TED@IBM
Grady Booch: Don't fear superintelligent AI
Grady Booch: Non temamos a superintelixente IA
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Novas creacións tecnolóxicas, novas ansiedades, di o filósofo Grady Booch, pero non temos por que temer unha IA todopoderosa e sen sentimentos. Booch calma os nosos peores medos (inducidos pola ciencia ficción) acerca dos ordenadores superintelixentes explicando como lles aprenderemos, e non programaremos, para que compartan os nosos valores. En vez de preocuparnos por unha, pouco probable, ameaza existencial, anímanos a que nos preguntemos como a intelixencia artificial pode mellorar a vida humana.
Grady Booch - Scientist, philosopher
IBM's Grady Booch is shaping the future of cognitive computing by building intelligent systems that can reason and learn. Full bio
IBM's Grady Booch is shaping the future of cognitive computing by building intelligent systems that can reason and learn. Full bio
Double-click the English transcript below to play the video.
00:12
When I was a kid,
I was the quintessential nerd.
I was the quintessential nerd.
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Cando era un neno,
era o típico friqui.
era o típico friqui.
00:17
I think some of you were, too.
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Creo que algúns de vostedes tamén.
00:19
(Laughter)
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(risos)
00:20
And you, sir, who laughed the loudest,
you probably still are.
you probably still are.
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E vostede, señor, o que ri máis alto,
pode que aínda o sexa.
pode que aínda o sexa.
00:24
(Laughter)
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(risos)
00:26
I grew up in a small town
in the dusty plains of north Texas,
in the dusty plains of north Texas,
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Medrei nunha cidade pequena
nas poirentas chairas do norte de Texas,
nas poirentas chairas do norte de Texas,
00:29
the son of a sheriff
who was the son of a pastor.
who was the son of a pastor.
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son fillo dun sheriff
que era fillo dun pastor.
que era fillo dun pastor.
00:33
Getting into trouble was not an option.
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así que mellor non meterme en problemas.
00:36
And so I started reading
calculus books for fun.
calculus books for fun.
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Por tanto comecei a ler libros
de cálculo por divertimento.
de cálculo por divertimento.
00:39
(Laughter)
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(risos)
00:40
You did, too.
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Vostede tamén.
00:42
That led me to building a laser
and a computer and model rockets,
and a computer and model rockets,
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Iso levoume a construir un láser,
un computador, cohetes,
un computador, cohetes,
00:46
and that led me to making
rocket fuel in my bedroom.
rocket fuel in my bedroom.
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e a facer combustible
para foguetes no meu cuarto.
para foguetes no meu cuarto.
00:49
Now, in scientific terms,
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Agora, en termos científicos,
00:53
we call this a very bad idea.
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a iso chámamoslle: unha moi mala idea.
00:56
(Laughter)
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(risos)
00:58
Around that same time,
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Ao mesmo tempo, estreábase
01:00
Stanley Kubrick's "2001: A Space Odyssey"
came to the theaters,
came to the theaters,
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2001, unha odisea no espazo
de Stanley Kubrick,
de Stanley Kubrick,
01:03
and my life was forever changed.
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e a miña vida cambiaba para sempre.
01:06
I loved everything about that movie,
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Encantoume todo desa película,
01:08
especially the HAL 9000.
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sobre todo HAL 9000.
01:10
Now, HAL was a sentient computer
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HAL era un computador consciente
01:13
designed to guide the Discovery spacecraft
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deseñado para guiar o Discovery
01:15
from the Earth to Jupiter.
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da Terra a Xúpiter.
01:18
HAL was also a flawed character,
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HAL era ademais un personaxe con defectos,
01:20
for in the end he chose
to value the mission over human life.
to value the mission over human life.
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xa que ao final lle deu máis importancia
á misión ca á vida humana.
á misión ca á vida humana.
01:24
Now, HAL was a fictional character,
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Agora, HAL pertence á ficción
01:26
but nonetheless he speaks to our fears,
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pero aínda así fala dos nosos medos
01:29
our fears of being subjugated
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a sermos dominados
01:31
by some unfeeling, artificial intelligence
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por unha intelixencia artificial (IA)
sen sentimentos
sen sentimentos
01:34
who is indifferent to our humanity.
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que é indiferente á nosa humanidade.
01:37
I believe that such fears are unfounded.
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Creo que eses medos non teñen fundamento.
01:40
Indeed, we stand at a remarkable time
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De feito, estamos nunha importante época
01:43
in human history,
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para a historia humana
01:44
where, driven by refusal to accept
the limits of our bodies and our minds,
the limits of our bodies and our minds,
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na que, por negarnos a aceptar
os límites dos nosos corpos e mentes,
os límites dos nosos corpos e mentes,
01:49
we are building machines
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estamos construíndo máquinas
01:51
of exquisite, beautiful
complexity and grace
complexity and grace
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de exquisita beleza, complexidade e graza
01:55
that will extend the human experience
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que ampliarán a experiencia humana
01:57
in ways beyond our imagining.
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de formas que nin imaxinamos.
01:59
After a career that led me
from the Air Force Academy
from the Air Force Academy
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Despois de pasar
da Academia da Forza Aérea
da Academia da Forza Aérea
02:02
to Space Command to now,
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ao Mando Espacial da Forza Aérea,
02:04
I became a systems engineer,
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pasei a enxeñeiro de sistemas
02:06
and recently I was drawn
into an engineering problem
into an engineering problem
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e hai pouco metéronme
nun problema de enxeñaría
nun problema de enxeñaría
02:08
associated with NASA's mission to Mars.
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relacionado coa misión da NASA a Marte.
02:11
Now, in space flights to the Moon,
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Agora, nos voos espaciais á Lúa,
02:13
we can rely upon
mission control in Houston
mission control in Houston
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dependemos do control
de Houston para vixiar
de Houston para vixiar
02:17
to watch over all aspects of a flight.
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todos os aspectos do voo.
02:19
However, Mars is 200 times further away,
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Porén Marte está 200 veces máis lonxe
e por tanto un sinal tarda
arredor de 13 minutos
arredor de 13 minutos
02:22
and as a result it takes
on average 13 minutes
on average 13 minutes
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02:25
for a signal to travel
from the Earth to Mars.
from the Earth to Mars.
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en viaxar dende a Terra ata alí.
02:29
If there's trouble,
there's not enough time.
there's not enough time.
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Se hai algún problema, é demasiado tempo.
02:32
And so a reasonable engineering solution
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Unha solución razoable
02:35
calls for us to put mission control
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pasa por incluír o control da misión
02:37
inside the walls of the Orion spacecraft.
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dentro das paredes da nave espacial Orión.
02:41
Another fascinating idea
in the mission profile
in the mission profile
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Outra idea fascinante do perfil da misión
02:43
places humanoid robots
on the surface of Mars
on the surface of Mars
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sitúa a robots humanoides
na superficie de Marte
na superficie de Marte
02:46
before the humans themselves arrive,
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antes ca os propios humanos,
primeiro para construír infraestruturas
02:48
first to build facilities
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02:50
and later to serve as collaborative
members of the science team.
members of the science team.
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e despois para serviren
como colaboradores do equipo científico.
como colaboradores do equipo científico.
02:55
Now, as I looked at this
from an engineering perspective,
from an engineering perspective,
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Desde a perspectiva da enxeñaría,
02:58
it became very clear to me
that what I needed to architect
that what I needed to architect
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quedoume moi claro
que o que necesitaba deseñar
que o que necesitaba deseñar
03:01
was a smart, collaborative,
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era unha intelixencia artificial
03:03
socially intelligent
artificial intelligence.
artificial intelligence.
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esperta, colaborativa
e socialmente intelixente.
e socialmente intelixente.
03:05
In other words, I needed to build
something very much like a HAL
something very much like a HAL
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É dicir, precisaba construír
algo moi parecido a HAL
algo moi parecido a HAL
03:10
but without the homicidal tendencies.
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pero sen as súas tendencias homicidas.
03:12
(Laughter)
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(risos)
03:14
Let's pause for a moment.
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Deteñámonos un momento.
03:16
Is it really possible to build
an artificial intelligence like that?
an artificial intelligence like that?
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É posible construírmos
unha intelixencia artificial coma esa?
unha intelixencia artificial coma esa?
03:20
Actually, it is.
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Pois, si.
03:22
In many ways,
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Por moitas razóns,
03:23
this is a hard engineering problem
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este é un difícil problema de enxeñaría
03:25
with elements of AI,
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cos elementos da lA,
03:26
not some wet hair ball of an AI problem
that needs to be engineered.
that needs to be engineered.
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non só unhas pedriñas no camiño
que deben ser tratadas pola enxeñaría.
que deben ser tratadas pola enxeñaría.
03:31
To paraphrase Alan Turing,
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Parafraseando a Alan Turing,
03:34
I'm not interested
in building a sentient machine.
in building a sentient machine.
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Non quero construír
unha máquina con sentimentos.
unha máquina con sentimentos.
03:36
I'm not building a HAL.
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Non constrúo un HAL.
03:38
All I'm after is a simple brain,
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Só busco un cerebro simple,
03:40
something that offers
the illusion of intelligence.
the illusion of intelligence.
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algo que ofrece a ilusión da intelixencia.
03:45
The art and the science of computing
have come a long way
have come a long way
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A arte e a ciencia informática
percorreron un longo camiño
percorreron un longo camiño
03:48
since HAL was onscreen,
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dende que vimos a HAL,
03:49
and I'd imagine if his inventor
Dr. Chandra were here today,
Dr. Chandra were here today,
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e creo que se o Dr. Chandra,
o seu inventor, estivese aquí hoxe,
o seu inventor, estivese aquí hoxe,
03:52
he'd have a whole lot of questions for us.
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tería moitas preguntas que facernos.
03:55
Is it really possible for us
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Énos posible coller un sistema
03:57
to take a system of millions
upon millions of devices,
upon millions of devices,
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de millóns e millóns de dispositivos,
04:01
to read in their data streams,
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medir os seus datos,
04:02
to predict their failures
and act in advance?
and act in advance?
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predicir os seus fallos e anticiparnos?
04:05
Yes.
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É.
04:06
Can we build systems that converse
with humans in natural language?
with humans in natural language?
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Podemos crear sistemas
que falen nunha linguaxe natural?
que falen nunha linguaxe natural?
04:09
Yes.
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Podemos.
Podemos crear sistemas
que recoñezan obxectos,
que recoñezan obxectos,
04:10
Can we build systems
that recognize objects, identify emotions,
that recognize objects, identify emotions,
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04:13
emote themselves,
play games and even read lips?
play games and even read lips?
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identifiquen e expresen emocións,
xoguen, lean os beizos?
xoguen, lean os beizos?
04:17
Yes.
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Podemos.
04:18
Can we build a system that sets goals,
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Podemos crear un sistema que fixe metas,
04:20
that carries out plans against those goals
and learns along the way?
and learns along the way?
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cree plans para acadalas
e de paso aprenda?
e de paso aprenda?
04:24
Yes.
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Podemos.
04:25
Can we build systems
that have a theory of mind?
that have a theory of mind?
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Podemos construír sistemas
que teñan unha teoría da mente?
que teñan unha teoría da mente?
Isto é o que estamos a aprender a facer.
04:28
This we are learning to do.
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04:30
Can we build systems that have
an ethical and moral foundation?
an ethical and moral foundation?
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Podemos construír un sistema
que teña principios éticos e morais?
que teña principios éticos e morais?
04:34
This we must learn how to do.
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Isto é o que debemos aprender.
04:37
So let's accept for a moment
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Aceptemos por un momento
04:38
that it's possible to build
such an artificial intelligence
such an artificial intelligence
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que podemos construír
esta intelixencia artificial
esta intelixencia artificial
04:41
for this kind of mission and others.
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para este e outro tipo de misións.
04:43
The next question
you must ask yourself is,
you must ask yourself is,
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A seguinte pregunta que se deben facer é:
04:46
should we fear it?
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deberiamos de lle ter medo?
04:47
Now, every new technology
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Todas as novas tecnoloxías
04:49
brings with it
some measure of trepidation.
some measure of trepidation.
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traen consigo certo grao de inquietude.
04:52
When we first saw cars,
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A primeira vez que a xente viu un coche,
04:54
people lamented that we would see
the destruction of the family.
the destruction of the family.
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queixábase de que ía destruír as familias.
04:58
When we first saw telephones come in,
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Cando vimos por primeira vez os teléfonos,
05:01
people were worried it would destroy
all civil conversation.
all civil conversation.
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preocupábanos que acabasen
coas conversas civilizadas.
coas conversas civilizadas.
05:04
At a point in time we saw
the written word become pervasive,
the written word become pervasive,
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Nalgún momento cremos
que a escritura se volvería ubicua,
que a escritura se volvería ubicua,
05:08
people thought we would lose
our ability to memorize.
our ability to memorize.
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que se perdería a capacidade de memorizar.
05:10
These things are all true to a degree,
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Todo isto é verdade ata certo punto,
05:12
but it's also the case
that these technologies
that these technologies
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pero tamén o é que estas tecnoloxías
05:15
brought to us things
that extended the human experience
that extended the human experience
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nos brindaron avances
que ampliaron a experiencia humana
que ampliaron a experiencia humana
05:18
in some profound ways.
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de formas moi profundas.
05:21
So let's take this a little further.
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Así que sigamos un pouco máis.
05:25
I do not fear the creation
of an AI like this,
of an AI like this,
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Non me dá medo a creación
dunha IA coma esta,
dunha IA coma esta,
05:29
because it will eventually
embody some of our values.
embody some of our values.
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xa que, co tempo, encarnará
algúns dos nosos valores.
algúns dos nosos valores.
05:33
Consider this: building a cognitive system
is fundamentally different
is fundamentally different
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Tendo isto en conta: construír
un sistema cognitivo é distinto
un sistema cognitivo é distinto
05:37
than building a traditional
software-intensive system of the past.
software-intensive system of the past.
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a crear un anticuado sistema
baseado en software intensivo.
baseado en software intensivo.
05:40
We don't program them. We teach them.
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Non os programamos, aprendémoslles.
05:43
In order to teach a system
how to recognize flowers,
how to recognize flowers,
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Para lles aprendermos
a como recoñeceren as flores,
a como recoñeceren as flores,
05:45
I show it thousands of flowers
of the kinds I like.
of the kinds I like.
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amosaríalles moitas flores
das miñas variedades preferidas.
das miñas variedades preferidas.
05:48
In order to teach a system
how to play a game --
how to play a game --
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Para aprenderlles como xogar a un xogo...
05:51
Well, I would. You would, too.
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Eu faríao, e vós tamén.
05:54
I like flowers. Come on.
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De verdade que me gustan as flores.
05:57
To teach a system
how to play a game like Go,
how to play a game like Go,
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Para ensinarlle a un sistema
a xogar a un xogo coma Go
a xogar a un xogo coma Go
06:00
I'd have it play thousands of games of Go,
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faríao xogar milleiros de partidas.
06:02
but in the process I also teach it
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E no proceso aprenderíalle
06:04
how to discern
a good game from a bad game.
a good game from a bad game.
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a distinguir unha boa partida dunha mala.
06:06
If I want to create an artificially
intelligent legal assistant,
intelligent legal assistant,
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Se quixese crear unha IA
coa función de asistente legal
coa función de asistente legal
06:10
I will teach it some corpus of law
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aprenderíalle un corpus legal
06:12
but at the same time I am fusing with it
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ao mesmo tempo que lle introduciría
06:14
the sense of mercy and justice
that is part of that law.
that is part of that law.
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o sentido da misericordia
e xustiza que é parte da lei.
e xustiza que é parte da lei.
06:18
In scientific terms,
this is what we call ground truth,
this is what we call ground truth,
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En termos científicos
chámaselles verdades fundamentais
chámaselles verdades fundamentais
06:21
and here's the important point:
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e o máis importante:
06:23
in producing these machines,
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ao producirmos estas máquinas
06:25
we are therefore teaching them
a sense of our values.
a sense of our values.
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estámoslles inculcando os nosos valores.
06:28
To that end, I trust
an artificial intelligence
an artificial intelligence
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Chegados a este punto, confío nunha IA
06:31
the same, if not more,
as a human who is well-trained.
as a human who is well-trained.
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tanto, se non máis,
ca nun humano ben adestrado.
ca nun humano ben adestrado.
06:36
But, you may ask,
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Preguntarédesvos
06:37
what about rogue agents,
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que pasa cos axentes corruptos,
06:39
some well-funded
nongovernment organization?
nongovernment organization?
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con algunhas ONG ben financiadas?
06:43
I do not fear an artificial intelligence
in the hand of a lone wolf.
in the hand of a lone wolf.
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Unha IA en mans dun lobo solitario
non me pon medo.
non me pon medo.
06:47
Clearly, we cannot protect ourselves
against all random acts of violence,
against all random acts of violence,
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Non nos podemos autoprotexer
de todo acto aleatorio de violencia
de todo acto aleatorio de violencia
06:51
but the reality is such a system
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pero a realidade é que tal sistema
06:53
requires substantial training
and subtle training
and subtle training
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precisa dun adestramento
substancial e sutil
substancial e sutil
06:57
far beyond the resources of an individual.
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moi por riba das capacidades
dun único individuo.
dun único individuo.
06:59
And furthermore,
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E ademais é máis complicado
07:00
it's far more than just injecting
an internet virus to the world,
an internet virus to the world,
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ca inxectarmos un virus informático
en todo o mundo.
en todo o mundo.
07:03
where you push a button,
all of a sudden it's in a million places
all of a sudden it's in a million places
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Premendo un botón
o virus chega a milleiros de lugares
o virus chega a milleiros de lugares
07:06
and laptops start blowing up
all over the place.
all over the place.
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e os portátiles empezan a estoupar.
07:09
Now, these kinds of substances
are much larger,
are much larger,
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Agora, este tipo de contidos
son moito máis grandes
son moito máis grandes
07:12
and we'll certainly see them coming.
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e vémolos vir.
07:14
Do I fear that such
an artificial intelligence
an artificial intelligence
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Teño medo a que unha IA deste tipo
07:17
might threaten all of humanity?
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poida ameazar a toda a humanidade?
07:20
If you look at movies
such as "The Matrix," "Metropolis,"
such as "The Matrix," "Metropolis,"
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Se ves películas como Matrix, Metrópolis,
07:24
"The Terminator,"
shows such as "Westworld,"
shows such as "Westworld,"
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Terminator, series como Westworld
07:27
they all speak of this kind of fear.
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todas tratan este tipo de medos.
07:30
Indeed, in the book "Superintelligence"
by the philosopher Nick Bostrom,
by the philosopher Nick Bostrom,
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De feito, no libro Superintelixencia
do filósofo Nick Bostrom
do filósofo Nick Bostrom
07:34
he picks up on this theme
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este trata o mesmo tema
07:35
and observes that a superintelligence
might not only be dangerous,
might not only be dangerous,
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e opina que unha superintelixencia
non só podería ser perigosa
non só podería ser perigosa
07:39
it could represent an existential threat
to all of humanity.
to all of humanity.
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podería representar unha ameaza
para toda a humanidade.
para toda a humanidade.
07:43
Dr. Bostrom's basic argument
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O argumento do Dr. Bostrom
07:46
is that such systems will eventually
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é que estes sistemas
van chegar a ter nun momento
van chegar a ter nun momento
07:48
have such an insatiable
thirst for information
thirst for information
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tal insaciable fame de información
07:52
that they will perhaps learn how to learn
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que pode que aprendan a como aprender
07:55
and eventually discover
that they may have goals
that they may have goals
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e poden chegar a descubrir
que teñen obxectivos
que teñen obxectivos
07:57
that are contrary to human needs.
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contrarios ás necesidades humanas.
08:00
Dr. Bostrom has a number of followers.
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O Dr. Bostrom ten seguidores.
08:01
He is supported by people
such as Elon Musk and Stephen Hawking.
such as Elon Musk and Stephen Hawking.
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É apoiado por xente
como Elon Musk ou Stephen Hawking.
como Elon Musk ou Stephen Hawking.
08:06
With all due respect
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Con todo o meu respecto
08:10
to these brilliant minds,
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por estas mentes prodixiosas,
08:12
I believe that they
are fundamentally wrong.
are fundamentally wrong.
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creo que se equivocan.
08:14
Now, there are a lot of pieces
of Dr. Bostrom's argument to unpack,
of Dr. Bostrom's argument to unpack,
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Hai moitas partes da argumentación
do Dr. Bostrom que analizar
do Dr. Bostrom que analizar
08:17
and I don't have time to unpack them all,
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e agora non teño tempo
08:19
but very briefly, consider this:
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pero de forma moi breve, direi isto:
08:22
super knowing is very different
than super doing.
than super doing.
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a supersabedoría é moi diferente
da superrealización.
da superrealización.
08:26
HAL was a threat to the Discovery crew
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HAL era unha ameaza
08:28
only insofar as HAL commanded
all aspects of the Discovery.
all aspects of the Discovery.
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para a tripulación do Discovery
só se tomaba o control de toda a nave.
só se tomaba o control de toda a nave.
08:32
So it would have to be
with a superintelligence.
with a superintelligence.
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O mesmo pasaría cunha superintelixencia.
08:35
It would have to have dominion
over all of our world.
over all of our world.
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Tería que ter o dominio de todo o mundo.
08:37
This is the stuff of Skynet
from the movie "The Terminator"
from the movie "The Terminator"
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Isto é o que pasa coa Skynet
de Terminator
de Terminator
08:40
in which we had a superintelligence
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onde temos unha superintelixencia
08:42
that commanded human will,
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que dirixe a vontade humana
08:43
that directed every device
that was in every corner of the world.
that was in every corner of the world.
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e cada dispositivo situado
en calquera recuncho do mundo.
en calquera recuncho do mundo.
08:47
Practically speaking,
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Falando dende a práctica
08:49
it ain't gonna happen.
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isto non vai pasar.
08:51
We are not building AIs
that control the weather,
that control the weather,
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Non estamos deseñando IA
que controlen o clima,
que controlen o clima,
08:54
that direct the tides,
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que dirixan as mareas,
08:55
that command us
capricious, chaotic humans.
capricious, chaotic humans.
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nin a nós, os caprichosos
e caóticos humanos.
e caóticos humanos.
08:59
And furthermore, if such
an artificial intelligence existed,
an artificial intelligence existed,
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Ademais, de existir
unha intelixencia artificial así
unha intelixencia artificial así
09:03
it would have to compete
with human economies,
with human economies,
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tería que competir coas economías humanas
09:06
and thereby compete for resources with us.
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e competir con nós polos recursos.
09:09
And in the end --
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E á fin e ao cabo
09:10
don't tell Siri this --
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(non llo digan a Siri)
09:12
we can always unplug them.
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podemos desconectalos.
09:13
(Laughter)
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(risos)
09:17
We are on an incredible journey
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Estamos nunha incrible viaxe
de coevolución
de coevolución
09:19
of coevolution with our machines.
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xunto coas nosas máquinas.
09:22
The humans we are today
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Os humanos que somos agora
09:24
are not the humans we will be then.
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non somos os que seremos daquela.
09:27
To worry now about the rise
of a superintelligence
of a superintelligence
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Preocuparse agora
polo auxe dunha superintelixencia
polo auxe dunha superintelixencia
09:30
is in many ways a dangerous distraction
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é unha distracción perigosa
09:33
because the rise of computing itself
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xa que o auxe da informática en si
09:36
brings to us a number
of human and societal issues
of human and societal issues
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xa dá lugar a algúns asuntos
humanos e sociais
humanos e sociais
09:39
to which we must now attend.
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aos que temos que atender.
09:41
How shall I best organize society
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Como se pode organizar a sociedade
09:44
when the need for human labor diminishes?
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cando diminúe
a necesidade de capital humano?
a necesidade de capital humano?
09:46
How can I bring understanding
and education throughout the globe
and education throughout the globe
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Como podo achegarlle
compresión e educación a todo o mundo
compresión e educación a todo o mundo
09:50
and still respect our differences?
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respectando as nosas diferenzas?
09:52
How might I extend and enhance human life
through cognitive healthcare?
through cognitive healthcare?
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Como podo mellorar a vida das persoas
a través da medicina cognitiva?
a través da medicina cognitiva?
09:56
How might I use computing
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Como podo utilizar a informática
09:59
to help take us to the stars?
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para que cheguemos ás estrelas?
10:01
And that's the exciting thing.
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E iso é o excitante.
10:04
The opportunities to use computing
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As oportunidades de usar a informática
10:06
to advance the human experience
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para que progrese a experiencia humana
10:08
are within our reach,
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están ao noso alcance
10:09
here and now,
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aquí e agora
10:11
and we are just beginning.
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e isto é só o comezo.
10:14
Thank you very much.
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Moitas grazas.
10:15
(Applause)
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(Aplausos)
ABOUT THE SPEAKER
Grady Booch - Scientist, philosopherIBM's Grady Booch is shaping the future of cognitive computing by building intelligent systems that can reason and learn.
Why you should listen
When he was 13, Grady Booch saw 2001: A Space Odyssey in the theaters for the first time. Ever since, he's been trying to build Hal (albeit one without the homicidal tendencies). A scientist, storyteller and philosopher, Booch is Chief Scientist for Software Engineering as well as Chief Scientist for Watson/M at IBM Research, where he leads IBM's research and development for embodied cognition. Having originated the term and the practice of object-oriented design, he is best known for his work in advancing the fields of software engineering and software architecture.
A co-author of the Unified Modeling Language (UML), a founding member of the Agile Allianc, and a founding member of the Hillside Group, Booch has published six books and several hundred technical articles, including an ongoing column for IEEE Software. He's also a trustee for the Computer History Museum, an IBM Fellow, an ACM Fellow and IEEE Fellow. He has been awarded the Lovelace Medal and has given the Turing Lecture for the BCS, and was recently named an IEEE Computer Pioneer.
Booch is currently deeply involved in the development of cognitive systems and is also developing a major trans-media documentary for public broadcast on the intersection of computing and the human experience.
Grady Booch | Speaker | TED.com