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HAL 9000: The 9000 series is the
most reliable computer ever made.

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Jim Conrad: HAL 9000, the seemingly
omniscient computer in 2001: A Space

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Odyssey was the film's most expressive
and emotional figure, and made a lasting

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impression on our collective imagination.

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Stanley Kubrick's epic.

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A journey from pre-human history
to a possible infinity that

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doesn't need humans at all.

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It is probably the most respected,
if not the most beloved science

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fiction film of all time.

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The story of the creation of HAL's
performance, the result of a last minute

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collaboration between the idiosyncratic
director and the veteran Canadian actor,

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Douglas Rain, has been somewhat lost in
the 50 years since the film's release

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in April, 1968, as has its impact.

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Artificial intelligence has borrowed
from the HAL persona and unwittingly

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a slight hint of Canadianness resides
in our phones and interactive devices.

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Siri: I'm not quite sure
how to help you with that.

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Jim Conrad: Mr. Rain's HAL has
become the default reference, not

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just for the voice, but also for the
humanesque qualities of what a sentient

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machine's personality should be.

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HAL 9000: No 9000 computer has ever
made a mistake or distorted information.

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Jim Conrad: The cadence, the friendly
formality, the pleasant intelligence.

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And a sense of calm control in
their voices evoke Mr. Rain's

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unforgettable performance.

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HAL 9000: We are all by any
practical definition of the words,

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foolproof and incapable of error.

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Jim Conrad: As warily eye a
future utterly transformed by AI

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incursions into all aspects of
our lives, HAL has been lurking.

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HAL 9000: I enjoy working with people.

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Jim Conrad: To Scott Brave, the
co-author of Wired for Speech: How

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Voice Activates and Advances the Human
Computer Relationship, HAL 9000 is a mix

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between a butler and a psychoanalyst.

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HAL 9000: My mission responsibilities
range over the entire operation of

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the ship, so I am constantly occupied.

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Jim Conrad: Mr. Brave said he has a sense
of deference and of detachment adding

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that he saw a ripple effect on, for
example, the iPhone's virtual assistant.

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When I listened to something
like Siri, said Brave, I feel

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there is a lot in common.

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Siri: Hi, I'm Siri.

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Jim Conrad: In a 1969 interview with the
author and critic, Joseph Gelmis, Kubrick

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said that he was trying to convey the
reality of a world populated, as ours soon

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will be, by machine entities that have as
much or more intelligence as human beings.

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We wanted to stimulate people to
think what it would be like to

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share a planet with such creatures.

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HAL 9000: I'm putting myself to
the fullest possible use, which

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is all I think that any conscious
entity can ever hope to do.

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Jim Conrad: The 2001 historian David
Larson said that Kubrick came up with the

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final how voice very late in the process.

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It was determined during 2001
planning that in the future the large

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majority of computer command and
communication inputs would be via

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voice rather than via typewriter.

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But in the late 1960s, artificial
intelligence was decades from a

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convincing facsimile of a human voice.

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And who was to say how a
computer should sound, anyway.

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HAL 9000: I'm sorry, Frank,
I think you missed it.

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Queen to Bishop three.

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Bishop takes Queen.

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Jim Conrad: To play HAL, Kubrick
settled on Martin Balson.

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A best supporting actor
winner for A Thousand Clowns.

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Martin Balsam: There is only one
thing that really bothers you.

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Other people, the enemy.

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Watch out, Murray.

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They're everywhere.

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Jim Conrad: Perhaps there was a
satisfying echo that appealed to Kubrick.

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Both were from the Bronx
and sounded like it.

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Martin Balsam: What did you do to him?

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I mean, you just left him standing there.

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You just left him standing there.

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Jim Conrad: In August, 1966, Balsam told
a journalist, I'm not actually seen in the

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picture at any time, but I create a lot
of excitement projecting my voice through

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that machine, and I'm getting an Academy
Award winner price for doing it too.

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Then the director changed his mind,
Kubrick said, in a 1969 interview,

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we had some difficulty deciding
exactly what HAL should sound like,

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and Marty, Martin Balsam just sounded
a little too colloquially American.

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Martin Balsam: Unfortunately for
you, Murray, you want to be a hero.

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If maybe a fellow falls into the
lake, you can jump in and save him.

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There's still that kind of stuff.

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Who gets opportunities like that in the
Midtown Manhattan with all that traffic?

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Jim Conrad: Douglas Rain recalls
Kubrick telling him, I'm having

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trouble with what I've got in the can.

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Would you play the computer?

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Kubrick had heard Mr. Rain's voice
in the 1960 documentary universe.

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Douglas Rain: The ground beneath
our feet is the surface of a planet

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whirling at thousands of miles
an hour around a distant sun.

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Our life is possible only because
of the light and warmth of that sun.

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A star.

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Jim Conrad: Kubrick wrote to a colleague
in a letter in the director's archive.

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I think he's perfect.

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The voice is neither patronizing,
nor is it intimidating, pompous,

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overly dramatic or actorish
despite this, it is interesting.

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HAL 9000: Certainly no one could
have been unaware of the very strange

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stories floating around before we left.

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Rumors about something
being dug up on the Moon.

00:14:03.790 --> 00:14:09.130
I never gave these stories much credence,
but particularly in view of some of

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the other things that have happened.

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I find them difficult
to put out of my mind.

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Jim Conrad: In December, 1967, Kubrick and
Mr. Rain met at a recording studio at the

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MGM lot in Borehamwood, outside London.

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The actor hadn't seen a frame of the
film, then in post-production, he met

00:14:31.395 --> 00:14:36.900
none of his co-stars, not even Keir
Dullea, who played the astronaut david

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Bowman, HAL's colleague turned nemesis.

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David Bowman: Open the pod bay doors, HAL.

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HAL 9000: I'm sorry, Dave,
I'm afraid I can't do that.

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David Bowman: What's the problem?

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HAL 9000: I think you know what the
problem is, just as well as I do.

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David Bowman: What are
you talking about, HAL?

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HAL 9000: This mission is too important
for me to allow you to jeopardize it.

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David Bowman: I don't know
what you're talking about, HAL.

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Jim Conrad: Mr. Rain hadn't even been
hired to play HAL, but to provide

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narration, Kubrick finally decided against
using narration, opting for the ambiguity

00:15:18.270 --> 00:15:20.040
that was enraging to some viewers.

00:15:20.550 --> 00:15:22.620
Transcendent to others.

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It's not a session Mr.
Rain remembers fondly.

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He was quoted as saying, if you could
have been a ghost at the recording, you

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would've thought it was a load of rubbish.

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Mr. Rain had the kind of bland and
Mid-Atlantic accent we felt was

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right for the part, Mr. Kubrick
said in the 1969 interview.

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But Douglas Rain's accent
isn't Mid-Atlantic.

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It's standard Canadian English.

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HAL 9000: Sorry about this.

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I know it's a bit silly.

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Jim Conrad: As the University of Toronto
Linguistics, professor Jack Chambers

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explained, you have to have a computer
that sounds like he's from nowhere

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or rather from no specific place.

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Standard Canadian English sounds normal.

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That's why Canadians are well received
in the United States as anchormen and

00:16:25.949 --> 00:16:30.810
reporters because the vowels don't
give away the region they come from.

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Peter Jennings: From ABC News, this is
World News Tonight with Peter Jennings,

00:16:37.079 --> 00:16:38.849
reporting tonight from Los Angeles.

00:16:39.240 --> 00:16:43.140
Good evening from California where it
is the eve of a controversial, exciting,

00:16:43.140 --> 00:16:47.530
tense history making effort to unseat.

00:16:47.599 --> 00:16:50.930
Jim Conrad: Mr. Rain had played an
astonishing range of characters in

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almost 80 productions at the Stratford
Festival in Ontario over 45 years.

00:16:57.770 --> 00:17:02.630
Understudying Alec Guinness in
Richard III and going on to play

00:17:02.930 --> 00:17:06.829
Macbeth, King Lear, and Humpty Dump.

00:17:08.204 --> 00:17:13.575
Douglas Rain: When we have matched our
rackets to these balls, we will in France,

00:17:13.575 --> 00:17:17.655
by God's grace play, a set shall strike
his father's crown into the hazard.

00:17:18.194 --> 00:17:24.645
Jim Conrad: Mr. Rain had to quickly
fathom and flesh out HAL recording all

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of his lines in 10 hours, over two days.

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Mr. Rain recalls, Kubrick sat three
feet away explaining the scenes

00:17:34.270 --> 00:17:36.520
to me and reading all the parts.

00:17:37.480 --> 00:17:42.310
Kubrick gave Mr. Rain only a few
notes of direction, including, sound

00:17:42.310 --> 00:17:47.889
a little more like it's a peculiar
request, a little more concerned, and

00:17:48.340 --> 00:17:51.480
just try it closer and more depressed.

00:17:52.080 --> 00:17:52.919
HAL 9000: It's puzzling.

00:17:53.010 --> 00:17:55.980
I don't think I've ever seen
anything quite like this before.

00:17:56.700 --> 00:17:57.930
Jim Conrad: When HAL says,

00:17:58.110 --> 00:18:02.340
HAL 9000: I know I've made some
very poor decisions recently, but I

00:18:02.340 --> 00:18:07.870
can give you my complete assurance
that my work will be back to normal.

00:18:08.350 --> 00:18:13.420
Jim Conrad: Mr. Rain somehow manages to
sound both sincere and not reassuring,

00:18:13.840 --> 00:18:15.250
and his delivery of the line,

00:18:15.635 --> 00:18:18.580
HAL 9000: I think you know what the
problem is, just as well as I do.

00:18:19.000 --> 00:18:22.960
Jim Conrad: Has the sarcastic drip
of a drawing room, melodrama, and

00:18:22.960 --> 00:18:27.385
also carries the disinterested
vibe of a polite sociopath.

00:18:28.255 --> 00:18:32.695
HAL 9000: Dave, this conversation
can serve no purpose anymore.

00:18:33.445 --> 00:18:33.925
Goodbye

00:18:35.725 --> 00:18:40.915
Jim Conrad: Kubrick had Mr. Rain
sing the 1892 love song Daisy Bell,

00:18:41.245 --> 00:18:47.470
almost 50 times in uneven tempos,
in monotone, at different pitches,

00:18:47.830 --> 00:18:49.689
and even just by humming it.

00:18:50.350 --> 00:18:54.490
In the end, he used the very first take.

00:18:56.949 --> 00:19:03.280
HAL 9000: My instructor was Mr. Langley
and he taught me to sing a song.

00:19:05.860 --> 00:19:10.300
If you'd like to hear it,
I can sing it for you.

00:19:10.665 --> 00:19:13.790
It's called Daisy.

00:19:17.520 --> 00:19:17.870
Daisy.

00:19:20.520 --> 00:19:20.870
Daisy.

00:19:23.475 --> 00:19:25.750
Give me your answer to.

00:19:26.600 --> 00:19:31.470
Jim Conrad: Sung as HAL's brain is
being disconnected, it's from his early

00:19:31.470 --> 00:19:34.470
programming days, his computer childhood.

00:19:35.010 --> 00:19:40.050
It brings to an end the most
affecting scene in the entire film.

00:19:40.740 --> 00:19:44.669
Author Scott Brave said, the
moment is so powerful that it

00:19:44.669 --> 00:19:46.470
made you feel uncomfortable.

00:19:47.040 --> 00:19:52.860
All of a sudden, HAL feels incredibly
close to being alive and being human.

00:19:53.550 --> 00:19:55.950
You start to empathize
with that experience.

00:19:56.260 --> 00:19:59.590
And you are responding to
the death of a machine.

00:20:07.990 --> 00:20:11.920
For a character that's been
endlessly caricatured, HAL has

00:20:11.920 --> 00:20:16.840
inspired a surprisingly rich range
of adjectives over the years.

00:20:17.590 --> 00:20:24.805
He and his voice have been described
as aloof, eerily neutral, silky,

00:20:25.345 --> 00:20:34.585
wheedling, controlled, baleful,
unisex, droll, soft, conversational,

00:20:34.645 --> 00:20:40.465
dreamy, supremely calm, and rational.

00:20:41.485 --> 00:20:50.765
He's discursive, suave, inhumanly
cool, confident superior, deadpan,

00:20:50.784 --> 00:20:55.320
sinister, patronizing, and asexual.

00:20:56.340 --> 00:21:00.750
The actor Anthony Hopkins has said
it influenced his performance as

00:21:00.750 --> 00:21:04.680
the serial killer Hannibal Lecter
in The Silence of the Lambs.

00:21:05.100 --> 00:21:07.050
Anthony Hopkins: First
principles, Clarice.

00:21:07.200 --> 00:21:08.610
Simplicity.

00:21:09.060 --> 00:21:10.590
Read Marcus Aurelius.

00:21:10.590 --> 00:21:13.710
Of each particular thing,
ask what is it in itself?

00:21:14.220 --> 00:21:15.270
What is its nature?

00:21:16.440 --> 00:21:19.020
What does he do, this man you seek?

00:21:22.065 --> 00:21:26.865
Jim Conrad: Douglas Rain never
saw 2001: A Space Odyssey.

00:21:27.615 --> 00:21:31.425
For Mr. Rain, the
performance was simply a job.

00:21:31.754 --> 00:21:34.125
HAL 9000: Well, I don't think
there is any question about it.

00:21:34.304 --> 00:21:36.705
It can only be attributable
to human error.

00:21:38.100 --> 00:21:42.600
Jim Conrad: Artificial intelligence,
voice synthesis can't yet deliver

00:21:42.600 --> 00:21:49.350
a performance as compelling as his
HAL, but it is becoming more human.

00:21:50.370 --> 00:21:54.720
Soon artificial intelligence
voice will be able to sound,

00:21:55.230 --> 00:21:56.400
HAL 9000: Like whoever you want it to.

00:21:59.700 --> 00:22:04.149
Douglas Rain passed November
11th, 2018 at the age of 90.

00:22:21.450 --> 00:22:24.480
Jim Conrad: We're back on the Conovision
Podcast, the spirit of storytelling.

00:22:25.050 --> 00:22:27.570
And with me right now
is a good, good friend.

00:22:27.570 --> 00:22:33.480
We've known each other for a very
long time, probably since, uh, 1981.

00:22:33.480 --> 00:22:34.620
Eric Westra: 81, I think.

00:22:34.620 --> 00:22:34.790
Yeah.

00:22:35.440 --> 00:22:37.050
Jim Conrad: And we both
started in broadcasting.

00:22:37.050 --> 00:22:38.730
We both worked at the same radio station.

00:22:38.730 --> 00:22:44.150
We both shared a flat in the West End
of, uh, Vancouver for a couple of years.

00:22:44.880 --> 00:22:47.570
And then we both kinda went
our separate ways, didn't we?

00:22:47.570 --> 00:22:50.540
I got out of radio and got
into freelance voice work.

00:22:50.570 --> 00:22:51.350
Eric Westra: Smart move.

00:22:51.350 --> 00:22:52.340
Jim Conrad: Thank you.

00:22:52.340 --> 00:22:55.639
Yeah, because my radio career
wasn't going along very well.

00:22:55.730 --> 00:22:56.270
Eric Westra: Neither was mine.

00:22:57.500 --> 00:23:00.780
Jim Conrad: So, you know, as
Clint Eastwood said, a good

00:23:00.780 --> 00:23:02.489
man knows his limitations.

00:23:02.489 --> 00:23:02.909
Eric Westra: That's right.

00:23:02.909 --> 00:23:04.830
And I started believing
my own press releases.

00:23:04.830 --> 00:23:05.129
Jim Conrad: Yes.

00:23:05.250 --> 00:23:06.800
Uh, well, exactly.

00:23:07.100 --> 00:23:09.810
So I got into the voiceover, uh, business.

00:23:09.840 --> 00:23:14.879
You using that incredible brain of
yours, my friend, uh, went back to school

00:23:14.879 --> 00:23:17.760
and learned to write computer code.

00:23:17.820 --> 00:23:19.260
So what was it like?

00:23:20.040 --> 00:23:23.939
Yeah, because I remember, uh, visiting
you up in Peachland when you were

00:23:23.939 --> 00:23:28.260
going to the University of Okanagan
taking, uh, computer science, right?

00:23:28.889 --> 00:23:32.610
And, uh, you told me that fascinating
statistic where they had a

00:23:32.610 --> 00:23:35.040
number of eager young applicants.

00:23:35.040 --> 00:23:40.765
You were a little bit older than most
in the class by maybe five or six years.

00:23:40.765 --> 00:23:41.215
Eric Westra: At least.

00:23:42.265 --> 00:23:46.045
Jim Conrad: And all of a sudden
the professor gets up and starts

00:23:46.075 --> 00:23:49.985
filling blackboard after blackboard
full of algebraic equations.

00:23:50.435 --> 00:23:54.835
And soon after the attrition rate
started to, started to kick in.

00:23:54.865 --> 00:23:56.285
Eric Westra: I don't think this is for me.

00:23:56.315 --> 00:23:56.945
I mean,

00:23:56.985 --> 00:23:58.375
Jim Conrad: I just like
playing computer games.

00:23:58.405 --> 00:23:58.645
Eric Westra: Yeah.

00:23:58.825 --> 00:24:00.115
I, that's exactly it.

00:24:00.115 --> 00:24:01.540
A lot of the people who got involved.

00:24:01.540 --> 00:24:04.270
Jim Conrad: So is that, is that
sort of, again, and in our timeline

00:24:04.270 --> 00:24:06.790
now, we're in the early nineties.

00:24:06.790 --> 00:24:07.600
Eric Westra: This is the early nineties.

00:24:07.690 --> 00:24:07.780
Yeah.

00:24:07.780 --> 00:24:10.840
I graduated, uh, 96.

00:24:10.870 --> 00:24:11.200
Yeah.

00:24:11.320 --> 00:24:14.560
Jim Conrad: So this is, so I wanna
get into the whole sort of evolution

00:24:14.560 --> 00:24:16.450
of tech from your perspective.

00:24:16.510 --> 00:24:16.780
Eric Westra: Okay.

00:24:16.900 --> 00:24:17.890
Jim Conrad: Since that time.

00:24:17.890 --> 00:24:21.970
So you started writing code, first of all,
that, that's, that was the perception,

00:24:22.060 --> 00:24:25.900
uh, of kids coming outta high school,
was that computers were these wonderful,

00:24:25.905 --> 00:24:31.530
fancy toys that they loved to play with
but they really didn't have any idea

00:24:31.949 --> 00:24:33.810
what the nuts and bolts were, right?

00:24:33.870 --> 00:24:34.260
Eric Westra: No.

00:24:34.260 --> 00:24:37.139
And, but at the same time, things
have changed since then because

00:24:37.139 --> 00:24:41.290
now, uh, kids actually learn
to code like in grade school.

00:24:41.290 --> 00:24:44.850
And, uh, and know that's a good
thing because it, math is not

00:24:44.850 --> 00:24:46.260
the greatest for a lot people.

00:24:46.290 --> 00:24:50.569
But if you, if you bring the math
piece into the computer realm then it's

00:24:50.569 --> 00:24:53.989
a lot easier for them to accept and
they're more inspired to, to do it.

00:24:54.229 --> 00:24:57.640
But yeah, I, I started writing
code, but that's not what I do now.

00:24:57.640 --> 00:25:00.389
I mean, I, I, we call
'em code monkeys, right?

00:25:00.389 --> 00:25:03.060
Because, you know, you're
essentially, that's what you're doing.

00:25:03.060 --> 00:25:04.245
You're tap, tap, tap, tap, tap.

00:25:04.290 --> 00:25:07.820
You're lucky to bang off six good
lines of computer code a day.

00:25:08.520 --> 00:25:09.330
Uh, 6 to 10.

00:25:09.660 --> 00:25:11.580
And I learned a bunch
of different languages.

00:25:11.610 --> 00:25:18.030
Cobol, you know, Modula-2, I learned,
uh, JavaScript and all this other stuff.

00:25:18.270 --> 00:25:20.280
I don't use any of that anymore.

00:25:20.620 --> 00:25:23.850
Uh, but it was a good way to sort
of set up what I ended up doing.

00:25:23.880 --> 00:25:24.150
Jim Conrad: Yeah.

00:25:24.180 --> 00:25:24.390
Yeah.

00:25:24.940 --> 00:25:29.350
Um, so from code writing, uh, what
was the first gig after university?

00:25:29.350 --> 00:25:33.370
You came to Vancouver as I recall,
and worked with a company here that

00:25:33.370 --> 00:25:37.750
was trying to do something a bit,
a bit ahead of their time, which

00:25:37.750 --> 00:25:42.190
was set up mainframe systems that
people would just access from their,

00:25:42.790 --> 00:25:44.680
Eric Westra: Well, that's
a bit of a simplification,

00:25:44.680 --> 00:25:46.150
but what happened was I got,

00:25:46.150 --> 00:25:46.810
Jim Conrad: I'm a simple guy.

00:25:46.870 --> 00:25:47.320
Eric Westra: No, no, no.

00:25:47.650 --> 00:25:48.025
I ended up.

00:25:48.435 --> 00:25:51.555
Uh, my first gig outta school
was with the Premier's office.

00:25:51.675 --> 00:25:51.915
Jim Conrad: Right.

00:25:52.245 --> 00:25:55.485
Eric Westra: I worked for, uh, BC
Trade Development and the Premier's

00:25:55.485 --> 00:25:59.175
office because they were under
the same IT umbrella in Vancouver.

00:25:59.625 --> 00:26:03.365
And there's a great story about Mike
Harcourt when he was the Premier.

00:26:03.830 --> 00:26:08.810
I was doing some of the, uh, the IT
support and one day I get a phone call

00:26:08.810 --> 00:26:11.899
from Mike's office, which was just down
the hall from the Trade Development

00:26:11.899 --> 00:26:13.760
Corp. Eric, can you come on over?

00:26:13.760 --> 00:26:16.639
'Cause Mike has a
problem with his printer.

00:26:16.699 --> 00:26:18.530
And I said, sure, I can, I can come over.

00:26:18.590 --> 00:26:18.710
Jim Conrad: Yeah.

00:26:18.860 --> 00:26:22.189
Eric Westra: So, uh, apparently I, I
walked into the office and, and Dixie,

00:26:22.280 --> 00:26:26.810
who is normally, uh, Mike Harcourt's EA,
executive assistant, was away on vacation.

00:26:26.810 --> 00:26:28.290
They got somebody from the pool, I guess.

00:26:28.820 --> 00:26:31.970
And so I said hello to her and I walked
into his office and he was sitting at his

00:26:31.970 --> 00:26:37.479
desk and he was signing a, a big stack of
paper and you know, one after the other.

00:26:38.229 --> 00:26:39.879
And I said, Hey, how's it going, Mike?

00:26:39.910 --> 00:26:41.840
'Cause he was, was a
first name kind of guy.

00:26:41.840 --> 00:26:43.510
And, uh, really nice guy.

00:26:44.020 --> 00:26:47.350
And I started to work on the printer
and then all of a sudden I hear this,

00:26:47.500 --> 00:26:49.840
you know what the, across the room.

00:26:50.310 --> 00:26:52.030
And I, I said, what's the problem?

00:26:52.030 --> 00:26:53.200
He said, well, have a look at this.

00:26:53.590 --> 00:26:57.750
And he was signing a whole bunch
of, uh, proclamations, thanking

00:26:57.750 --> 00:27:01.620
people for participating in the,
uh, the Vancouver Centennial.

00:27:01.649 --> 00:27:03.389
There must have been 5
or 600 of these things.

00:27:03.810 --> 00:27:09.510
And the salutation at the bottom of the
letter, what had happened was the, the new

00:27:09.600 --> 00:27:12.840
EA had just gone through, you know, spell
check, click, click, click, click, without

00:27:12.840 --> 00:27:14.899
actually looking at what she was doing.

00:27:15.250 --> 00:27:19.050
And the salutation read, the
right honorable Mike haircut.

00:27:21.905 --> 00:27:26.930
And, and, uh, you know, Mike, not
exactly what you would call hirsute.

00:27:27.190 --> 00:27:31.319
Uh, and, and so, uh, that was, that
was one of the funnier stories.

00:27:31.319 --> 00:27:31.719
But yeah, I,

00:27:31.719 --> 00:27:33.439
Jim Conrad: Follicly challenged.

00:27:33.459 --> 00:27:34.989
Eric Westra: Follicly challenged
Mike was, yeah, that's right.

00:27:36.340 --> 00:27:38.889
Uh, but yeah, that was one of
the, uh, the earliest gigs.

00:27:38.889 --> 00:27:42.250
And then eventually I, I got into
tech communications, you know, tried

00:27:42.250 --> 00:27:46.810
to marry my background in tech with
broadcasting, and then got involved

00:27:46.810 --> 00:27:50.345
with business analysis and business
process and business optimization

00:27:50.675 --> 00:27:53.104
and then solution architecting.

00:27:53.104 --> 00:27:55.534
Uh, putting technology together
with companies that were

00:27:55.534 --> 00:27:56.695
going through a lot of change.

00:27:56.884 --> 00:27:58.314
So that's, that's what I do now.

00:27:58.665 --> 00:28:04.905
Jim Conrad: An overall sort of context
of this digital revolution of ours,

00:28:06.435 --> 00:28:10.645
obviously, uh, it's the machine that
changed the world, the computer.

00:28:11.175 --> 00:28:17.860
But a lot of people now are, I
guess, rethinking what that change

00:28:18.000 --> 00:28:21.470
or how much it has changed us.

00:28:21.530 --> 00:28:29.090
And, and relating back to, you know, being
human and, and how we relate to computers.

00:28:29.600 --> 00:28:34.410
And now the whole idea of
artificial intelligence.

00:28:35.420 --> 00:28:42.380
And we're seeing, while we first saw
AI literally and viscerally in 2001.

00:28:42.794 --> 00:28:44.925
And the voice of HAL, the computer.

00:28:45.245 --> 00:28:49.455
My favorite line, which I've dubbed
the HAL 9000 breakup line is,

00:28:49.784 --> 00:28:54.254
HAL 9000: Dave, this conversation
can serve no purpose anymore.

00:28:55.010 --> 00:28:55.500
Goodbye.

00:28:56.399 --> 00:28:56.979
Jim Conrad: That's right.

00:28:57.794 --> 00:28:58.274
Goodbye.

00:28:58.304 --> 00:29:00.225
Eric Westra: Yeah, goodbye.

00:29:00.225 --> 00:29:01.034
Jim Conrad: Uh, HAL.

00:29:01.084 --> 00:29:01.444
HAL?

00:29:01.684 --> 00:29:02.414
Do you read me, HAL?

00:29:02.824 --> 00:29:05.895
Eric Westra: There's a great example
of an artificial intelligence machine

00:29:06.135 --> 00:29:10.094
that didn't have any morality and,
and a lot of the discussion around,

00:29:10.485 --> 00:29:13.455
you know, artificial intelligence
these days, 'cause now computers

00:29:13.455 --> 00:29:14.584
are writing their own algorithms.

00:29:15.165 --> 00:29:17.925
They're learning and they're
changing their own computer code.

00:29:18.014 --> 00:29:22.665
Jim Conrad: Now explain to me what
is defined as machine learning.

00:29:22.905 --> 00:29:25.064
Eric Westra: Well, there's,
there's deep machine learning

00:29:25.064 --> 00:29:26.115
and there's machine learning.

00:29:26.115 --> 00:29:28.004
And so the two are a little different.

00:29:28.064 --> 00:29:34.409
Um, machine learning is when a computer
algorithm is given the capacity to write

00:29:34.470 --> 00:29:37.020
its own code, to learn from its mistakes.

00:29:37.080 --> 00:29:37.960
And to

00:29:37.990 --> 00:29:40.379
Jim Conrad: To replicate
itself and heal itself.

00:29:40.409 --> 00:29:40.620
Eric Westra: Right.

00:29:40.620 --> 00:29:43.699
So there's a core set of code and
instructions in the algorithm.

00:29:43.699 --> 00:29:48.000
And then it says, you know, go out and try
something and under these circumstances

00:29:48.380 --> 00:29:50.179
if it works, make a note of that.

00:29:50.250 --> 00:29:53.350
And write your own code so that you
do it the same way the next time.

00:29:53.990 --> 00:29:56.370
And then there's deep machine
learning, which is really interesting.

00:29:56.370 --> 00:30:01.264
And that's around you can build reward
systems into computers the same way

00:30:01.264 --> 00:30:03.065
that you do with pets and humans.

00:30:03.485 --> 00:30:08.084
You know, if a dog does something right,
uh, you give it a, you give it a treat.

00:30:08.465 --> 00:30:09.104
If a child,

00:30:09.104 --> 00:30:09.965
Jim Conrad: Good boy, good boy.

00:30:10.294 --> 00:30:12.985
Eric Westra: If a child does
something right, you reinforce that.

00:30:12.985 --> 00:30:14.794
You give them a hug,
you say, good, good job.

00:30:15.004 --> 00:30:15.895
That's the way you do it.

00:30:16.375 --> 00:30:18.365
So we're doing the same
thing with machines now.

00:30:18.365 --> 00:30:21.274
We're actually creating what we
call artificial reward systems.

00:30:21.485 --> 00:30:21.665
Jim Conrad: Wow.

00:30:21.754 --> 00:30:25.725
Eric Westra: So computer will do
something right, it will earn two stars.

00:30:26.124 --> 00:30:28.480
And if it does better,
it gets three stars.

00:30:28.510 --> 00:30:33.850
So it focuses completely on making
sure it gets as many rewards as it can.

00:30:34.149 --> 00:30:36.370
And through that process,
it learns faster.

00:30:36.460 --> 00:30:36.820
Jim Conrad: Wow.

00:30:37.540 --> 00:30:41.740
Now, and this is one, once again,
one of those ethical questions

00:30:41.740 --> 00:30:43.780
that, uh, that has to come up.

00:30:44.230 --> 00:30:46.330
It came up when they were
making the atomic bomb.

00:30:46.540 --> 00:30:52.030
Yes, we have the scientific capacity
and the knowledge to create this.

00:30:52.845 --> 00:30:54.784
The question is, should we.

00:30:56.175 --> 00:31:01.185
Have we reached a point of that
question in artificial intelligence?

00:31:01.305 --> 00:31:03.024
Eric Westra: I think we
continue to ask that question.

00:31:03.024 --> 00:31:04.504
And it's a good question to ask.

00:31:04.824 --> 00:31:09.799
Um, there's no, you know, artificial
intelligence has huge promise.

00:31:10.110 --> 00:31:14.100
Um, there, there are lots of
positive things that can come of it.

00:31:14.470 --> 00:31:19.139
Um, but like anything, there are a lot
of very scary and negative things that

00:31:19.139 --> 00:31:20.850
come of it, if it isn't handled properly.

00:31:20.850 --> 00:31:24.990
And this is all through this
emerging field called Robo Ethics.

00:31:25.050 --> 00:31:30.310
Jim Conrad: Now, thank God we had
Isaac Asimov way back when because

00:31:30.330 --> 00:31:34.230
I, I was actually a big fan of Isaac
Asimov, uh, science fiction novels.

00:31:34.290 --> 00:31:34.470
Eric Westra: Yeah.

00:31:34.709 --> 00:31:38.600
Jim Conrad: Now what were
the three rules of robotics?

00:31:38.950 --> 00:31:40.960
Eric Westra: So the, the,
Asimov proposed that there were

00:31:40.960 --> 00:31:42.945
three laws in his writings.

00:31:43.305 --> 00:31:48.285
The first law was that a robot or
a machine could not, through either

00:31:48.285 --> 00:31:51.635
action or inaction, harm a human being.

00:31:52.325 --> 00:31:57.525
The second law was that, uh, the
robot or the machine had to follow

00:31:57.795 --> 00:32:01.515
the instructions given to it by a
human, unless it broke the first law.

00:32:02.175 --> 00:32:05.909
And the third law was that it
had to self preserve itself.

00:32:05.915 --> 00:32:10.530
It, it couldn't, uh, it had to go through,
you know, all the machinations necessary

00:32:10.530 --> 00:32:14.360
to preserve its existence provided
it didn't break the first two laws.

00:32:15.129 --> 00:32:17.250
Jim Conrad: So it had a, it had
a built in, the third law was

00:32:17.250 --> 00:32:20.909
self-preservation on, with a caveat,
if it didn't break the first two laws.

00:32:20.909 --> 00:32:21.270
Eric Westra: That's right.

00:32:21.720 --> 00:32:25.220
Jim Conrad: So inside that sort
of closed system was an ethical

00:32:25.880 --> 00:32:27.780
behavior model for robots.

00:32:27.870 --> 00:32:28.020
Eric Westra: Right.

00:32:28.260 --> 00:32:32.504
Jim Conrad: Uh, how practical
is that to build into today's

00:32:32.565 --> 00:32:36.945
artificial intelligence, can we
create those three laws to govern AI?

00:32:37.004 --> 00:32:38.055
Eric Westra: The laws are good ones.

00:32:38.055 --> 00:32:39.105
They seem to make sense.

00:32:39.345 --> 00:32:41.295
But they can produce, um,

00:32:41.325 --> 00:32:42.225
Jim Conrad: Asimov was a genius.

00:32:42.345 --> 00:32:43.065
Eric Westra: Yeah, he was.

00:32:43.125 --> 00:32:44.175
This is 1942.

00:32:44.295 --> 00:32:44.565
Jim Conrad: Yeah.

00:32:45.135 --> 00:32:48.615
Eric Westra: The thing about it though
is that even making things as simple

00:32:48.615 --> 00:32:52.935
as that, you can end up with machines,
uh, getting into, uh, you know, uh,

00:32:52.965 --> 00:32:54.405
cognitive dissonance we call it.

00:32:54.405 --> 00:32:58.980
Where, where it tries not to break
a law, it makes a move to avoid

00:32:58.980 --> 00:33:03.030
breaking that law and then by doing
so, it breaks another law and then

00:33:03.030 --> 00:33:04.470
it goes back to the first one.

00:33:04.770 --> 00:33:05.760
And so it gets caught,

00:33:05.760 --> 00:33:06.270
Jim Conrad: Vapor lock.

00:33:06.300 --> 00:33:06.500
Eric Westra: Yeah.

00:33:06.669 --> 00:33:07.240
Essentially.

00:33:07.870 --> 00:33:11.280
Um, and he, he actually did write
about that in a short story.

00:33:11.280 --> 00:33:14.040
He talked about a robot that got
caught in one of those loops.

00:33:14.130 --> 00:33:18.350
But, you know, if you use modern
day sort of explanations around this

00:33:18.350 --> 00:33:23.909
sort of thing, it becomes much more
difficult to nail all this down into

00:33:23.909 --> 00:33:25.550
a, to a very small set of rules.

00:33:25.610 --> 00:33:27.409
Jim Conrad: Because there
are so many applications.

00:33:27.440 --> 00:33:29.410
You mentioned the positive aspects of AI.

00:33:29.930 --> 00:33:33.139
Uh, give me, let's say
the top three, not Alexa.

00:33:33.260 --> 00:33:36.200
Eric Westra: Well, Alexa and
voice recognition certainly

00:33:36.200 --> 00:33:37.310
are very, very big right now.

00:33:37.310 --> 00:33:39.409
Jim Conrad: If they make, if they
make one of those things that sounds

00:33:39.409 --> 00:33:41.760
like Stephen Fry doing Jeeves.

00:33:42.570 --> 00:33:43.260
I'm on it.

00:33:43.560 --> 00:33:46.470
Jeeves: I was sent by the agencies
and I was given to understand

00:33:46.470 --> 00:33:47.399
that you're required a valet.

00:33:47.785 --> 00:33:50.460
Eric Westra: I, I think eventually you,
you'll, you can have your voice, voice

00:33:50.460 --> 00:33:52.010
assistant be whoever you want it to be.

00:33:52.510 --> 00:33:57.210
There are a set of circumstances can
come up in modern life where the machine

00:33:57.210 --> 00:34:00.930
would be faced with so many different
criter to make a decision, it would

00:34:00.930 --> 00:34:04.320
be very difficult for it necessarily
to make the moral or the ethical one.

00:34:05.010 --> 00:34:08.574
Jim Conrad: You mentioned this
ethical, moral dilemma in a, and I

00:34:08.574 --> 00:34:12.014
guess it was a thought experiment
in regards to self-driving cars.

00:34:12.205 --> 00:34:13.105
Gimme a run through on that.

00:34:13.134 --> 00:34:16.674
Eric Westra: This was put to a group
of university students, uh, it's called

00:34:16.674 --> 00:34:18.114
the child in the tunnel conundrum.

00:34:18.654 --> 00:34:21.895
So you're in an autonomous vehicle
and you're with your family and the

00:34:21.895 --> 00:34:23.605
car is driving you on a mountain road.

00:34:23.605 --> 00:34:27.250
It's a two-lane mountain road, and
your two kids are in the backseat.

00:34:27.250 --> 00:34:28.375
Your wife is sitting beside you.

00:34:28.975 --> 00:34:32.614
And you come around a curve and
you're, you know, doing relatively

00:34:32.774 --> 00:34:36.255
the speed limit, you know, it's an
autonomous car, it's following the law.

00:34:36.855 --> 00:34:40.995
But all of a sudden, uh, as you come
around the curve, there is a tunnel

00:34:40.995 --> 00:34:45.614
entrance and uh, it's got a concrete
sort of abutment around the face of it.

00:34:46.125 --> 00:34:50.444
And, uh, a small child darts out
from behind a rock near the tunnel

00:34:50.444 --> 00:34:52.615
entrance and falls onto the road.

00:34:53.275 --> 00:34:56.480
The car has two choices really,
given the circumstances.

00:34:56.509 --> 00:34:59.480
It's not going slow
enough to stop in time.

00:34:59.569 --> 00:35:05.450
It either can send the car flying into
the concrete or run over the child.

00:35:06.109 --> 00:35:09.020
Jim Conrad: So into the abutment,
the, the passenger's in the

00:35:09.020 --> 00:35:10.849
car, the self-driving car.

00:35:11.109 --> 00:35:16.200
So the computer that's, that's
governing that should try to preserve

00:35:16.319 --> 00:35:21.009
what it's meant to do, which is to
avoid harm to human life, meaning

00:35:21.009 --> 00:35:22.620
the passengers inside the car.

00:35:22.649 --> 00:35:23.220
Eric Westra: Right.

00:35:23.250 --> 00:35:27.220
Jim Conrad: However, by, by
running over the child, it's

00:35:27.290 --> 00:35:28.700
potentially killing the child.

00:35:28.700 --> 00:35:31.360
In fact, it's almost a certainty,
given the circumstances.

00:35:31.360 --> 00:35:33.690
Eric Westra: Okay, so
what does the car do?

00:35:33.750 --> 00:35:37.470
And when the group of university
students were asked this about this

00:35:37.470 --> 00:35:41.459
problem, more than 60% of them said
the car should run over the child.

00:35:42.329 --> 00:35:45.875
What the heck does a child, what,
what is that child doing in the

00:35:45.875 --> 00:35:47.535
middle of nowhere in the first place?

00:35:47.645 --> 00:35:49.715
Jim Conrad: The evil spawn
of a wiley coyote or what?

00:35:49.715 --> 00:35:49.775
Eric Westra: Yeah.

00:35:49.775 --> 00:35:54.315
It would be one death compared to
potentially one or more in the car.

00:35:54.545 --> 00:35:58.095
Jim Conrad: So there's a value judgment
that has to be made almost instantaneously

00:35:58.125 --> 00:36:00.255
by the autonomous computer driven car.

00:36:00.275 --> 00:36:03.815
Eric Westra: It's no longer a
machine just making, uh, a judgment

00:36:03.815 --> 00:36:05.465
based on the best way to do things.

00:36:05.465 --> 00:36:07.115
It's making life and death decisions.

00:36:07.115 --> 00:36:07.445
Jim Conrad: Yes.

00:36:07.565 --> 00:36:07.925
Yes.

00:36:07.955 --> 00:36:11.790
Eric Westra: And that is
where things get really weird.

00:36:14.955 --> 00:36:21.435
Jim Conrad: Well, and then given
the technology surrounding military

00:36:21.654 --> 00:36:28.125
applications of drones, and right
now, as I believe they are operated

00:36:28.125 --> 00:36:32.215
by human beings in a bunker
somewhere outside of Las Vegas.

00:36:32.345 --> 00:36:34.925
Eric Westra: They're autonomous,
some of them, uh, they, they don't

00:36:34.925 --> 00:36:36.305
need, require supervision at all.

00:36:36.335 --> 00:36:40.625
Jim Conrad: Well, that's where I,
there's another ethical, moral question.

00:36:40.655 --> 00:36:43.895
You know, you've got a basically
death from above being run

00:36:43.895 --> 00:36:47.265
by an AI driven computer.

00:36:47.955 --> 00:36:53.584
And the decision making processes inside
that computer were coded by humans.

00:36:53.884 --> 00:36:56.944
So there still is a human connection.

00:36:57.234 --> 00:36:59.625
But it's, but it's pretty
far removed, isn't it?

00:36:59.745 --> 00:37:00.225
Eric Westra: It is.

00:37:00.314 --> 00:37:04.335
And uh, you know, there's talk about
eventually some of these drones,

00:37:04.335 --> 00:37:06.495
I mean, we're getting pretty dark
here, but some of these drones,

00:37:06.524 --> 00:37:08.720
Jim Conrad: It's a dark and
stormy Saturday morning.

00:37:08.720 --> 00:37:08.870
Eric Westra: Yes.

00:37:10.069 --> 00:37:12.830
You know that they would use face
recognition to sort of, you know,

00:37:12.830 --> 00:37:15.200
recognize the face of a terrorist and,

00:37:15.200 --> 00:37:16.490
Jim Conrad: As opposed to a child,.

00:37:16.490 --> 00:37:17.089
Eric Westra: Uh, yeah.

00:37:17.299 --> 00:37:20.890
And then, you know, go out and, and
essentially assassinate that person.

00:37:21.410 --> 00:37:26.930
So that's a really dark side of AI and,
and there will always be that, I guess.

00:37:26.930 --> 00:37:29.660
But there are some very positive things.

00:37:29.660 --> 00:37:31.610
I'm running into it now every day.

00:37:31.610 --> 00:37:31.670
Jim Conrad: Yeah.

00:37:31.670 --> 00:37:35.330
I thought I mentioned, or I
requested a bright side aI story.

00:37:36.799 --> 00:37:39.799
We, we went immediately to the dark
side, so let's, let's find some

00:37:39.950 --> 00:37:41.399
ray of sunshine here somewhere.

00:37:41.399 --> 00:37:45.560
What's, what's the number one
beneficial use to humans and

00:37:45.560 --> 00:37:47.570
humankind for artificial intelligence?

00:37:47.600 --> 00:37:49.400
Eric Westra: Well, there, there,
there are lots of them, you know.

00:37:49.430 --> 00:37:50.360
Jim Conrad: Robot surgeons?

00:37:50.810 --> 00:37:52.549
Eric Westra: Robotic surgery is one.

00:37:52.670 --> 00:37:54.170
Robotic diagnosis.

00:37:54.460 --> 00:37:58.740
Jim Conrad: I don't know if I want
HAL, uh, doing my prostate surgery.

00:38:00.330 --> 00:38:01.259
HAL 9000: I'm sorry, Jim.

00:38:01.320 --> 00:38:02.730
The knife slipped.

00:38:04.500 --> 00:38:07.740
Eric Westra: But you know, I'm running
into situations now where, uh, it's being

00:38:07.740 --> 00:38:14.310
used for example, to determine how to hook
up a borrower with a lending institution

00:38:14.610 --> 00:38:16.470
based on the borrower's profile.

00:38:16.470 --> 00:38:19.920
There's a whole bunch of, you know, stuff
that goes into making that decision.

00:38:20.650 --> 00:38:23.650
And AI can be very helpful
in making those connections.

00:38:24.000 --> 00:38:26.010
So that's more of a
business efficiency thing.

00:38:26.160 --> 00:38:27.000
HAL 9000: I'm sorry, Jim.

00:38:27.524 --> 00:38:29.595
Your loan application has been denied.

00:38:30.495 --> 00:38:30.975
Eric Westra: That's right.

00:38:31.575 --> 00:38:35.805
Uh, and you know, but there are lots
of applications emerging now, and

00:38:35.805 --> 00:38:40.095
it's gonna become more and more, uh,
a part of our lives, uh, every day.

00:38:42.314 --> 00:38:46.274
Jim Conrad: I've got a question
for you, given that technology is

00:38:46.365 --> 00:38:51.754
speeding up, that some people are
becoming somewhat overwhelmed by it.

00:38:52.174 --> 00:38:53.680
We're, we're trying to adapt.

00:38:54.345 --> 00:38:59.175
But it seems that as we, as we
adapt, the next thing comes along

00:38:59.685 --> 00:39:01.455
and then we have to adapt again.

00:39:01.545 --> 00:39:06.555
And some people are retreating
and there's a kind of a backlash.

00:39:06.915 --> 00:39:12.900
Do you think that there will be a, a
time when when we'll reject technology

00:39:13.080 --> 00:39:17.730
and, and try to go back, back in
time if it, if it was possible.

00:39:17.760 --> 00:39:18.900
Eric Westra: Well, there already has been.

00:39:18.900 --> 00:39:22.160
I mean, I keep thinking
about Joe Walsh's song,

00:39:24.340 --> 00:39:26.460
Analog Man.

00:39:29.730 --> 00:39:32.910
There already has been a bit of a
backlash, especially in the music scene.

00:39:33.570 --> 00:39:37.279
It started with the release
of CDs many years ago.

00:39:37.690 --> 00:39:41.415
And the digitized sound just didn't
have the same kind of, the, the

00:39:41.415 --> 00:39:43.095
word that was used was warmth.

00:39:43.215 --> 00:39:43.515
Jim Conrad: Right.

00:39:43.965 --> 00:39:47.595
Eric Westra: And so in the last few
years especially, we've been seeing a

00:39:47.595 --> 00:39:53.115
resurgence in, uh, good old vinyl and
artists actually pressing their own, uh,

00:39:53.145 --> 00:39:54.615
instead of going through record companies.

00:39:54.615 --> 00:39:58.455
And, and it's because that
audio files prefer the sound.

00:39:58.455 --> 00:39:59.675
So there's one example.

00:40:00.375 --> 00:40:02.835
I think the latest thing
that's, that's been.

00:40:03.195 --> 00:40:09.745
Sort of making people recoil sometimes
in sheer, utter terror is AI.

00:40:10.155 --> 00:40:12.915
Jim Conrad: Now define AI for me.

00:40:12.945 --> 00:40:16.125
In a practical sense, what is AI?

00:40:16.635 --> 00:40:18.255
And how did it develop?

00:40:19.065 --> 00:40:23.805
Eric Westra: So it's based on what's
called an LLM or a large language model.

00:40:23.935 --> 00:40:32.015
And the idea is you synthesize, uh,
using algorithms, and hardware, uh,

00:40:32.045 --> 00:40:37.905
the neural pathways in the mind, the
human brain, that process language.

00:40:37.965 --> 00:40:40.665
Jim Conrad: And it was originally
developed to actually model the

00:40:40.665 --> 00:40:44.655
brain in order to do research on
how, on how the brain works, right?

00:40:44.885 --> 00:40:46.275
Eric Westra: Neural networks work, yes.

00:40:46.275 --> 00:40:50.415
And then they became quite helpful
when it came to large language models.

00:40:50.475 --> 00:40:55.785
Because you think about, you know,
one word, um, the word right could be

00:40:55.785 --> 00:40:57.940
spelled a couple of different ways.

00:40:58.390 --> 00:41:00.000
Could mean several different things.

00:41:02.709 --> 00:41:10.440
So, you know, the large language model
is there to teach the algorithm what the

00:41:10.440 --> 00:41:15.030
actual meaning of the word and a number
of words fit, that are fitted together,

00:41:15.090 --> 00:41:17.310
what that means in the context for it.

00:41:17.460 --> 00:41:17.850
Jim Conrad: Yes.

00:41:18.570 --> 00:41:21.899
One could define intelligence
a number of different ways.

00:41:22.680 --> 00:41:29.535
A lot of people define intelligence
as in AI, in the ability to assimilate

00:41:29.745 --> 00:41:34.274
all sorts of information to correlate
to, to come up with solutions and

00:41:34.274 --> 00:41:37.234
answers to questions quicker and faster.

00:41:37.964 --> 00:41:45.165
Or is intelligence coming back to the
human aspect is intelligence, creativity?

00:41:46.424 --> 00:41:49.109
Eric Westra: I think in,
in many respects it is.

00:41:49.299 --> 00:41:52.830
I mean, we can be creative with
language, which is a structure, and

00:41:52.830 --> 00:41:58.109
we find all sorts of different ways of
using musical notes and being creative.

00:41:58.770 --> 00:42:03.419
And they're, they're a very
finite set of sort of things.

00:42:03.540 --> 00:42:07.880
Uh, ABC, you know, the
notes, uh, the chords.

00:42:08.430 --> 00:42:13.740
So we start to see that, um, the,
the real danger actually that's being

00:42:13.740 --> 00:42:20.460
presented by AI is in the creative space,
because now it's possible to manipulate

00:42:20.760 --> 00:42:29.360
imagery, audio in a way that most fools,
uh, the human consumer, if you will,

00:42:29.390 --> 00:42:34.020
because the, the artificial intelligence
has learned what matters most to us.

00:42:34.410 --> 00:42:36.060
Jim Conrad: And that is the image?

00:42:36.150 --> 00:42:38.760
Eric Westra: Well, it could be
the image or nuances of the image.

00:42:38.760 --> 00:42:44.240
So you take a, for example, you could
ask a, a chat bot, or, uh, a piece of

00:42:44.240 --> 00:42:49.610
artificial intelligence in say, Adobe
Photoshop, create a picture for me of

00:42:49.610 --> 00:42:55.610
a guy age, so and so, uh, that has very
pleasant features, is a professional

00:42:55.610 --> 00:43:00.650
person and is modeled after people
who have good leadership qualities.

00:43:00.680 --> 00:43:01.000
Jim Conrad: Yes.

00:43:01.620 --> 00:43:08.420
So, so the, the AI functions as, but you
still a, a human being still has to input.

00:43:08.875 --> 00:43:09.235
Eric Westra: Oh yeah.

00:43:09.265 --> 00:43:10.195
Jim Conrad: Certain things.

00:43:10.225 --> 00:43:10.405
Eric Westra: Yeah.

00:43:10.405 --> 00:43:14.245
The intelligence is, is, is
essentially, you know, called from,

00:43:14.515 --> 00:43:17.785
from a lot of different sources and
usually from other people's input.

00:43:18.625 --> 00:43:21.365
It's, it's only as good as
the data that goes into it.

00:43:21.385 --> 00:43:26.125
And this is part of the problem right
now with AI, is that there's so much data

00:43:26.775 --> 00:43:30.105
going into it, that it's getting confused.

00:43:30.215 --> 00:43:33.075
Jim Conrad: And they
call that hallucination?

00:43:33.075 --> 00:43:34.315
Eric Westra: Hallucination, yeah.

00:43:35.105 --> 00:43:35.305
Jim Conrad: Yeah.

00:43:35.305 --> 00:43:37.305
We're familiar with that, aren't we?

00:43:38.955 --> 00:43:43.005
Eric Westra: For many years, my life
seemed to be one large hallucination.

00:43:43.605 --> 00:43:46.795
Uh, thankfully those days are over.

00:43:46.795 --> 00:43:51.134
Um, but the, the hallucinations
are, are created by just throwing

00:43:51.134 --> 00:44:01.024
a lot of data into the model rather
than focusing on quality of data.

00:44:01.254 --> 00:44:05.565
Jim Conrad: And, and that's where I,
I come always back to creativity and

00:44:05.565 --> 00:44:07.705
the artist when it comes to technology.

00:44:08.325 --> 00:44:13.605
Technology certainly has, has
released our ability to create,

00:44:13.875 --> 00:44:15.945
even in multi-track recording.

00:44:16.180 --> 00:44:20.235
You know, now you can track almost
infinitely and sound bites and

00:44:20.235 --> 00:44:21.705
samples and things like that.

00:44:21.795 --> 00:44:24.255
Eric Westra: But it's all
mimicry in one form or another.

00:44:24.285 --> 00:44:24.560
Jim Conrad: That's true.

00:44:24.920 --> 00:44:31.730
But as we go forward into this AI
world, how is our humanity going

00:44:31.730 --> 00:44:33.770
to be preserved, do you think?

00:44:34.940 --> 00:44:37.570
Eric Westra: Well, I think a lot of
people are asking that question now.

00:44:37.600 --> 00:44:42.689
And thankfully, some of the people like
Sam Altman, uh, you know, who heads

00:44:42.689 --> 00:44:47.165
up ChatGPT, are thinking not just in
terms of what the technology can do,

00:44:47.240 --> 00:44:48.525
but how it should be guard railed.

00:44:49.095 --> 00:44:49.695
Jim Conrad: Yes.

00:44:49.785 --> 00:44:52.875
Eric Westra: Uh, anybody working in
AI who isn't thinking about that,

00:44:53.085 --> 00:44:58.485
the ethics of AI and the humanity
behind AI, shouldn't be in the field.

00:44:58.575 --> 00:45:02.985
Because the potential is
so there for, for misuse.

00:45:03.255 --> 00:45:04.785
Jim Conrad: And that's altruistic.

00:45:05.355 --> 00:45:09.225
But as we know, corporate
culture is ruthless.

00:45:09.225 --> 00:45:09.615
Eric Westra: Sure.

00:45:09.880 --> 00:45:11.384
But, but the genie's outta the bottle.

00:45:11.535 --> 00:45:12.075
Jim Conrad: Yeah, that's true.

00:45:12.080 --> 00:45:12.420
Eric Westra: I mean, right.

00:45:12.525 --> 00:45:16.815
I mean, and, and, and every time a new
technology comes along, there's always a,

00:45:16.995 --> 00:45:18.735
Jim Conrad: A human cry.

00:45:18.735 --> 00:45:20.625
It's it's gonna be the end of humanity.

00:45:20.835 --> 00:45:24.375
Eric Westra: You know, uh, digitized
music was, you know, we use that example

00:45:24.375 --> 00:45:25.524
at the beginning of the conversation.

00:45:25.524 --> 00:45:31.794
I mean, everybody said, oh, it's, that's
the end of, you know, a lot of things.

00:45:32.154 --> 00:45:34.694
Uh, a lot of the, the artists
now are just gonna go for the

00:45:34.694 --> 00:45:35.805
lowest common denominator.

00:45:35.805 --> 00:45:37.935
They're not gonna get
reimbursed, et cetera, et cetera.

00:45:38.415 --> 00:45:38.805
Okay.

00:45:38.985 --> 00:45:39.495
Yes.

00:45:39.525 --> 00:45:43.825
There are changes whenever you
have a new technology introduced.

00:45:44.674 --> 00:45:46.365
Sometimes more than others.

00:45:46.845 --> 00:45:51.715
The thing is, how do we adapt
as humans to the technology?

00:45:51.775 --> 00:45:56.845
How do we make the best use of it,
and how do we make sure that we

00:45:56.845 --> 00:45:58.805
don't squander the opportunity?

00:45:59.595 --> 00:46:04.525
Instead of being afraid constantly about
what the technology might do wrong,

00:46:04.735 --> 00:46:06.155
let's focus on what it might do right.

00:46:11.545 --> 00:46:16.165
Jim Conrad: Artificial
intelligence, alien intelligence.

00:46:17.485 --> 00:46:17.545
Hmm.

00:46:18.779 --> 00:46:22.140
We live in interesting times, don't we?

00:46:23.160 --> 00:46:26.520
Here's what big tech has to say about AI.

00:46:27.540 --> 00:46:33.990
Sundar Pichai, CEO of Google, the future
of AI is not about replacing humans,

00:46:34.290 --> 00:46:37.230
it's about augmenting human capabilities.

00:46:38.000 --> 00:46:43.590
Ginni Rometty, former CEO of IBM says,
AI will not replace humans, but those

00:46:43.590 --> 00:46:47.550
who use AI will replace those who don't.

00:46:49.004 --> 00:46:56.924
And then perched high on the proverbial
fence, CEO of SpaceX and Tesla, Elon Musk

00:46:56.984 --> 00:47:02.955
said, AI is likely to be either the best
or worst thing to happen to humanity.

00:47:04.154 --> 00:47:04.845
Thanks, Elon.

00:47:06.044 --> 00:47:12.134
But the final word should go to
the ultimate tech nerd Bill Gates,

00:47:12.314 --> 00:47:17.730
co-founder of Microsoft, said, artificial
intelligence will evolve to become a

00:47:17.730 --> 00:47:25.320
super intelligence, we need to be mindful
of how it's developed and ensure that it

00:47:25.320 --> 00:47:30.255
aligns with humanities best interests.

00:47:34.125 --> 00:47:36.075
James Cromwell: There have always
been ghosts in the machine.

00:47:38.145 --> 00:47:43.545
Random segments of code that have grouped
together to form unexpected protocols,

00:47:45.165 --> 00:47:50.190
unanticipated these free radicals
and gender questions of free will.

00:47:52.299 --> 00:47:59.049
Creativity and even the nature of
what we might call the soul, or

00:48:01.140 --> 00:48:16.890
is it something

00:48:24.779 --> 00:48:25.910
more.

00:48:28.095 --> 00:48:30.885
Jim Conrad: That is the
Conovision Podcast, the spirit of

00:48:30.885 --> 00:48:35.745
storytelling, episode three, all
about artificial intelligence.

00:48:36.225 --> 00:48:41.715
My thanks to all the conscious
entities in the first AI G7 Summit.

00:48:41.985 --> 00:48:45.585
We are still trying to decode
that digital word salad.

00:48:46.075 --> 00:48:52.524
To Amazon's Alexa for dropping by with
illuminating answers to absurd questions,

00:48:53.185 --> 00:48:57.654
to Professor  Yuval Noah Harari, and his
insight into the differential patterns

00:48:57.654 --> 00:49:00.685
between intelligence and consciousness.

00:49:01.435 --> 00:49:06.279
The New York Times, for the brilliant
story about Douglas Rain, the Canadian

00:49:06.279 --> 00:49:10.840
Shakespearean actor, and the voice of
HAL, the computer in Stanley Kubrick's,

00:49:10.840 --> 00:49:15.670
1968 Masterpiece 2001: A Space Odyssey.

00:49:16.840 --> 00:49:20.710
And as well our tech guru Eric Westra,
for his thoughts on the future of

00:49:20.710 --> 00:49:23.200
AI and what it will mean to us all.

00:49:23.980 --> 00:49:28.375
And finally, we just heard a monologue
from the film I, Robot and the

00:49:28.375 --> 00:49:31.225
majestic voice of actor James Cromwell.

00:49:31.735 --> 00:49:37.475
I am James Conrad, AKA Cono,
and this has been Conovision,

00:49:37.495 --> 00:49:39.475
the spirit of storytelling.

00:49:40.135 --> 00:49:44.935
Until next time, remember, we
are all stories to be told.