ARTIFICIAL INTELLIGENCE.
WE'RE LOOKING FOR OTHER MEMBERS
TO COME AND VISIT WITH US --
SENATOR BORDERS SENATOR CHIANG
CENTER DORADO SENATOR STERN
SENATOR WINNER.
IF YOU WITHIN EARSHOT OF MY
VOICE WE WOULD WELCOME.
YOUR PRESENCE THANKS
[inaudible]
WE CALLED [inaudible]
YEAH.
DO YOU HAVE -- SELF ALL RIGHT
ARM SIR CHIANG WE HAVE CENTER
CHIANG WITH SENATOR.
FORGES HERE SO WHAT WE'RE GOING
TO GO AHEAD AND KICK OFF THE
SENATE SELECT COMMITTEE ON THE
GROWING IMPACT OF ARTIFICIAL
INTELLIGENCE IN.
CALIFORNIA -- WE'RE STILL
WAITING SEVERAL OTHER SENATORS
BUT I THINK AS MANY OF YOU IN
THE AUDIENCE KNOW.
OF WE MULTIPLE.
ASK HERE OF SOME OF US ARE.
DOUBLE TASKING S IS A TRIPLE
TESTING MAYBE EVEN QUADRUPLE
TASKING.
SO.
LET'S GO AHEAD AND GET SOARED
MORNING EVERYBODY THANK YOU FOR
COMING THE FIRST HEARING OF THE
SENATE SELECT COMMITTEE ON THE
GROWING IMPACT OF ARTIFICIAL
INTELLIGENCE IN CALIFORNIA.
OTHERS FIRST HEARING IS JUST
GOING TO BE AN INDUCTION INTO
ARTIFICIAL INTELLIGENCE IN
ARTIFICIAL INTELLIGENCE POLICY
ISSUES.
WE'RE GOING TO SCRATCH THE
SURFACE ON A LOT OF ISSUES
BECAUSE WE'VE GOT A HUGE SCOPE
OF ISSUES -- I WANT TO THANK THE
FOLKS WERE WATCHING ONLINE AND
ALL THE STAKEHOLDERS IN THE A I
FEEL THAT REACHED OUT TO OUR
OFFICE WE'VE GOTTEN QUITE A
NUMBER OF ENQUIRIES -- WE'VE
HEARD FROM.
YOU O A WIDE VARIETY OF ISSUES
EVERYTHING FROM AUTONOMOUS
VEHICLES MEDICAL TECHNOLOGY. TO
A AYE BIAS TO WORK FORCE
CONCERNS AND PRIVACY ISSUES ALL
OF THEM ARE IMPORTANT.
UP.
WE ARE WE'RE NOT GONNA BE ABLE
TO INCLUDE EVERYONE IN EVERY
TOPIC CERTAINLY IN THIS HEARING --
BUT I DO APPRECIATE FOLKS.
PROVIDING THEIR CONTRIBUTION OF
BOTH -- IN WRITING AND BY EMAIL
BY LETTER BY EMAIL AND ON THE
PHONE -- IF I TIME ALLOWS AND I
THINK IT WILL WE'RE GONNA HAVE
AN OPPORTUNITY FOR THOSE YOU IN
THE AUDIENCE TO COME UP AND GIVE
US YOUR THOUGHTS ON ARTIFICIAL
INTELLIGENCE AND WHEN WHERE THE
COMMITTEE.
OF MAKEOVER SHOULD GO -- WE'RE
LIVING IN AN EXCITING TIME --
WITH CUTTING EDGE ARTIFICIAL
INTELLIGENCE TECHNOLOGY BEING
DEVELOPED AND RELEASED EVERY DAY.
I THINK I SPEAK FOR EVERYONE
HERE WHEN I SAY WE NEED TO BE
MORE PROACTIVE IN GOVERNMENT.
AS A AYE.
BASICALLY TAKES OFF.
THAT'S WHY IT'S IMPORTANT WE
HAVE A HEARING LIKE THIS SO WE
CAN HEAR FOR FOLKS ARE DOING THE
RESEARCH WORK IN THE A. I. FIELD.
I WE'VE GOT FOLKS HERE FROM THE
ALCHEMY TESTIFYING TODAY AND
WE'RE STARTING WITH. ONE OF MY
FORMER COLLEAGUES ASSEMBLY
MEMBER PEDRO NAVA WHO'S
PRESENTING ON A LITTLE HAVE
HOOVER COMMISSION REPORT --
WHICH IS AVAILABLE IN THE BACK
OF THE ROOM.
ASSEMBLYMEMBER NAVA.
CONSECUTIVE TERMS CHAIR LITTLE
HOOVER COMMISSION HE'S A FORMER
CIVIL LITIGATOR -- DEPUTY
DISTRICT ATTORNEY MEMBER THE
CALIFORNIA COMMISSION ON
CATASTROPHIC WHILE FAR COST
RECOVERY IN AS I RECALL ALSO
MEMBER THE COASTAL COMMISSION.
SO FIRST THANK YOU FOR YOUR
EXTENSIVE AND DEDICATED AND
INCREDIBLY VALUABLE GOVERNMENT
SERVICE AND WE INVITE YOU.
TO START US OFF THANK YOU
ASSEMBLYMEMBER NOW [inaudible]
THE WITH RESPECT TO MY RESUME
THAT'S WHAT HAPPENS WHEN YOU
DON'T SAY NO.
BUT THE GOOD MORNING TO ALL OF
YOU -- I PAID OR NOT AND I'M THE
CHAIRMAN OF THE LITTLE HOOVER
COMMISSION.
THE COMMISSION IS AN INDEPENDENT
BIPARTISAN AGENCY CHARGED WITH
RECOMMENDING WAYS. TO IMPROVE
THE EFFICIENCY AND EFFECTIVENESS
OF STATE GOVERNMENT.
LAST YEAR THE COMMISSION AND
BARKED ON ELEVEN MONTHS STUDY TO
UNDERSTAND HOW OUR STATE IS
PREPARING FOR THE USE OF
ARTIFICIAL INTELLIGENCE THE
OPPORTUNITIES.
THAT A I CAN PROVIDE TO IMPROVE
THE LIVES OF ALL CALIFORNIANS.
LAST FALL WE RELEASED OUR REPORT
ARTIFICIAL INTELLIGENCE A ROAD
MAP FOR CALIFORNIA.
OUR STAFF HAS PROVIDED THE
COMMITTEE WITH ADDITIONAL COPIES
OF THE REPORT I BELIEVE YOU HAVE.
ARE OU INCLUDED UP PUBLIC
HEARINGS AND ADVISORY MEETINGS
AND WAS INFORMED BY
CONVERSATIONS WITH.
NUMEROUS STAKEHOLDERS MUCH AS
YOU ARE GOING TO BE DOING WITH
YOUR SELECT COMMITTEE AS WELL.
DOOR STUDY WE IDENTIFIED MANY
OPPORTUNITIES TO USE ARTIFICIAL
INTELLIGENCE.
JUST A COUPLE OF EXAMPLES.
A A I CAN BE USED TO HELP
EMERGENCY RESPONDERS PREDICT
WHERE AND WHEN FIRES ARE LIKELY
TO OCCUR YOU CAN ASK -- MISTER-GELLER DUTY SECRETARIAL TO CHIP
OUT HOW THEY ARE APPLYING THOSE
IN THEIR PARK.
HEY I MAY HELP CATERS AND DOES%
HELP EDUCATORS IMPROVE STUDENT
OUTCOMES AND INCREASE GRADUATION
RATES.
AND WHILE CALIFORNIA STATE
GOVERNMENT HAS MADE STRIDES TO
IMPROVE OPERATIONS AND SERVICES
EMPLOYMENT OR TECHNOLOGY.
WE ARE UNFORTUNATELY UNDER
pPREPARE. TO RESPOND IN ADOPTED
THE SPEED WITH WHICH ARTIFICIAL%
INTELLIGENCE IS CHANGING OUR
WORLD.
IT BECAME CLEAR TO USTHROUGH
OUR RESEARCH THE CALIFORNIA
LACKS THE NECESSARY
INFRASTRUCTURE. TO IMPLEMENT A
AYE IN STATE GOVERNMENT.
WE'RE FALLING BEHIND OTHER
STATES.
LIKE INDIANA.
MICHIGAN AND VERMONT.
WE ARE THE FIFTH LARGEST ECONOMY
IN THE WORLD AND A TECHNOLOGICAL
POWERHOUSE BUT THE COMMISSION
FOUND THAT A STRATEGIC PLANNING
VOID EXISTS AND STATE GOVERNMENT.
AROUND SEIZING THE OPPORTUNITIES
OF A AYE AND MINIMIZING ITS
RISKS.
WE SHOULD TEN RECOMMENDATIONS
FOR THE GOVERNOR AND THE
LEGISLATURE. TO PROVIDE THE
VISION AND COORDINATION TO
GOVERN FOR THE FUTURE.
THIS INCLUDES ESTABLISHING A AYE
LEADERSHIP AT VARIOUS LEVELS OF
STATE GOVERNMENT.
WE RECOMMENDED INCLUDING THE
CABINET LEVEL A AYE SPECIAL
ADVISER TO OVERSEE THE
BENEFICIAL AND TRANSPARENT
DEPLOYMENT THEY AYE TECHNOLOGY.
AND APPLICATIONS OF STATE
GOVERNMENT.
WE ADVOCATE FOR THE CREATION OF
AN EXPERT COMMISSION FROM
DIVERSE SECTORS TO DEVELOP
INCORPORATE THEY ARE RELATED
DEMONSTRATION PROJECTS FOR
CRITICAL STATE SERVICES.
WE ALSO CALL FOR THE STATE TO
IMPROVE THE COLLECTION OF DATA
ON JOBS AND SKILLS FOR FUTURE
WORKERS.
CALIFORNIA SHOULD IMPLEMENT
CHANGES TO PROPERLY FORECAST A
EYES AFFECTS ON EMPLOYMENT.
WE PROPOSE DEVELOPING OUR
WORKFORCE BY PROMOTING
APPRENTICESHIPS AND TRAINING FOR
WORKERS WHO JOBS MAY BE
DESTROYED.
OR TRANSFORMED BY.
THIS INCLUDES REPAIRING OUR
FUTURE WORKFORCE BY ENSURING AYE
EDUCATIONS IS SUCCESSFUL.
IN CALIFORNIA SCHOOLS AND
INSTITUTIONS OF HIGHER EDUCATION.
WE HAVE BEEN PLEASED TO SEE THE
INTEREST BY THIS ADMINISTRATION
AND THE LEGISLATURE TO HELP.
CALIFORNIA LEAD ON A THE
CREATION OF THE OFFICE OF
DIGITAL INNOVATION IN THE FUTURE
OF WORK COMMISSION UNDER
GOVERNOR NEWSOME DEMONSTRATES
THE STATE'S COMMITMENT TO
UNDERSTAND HOW TECHNOLOGY.
CAN DELIVER BETTER GOVERNMENT
SERVICES AND POTENTIAL IMPACTS
ON THE WORK FORCE.
WE PROUDLY SUPPORT THREE BILLS.
INCLUDING SENATE BILL THREE
FORTY EIGHT BY SENATOR JANE
WOULD REQUIRE THE DEPARTMENT OF
TECHNOLOGY TO PRODUCE STRATEGIC
PLANS TO USE A AYE TACK. TO
IMPROVE STATE SERVICES AND
MINIMIZE THE IMPACT ON THE
PUBLIC SECTOR WORSE WORSE AND
JOB CLASSIFICATIONS.
AB.
NINE SEVEN SIX ASSEMBLY MEMBER
SHALL WOULD CREATE AN A I
COMMISSION TO DEVELOP A AYE
RELATED DEMONSTRATION PROJECTS
FOR CRITICAL STATE SERVICES.
AND TO STUDY HOW DATA SCIENCE
CAN BE EFFECTIVELY USED BY STATE
GOVERNMENT.
AB FIVE NINE FOUR SALAS FOR THE
DEPARTMENT OF TECHNOLOGY TO
APPOINT A CHIEF ARTIFICIAL
INTELLIGENCE OFFICER TO EVALUATE
THE USES OF A AYE IN STATE
GOVERNMENT.
AND THERE ARE OTHER BILLS AS
WELL THEY CAN HELP MOVE
CALIFORNIA.
FOR AB FIFTEEN SEVENTY SIX BY
CALDERON WOULD APPOINT AN A I
WORKING GROUP RELATED TO THE USE
OF A AYE.
BY CALIFORNIA BASED BUSINESSES
AND DEFINE ARTIFICIAL
INTELLIGENCE IN STATE LAW.
AND SENATE BILL SEVEN FIVE TWO
SENATOR STERN.
WOULD CREATE A PUBLIC PROCESS TO
GATHER INPUT AND UNDERSTAND
ECONOMIC SOCIAL WORKPLACE AND
TECHNOLOGICAL LANDSCAPE OF
INNOVATION AND TECHNOLOGY
CALIFORNIA.
THANK YOU MISTER CHAIRMAN FOR
CONVENING THIS CRITICAL
CONVERSATION.
LOU HOOVER COMMISSION STANDS
READY TO HELP CALIFORNIA LEAD IN
THE DEPLOYMENT OF A AYE FOR THE
BENEFIT OF ALL CALIFORNIANS.
I'M HAPPY TO ANSWER ANY OF YOUR
QUESTIONS THAT I'M CAPABLE OF
ANSWERING.
BUT I ALSO.
WANT TO POINT OUT.
HOW?
PRESENT ISSUES ON A. I. R..
SO.
THIS MORNING I WAS READING THE
WALL STREET JOURNAL.
AND SAW ONE OF THE ARTICLES IS
APPRENTICED PLANS FACE RETOOLING.
SO THE TRUMP ADMINISTRATION HAS --
PROPOSED CHANGES TO
APPRENTICESHIP PROGRAMS.
THE SENSUALLY REMOVING
SUPERVISION OF A PRESSURE
PROGRAMS FROM THE DEPARTMENT OF
LABOR.
AND RELYING MORE ON OTHER PUBLIC
SECTOR GROUPS AS WELL AS A
BUSINESS AND LABOR UNIONS
[inaudible]
SO.
UNDERSTANDING THE TRENDS AND
APPLYING A I'D.
PARTICULARLY IN THE FACE OF
THESE KINDS OF CHANGES WOULD BE
VERY IMPORTANT TO WORKERS IN
CALIFORNIA.
AND IN ADDITION TO THAT THERE
WAS A ON THAT SAME PAGE THE
STORY THE TRUMP ADVISORS CALL
JOB TRAINING EFFORTS IN AFFECTED.
SO YOU CAN'T MANAGE WHAT YOU
CAN'T MEASURE. TO ONE OF THE
USES OF A AYE IS TO EVALUATE THE
DIRECTION THAT WE ARE TRAVELING
IN TERMS OF EMPLOYMENT AS WELL
AS OTHER AREAS.
AND THEN COME UP WITH METRICS
AND STANDARDS SO THAT WE CAN
BETTER PREDICT WHERE WE THINK
JOBS WILL BE IN THE FUTURE AND
HOW TO TRAIN.
A DIFFERENT SORT OF WORK FORCE.
WE HAD TESTIMONY WILL HOOVER
COMMISSION HAD TESTIMONY JUST
LAST WEEK.
FROM THE CHANCELLOR OF COMMUNITY
COLLEGES -- EXPLAINED TO US THAT
THE OLD NOTION OF A HIGH SCHOOL
DIPLOMA WHICH USED TO BE.
THE PLACE WHERE YOU STARTED.
ESSENTIALLY NOT THAT SIGNIFICANT
ANYMORE.
AND THAT WHAT MATTERS MORE OUR
CERTIFICATIONS YOU MIGHT HAVE
THOUGHT AND I DID WHEN HE FIRST
BROACH THE SUBJECT BUT IT WOULD
BE THE COLLEGE.
EDUCATION OF COURSE THAT'S
IMPORTANT FOR CERTAIN KINDS OF
JOBS.
BUT WHAT HE POINTED OUT IS IT
MANY MANY EMPLOYMENT
OPPORTUNITIES LOOK MORE TOWARDS
CERTIFICATION IN SPECIFIC FIELDS
OF WORK THAN WE HAVE IN THE PAST
AND HE EXPECTS THAT WILL
CONTINUE TO GROW.
IN THINKING ABOUT A I ALSO IN
THE WALL STREET JOURNAL.
WAS ANOTHER ARTICLE.
CALLED CRADLES THE PEWS AND
SHIFTING POLITICS.
SO.
THE THRUST OF THIS ARTICLE WAS
THAT.
THE BIRTH RATE IN AMERICA IS
DECLINING.
SO THE IMMEDIATE IMPLICATIONS
ACTUALLY MAYBE NOT IMMEDIATE BUT
THE IMPLICATIONS WILL BE FEWER
WORKERS THAT WILL CONTRIBUTE TO
THE SOCIAL SECURITY SYSTEM.
AND OTHER FORMS OF RETIREMENT
PLANS.
IT ALSO SEEMS TO ME THAT WE
OUGHT TO BE LOOKING TO
ARTIFICIAL INTELLIGENCE. TO GIVE
US SOME IDEA ABOUT THE
CHARACTERISTICS OF THIS NEW
SMALLER POPULATION.
AND IN FACT PERHAPS WHAT WE SEE
AS INCREASE PRODUCTIVITY THROUGH
THE APPLICATION OF A AYE MAYBE
ONE ANSWER TO HOW IT IS WE DEAL
WITH A UP OFA POPULATION THAT
DOESN'T GROW IN THE SAME RATE AS
IT DID IN THE PAST.
THE OTHER ASPECT OF THE ARTICLE
HAD TO DO WITH USE -- AND THE
FACT THAT FEWER AND FEWER PEOPLE
IDENTIFY AS REGULARLY ATTENDING
CHURCH.
WELL WHAT DOES THAT HAVE TO DO
WITH ANYTHING WELL I SUSPECT.
THAT THE APPLICATION TODAY I
WILL GIVE US SOME INSIGHT INTO
WHERE DO PEOPLE.
GO TO SEEK AFFIRMATION OF THE
DECISIONS THAT THEY MAKE IN OUR
LIVES THE FAITH COMMUNITY.
HISTORICALLY PLAYS A ROLE IN
PROVIDING COMFORT IN DIRECTION
AND GUIDANCE IF THERE ARE FEWER
PEOPLE WHO ARE GOING TO ORGANIZE
CHURCHES.
WHERE IN FACT WILL THEY GAIN
THEIR INSPIRATION?
WHO WILL THEY LOOK TO FOR
DIRECTION AND AND FOR GUIDANCE
IN TERMS OF HOW TO CONDUCT THEIR
LIVES?
I'M NOT SURE THAT WE WANT THEM.
NECESSARILY GOING ONLINE.
AND LOOKING AT YOUTUBE IN ORDER
TO TRY TO FIGURE OUT THEIR PLACE
IN THE WORLD.
BUT IT DOES RAISE SOME ISSUES
THAT A I MAY BE HELPFUL IN OF
REACHING SOME ANSWERS.
SO.
I HOPE I CAN ANSWER THE
QUESTIONS THAT YOU POSE IF NOT
I'M LOOKING AT THE AGENDA AND
YOU CERTAINLY HAVE A LOT OF
PEOPLE SMARTER THAN I AM WITH A
GREAT DEAL MORE EXPERIENCE.
THANK YOU ASSEMBLYMEMBER NOTA
X. EXCELLENT KICK OFF AND ALSO
THANK YOU FOR THE REVIEW OF WALL
STREET DRIED UP TO READ IT TODAY
SO.
ALREADY.
DONE THAT FOR ME SO CENTER
BORDERS YOUR QUESTION.
YEAH.
REMARKS EVER GO.
THANK YOU CHAIRMAN -- I THINK
THIS IS A FANTASTIC.
OUR COMMITTEE THAT YOU HAVE --
ESTABLISHED -- I THINK IT'S
CERTAINLY -- IT COMMON KNOWLEDGE
REALLY I HOPE IT'S COMMON
KNOWLEDGE AT THIS POINT THAT
WERE A BIT BEHIND THE EIGHT BALL.
IN SO WITH WITH THAT IN MIND.
OF MY QUESTION TO YOU IS.
I SEE IN THE RECOMMENDATIONS A
LITTLE HOOVER COMMISSION -- OF
CREATING LEADERSHIP POSTS.
ARE OR ENHANCING EXISTING
LEADERSHIP POSE FOR THOSE WHO
COULD SERVE AS A INTERFACES
WITHIN THE A. I. TOPICS IN A
GIVEN -- WE SEE WHAT HAPPENS
WITH WILE AWAY AND HOW.
THIS IS MORE OF A NATIONAL ISSUE
BUT I THINK IT BEARS ON SILICON
VALLEY IN OUR TECH SECTOR IS
THAT -- WE RELY SO HEAVILY ON
SUPPLY CHAIN IN INFORMATION --
ASSETS FROM ELSEWHERE IN THE
WORLD.
AND WE DON'T HAVE -- ANY REAL
DOMESTIC PLAYERS THAT ARE -- IT
ADVANCING THE INFRASTRUCTURE AT
A RATE THAT WE NEED.
MY QUESTION TO YOU IS THIS IS.
LITTLE HOOVER COMMISSION'S
RECOMMENDATION INVOLVES THE
GOVERNOR AND THE LEGISLATURE MY
EXPERIENCE LEGISLATURE IS A
WONDERFUL PART OF THE PROCESS.
BUT THE SPEED AT WHICH WE NEED
TO ADDRESS THESE ISSUES.
I CANNOT IMAGINE BEING ANYTHING
OTHER THAN AT THE EXECUTIVE
LEVEL.
IN YOUR RECOMMENDATION OR IN
YOUR OPINION DO YOU HAVE.
A STRONG RECOMMENDATION.
THAT THE GOVERNOR'S OFFICE CAN
TAKE.
ARE A COHERENT LEAD.
EN ADVANCING.
THE TECH RELATED TOPICS AT THE
STATE LEVEL EVEN THOUGH THEY
WOULD NORMALLY BE RESERVED --
FOR NATIONAL AND FEDERAL
JURISDICTION GIVEN THE OPINIONS
ON HOW GOVERNOR NEWSOME CAN.
MOVE OUR SECTOR IN THAT RIGHT
DIRECTION.
WELL I I THINK WHAT WE SEEN
FIRST OF ALL.
DEPENDING ON WHO YOU ASK YOU THE
FOR THE FOR THE SIX LARGEST
ECONOMY IN THE WORLD.
SO WE ARE.
HAVE SIGNIFICANT ECONOMIC
LEVERAGE OVER WHAT HAPPENS
AROUND THE WORLD IN THE EXAMPLE
THAT WE SET FOR OTHERS WILL BE
FALL USUALLY. ONE OF THE THINGS
I REMEMBER AS OF CALIFORNIA IS
DOING AND OTHER STATES WILL
PROBABLY PURSUE PURSUE THE SAME.
AVENUE.
AND I I AGREE WITH YOU THAT
LEADERSHIP ON THIS ISSUE AND SO
MANY OTHER START FROM THE TOP I
REMEMBER HAVING A CONVERSATION
SOMETIME BACK.
WITH SOMEBODY ABOUT WANTING TO
CHANGE OF POLICY.
IN AN AGENCY AND THE ANSWER THAT
I WAS GIVEN WAS AS SOON AS IT
BECOMES POLICY WILL DO IT.
SO WHEN THE GOVERNOR DECIDES
THAT.
HE OR MAYBE SOMEDAY SHE WANTS TO
PURSUE A PARTICULAR AVENUE.
PEOPLE JUST LINE UP.
AND THAT'S THE WAY IT WILL
HAPPEN AND THAT'S WHY IT'S
IMPORTANT WITH LEGISLATIVE
EFFORTS WORKING IN CONJUNCTION
WITH THE GOVERNOR. TO SEE WHAT
IT IS THAT NEEDS TO BE PUT IN
PLACE THAT THIS GOVERNOR CAN
SUPPORT IN ORDER FOR IT TO
BECOME POLICY.
AND NOT JUST A CONVERSATION --
MAN MAN. ONE SO WE'VE HEARD
ABOUT SMART CITIES AND WE'VE
HEARD ABOUT -- CHINA'S
PREEMINENCE IN THIS IN THIS THIS
FIELD IN THIS DEVELOPING FIELD --
WE SIT.
CHAIRMAN I SAID ON JUDICIARY AND
WE DEAL HEAVILY AND PRIVACY.
ARE RELATED ISSUES SPECIALLY
DURING THIS SESSION.
DO YOU THINK THAT.
AS WE TRIED -- RATING BACK THE
FLOW OF INFORMATION FROM THOSE
WHO GATHERED AND BROKER IT.
THAT THAT WILL PUT HARD.
TACK OPERATIVES AT A
DISADVANTAGE COMPARED TO THE
SHEER VOLUME.
THAT CHINA HAS TO BRING INTO ITS
SYSTEM IN LEARNING AND PREDICT
HUMAN BEHAVIOR.
YEAH WELL YOU KNOW ONE OF THE
ADVANTAGES OF CHINA HAS IS YOU
KNOW.
THEY'VE GOT A PRESIDENT FOR LIFE.
IT IS TERRIBLY CONVENIENT WELL.
JUST JUST.
IF YOU'RE.
YOU SHOULD SEE IT IF WE'RE
TALKING ABOUT THE GOVERNOR
CALIFORNIA DECIDING.
THAT HE WANTS SOMETHING TO BE
POLICY THAN THINGS LINE UP.
IMAGINE THAT ON STEROIDS IN
CHINA BECAUSE QUITE FRANKLY MANY
MANY YEARS AGO THEY RECOGNIZED.
THAT THEY WERE GOING TO HAVE TO
COMPETE IN A DIFFERENT WAY.
ARM AND EMBRACED ARTIFICIAL
INTELLIGENCE -- AND COMPUTER
SCIENCES AND ALL THE REST I'M
REMINDED.
OF OF A STORY.
THERE WAS A A CHINESE AVERELL.
WHO -- EXPLORED THE WORLD I MEAN
INCREDIBLE NAVY'S LARGER THAN
ANY NAVIES THAT EVER EXISTED AT
THAT TIME -- BUT THEN LEADERSHIP
CHANGE IN CHINA.
AND THAT DYNASTY DESTROYED THE
SHIP'S BURNT THE COAST -- AND
PROHIBIT ANYONE FROM BUILDING
SHIPS LARGER THAN A PARTICULAR
SIZE.
BECAUSE CHINA DECIDED THEN THAT
THEY WERE GOING TO TURN IN WORK.
THAT LASTED FOR HOWEVER LONG IT
LASTED.
BUT IT'S NOT THE CASE ANYMORE
AND HAS BEEN FOR A LONG TIME.
AND SO YOU SEE CHINA ENGAGED IN
PLACES LIKE AFRICA -- MAKING
SIGNIFICANT.
INVESTMENTS IN INFRASTRUCTURE --
WHERE IN FACT THE COLLATERAL IS
THE INFRASTRUCTURE ITSELF SO
THAT IF THE COUNTRY UNABLE TO
MAKE ITS PAYMENT GUESS WHAT THEY
GET A PORT?
SO THEY'RE VERY FORWARD LOOKING
IF IF AMERICA.
IS GO HAS ANY HOPE OF CATCHING
UP.
IT IS GOING TO HAVE TO BE MUCH
MORE ASSERTIVE.
ABOUT PURSUING A AYE HOWEVER.
WHAT MAKES WHAT WE DO HERE IN
THIS COUNTRY?
A LITTLE DIFFERENT IS WE DO HAVE
RESPECT FOR IDEAS OF PRIVACY.
AND SO WHAT WE HEARD DURING OUR
CONVERSATIONS WITH STAKEHOLDERS
OF OUT.
THE PURSUIT OF A I WE NEED TO BE
SENSITIVE TO THE ROLE OF
REGULATION.
IN THROTTLING BACK INNOVATION
[inaudible]
SO THAT [inaudible]
IF.
WE REACT IN A WAY THAT.
IS REFLECTIVE OF ANXIETY AND
FEAR FOR THE TECHNOLOGY.
THEN WE COULD END UP IN A
SITUATION THAT YOU'RE TALKING
ABOUT WHERE THERE'S A
DISINCENTIVE. TO PURSUE THAT
WHICH WE NEED.
WHICH IS A PART OF WHY SOME A
RECOMMENDATION IN THE REPORT IS
AT THE STATE NEEDS TO ACTIVELY.
AND AGGRESSIVELY ENGAGE IN A
PUBLIC EDUCATION AND OUTREACH
PROGRAM. TO ENSURE THAT PEOPLE
UNDERSTAND A I AND ITS BENEFITS
SO THAT WE UNDERSTOOD BECAUSE I
THINK THERE ARE PEOPLE ARE YOU
TALKING ABOUT THE RISKS.
WHEN YOU SEE STORIES ABOUT
FACIAL RECOGNITION IN YOUR
WALKING THE REPORTS AND GUESS
WHAT?
THEY'RE GOING TO PROFILE YOU
THAT MAKES PEOPLE ANXIOUS WHEN
THERE ARE REPORTS THAT HAVE BEEN
PUT OUT.
BY -- CERTAIN -- FOR COMPANIES
THAT EVALUATE IMPACTS OF A AYE
UNEMPLOYMENT AND PREDICTS 60%
LOSSES IN JOBS THAT MAKES PEOPLE
SCARED.
AND THE RESPONSES TO TURN TO YOU.
AND SAY I DON'T WANT.
TO I DON'T WANT TO LOSE MY JOB
BECAUSE A I HAS CHANGED I AM A
TO THE WORKPLACE.
AND YOU'LL GET PRESSURE UNLESS
IT'S HANDLED CORRECTLY TO DO
JUST THAT.
WE WERE VERY.
PLEASED THAT THROUGHOUT THE
PROCESS OF OUR REPORT.
BUT LABOR UNIONS -- BECAUSE
CALIFORNIA SUCH AS SIGNIFICAN
EMPLOYER.
OF OF OF PEOPLE IN OPERATING THE
STATE.
AND WHAT WE HEARD FROM THEM FOR
THE MOST PART WAS.
WE UNDERSTAND IT'S COMING WE
REALIZE ARE GOING TO BE
IMPLICATIONS.
WE NEED TO MAKE SURE THAT
TRAINING IS PUT IN PLACE AS PART
OF THE RESPONSE TO ADOPT.
A LOT BUT THE ANSWER TO YOUR
QUESTION IS.
WE HAVE TO STRIKE A BALANCE AND
THAT'S GOING TO BE THROUGH A
PROCESS OF THE EXERCISE OF
WISDOM.
AND INTELLIGENCE AND INFORMATION
GATHERING.
AND SCIENCE AND DATA AND TALKING
TO STAKEHOLDERS ABOUT HOW DO WE
MAKE PEOPLE FEEL COMFORTABLE
WITH A ON HOW DO WE ENSURE THAT
THEIR PRIVACY PROTECTIONS BUT
HOW DO HOW DO WE NOT.
CREATE A DISINCENTIVE TO
CONTINUE DEVELOPING [inaudible]
WHAT?
THANK YOU -- SOME OF NUMBER NAVA.
EXCELLENT WAY TO KICK OFF ONE
MORE QUESTION IS YOU'D MENTIONED
SEVERAL IS THESE ARE AHEAD OF US
IF YOU WERE TO PICK ONE EXAMPLE
FROM ANY OTHER STATES THAT.
ARE AHEAD OF CALIFORNIA WHAT
WHAT WITH THAT EXAMPLE BE.
WELL MIKE PENCE'S FROM INDIANA
SO LET'S START THERE.
SO INDIANA STATE LEADERS CREATED.
THE FUTURE OF WORK TASK FORCE TO
STUDY NEW TECHNOLOGIES AND
DIVIDES INNOVATIVE WORKFORCE
DEVELOPMENT STRATEGIES TO DRIVE
ECONOMIC GROWTH AND PRODUCTIVITY
[inaudible]
SO.
THEY UNDERSTAND THAT YOU'RE
GOING TO BE APPLYING A AYE BUT
THEY ALSO UNDERSTAND THAT IF YOU.
THAT THEIR OPPORTUNITIES HERE.
I THINK INITIALLY.
AND I'M SORT OF A ROUND ABOUT
WAY ISSUE QUESTIONER NUMBER
STATE BUT INITIALLY -- WHAT
HAPPENED [inaudible]
IS.
THERE WERE SOME PEOPLE IN THE A
COMMUNITY THAT WERE A LITTLE
OVER ENTHUSIASTIC.
AND TALKING ABOUT HOW.
THE ROBOTS RIGHT WE'RE GOING TO
END UP DOING ALL THESE DIFFERENT
THINGS AND SCARED AND SCARE
PEOPLE TO DEATH.
THAT PERSPECTIVE IS CHANGE.
IN IN IN IN A COUPLE WAYS NOW I
SEE THEM CALLED CALL BOX.
THERE WILL BE THE APPLICATION OF
ARTIFICIAL INTELLIGENCE THAT
WILL WORK COOPERATIVELY WITH.
THE EMPLOYEE. TO GET THE TASK
DONE SO THAT A AYE IS DOING THE
REPETITIVE SORT OF MINDLESS.
NUMBING KINDS OF THINGS THAT
WILL FREE UP THE EMPLOYEE TO USE
CREATIVITY AND INGENUITY -- AND
AND THEIR OWN ABILITY TO HELP
PROBLEMS ALL.
SO THEY TALK ABOUT WORKING IN
COOPERATION -- YOU LOOK AT AN
APPLICATION FOR EXAMPLE IN
AGRICULTURE.
SO THEY AYE IN AGRICULTURE CAN
HELP WITH THE DIMINISH THE USE
OF PESTICIDES BY THE VERY
PRECISELY ADMINISTERING WHAT
NEEDS TO BE DONE BASED ON
CONDITIONS THAT ARE.
OBSERVED ON THE GROUND SO IN THE
END IS A GOOD PLACE.
MASSACHUSETTS HAS ESTABLISHED A
COMMISSION ON DIGITAL INNOVATION
AND LIFELONG LEARNING.
THAT'S ANOTHER ASPECT OF THIS
THAT.
THE CAN BE VERY BENEFICIAL
BECAUSE YOU HAVE OLDER.
OF FOLKS I MEAN I REMEMBER.
I'M ALL OKAY I'M SEVENTY ONE
YEARS OLD AND I REMEMBER GROWING
UP THE DREAM WAS TO GET A JOB
AND YOU'RE THERE FOR TWENTY
TWENTY FIVE YEARS.
GET YOUR PENSION RETIRE EAGLE
FISH OR WHATEVER IT IS YOU LIKE
TO DO.
BUT THEN I HAD A FRIEND TELL ME
THE OTHER DAY NO NO NO THE
FUTURE SIX TEN NINETY NINES.
PEOPLE ARE GONNA BE HAVING ON A
LOT OF DIFFERENT JOBS OVER THE
COURSE OF A LIFETIME MINUTES
COMING TRUE.
A FEW PEOPLE HAVE LIFETIME JOBS
ANYMORE.
SO HEY I IS GOING TO PLAY AN
IMPORTANT ROLE IF IT'S APPLIED.
CORRECT. TO HELP ENSURE THAT YOU
DON'T LOSE THE EXPERIENCE OF
THOSE THAT HAVE BEEN WORKING.
AND THAT THEY CAN CONTINUE TO
GROW AND DEVELOP AND AND MAKE A
CONTRIBUTION.
THE NOTION OF WORK IS GOING TO
CHANGE.
OVER TIME BECAUSE OF A I WHAT IT
IS THAT WE ARE YOU KNOW I WORK
FOR A WHILE IN A STEEL MILL.
YOU CAN'T HAVE ANYTHING MORE
MACHO THAN THAT RIGHT.
THERE'S LIKE METAL FLYING ALL
OVER THE PLACE IF YOU'RE IN THE
WRONG PLACE AT THE WRONG TIME TO
GET BURNED IN YOUR SEAT AFTER-YOU GET THE MOVE STUFF.
THAT WAS GREAT.
BUT THAT'LL CHANGE AND IT HAS
CHANGED.
INTO WHERE YOU JUST PUSH THE
BUTTON AND THOSE SYSTEMS
CONTINUE TO GO.
I READ A BOOK.
AND THIS AUTHORS PERSPECTIVE WAS.
THIS A AYE REVOLUTION IS
DIFFERENT FROM AUTOMATION.
IN THE AUTOMATION.
WE CREATED MACHINES THAT WOULD
DO THE WORK THAT PEOPLE WERE
DOING.
RIGHT BUT A HIGH IS DOING THE
THINKING.
THAT IS IT THAT IS A DRAMATIC
SHIFT.
AND IT'S NOT.
VIED FOR MEMBERS OPPORTUNITIES
FOR US
AND IT ALSO CARRIES WITH IT
RISKS.
AND I DO THINK THAT THE THE ROLE
OF THE LEGISLATURE AND OTHER
POLICY MAKERS LIKE YOURSELVES.
IS IN EXPLORING THOUGH SO THAT
WE UNDERSTAND IT WELL.
AND KNOW HOW TO COMMUNICATE IT
TO OTHERS TO HELP.
MAKE THEM FEEL BETTER ABOUT THE
CHANGES ARE COMING.
THANK YOU KNOW -- THERE ARE NO
OTHER QUESTIONS WILL EXCUSE YOU
LOOK FORWARD TO WORKING WITH YOU.
NOT WHAT WHAT WE'RE OVER THERE
AND I WANTED MONEY GIVE.
THANKS -- TO MY STAFF.
WITH A NONE OF THIS WOULD HAVE
BEEN POSSIBLE WITHOUT THE WORK
BY STAFF COMMUNICATING WITH ALL
OF THE PEOPLE AND THE PHONE TWO
DOCTOR WHO DO COME TO TESTIFY
BEFORE THE LITTLE HOOVER -- DO
ON OUR OWN DONE.
WE CAN'T COMPEL THEM TO TESTIFY --
AND THEY OFFERED THE BEST
INFORMATION THEY HAVE AND WE'RE
VERY PLEASED TO BE ON THE SHOW.
THANK YOU THANK YOU.
THANK YOU -- I WE ALSO WELCOME --
CENTERED RUSSELL.
THANK YOU SENATOR RUSSELL.
WHAT WE'LL DO IS LET'S LET'S
CALL THE ROLL HERE -- CHAIR
NUMBER HERE [inaudible]
SENATOR BORDERS.
SENATOR CHIANG.
SENATOR RAZA.
YES SENATOR STERN.
SENATOR WINNER.
WE HAVE A QUORUM THANK YOU --
NEXT UP WE HAVE A DOCTOR OF SOME
YEARS SAYING DOCTOR.
PROFESSOR OF COMPUTER SCIENCE AT
THE UNIVERSITY OF CALIFORNIA.
IRVINE -- WORKS ON LARGE SCALE
INTERVAL.
MACHINE LEARNING APPLIED
INFORMATION EXTRACTION AND
NATURAL LANGUAGE PROCESSING --
I'M I'M SURE WILL UNDERSTAND
THAT SO -- BEFORE YOU SEE AYE.
DOCTOR SAYING WAS A POSTDOCTORAL
RESEARCH ASSOCIATE AT THE
UNIVERSITY OF WASHINGTON HE
RECEIVED HIS PHD FROM UNIVERSITY
MASSACHUSETTS AMHERST.
TWO THOUSAND FOURTEEN UNDER THE
SUPERVISION OF ANDREW MCCOLLUM
DURING WHICH HE ALSO INTERNED AT
MICROSOFT.
RESEARCH GOOGLE RESEARCH AND
YAHOO LABS.
HE WAS AWARDED THE ADOBE
RESEARCH DATA SCIENCE FACULTY
AWARD WAS SELECTED AS A STAR
PART RISER. ONE THE GRAND PRIZE
IN THE YELP DATA SAID CHALLENGE
AND RECEIVE THE YAHOO KEY
SCIENTIFIC CHALLENGE AWARD.
A DOCTOR SINGLE GIVE US A
GENERAL OVERVIEW OF A AYE -- IN
TALK ABOUT MULTIPLE WAYS TO
REDUCE BIAS IN A AYE INCLUDING
INCREASING DIVERSITY.
IN A AYE TECHNOLOGIES THE
IMPORTANCE OF DATA LABELING
COLLECTION.
INSURING LESS BIAS IN INPUT DATA
AND UTILIZING MACHINE LEARNING
TO CHECK A EYES OUTPUT. FOR BY
SEIZE -- DOCTOR SAYING LOOK THE
FLOOR IS YOURS MAYBE START BY
TELLING US WHAT A DARK ARISE OR
IS.
THAT WAS JUST SOMETHING THAT ARE
PRO WAS LOOKING OUT FOR YOUNG
SCIENTISTS TO SORT OF LOOK AT AS
FUTURE.
PEOPLE WHO.
ARE USED TO REMEMBER WHAT DARPA
STOOD FOR WHAT DOES IT STAND FOR
DEFENDS IN BONDS RESEARCH.
BEING ADMINISTRATION STANDS FOR
DARPA YEAH THEY WON'T BE HAPPY
THAT I DON'T KNOW WHAT.
OKAY ALL RIGHT ALL RIGHT WELL
SORRY FOR THAT -- ALL RIGHT --
DOCTOR SAYING THAT THE FLOOR IS
YOURS.
THANK YOU YEAH SO I'M GOING TO
GIVE A OVERVIEW OFF A I TRIED TO
KEEP IT PRETTY ON NON TECHNICAL --
AND THEN I'LL ENTERTAIN
QUESTIONS AT THE END.
SO JUST THINKING ABOUT WHAT A
AYE IS VERY BROADLY SPEAKING
IT'S DEFINED AS ANY SOFTWARE --
THAT IS ABLE TO CARRY OUT
COGNITIVE DOS.
SAMPLES OF COGNITIVE TASKS
INCLUDE THINGS LIKE DRIVING ON
TRANSLATING LANGUAGES ANSWERING
QUESTIONS ABOUT THE WORLD --
BEING ABLE TO DIAGNOSE DISEASE.
OF PLAYING GAMES UNDERSTANDING
SPEECH THESE ARE ALL SORT OF
HIGHER LEVEL COGNITIVE COSTS AND
IF A SOFTWARE.
THAT'S ARTIFICIAL INTELLIGENCE --
UNFORTUNATELY THE STIFF
DEFINITIONS START REALLY USEFUL
IT'S NOT VERY PRECISE PARTLY
BECAUSE PEOPLE DON'T TEND TO
AGREE WITH WHAT THE COGNITIVE
COSTS ARE.
AND THERE IS THIS AND THIS
NOTION KNOWN AS A AYE EFFECT.
WHERE IF A COMPUTER CAN DO IT WE
DON'T THINK OF IT AS AN
INTELLIGENT ASK ANYMORE -- AND
SO THE DEFINITION OF A I SORT OF
CHANGES AS WE GET BETTER AT
DOING A AYE -- SO INSTEAD WHAT'S
MUCH MORE USEFUL IS TO THINK
ABOUT WHY A AYE IS CURRENTLY.
ON TRANSFORMING SOCIETY AND IT'S
IT'S REALLY IN THE CENTER FOR
YOU -- AND THAT IS TO LOOK AT
MACHINE LEARNING THIS IS OF THIS
IS WHAT MAJORITY OF AA LOOKS
LIKE RIGHT NOW YOU MIGHT HAVE
HEARD OF MACHINE LEARNING ALMOST
INTERCHANGEABLY BUT THEY I AND
THE IDEA HERE IS THAT.
MACHINE LEARNING IS TRYING TO
CREATE SOFTWARE -- THAT LOANS TO
WHAT TO DO FROM EXAMPLES.
IN OTHER WORDS IT'S TRYING TO
IMPROVE AUTOMATICALLY WITH
EXPERIENCE.
AND IF IT IMPROVES TO THE EXTENT
THAT IT CAN DO THE INTELLIGENT
COGNITIVE PROCESS.
THEN -- YOU HAVE IN A A SOFTWARE.
SO JUST TO BE MORE PRECISE LET'S
STICK OR EXAMPLE.
SUPPOSE YOU NEED SOME SOFTWARE
THAT CAN TAKE ONE FOR DOLE --
AND TELL YOU WHETHER THAT. FOR
TO OFTEN ANIMAL IS A WOLF OR A
HUSKY ON HUSKIES A BREED OF DOG
THAT LOOKS A LOT LIKE A WOLF --
AND SO THE IDEA IS THAT IF YOU
GIVE THE FIRST IMAGE TO THE
SOFTWARE IT SHOULD BE ABLE TO
TELL YOU ABOUT THE WORLD BECAUSE
IT IS.
AND IF YOU GIVE IT A SECOND
IMAGE IT SHOULD BE ABLE TO TELL
YOU THAT'S A HUSKY.
I SAID TO GIVE YOU SOME IN
TUITION FOR HALL OF THE SOFTWARE
IS SORT OF LOOKED.
THE WAY THE MACHINE LEARNING
BOOKS.
IS YOU HAVE THE STEP OF TRAINING
AND AND SO WHAT YOU WOULD DO
HERE IS YOU WOULD COLLECT A LOT
OF EXAMPLES OF FOUR DOORS OF
WHEELS.
ANOTHER SET OF EXAMPLES OF
PHOTOS OF HUSKIES AND YOU WOULD
USE THEM TO TRAIN YOUR SOFTWARE --
SO THE SOFTWARE WOULD LOOK AT
ALL OF THESE EXAMPLES.
AND IT'LL.
FROM THESE EXAMPLES LOW AND WHAT
MAKES A WILL FOR WOLF AND WHAT
MAKES A HUSKY A HUSKY.
AND STORE SOME REPRESENTATION OF
THIS KNOWLEDGE INTERNALLY.
AND THEN WHEN YOU ACTUALLY WANT
TO USE IT -- YOU BASICALLY ALSO
GET TO GUESS ON NEW IMAGES.
SO ONCE THE SOFTWARE IS TRAINED
YOU GIVE IT A NEW FOR DON'T --
AND THE SOFTWARE WILL USE WHAT
IT HAS SEEN ALL YEAR TO MAKE A
GUESS.
IF IT SUCCESSFULLY TRAINED THEN
IT WILL GET IT -- RIGHT MORE
OFTEN THAN IT WILL NOT AND IF
YOU GET A DATE.
ALMOST 100% IF IT'S REALLY
REALLY GOOD.
SO IN THIS EXAMPLE THAT I'VE
BEEN TALKING ABOUT THESE ARE SIX
FOUR DOES THAT IT HAS NEVER SEEN
BEFORE -- AND THE SOFTWARE THAT
WE TRAINED.
GETS A GRADE FIVE OF THE SIX
TIMES -- WHICH IS QUITE
IMPRESSIVE IT'S ACTUALLY -- YOU
MIGHT SAY THAT AS LOAN HOLDEN
FRIEND SHARED BETWEEN WILSON
HUSKY THAT CASE IT'S A DOING A
BETTER JOB THAN I WOULD SO.
THAT'S THAT'S SOMETHING.
ARM AND SO LET'S THINK A LITTLE
BIT BROADLY ABOUT WHAT THE
MACHINE LEARNING ACTUALLY IS --
AND SO THE IDEA WITH MACHINE
LEARNING IS THAT WHATEVER
PROBLEM YOU'RE INTERESTED IN YOU
SORT OF SPLIT IT INTO WHAT IS
GOING TO BE THE INPUT TO YOUR
SYSTEM.
AND WHAT IS GOING TO BE THE
OUTPUT -- AND YOU FIRST GATHERED
BEARS OF INPUT AND OUTPUT THAT
YOU USED TO TRAIN YOUR MACHINE
LEARNING ALGORITHMS -- AND
MACHINE LEARNING ARE GOOD THEM
ONCE IT STRAINED IT GIVES YOU
THE SOFTWARE -- THAT WILL TAKE
NEW IN BOTH STUDIED HASN'T SEEN
BEFORE.
AND TRY TO GUESS WHAT THE OUTPUT
WITH -- THREE SO LET'S LOOK AT A
FEW EXAMPLES SO IF YOU WANT TO
CREATE A MACHINE LEARNING
SOFTWARE THAT CAN PREDICT
WHETHER LOAN SHOULD BE GRANTED
OR NOT.
THE INPUT HERE WOULD BE THE
DETAILS OF THE LOAN APPLICATION
EVERYTHING THAT WOULD OTHERWISE
GO IN THE LOAN APPLICATION.
AND THE OUTPUT WILL BE WHETHER
THE LOAN.
WILL BE SUCCESSFUL OR NOT IF
GRANTED.
AND WHAT YOU WOULD DO IS YOU
WOULD USE BOSS DATA TO COLLECT --
SUCH EXAMPLES AND USE THAT TO
TRAIN YOUR MACHINE LEARNING
ALGORITHMS SO IN BOSTON.
YOU GROUND SOME LOANS AND THE
PERSON I DID NOT WANT TO PAY IT
BACK.
THAT'S A BAD APPLICATION ARE BAD
LOAN APPLICATION.
IF YOU WANT TO DIAGNOSE DISEASES
WHAT YOU WOULD DO IS YOUR INPUT
WOULD BE ALL OF THE PATIENTS
SYMPTOMS THAT'S NUMBER TWO THERE.
AND YOUR OUTPUT WOULD BE THE
DISEASE THAT THE PATIENT HAS AND
FOR TRAINING PURPOSES YOU WOULD
GATHER DATA BY HAVING A DOCTOR
DECIDE WITH THE DISEASE SHOULD
BE.
OUR AND SORT OF USING THAT DRAIN
YOUR SOFTWARE.
FINALLY THIS TAKE ANOTHER
EXAMPLE OF CONSOLATION WHERE.
YOU WANT TO TRANSLATE FROM
ENGLISH TO SPANISH FOR EXAMPLE
YOU MIGHT DO THAT ON GOOGLE
TRANSLATE.
THE INPUT HERE WOULD BE A
ENGLISH SENTENCE.
AND THE OUTPUT HERE IS GOING TO
BE A SPINE IF AND BANDS AND SO
AGAIN TO TRAIN AND YOU RIGHT TO
THE SPANISH SENTENCE -- BY A
TRANSLATOR AND GIVE THAT AS AN
EXAMPLE TO THE SOFTWARE.
AND SO ONCE THIS TRAINING IS
FINISHED YOU GET A SOFTWARE
WHICH CAN TAKE ANY NEW INPUT.
AND PREDICT WHAT ABOUT WHAT
WOULD BE SO SHOULD BE ABLE TO
TAKE.
A NEW PATIENT IN ALL OF ITS
SYMPTOMS AND IT CAN PREDICT WHAT
THE DISEASE THE PATIENT HOUSE.
OF WITHOUT THE NEED OF A DOCTOR
AT THAT POINT.
I TO BE ABLE TO TAKE A ENGLISH
SENTENCE AND GIVE YOU THE FINEST
SENTENCE WITHOUT THE NEED OF A
TRANSIT.
SO ONE OF THE MAJOR QUESTIONS AS
WELL WHY DOES IT WORK AND HOW IS
IT ABLE -- TO WISE MACHINE
LEARNING SO SO PREVALENT.
AND HEAR A SORT OF THE TWO
PRIMARY REASONS.
OF WHICH COMBINED TOGETHER TO
MAKE MACHINE LEARNING WORKED THE
WAY IT DOES SAY NOW.
THE FIRST IS THAT A WHOLE LOT OF
EXAMPLES ARE AVAILABLE -- TO
TRAIN SOFT RIGHT NOW THIS IS
MOSTLY WITH THE BIG DATA LUCIEN
BUT STORAGE COMPETITION BEING J.
CHEAP WITH PROFIT PERFORATION OF
INTERNET WE JUST HAVE A LOT OF
EXAMPLES.
PRETTY MUCH ANY DOS THAT -- THAT
ARE AVAILABLE TO TRAIN MACHINE
LEARNING ALGORITHMS -- TO
ANYBODY WHO STORING ANY KIND OF
DATA CAN POTENTIALLY USE IT AS A
WAY TO TRAIN MACHINE RUNNING ON
THE SECOND PART OF THIS WHOLE.
PROCESS THAT MAKES MACHINE
LEARNING -- SO PREVALENT IS THAT
THERE IS A LOT OF COMPLEX MATH
AND COMPETITION THAT'S INVOLVED.
AND ASK COMPUTING BECOMES
CHEAPER -- THE SOFTWARE
INTERNALLY KEEPS BECOMING MORE
AND MORE COMPLEX AND IT'S ABLE
TO SUPPORT MORE COMPLEX.
OPERATIONS.
I'M THIS COMBINATION OF LOTS OF
EXAMPLES AND LOT OF COMPETITION
IS ACTUALLY QUITE AMAZING IF YOU
HAVE ENOUGH DATA AND IF YOU HAVE
ENOUGH COMPETITION -- THE GUESS
IS THAT THEY ARE MADE BY THIS
MACHINE LEARNING ALGORITHMS CAN
BE ARBITRARILY GOOD.
SO YOU KNOW IN MANY CASES YOU
MAY NOT HAVE AN UPDATE OR
COMPETITION BUT IF YOU DO -- SO
SKY'S THE LIMIT [inaudible]
BEYOND [inaudible]
SO ARM.
I DO WANT TO GIVE A CABBIE OUT
AND TALK A LITTLE BIT.
ABOUT THIS -- IT'S NOT ALL JUST
GOOD NEWS -- THE THE TING THAT
HAPPENS WITH MACHINE LEARNING IS
THAT IT'S TRYING TO MATCH THE
OLD PORT THE BEST IT CAN --
WHICH IS IN SOME SENSE MANY
DIFFERENT FROM AN INTELLIGENT
BEHAVIOR.
WHAT MACHINE LEARNING IS REALLY
GOOD AT IS MIMICKING INTELLIGENT
BEHAVIOR? TO THE EXTENT THAT IT
CAN.
GET THE ANSWER RIGHT BUT THE
REASONING PROCESS MAY NOT BE THE
SAME AS WHAT WE WOULD DO.
OTHERS ALSO GOING TO DO THE
SECOND GABBY ART -- WHICH IS
THAT IN MOST CASES THE
UNDERLYING REASONING OFF THE
SOFTWARE HOW IT CAME TO MAKE A
DECISION.
IS SOMETHING THAT IS NOT
AVAILABLE -- IN ANY JUDITH FORM
OR IN ANY ACCESSIBLE FORM THAT
WE CAN EASILY GRADY AND OF IT --
AND SO.
THAT SORT OF CAUSES A LITTLE BIT
OF A CONCEPT.
AND THE COMBINATION OF THESE TWO
MEANS THAT SOMETIMES MACHINE
LEARNING ALGORITHMS THAT I WOULD
SAY OFTEN MACHINE LEARNING
ALGORITHMS.
END UP CHEATING IN REYES THAT
ARE NOT VERY OBVIOUS SO I GAVE
YOU -- THIS WILL FOR AND HUSKY
EXAMPLE IF IT DON'T DO IT.
OF RETARDED LOOKED QUITE
INTELLIGENT -- BUT ACTUALLY WHAT
WAS HAPPENING AND I DIDN'T TELL
YOU THIS.
WAS THE FACT THAT IT WAS
PRIMARILY DETECTING SNOWFALL IN
THE IMAGE.
SO ALL THIS OFFER WAS DOING WAS
LOOKING FOR WHITE STUFF ON THE
GROUND WHICH IS ACTUALLY PRETTY
EASY TO DO.
AND IF IT SAW WHITE STUFF ON THE
GROUND IT PREDICTED WOLF AND IF
IT DID NOT.
A PREDICTED HUSKY.
AND THAT WOULD ALSO EXPLAIN THE
MISTAKE IT MAKES WHEN IT HAPPENS.
ARMED.
WITH IN A SNOWY ENVIRONMENT.
BUT FOR THE STARS.
CLEARLY THIS IS NOT INTENDED
BEHAVIOR THIS IS NOT AS
INTELLIGENT BEHAVIOR.
BUT IN JUST IN TERMS OF NUMBER
OF GUESSES THAT BOOK CORRECT IT
CAUGHT -- REALLY REALLY HIGH ON
THE HIGH SCORE.
AND SO IF YOU COULD GET IT.
TO EXPLAIN WHY IT WAS MAKING
THESE DECISIONS YOU WOULD BE
ABLE TO SPOT BUT THIS IS AN
ERROR BUT THAT'S NOT SOMETHING
THAT'S EASILY SUPPORTED IN
MACHINE LEARNING AS WE KNOW
[inaudible]
SO.
JUST TO SOME REYES -- THE TALKS
SO FAR.
WE HAVE DEFINED A A AS ANY
SOFTWARE THAT CAN CARRY OUT
INTELLIGENT COGNITIVE LEE --
HEAVY DAS OF AND THE MOST
PROMINENT APPROACH FOR ARE IS
THIS IDEA OF MACHINE LEARNING.
WHERE YOU JUST CREATE SOFTWARE
THAT LOANS FROM EXPEDIENCE THOSE
COMPLEX MOUNTAIN WALLS
COMPETITION INVOLVED?
BUT THERE IS ALSO THIS ASPECT OF
EXPEDIENCE WHICH IS PURELY --
GIVEN BY THE DATA YOU GIVE TO
SYSTEM AND THE MORE EXAMPLES YOU
GIVE THE MORE.
ACCURATE IT GETS OF THE BETTER
IT GETS AND THE MORE INTELLIGENT
ITS ITS BEHAVIOR LOOKS.
AND THEN THERE IS THE
SIGNIFICANT EVERY OTHER TO
DESTROYING TO MIMIC INTELLIGENCE
THE BEST IT CAN.
SINCE IT IS LEARNING FROM THE
DATE OF THAT THAT THIS -- BEING
PROVIDED.
IT CAPTURES ALL THE PATTERNS
THAT ARE IN THE DATA.
THAT'S BOTH A POSITIVE AND A
NEGATIVE ASPECT AS WE SAW IN THE
WILL FOSSE CASE IT IS CAPTURING
SOME SPOT ON BUT THAT'S NOT WHAT
WE ALL WANT TO DO -- AND THE
CONCERN IS THAT IN IN MOST REAL
APPLICATIONS THERE'S ALWAYS
UNDECIDABLE BY TONS AND THE DATE
ARE -- THAT ARE BY A SEIZE THAT
ARE PRESENT BECAUSE OF MISTAKES
OF BECAUSE OF THE WAY SOCIETY'S
DOCTOR RIGHT NOW.
AND MACHINE LEARNING BY PICKING
UP ON THESE SORT OF REINFORCES
THE SAME.
PRICES AND ITS OUTPUT AS WELL.
SO THIS IS A VERY IMPORTANT
THING TO KEEP IN MIND AS WE
THINK ABOUT MACHINE LEARNING.
THAT'S ABOUT HALF FULL THANK YOU
THANK YOU DOCTOR ZING THANK YOU
FOR COMING TO VISIT WITH US A
COUPLE THINGS.
ONE IS OUR COLLECTIVE
RESPONSIBILITY AS LEGISLATORS IS
TO IMPROVE THE QUALITY OF LIFE
OF CALIFORNIANS ARE AT LEAST TO
PROTECT THE QUALITY OF LIFE IS
THAT EXISTS -- AND SO WITH
RESPECT TO ARTIFICIAL
INTELLIGENCE YOU'VE -- DEDICATED
YOUR YOUR LIFE TO THE
DEVELOPMENT AND EXPLORATION. TWO
QUESTIONS ONE WHAT ARE YOU MOST
EXCITED ABOUT TERMS OF IMPROVING
THE QUALITY OF LIFE CALIFORNIANS
AND THEN THE SECOND QUESTION IS
WHAT ARE YOU MOST CONCERNED
ABOUT -- SO LET ME START WITH
THE CONCERNED ABOUT ASPECT SO --
I THINK THERE ARE A LOT OF
POSITIVE RESULTS OF MACHINE
LEARNING THAT SEEM PROMISING AND
TRANSFORMATIVE. FOR MANY
DIFFERENT AREAS OF BUT THE
CABBIE OUT CERTAIN AREN'T READY
RATHER UNDERSTOOD I THINK IT'S
SOMETHING THAT.
THE PEOPLE WHO ARE VERY CLOSE TO
THE ALGORITHMS PROBABLY
APPRECIATE BUT EVEN ONE STEP
REMOVED IT'S DIFFICULT -- TO
MAKE THAT DIVISION AND SO IF YOU.
DON'T DO A GRADUAL OR INFORMED
DOLE OUT OF MACHINE LEARNING A
FOR ANY APPLICATION -- THAT ARE
SORT OF OF THE CAN BE SIDE
EFFECTS THAT YOU DON'T REALIZE
SO -- WHETHER IT'S EIGHT IT
MIGHT LOOK LIKE A NOT ALREADY
HIGH STATE APPLICATION BUT IF
THAT OUR BIASES THERE THEY GET
REINFORCED IN WAYS THAT -- WE
DON'T QUITE UNDERSTAND RIGHT NOW
SO.
YOU KNOW PEOPLE USED TO THINK OF
LOS STEAK PAYING WELL YOU CAN
ALWAYS READ THE NEWS YOU WANT TO
READ SO WHY DOES.
RECOMMENDING USE MATTER SO MUCH
BUT WE'VE SEEN -- IN THE BUS
THAT WHAT PEOPLE REGIONALLY
INFORMS THEIR DECISIONS WHEN
THEY GO TO THE ELECTION -- AND
SO.
IF THERE ARE BIASES IN MACHINE
LEARNING ALGORITHM THEY CAN GET
AFFECTED IN WAYS THAT WE DON'T
UNDERSTAND YET SO -- DID THE
CAVEAT IS FOR THE ALLOWED TO BE
INFORMED AND GRADUATE TO SOME
DEGREE -- IN TERMS OF WHAT I'M
MOST EXCITED ABOUT -- MY
RESEARCH IS.
PRIMARILY FOCUSED ON BEING ABLE.
TO READ AND UNDERSTAND TEXT --
AND SO.
NG ABLE TO INGEST A LOT OF TEXT
AND BEING ABLE TO OUR ANSWER ANY
QUESTION ABOUT IT BEING ABLE TO
EXTRACT INFORMATION ABOUT IT.
AND EFFECTIVELY BEING ABLE -- TO
DO INFERENCES AND REASONING OVER
LARGE COLLECTION OF TEXT WITHOUT
REQUIRING YOU TO ACTUALLY READ
IT -- THAT THAT'S SOMETHING THAT
CAN TRANSFORM RADIUS FOR YOUTH
AND THAT'S THAT'S KIND OF WHAT
I'M MOST EXCITED [inaudible]
THANK YOU [inaudible]
SIR BORDERS [inaudible]
THANK CHAIRMAN.
LOOK AT YOUR YOUR SLIDE THERE
AND IT SAYS.
ON THE THIRD BULLET -- RATHER
THE THE SECOND.
ONE THE MORE EXAMPLES YOU GIVE
THE BETTER A CAT'S.
SO MY QUESTION TO YOU IS ARE WE
IN A SITUATION STILL OR IS IT
CHANGING DRAMATICALLY WHERE.
INPUT.
IS -- BY DESIGN AS OPPOSED TO
THE MACHINE'S ABILITY OR THE
PLATFORM SOFTWARE'S ABILITY. TO
ACCESS -- WORLD PLATFORMS IN
INFORMATION -- NETWORKS ON ITS
OWN. TO CREATE ITS OWN INPUT.
OKAY -- YEAH SO WE ARE NOT IN
THE SECOND STAGE AT ALL -- SO
THE QUALITY OF WHAT WE HAVE
RIGHT NOW IS.
IN THE UNIVERSE FROM WHICH IT
WILL.
ANALYZE THE INFORMATION IN AND
PRODUCE AN OUTCOME YES.
YES AND I THINK THAT'S A VERY
IMPORTANT STEP -- IT MADE ME
THINK ABOUT REGULATION AND
THINGS THAT I DIDN'T KNOW WHAT
IS WHAT SET OF EXAMPLES IS BEING
GIVEN TO THE MACHINE LEARNING
ALGORITHM.
WE SHOULD BE WELL AWARE OF FOR
IT AND THAT SHOULD BE SOMETHING
THAT IS.
WHAT WE CONTROL SO IF WE'RE
LOOKING AT?
OTHER PARTS OF THE WORLD -- WITH.
SMART CITIES FOR EXAMPLE.
AND CREATING OUT OF NOTHING --
ENVIRONMENTS CONTROLLED
ENVIRONMENTS WHERE AUTOMOBILES
CAN BE STUDIED -- THE
ENVIRONMENT -- IS RESTRAINED FOR
MAXIMUM LEARNING -- SO WANTED SO
FORTH.
THAT IS IS THAT WOULD YOU SAY
THAT IS JUST SIMPLY A TEMPLATE
FOR LEARNING THAT AT SOME POINT
IT WILL GRADUATE BEYOND.
THAT INPUT PHASE THAT MANUAL
INPUT PHASE INTO ITS OWN
CAPACITY TO REACH OUT INTO --
THE INFORMATION NETWORKS.
SO ON THE REACHING OUT INTO
INFORMATION NETWORKS -- FIRST AS
A QUESTION OFF DO WE FEEL THAT
THAT'S FEATURED THAT IS
BENEFICIAL AT ALL FOR MACHINE
LEARNING ALGORITHMS TO HALF THE
PURELY PRAGMATICALLY.
IS THIS SOMETHING THAT.
LAKE.
IT WOULD BE READING THAT MACHINE
LEARNING ALGORITHMS WOULD BE
BETTER AT IF THEY WERE TO DO
THAT OR NOT AND SO THAT'S ONE
QUESTION.
THE SECOND QUESTION IS WHETHER --
THE EFFORT OFF US BEING THE
GATEKEEPERS TO WHAT DATA IT HAS
ACCESS TO IS SOMETHING THAT'S
PROHIBITIVE IN TERMS OF COST AND
SO FAR THAT'S NOT THE PROBLEM
THE PROBLEM IS IT'S NOT THAT IS
NOT A PROBLEM NOW.
SO GET KEEPING OUR HAVING DATA
IN A WAY THAT MACHINE LEARNING
MODELS AND MODELS CAN INGEST IS
NOT THE THE PROHIBITIVE PART OF
THE BY.
SO IN TERMS OF MEDICAL HISTORY.
WE TALKED ABOUT MAKING MEDICAL
HISTORY AVAILABLE.
ONLINE AND PATIENT RIGHT RATHER
THAN IT BEING IN PAPER FORM.
IS THAT AN EXAMPLE THAT THE MORE
YOU CONCENTRATE.
MEDICAL HISTORY.
THEN YOU HAVE A UNIVERSE THAT
CAN CREATE INPUTS.
AND FROM THAT.
ON THAT UNIVERSE -- THEN WE CAN
HAVE A AYE OUTPUTS. FOR
DIAGNOSIS AND STUFF LIKE THAT --
YES SO TO THAT WOULD BE AN
EXAMPLE WHERE YOU WOULD CREATE
THE UNIVERSE THAT THE A LIVES.
THAT DOESN'T MEAN THAT IT SHOULD
STILL HAVE ACCESS TO ANY
INFORMATION NETWORKS OUTSIDE OF
THE THE COLLECTION OF THE
PATIENT HAD TO COURTS.
YEAH RIGHT YEAH AND AND SO SO
FAR THE DATA IS READY.
SORT OF P. FORMATTED WHEN IT'S
GIVEN TO MACHINE LEARNING SYSTEM
THAT ARE SORT OF PIPELINES THAT
SORT OF THE DATA GOES THROUGH.
AND THERE IS VERY LITTLE OKAY IF
ANY THAT OPPORTUNITY GOES OUT TO
THE INTERNET AND TRIES -- TO
PRESS -- TWO DO THINGS WITH IT.
AT THE MOST PROMINENT EXAMPLE I
CAN THINK OFF WHICH IS SOMEWHAT
RELATED IS THIS MICROSOFT THE
EIGHTY CHAD PART WHICH CAME A
COUPLE YEARS AGO.
WHERE WHAT THEY DID WAS IT WAS
JUST A JOB PORTAL OF THING WHICH
IS LIKE A TWITTER ACCOUNT?
THANK YOU CAN CONVERSE WITH.
AND INSTEAD OF JUST CONVERSING
IT HAD THIS MODE OF BEING ABLE
TO LEARN FROM WHAT THE PEOPLE
WERE.
TALKING TO IT AND SO IN THAT
SENSE.
OF PEOPLE'S QUICKLY FIGURED OUT
THAT IF THERE WAS CERTAIN WAYS
THAT YOU TALK TO THE AGENT --
YOU COULD GET IT TO REPRODUCE
WHAT DO YOU SAY.
TO THE THE CHART PART -- AND
THEN CLEARLY WHEN YOU DO THAT ON
THE INTERNET THE JOB BOARD
RESULTED IN SORT OF SORT OF
LANGUAGE THAT MICROSOFT WASN'T
PROUD OFF SPACES.
AND I'M THEY SHUT IT DOWN AND
EVERYTHING SO -- ANY EXPERIENCE
HAS SHOWN THAT IF YOU SORT OF
DON'T CONTROL WHAT DATA CLOSING
THINGS CAN GO HERE FOR A WIRE
PRETTY QUICKLY -- PARTLY BECAUSE
OF THE SORT OF EXAMPLES AND
GIVING YOU EVEN IF YOU DO GIVE
IT CLEAN DATA THAT OUR PATENTS
IT CAN FIND.
OF WHEN YOU LET IT GO OUT ON THE
INTERNET YOU HAVE NO CONTROL
OVER.
WHAT THE HUSKY EXAMPLE?
IF YOU WERE PROGRAM THAT AGAIN
NOW KNOWING THAT YOU SAW THAT IT
PICKED UP ON SNOW.
YOUR NEXT.
YOU KNOW YOU'RE YOU'RE NEXT TO
PIECE OF INTELLIGENCE THAT
YOU'RE GONNA PUT INTO THE SYSTEM.
IS DO NOT LOOK AT EXTERNALITIES.
ONLY LOOK AT THE PRINCIPLE.
THAT IS YES -- BUT THAT'S EASIER
SAID THAN DONE YEAH LIKE MAYBE
WILL TAKE CARE OF THE SNOW BUT
MAYBE TO PICK UP ON SOMETHING
ELSE THAT BE DID IN TWO DAYS
STRAIGHT -- MAYBE TO SOME OTHER
BUTTON AND THE IN THE IMAGE THAT
YOU KNOW MAYBE THOSE SKY COLOR
CODED -- YEAH AND YOU KNOW WHAT
IS PRIMARY WHAT IS BACKED OFF
AND WELL THANK YOU OF TAXING AND
AS SOME OF YOU KNOW -- YOU SEE I
LAW SCHOOLS WORKING WITH US --
IN THE STUDENTS OF THE LAW
SCHOOL ALONG WITH FORMER SENATOR
JOE DONE -- IN TERMS OF CRAFTING
LEGISLATION THAT HAS RELEVANCE
TO ARTIFICIAL INTELLIGENCE AND
WHERE WE GO AS A POLICYMAKERS
HERE.
OF AN EARLIER VERSION OF THE
AGENDA HEAD SENATOR DONE
TESTIFYING SIR FOR THOSE OF YOU
WHO ARE HERE AND LISTENING AND
ARE HERE ONLY BECAUSE YOU WANT
TO HEAR FORMER SENATOR JOE DONE --
I'M SORRY TO DISAPPOINT YOU HE
WON'T BE ABLE TO ATTEND TODAY'S
HEARING.
BUT THANK YOU AND YOU CAN GIVE
OUR REGARDS THE FOLKS AT UCI FOR
THEIR ASSISTANCE.
THANK YOU ALL RIGHT.
IN THE NEXT -- UP WE HAVE DOCTOR
GREEN A CHILD.
DOCTOR CHAO OF LEADS GOOGLE'S
GLOBAL PUBLIC POLICY STRATEGY
FOR EMERGING TECHNOLOGIES WHICH
INCLUDES ARTIFICIAL.
QUANTUM COMPUTER COMPUTING AND
HEALTH FRIDAY GOOGLE DOCTOR
CHARLES SERVED AS A WHITE HOUSE
FELLOW THE OFFICE OF SCIENCE.
AND TECHNOLOGY POLICY WORK HAS
BEEN PUBLISHED IN SEVERAL PEER
REVIEWED JOURNALS AND RECOGNIZE
WITH AWARDS FOR THE NATIONAL
SCIENCE FOUNDATION.
AND THE MATERIALS RESEARCH
SOCIETY.
SHE HOLDS A B. S. IN CHEMISTRY
FROM STANFORD UNIVERSITY AND A
PHD IN NANO TECHNOLOGY FROM UC
BERKELEY.
DR CHARLES GOING TO TELL US
ABOUT SOME OF THE EXCITING
THINGS INDUSTRY LEADERS LEADERS
ARE DOING IN THE FIELD OF
ARTIFICIAL INTELLIGENCE.
SOME OF CHALLENGES FACING A AYE
IN THE INDUSTRY BEHIND IT IN AND
I'LL ASK YOU THE SAME QUESTIONS
I ASKED.
OF DOCTOR SAYING ABOUT AT THE
END ABOUT WHAT YOU MOST EXCITED
ABOUT WHAT YOU'RE MOST CONCERNED
ABOUT IN IN YOU SHOULD BEAR IN
MIND.
OF THAT TO TARGET TO LAWYERS SO
LEASE THAT SUITS HERE IN THE
ROOM RIGHT NOW.
SO THANK YOU VERY MUCH DOCTOR
CHAO WE APPRECIATE YOU BEING
HERE SOUNDS GREAT AND THANKS
MISTER CHAIRMAN SENATOR GLAD TO
BE HERE WITH YOU.
I'M GONNA TALK A LITTLE BIT
TODAY ABOUT A AYE AYE FROM A
GOOGLE PERSPECTIVE HOW WE'VE
BEEN LOOKING AT IT FROM THE
COMPANY.
I'M DOCTOR SEEING WENT OVER A
LOT OF THE ORIGINAL AND KIND OF
THE BASICS OF HOW THE TECHNOLOGY
WORKS IF YOU LOOK AT THIS FIRST
SLIDE HERE YOU CAN SEE.
ON OUR DEFINITION THAT THE
COMPANY ARTIFICIAL INTELLIGENCE
IS JUST THIS LARGER SENSE OF THE
SCIENCE OF MAKING THINGS SMART
YOU COULD IMAGINE YOU COULD
PROGRAM A COMPUTER RIGHT WITH
THE DICTIONARY YOUR CALCULATOR
ENCYCLOPEDIA.
THAT COULD BE CONSIDERED SMART
WITHIN NOT AND WE SEE A SUBSET
THAT WE ARE CALLING MACHINE
LEARNING ITS TECHNIQUES TO LEARN
FROM DATA SO INSTEAD OF BEING
HAND PROGRAM IT'S AS DR SINGH
SAID TEACHING COMPUTERS TO LEARN
FROM EXAMPLES -- YOU KNOW TO BE
ABLE TO DISTINGUISH THINGS LIKE
WOLF AND HUSKY AND MANY OTHER
DIFFERENT.
THE REASON THIS IS BEEN SO
IMPORTANT TO US ACT GOOGLE IS
FOR THE REASON ON THE NEXT SLIDE
MACHINE LEARNING SKILLS BETTER
THAN RULE BASED CODE.
IF YOU THINK ABOUT THE FLAGSHIP
GOOGLE PRODUCT GOOGLE SEARCH AYE
IT'S CHANGED A LOT IN THE LAST
FIFTEEN TWENTY YEARS.
IF YOU DID A SEARCH LET'S SAY
FIFTEEN YEARS AGO PEOPLE USED TO
SEARCH FOR THINGS LIKE WATER OR
COFFEE.
AND AND YOU KNOW YOU WOULD GET A
RESULTS I'M TEN BLUE LINKS A LOT
OF THAT WAS HAND CODED --
PROGRAMS BEHIND THE RESULTS
RIGHT SO IF USER SEARCHES FOR
WATER THEN SHOW THESE TYPES OF
WEEKS RIGHT IF USER SEARCHES FOR
COFFEE ENSURE THESE TYPES OF
THINGS THAT'S NOT POSSIBLE TODAY.
AND PEOPLE ARE SEARCHING IT IN
MANY MORE LANGUAGES THAN ENGLISH
FOR EXAMPLE SO TO HAND PROGRAM
THINGS IN HUNDREDS OF LANGUAGES
WOULD BE HUNDREDS OF TIMES MORE
WORK -- PEOPLE ARE ALSO
SEARCHING FOR A LOT HARDER
QUESTIONS THEY'RE NO LONGER JUST
SEARCHING FOR COFFEE THEY'RE
SEARCHING FOR COFFEE SHOP NEAR
ME RATED MORE THAN FOUR STARS
GOOD VIBE.
YOU COULD NEVER ACTUALLY.
AND PROGRAM ALL OF THOSE TYPES
OF ANSWERS INTO SEARCH ENGINE
AND IN FACT TODAY MORE THAN 15%
OF SEARCHES EVERY SINGLE DAY OUR
UNIQUE THEIR COMPLETELY NEW
GOOGLE'S NEVER SEEN BEFORE SO WE
WOULD NOT BE ABLE TO USE.
PREVIOUS METHODS OF HAND CODING --
THE THIRD PIECE WHICH IS
INTERESTING IS THE INTERNET
TODAY IS NO LONGER JUST TEXT A
LOT OF IT IS.
AND VIDEO IMAGES SOUNDS MUSIC
AND AUDIO OTHER THINGS LIKE THAT
SO AGAIN WE HAVE TO MOVE TO
MACHINE LEARNING AS A COMPANY IT
SCALES BETTER THAN RULE BASED
CODE HELPS US TO DR ALL THE
DIFFERENT KINDS OF THINGS USERS
ARE LOOKING.
FOR ON THE NEXT PAGE YOU'LL SEE
A FEW DIFFERENT EXAMPLES OF HOW
PEOPLE ARE USING MACHINE
LEARNING AGAIN DOCTOR SEEING
REFERRED TO YOU I'M THIS IDEA OF
COMPUTATION.
ON THERE'S A LOT OF DIFFERENT
TYPES OF MATHEMATICAL MODELS
LIKE SOME RICE TO COUPLE HERE
ALGORITHMS TO CIRCLE MODELS AND
THEN ONE OF THE MOST COMMON
WHICH YOU MAY HAVE BEEN HEARING
INCREASING ABOUT IT'S CALLED
NEURAL NETS -- NEURAL NETS LEARN
FROM EXAMPLES.
IF YOU GO TO THE NEXT SLIDE
AGAIN SIMILAR TO WHAT DOCTOR
SING TALKED ABOUT YOU CAN TRAIN
NEURAL NETS TO LEARN FROM MANY
MANY DIFFERENT EXAMPLES.
I'M IN EACH OF THE CIRCLES THAT
YOU SEE HERE ON THE SLIDES
REPRESENT ONE MATHEMATICAL
OPERATIONS SO COULD BE SOMETHING
LIKE AT FIVE OR DIVIDE BY THREE
YOUR TAKE A DERIVATIVE.
I'M CENTURY YOU'VE GOT INPUTS TO
LEARN FROM ON THE LEFT SIDE
YOU'VE GOT AN IMAGE OF A CAT
IT'S LABELED CAT YOU KNOW WHAT
THE OUTPUT IS IT YOU WANT AN
OUTSIDE.
YOU CAN CONSTRAIN MODEL TO TRY
TO KEEP UPDATING WHAT THOSE
MATHEMATICAL OPERATIONS ARE SO
THAT IT CAN ALSO PROPERLY FIT
DOG IN CAR APPLE.
ON FLOWER YOU CAN GO THROUGH
MILLIONS OF THESE EXAMPLES AND
THEN WHEN YOU SHOW THE AND
MACHINE LEARNING MODEL SOME NEW
IMAGE HASN'T SEEN BEFORE
HOPEFULLY ALL OF THE OPERATIONS
HAVE BEEN CONFIGURED SUCH THAT
YOU GET THE CORRECT OUTPUT ON
THE END.
IF NOT YOU GO BACK AND TRY TO
EXAMINE WHAT NEEDS TO BE
IMPROVED INTRIGUED.
I'M FROM OUR POINT OF VIEW IT
GOOGLE MACHINE LEARNING REALLY
REQUIRES FOUR INGREDIENTS ONE OF
THEM THE MOST OBVIOUS AGAIN DR
SINGH TALKED ABOUT THIS IS
TRAINING EXAMPLES SO YOU KNOW
IMAGES WHICH HAVE LABELS LIKE
CATS THIS IS WHAT A LOT OF
PEOPLE WOULD CALL DATA.
HOWEVER THAT IS NOT THE ONLY
THING THAT'S NEEDED FOR MACHINE
LEARNING IT'S JUST ONE OF THE
FOUR SO ON THE RIGHT YOU'LL SEE
ALGORITHMS AND TOOLS SO WHAT
THOSE MATHEMATICAL MODELS LOOK
LIKE ALMOST JUST AS IMPORTANT IF
NOT MORE IMPORTANT THAN HAVING
THE DATA.
YOU'VE GOT TO BE ABLE TO HAVE
THE TOOLS TO LEARN FROM THE DATA.
I'M ON THE BOTTOM LEFT YOU'LL
SEE COMPUTATIONAL RESOURCES AT
THIS HAS REALLY IMPROVED OVER
THE LAST -- ESPECIALLY A FEW
YEARS BUT OVER THE LAST DECADE
AND THESE ARE COMPUTER CHIPS YOU
KNOW YOU MAY BECOME FAMILIAR
WITH CPUS OR GPUS NOW THERE'S A
LOT OF COMPANIES WORKING TO MAKE.
NEW NEXT GENERATION COMPUTER
CHIPS THAT CAN SPECIFICALLY
PROCESS THE MATH THAT'S NEEDED
FOR NEURAL NETS SO NEURAL NETS
USE A LOT OF MATRIX
MULTIPLICATION THAT'S EXPENSIVE
AND THAT TAKES A LONG TIME ON
CPUS AND GPUS.
ON THERE'S A LOT OF WORK GOING
ON AT GOOGLE AND OTHER PLACES TO
MAKE CHIPS THAT CAN HANDLE
SPECIFICALLY THAT TYPE OF
NOTHING BE VERY EFFICIENT
THOUGHT IT.
I'M WHICH IS NOW ENABLING HUGE
GROWTHIN MACHINE LEARNING --
THE LAST PIECE HERE'S CREATIVITY
AND INGENUITY.
SENATOR BORDERS YOU TOUCHED A
LITTLE BIT ON THIS BUT BEHIND
ANY MODEL YOU REALLY DO NEED THE
EVEN THAT ARE DESIGNING WHAT
EXACTLY DOES THIS MODEL DO YOU
HOW DOES IT PERFORM WHAT ARE THE
INTERESTING WAYS.
ON THAT IT CAN LEARN.
AND SO TALENT IS ABSOLUTELY
CRUCIAL TO BEING ABLE TO DEVELOP
MACHINE LEARNING TECHNOLOGY.
AGAIN FROM GOOGLE PERSPECTIVE A
I IS USED ACROSS GOOGLE PRODUCTS
SO I JUST LISTED FIFTEEN YEAR
AND THERE ARE SO MANY DIFFERENT
WAYS THAT WE'RE USING MACHINE
LEARNING IN ALL OF THESE
PRODUCTS TALKED ABOUT SEARCH.
BUT WE COULD GO INTO ANY OF
THESE IN DETAILS REALLY
TRANSFORMING OUR ABILITY. TO
CREATE NEW THINGS DESIGN NEW
FEATURES WELL EVEN THOUGH WE
THINK WORKS ON A LOT OF
IMPORTANT PROBLEMS IT'S REALLY
ONLY A FRACTION OF THE PROBLEMS
THAT EXIST IN THE WORLD SO THERE
ARE.
MANY DIFFERENT.
OPENS THAT LOTS OF PEOPLE CARE
ABOUT IN THE WORLD AND WE'RE
ACTUALLY STARTING TO SEE THE USE
OF A I AND MACHINE LEARNING TO
ADDRESS A LOT OF THOSE PROBLEMS.
RIGHT SO TOP LEFT YOU'VE GONE
IMAGE OF AN AYE WE'RE SEEING
DOCTORS STARTING TO USE MACHINE
LEARNING FOR DIAGNOSIS ON THIS
HERE IS A CASE OF DIABETIC
RETINOPATHY.
DOCTORS USING IMAGES TO SEE
WHETHER PATIENT HAS EARLY SIGNS
OF BLINDNESS THAT COMES WITH
DIABETES I'M WERE SEEN USE OF
THIS FOR CANCER HEART DISEASE --
MEAN DISEASE'S AXE RAISE AND
MANY OTHER THINGS THE NEXT PHOTO
WE'VE GOT ON LOTS OF DIFFERENT
FARMERS AGRICULTURE -- NEW
COMMUNITIES WITH AT LOOKING BACK
HOUSE AND CATTLE AND SHEEP AT A
LOTS OF DIFFERENT -- PLACES IN
WHICH FARMERS ARE USING MACHINE
LEARNING TO PREDICT BASS
CONDITIONS FOR THEIR FARMS
INCREASE EFFICIENCY I'M INCREASE
EFFECTIVENESS INCREASE THE
HEALTH OF THEIR ANIMALS.
I'M CONSERVATION.
RAIN FOREST SPACE EXPLORATION
AND THEN ON THE BOTTOM RIGHT AND
THIS IS AN EXAMPLE ACTUALLY FROM
THE STATE OF ILLINOIS SO THEY'RE
USING MACHINE LEARNING AND TO
BETTER PREDICT TRAFFIC FLOW AND
BETTER MONITOR AND BETTER --
IDENTIFY.
WAYS TO IMPROVE TRAFFIC ON THEIR
STREETS THERE'S A LOT OF
DIFFERENT WAYS THAT HUMAN CAN BE
USED FOR PUBLIC SERVICES.
ASSEMBLY MEMBER.
NUMBER SPOKE TO THIS A LITTLE
BIT.
I'M HAPPY TO GO INTO THAT A
LITTLE BIT MORE IN DETAIL -- YOU
MENTION THIS CENTER I'M BURKE
BUT AT YOU KNOW THEY'RE LIKE ANY
TECHNOLOGY THEY'RE AMAZING
OPPORTUNITIES THERE ARE ALSO
RISKS THAT COME WITH THE
TECHNOLOGY.
I'M WE'VE EXPERIENCES THAT
GOOGLE OURSELVES EVEN AS WE'VE
BEEN DESIGNING YOU KNOW HUNDREDS
OF NEW FEATURES AND PRODUCTS AND
ALL THESE OPPORTUNITIES THAT WE
SEE WE'VE HAD A LOT OF DIFFERENT
QUESTIONS COME UP.
AS TO WHETHER OR NOT WE SHOULD
DO SOMETHING OR HOW WE SHOULD
DESIGN A CERTAIN FEATURE.
SO I'LL GIVE AN EXAMPLE.
LAST YEAR WE WERE APPROACHED BY
A HOSPITAL A HOSPITAL THAT TAKES
CARE OF A LOT OF PATIENTS WHO
HAVE A CONDITION CALLED IPHONEA.
SO I HAVEN'T HEARD OF THIS
BEFORE LAST YEAR BUT A PHONY AS
A CONDITION.
WHERE PEOPLE?
FOR ACCIDENT OR OTHER HAVE LOST
THE ABILITY TO SPEAK SO THEY CAN
STILL THINK AND THEY CAN STILL
THEY KNOW EXACTLY WHAT THEY WANT
TO SAY BUT WHEN THEY MOVE THEIR
MOUTH.
NO SOUND IS COMING OUT.
AS YOU CAN IMAGINE THIS IS
REALLY FRUSTRATING.
CONDITION THEY'RE NOT ABLE TO
IMMEDIATELY COMMUNICATE WITH
THEIR FAMILY AND FRIENDS THE
HOSPITAL CAME TO US AND SAID HEY
WE HEARD GOOGLE IS DOING A LOT
OF WORK WITH.
A MACHINE LEARNING WITH TEXT TO
SPEECH WE WONDER IF YOU COULD
USE AB YOU KNOW YOUR TECHNOLOGY
TO DEVELOP A NEURAL NET MODEL
THAT COULD AUTOMATICALLY READ
LIPS.
THIS WOULD BE VERY HELPFUL FOR
PATIENTS IN THAT INSTEAD OF YOU
KNOW HAVING TO SIGN OR WRITE OR
TYPE OR SPEAK THROUGH YOU KNOW
COMPUTERIZED VOICE.
THEY COULD ACTUALLY JUST MAKE
THEIR MOUTH SAY WHAT THEY'RE
TRYING TO SAY AND THEIR FAMILY
MEMBERS WOULD KNOW WHAT THEY'RE
SAYING.
WELL WE THOUGHT ABOUT THIS
BECAUSE OF COURSE ON FIRST BLUSH%
WHO DOESN'T WANT TO HELP THESE
KIND OF PATIENTS RIGHT THAT'S AN
AMAZING USE CASE.
SOMETHING THAT I'M YOU WOULD
REALLY WANT TO BE ABLE TO HELP
PEOPLE COMMUNICATE WITH THEIR
LOVED ONES.
HOWEVER YOU COULD ALSO IMAGINE
KIND OF GOING ONE STEP FURTHER A
LOT OF CHALLENGES AROUND THAT
WHO HAS ACCESS TO THIS
TECHNOLOGY WHO'S ABLE TO READ
THIS PERSON'S LIPS.
WHAT HAPPENS IF -- I DON'T KNOW
LIKE A ROGUE ACTOR SOMEBODY
WANTS TO SPY ON A CO WORKER
FAMILY MEMBER COULD JUST HIDE A
CAMERA AND THEN USE NEURAL NET
MODEL TO SPY ON THEM.
HOW WOULD WE CONTROL THE -- YOU
KNOW SHARING OF THAT TYPE F
MODEL -- WHAT HAPPENS AN EVEN
LARGER SCALE WHAT ABOUT
GOVERNMENTS YOU KNOW HOW MUCH
GOVERNMENTS -- POWER SHOULD BE
ABLE TO LOOK INTO LIVES OF
PEOPLE WHO THOUGHT THEY WERE
JUST WALKING BY ON THE SIDEWALK --
WHAT HAPPENS IF THAT GETS INTO
THE HANDS OF ROGUE GOVERNMENTS?
I'M WHO HAVE INTENTIONS MAYBE
EVEN AGAINST HUMAN RIGHTS SO WE
DEBATED THIS A LOT INTERNALLY
REALLY TRIED TO FIGURE OUT WHAT
WE WANTED TO DO.
THIS WAS JUST ONE EXAMPLE OF
MANY OF THE KINDS OF CASES THAT
WE'VE BEEN THINKING ABOUT I'M IN
THIS CASE THE WAY THAT WE ENDED
UP RESOLVING IT WE DID WORK WITH
THE HOSPITAL.
WE DESIGNER ON THAT MODEL BUT IT
ONLY WORKED FOR PATIENTS WHO
WERE LOOKING DIRECTLY AT EIGHT
ZERO DEGREE ANGLE SO IT WOULD
NOT WORK FOR SURVEILLANCE
CAMERAS THAT WERE.
POSTED AT A DISTANCE AT AN ANGLE.
PACIFIC WE WITH THEM AND TO MAKE
SURE THAT THE TIME RESOLUTION
AND THE SPATIAL RESOLUTION WAS
SUCH THAT IT WOULD ONLY WORK FOR
PATIENTS WHO HAVE OPTED INTO
SPEAKING OVER A WEBCAM OR INTO
SPECIFIC CAMERA.
WITH THEIR FRIENDS AND FAMILY
AND WE ALSO ONLY SHARE THE MODEL
WITH THE HOSPITAL SO THAT'S
PROJECT THAT WE'VE BEEN WORKING
WITH THEM ON SPECIFICALLY TO
DEVELOP -- WHILE WE PUBLISHED
THE RESEARCH WE NOT PUBLISHER
OPEN SOURCE MODEL SO THAT'S WAY
THAT WE KIND OF ADDRESS STOCK --
BUT AS I MENTIONED THERE'S BEEN
HUNDREDS OF CASES LIKE THIS AND
AS A COMPANY LAST JUNE WE
ACTUALLY DECIDED TO PUT TGETHER.
A SET OF OUR OWN GOOGLE A AYE
PRINCIPLES FOR RESPONSIBLE
DEVELOPMENT THIS WAS OUR
COMPANY'S WAY OF SETTING OUT
WHAT OUR OWN ETHICAL CHARTER IS
HOW WE SHOULD GUIDE OF THE
RESPONSIBLE USE.
OF THIS TECHNOLOGY AT THE
COMPANY I'M HAPPY TO GO INTO ANY
OF THESE IN MORE DETAIL ON THE
LEFT YOU'LL SEE SEVEN THINGS
THAT WE THOUGHT A I SHOULD DO
YOU OR BE RIGHT BE SOCIALLY
BENEFICIAL.
AVOID CREATING A REINFORCING
UNFAIR BIAS BE BUILT AND TESTED
FOR SAFETY BE ACCOUNTABLE TO
PEOPLE CORPORATE PRIVACY DESIGN
PRINCIPLES.
UPHOLD HIGH STANDARDS OF
SCIENTIFIC EXCELLENCE AND THE
NUMBER SEVEN BE MADE AVAILABLE
FOR USES THAT ACCORD WITH THESE
PRINCIPLES AGAIN HAPPY TO GO
INTO THIS IN MORE DETAIL BUT
THIS NUMBER SEVEN WAS REALLY
AROUND THE IDEA THAT GOOGLE.
WE DON'T WANT TO BE THE ONES
THAT JUST CREATE THE TECHNOLOGY
AND HOLD ON TO IT WE THINK LOADS
OF PEOPLE ARE WORKING ON
IMPORTANT PROBLEMS WE WANT THEM
TO BE ABLE TO HAVE ACCESS TO THE
TECHNOLOGY.
AS LONG AS THEY'RE DOING SO IN A
RESPONSIBLE MANNER SO WE'VE
RELEASED A LOT OF DIFFERENT.
I'M OPEN SOURCE MODELS TOOLS OUR
OWN MACHINE LEARNING LIBRARY
TENSER FLOW WHICH WE USE FOR
INTERNAL DEVELOPMENT WE
COMPLETELY OPEN SOURCE LOTS OF
OTHER PEOPLE.
OUTSIDE CAN USE IT ON THE RIGHT
YOU'LL SEE FOR APPLICATIONS THAT
WE WILL NOT PURSUE.
ANY THAT ARE LIKELY TO CAUSE
OVERALL HARM PRINCIPLE PURPOSE
IS TO DIRECT INJURY SURVEILLANCE
VIOLATING INTERNATIONALLY
ACCEPTED NORMS AND THE NUMBER
FOUR AND THOSE WHOSE PURPOSE.
CONTRAVENES INTERNATIONAL LAW
AND HUMAN RIGHTS THIS IS THE SET
OF PRINCIPLES THAT WE HAVE BEEN
USING -- OVER THE LAST.
YEAR YEAR AND A FEW WEEKS I'M TO
REALLY ASSESS EVERY SINGLE CASE
EVERY FEATURE EVERY PRODUCT
EVERY RESEARCH PAPER THAT WE GET
OUT TO TRY TO MAKE SURE THAT
WERE LIVING UP TO THE
COMMITMENTS WE'VE SET UP.
OF COURSE IT'S NOT ALWAYS EASY
THERE ARE CASES WHERE SOME OF
THE PRINCIPLES COME INTO
CONFLICT RIGHT EVERYBODY WANTS
FAIRNESS EVERYBODY WANTS PRIVACY
EVERYONE WANTS ACUITY BUT THERE
ARE PLACES WHERE YOU NEED TO
MAKE TRADE OFFS.
AND THESE ARE SOME OF THE
CHALLENGING ISSUES THAT WE HAVE
BEEN GRAPPLING WITH OVER THE
PAST YEAR.
LOT OF PEOPLE TALK ABOUT A AYE
BIAS I DO WANT TO MAKE THIS ONE
POINT HERE THAT A I CAN ALSO
HELP YOU MEANS TO BE MORE
RESPONSIBLE.
AND SO THE GINA DAVIS INSTITUTE
CAME TO US A FEW YEARS AGO GINA
DAVIS HAD A HUNCH THAT WOMEN ARE
UNDER REPRESENTED IN FILM AND
MEDIA SHE SAID.
HEY YOU KNOW I'VE BEEN IN THIS
BUSINESS A LONG TIME I FEEL LIKE
WOMEN HAVE LESS SCREEN TIME IF
YOU LIKE WOMEN HAVE LESS
SPEAKING TIME THEY'RE NOT
TREATED FAIRLY.
HOWEVER I HAVEN'T BEEN ABLE TO
PUT MY FINGER ON I HAVEN'T BEEN
ABLE TO QUANTIFY EXACTLY WHAT
THAT LOOKS LIKE WE PARTNER
TOGETHER BUILDING MACHINE
LEARNING MODEL THAT CAN
AUTOMATICALLY IDENTIFY FACES OF
MEN AND AUTOMATICALLY IDENTIFY
FACES OF WOMEN.
WORKING TOGETHER WITH THE GINA
DAVIS INSTITUTE OUR MODEL
WATCHED THOSANDS AND THOUSANDS
OF MOVIES AND ACTUALLY
DOCUMENTED WHEN A MAN WAS ON
STAGE WHEN A WOMAN WAS ON STAGE
AND WHEN THEY WERE SPEAKING.
THAT SOMETHING THAT NO PERSON
WOULD BE ABLE TO DO NO ONE'S
GOING TO SIT THERE AND YOU KNOW
BOX AND LABEL ALL THESE
DIFFERENT TIMES FOR MILLIONS OF
HOURS OF FOOTAGE.
WE SHOULD -- WITH THE GENE DAVIS
INSTITUTE WAS THAT MEN IN FACT
DO YOU HAVE MUCH MORE SCREEN AND
SPEAKING TIME ABOUT SEVENTY TO
THIRTY AND IN FACT IN THE NEXT
STEP BEYOND THAT.
AT FILMS THAT HAD WOMEN IN 50%
OR MORE OF THE SCREEN AND
SPEAKING TIME DID BETTER AT THE
BOX OFFICE.
SO THIS IS SOMETHING THAT GINA
DAVIS AND HER TEAM COULD
ACTUALLY TAKE TWO STUDIOS ON TO
TRY TO PROMOTE WOMEN MORE IN
MEDIA.
I IT'S AN EXAMPLE THAT I WOULD
NOT HAVE BEEN POSSIBLE WITHOUT
THE USE OF MACHINE LEARNING SO
WANTED TO POINT OUT THERE ARE A
LOT OF OPPORTUNITIES HERE. TO
MAKE US BETTER.
LAST PAGE JUST TO GIVE YOU A
SNEAK PREVIEW OF HOW WE'RE
THINKING ABOUT A I AT THE
COMPANY WHAT'S COMING NEXT FROM
US.
THERE'S REALLY THREE MAIN AREAS
THAT WERE WORKING IN NUMBER ONE
CUTTING EDGE RESEARCH NUMBER TWO
APPLICATIONS.
NUMBER THREE HUMAN A AYE
INTERACTION SO IN NOT CUTTING
EDGE RESEARCH AREA I LISTED
SEVERAL DIFFERENT PLACES I'LL
CALL OUT A FEW.
NUMBER ONE SMALL DATA WE'VE
TALKED A LOT ABOUT LEARNING FROM
BIG DATA FROM EXAMPLES MILLIONS
OF PHOTOS THAT KIND OF THING.
HOWEVER THERE ARE A LOT OF CASES
IN THE WORLD YOU'VE GOT VERY.
RARE SEARCH QUERIES FOR RARE
DISEASES OR RARE LANGUAGES NO AS
HUMANS WERE ACTUALLY ABLE TO
LEARN FROM JUST A SMALL NUMBER
OF EXAMPLES YOU LOOK AT A THREE
YEAR OLD A FOUR YEAR OLD.
THEY CAN PROBABLY SEE FOR FIRE
TRUCKS MAYBE FIVE FIRE TRUCKS IN
THE AUTOMATICALLY NOTIFIED TRUCK
IS THERE'S A LOT OF RESEARCH
GOING ON AT OUR COMPANY AS WELL
AS OTHERS INTO HOW CAN WE BUILD
BETTER MODELS THAT CAN LEARN
FROM SMALL DATA EXAMPLES.
THIS IS GREAT FOR THOSE RARE
CASES IT'S ALSO GREAT FOR
PRIVACY IT'S GREAT FOR A LOT OF
DIFFERENT REASONS -- AND YOU
KNOW I WOULD SAY THE RESEARCH IS
STILL.
INCIPIENT SO JUST IN ITS EARLY
DAYS BUT IT IS A PROMISING ON
AREA THERE'S A LOT OF WORK GOING
INTO LANGUAGE UNDERSTANDING
MACHINE PERCEPTION BEING ABLE TO
LOOKAT A SCENE AND UNDERSTAND
WHAT'S HAPPENING THERE YOU CAN
IMAGINE LOADS OF ACCESSIBILITY
AS WELL AS OTHER REASONS WHY
THAT'S IMPORTANT.
IN TERMS OF UP WITH.
ACROSS THE BOARD INSIDE THE
COMPANY WE'RE LOOKING -- ACROSS
BUSINESS SCIENCE HEALTH MUSIC
OUR PUBLIC SERVICES PARTNERING
IN COLLABORATING WITH EXPERTS IN
ALL OF THOSE AREAS ACROSS
SECTORS AND WE'RE STARTING TO
SEE A LOT OF DIFFERENT.
SECTORS IN CALIFORNIA AS WELL AS
ACROSS THE COUNTRY AND THE WORLD
USING MACHINE LEARNING FOR THE
SECTORS AND MORE SO WE'RE ALSO
DOING OUR BEST TO CREATE TOOLS
THAT THOSE.
PEOPLE CAN USE.
AND KIND OF RUN WITH.
ON THE LAST PIECE YOU'LL SEE HIM
IN A AYE INTERACTION -- IVORY IN
HERE INTERFACE EASE OF USE WHY
PARTICIPATION THIS IS SOMETHING
THAT SEEMS REALLY IMPORTANT.
THE LAST THING THAT WE WOULD
WANT IS FOR THIS TECHNOLOGY
WHICH YOU KNOW ON ITS FACE MAY
SOUND COMPLICATED TO BE
SOMETHING THAT IS BEEN RELEGATED
JUST TO PEOPLE WHO HAVE
EXPERTISE AND INCREASINGLY OTHER
PEOPLE WOULD NOT BE ABLE TO
ACCESS IT OR HAVE USE.
OF IT I'M WE THINK IT'S CRUCIAL
FOR THERE TO BE WHY
PARTICIPATION EDUCATION HAPPY TO
GO INTO A LOT OF THESE DIFFERENT
ISSUES.
INTERFACE HAVE WRITTEN HERE YOU
KNOW MOST OF US IN THIS ROOM WE
CAN PROBABLY DRIVE A CAR BUT
MOST OF US DON'T KNOW HOW TO
BUILD A CAR.
I THINK THAT'S A SIMILAR ANALOGY
THAT WE'VE BEEN THINKING ABOUT
WITH MACHINE LEARNING MODELS WE
THINK THEY'RE VERY POWERFUL.
THERE'S A LOT OF WORK GOING INTO
WHAT SHOULD THOSE HUMAN COMPUTER
INTERFACES LOOK LIKE SO A LOT OF
PEOPLE CAN OPERATE MACHINE
LEARNING MODELS.
EVEN IF THEY DON'T NECESSARILY
KNOW HOW TO BUILD THEM -- SO
I'LL LEAVE IT THERE I THINK
THERE'S A TON OF DIFFERENT
OPPORTUNITIES A LOT OF DIFFERENT
THINGS THAT WE NEED TO WORK ON
TOGETHER THANKS.
THANK YOU DOCTOR CHAO A MOST
INTERESTING AND AS I MENTIONED
EARLIER THAT WE HAVE T BE IN
MANY PLACES AT THE SAME TIME.
AND I AM THOáT SENATOR ALSO
ALSO HAS TO BE MANY PLEASE STAND
UP BUT I'M SORRY YOU WERE HERE
FOR DOCTOR CHARLES TESTIMONY
ABOUT THE BIAS -- WITH RESPECT
TO THE FILM INDUSTRY IT MIGHT BE
SOMETHING.
ALL OF US ARE INTERESTED IN YOU
MAY WANT TO TALK TO DOCTOR CHAO
ABOUT OF WHAT ONE OF THE
CONCERNS AND I THINK IT'S A
GENERAL CONCERN.
IS TRANSPARENCY IN TERMS OF THE
COLLECTION ANALYSIS AND THOSE
KINDS OF THINGS AND AND MAYBE
YOU CAN SPEAK TO THAT I REALIZE
THAT FOR EXAMPLE GOOGLE OR OTHER
ENTITIES.
NO YOU YOU YOU CAN'T.
YOU CAN'T REVEAL TRADE SECRETS
BUT TO THE EXTENT THAT YOU CAN --
REVEAL.
OF FOR EXAMPLE WHAT WHAT KIND OF
TRANSPARENCY WILL BE ACCESSIBLE
TO THE INDIVIDUAL WHO IS --
INTERFACING WITH WITH GOOGLE
YEAH DEFINITELY THIS IS
SOMETHING THAT WE TALK ABOUT.
A LOT YOU THINK ABOUT ALL THE
DIFFERENT TYPES OF MODELS AT
GOOGLE WE THOUGHT A LOT ABOUT
YOU KNOW WHAT DOES THE OPTIMAL
TRANSPARENCY LOOK LIKE IN OUR A.
I. PRINCIPLES WE'VE STATED.
AS NUMBER FOR A I SHOULD BE
ACCOUNTABLE AND WITHIN THAT
ACCOUNTABILITY WE WOULD CONSIDER
EXPLAIN ABILITY TRANSPARENCY AS
WELL AS THE NEED AND AND THE
ABILITY FOR SOMEBODY.
TO CONTEST YOU KNOW THE KIND OF
ANSWER PRODUCTION COMING FROM
MODEL.
I'M SO THERE'S A COUPLE
DIFFERENT WAYS TO LOOK AT IT YOU
MENTIONED AND TRADE SECRETS OF
COURSE THAT IS SOMETHING THERE'S
PROPRIETARY CONCERNS YOU KNOW WE
WANT TO BE ABLE TO PROTECT THAT.
BUT THERE'S A LOT OF DIFFERENT
OTHER PIECES IN IT TOO IF YOU
THINK ABOUT SEARCH SEARCH MODEL
FOR EXAMPLE.
AND IF YOU WERE TO SHOW THE
EXACT COMPLETE MODEL I'M WE HAVE
YOU KNOW NO DOUBT THAT PEOPLE
WOULD USE THAT AND TRY TO HACK
THE SYSTEM.
SO WE TALK ABOUT PRIVACY RE TALK
ABOUT SECURITY YOU KNOW WHAT
WOULD HAPPEN IF SOMEBODY
ACTUALLY HACKED THAT MODEL AND
MADE ON YOU KNOW DIFFERENT
RESULTS OF YOUR AN EARLIER OR
LATER.
I'M ACTUALLY TRYING.
TO MAYBE I'VE DISRUPTS
TRANSLATION FOR GOOGLE TRANSLATE
OR YOU KNOW VIDEOS FOR YOU TO
BURKE OR ANY OF THE LIKE SO
THAT'S ANOTHER THING THAT WE
THINK ABOUT HOW DO WE PROTECT
PRIVACY AND SECURITY OF OUR
MODELS THINK ABOUT RESPONSIBLE
DEVELOPMENT.
WHILE ALSO BEING AS TRANSPARENT
AS POSSIBLE ANOTHER I DID
MENTION THAT WE THINK ABOUT IS
WHAT IS THE MOST USEFUL FOR THE
USER.
SO WE TALK ABOUT TRANSPARENCY
YOU KNOW SOMETIMES WE'VE HEARD
I'M PEOPLE CALL FOR ME HAD THESE
DISCUSSIONS INTERNALLY ALSO WHAT
IF YOU KNOW FOR GOOGLE TRANSLATE
WE JUST PUBLISHED THE FULL
SOURCE CODE AND MEAN ABLE PEOPLE
TO TAKE A LOOK AT NOW BE
COMPLETELY TRANSPARENT.
WELL TO MOST PEOPLE THAT WOULD
BE COMPLETELY USELESS THEY
WOULDN'T NECESSARILY UNDERSTAND
WHAT ANY OF THAT SOURCE COULD
MEAN THAT'S NOT REALLY GETTING
THEM TO THE ANSWERS THAT THEY
WANT.
ON THE ALSO THINK ABOUT WHAT
DOES IT MEAN FOR DIFFERENT USER
SO AS WE'RE STARTING TO PARTNER
A LOT WITH CLINICIANS POSITIONS.
HOSPITAL THE HEALTHCARE SYSTEM
YOU KNOW WHAT KIND OF
EXPLANATIONS WHAT KIND OF
TRANSPARENCY DO DOCTORS NEED IN
ORDER TO TRUST AND ANSWER I'M AT
HOW'S THAT DIFFERENT FROM
PATIENTS HOW'S THAT DIFFERENT
FROM NURSES OR TECHNICIANS OR
MAYBE THE INSURANCE INDUSTRY IN.
DIFFERENT ANSWERS FOR DIFFERENT.
I'M PEOPLE SO THAT'S SOMETHING
WE'VE BEEN I'M THINKING A LOT
ABOUT AND IN THE CASE OF AT
HEALTH CARE INDUSTRY OR
TRANSPORTATION OR OTHERS WE
ACTUALLY THINK IT'S ABSOLUTELY
CRUCIAL TO BE WORKING WITH THE
LEGISLATORS REGULATORS EXPERTS
IN THOSE -- YOU KNOW WHEN HEALTH
CARE FOR EXAMPLE WE DON'T THINK
IT SHOULD BE UP TO GOOGLE IT'S
NOT OUR RESPONSIBILITY BUT ALSO
NOT OUR EXPERTISE TO SAY DOCTOR
SHOULD KNOW THIS AND PATIENTS
SHOULD KNOW THIS AND TECHNICIANS
KNOW THIS RIGHT BUT WE'VE GOT TO
WORK TOGETHER TO IDENTIFY.
WHAT ARE THOSE CRUCIAL ASPECTS
OF TRANSPARENCY THAT NEED TO BE
KNOWN HOW CAN WE TRY TO BUILD
MODELS THAT CAN SHOW THAT
BECAUSE DR SINGH SAID IT'S NOT
PERFECT WE DON'T ALWAYS KNOW
EXACTLY WHY MODELS ARE
PREDICTING THINGS THEY DO -- BUT
THERE'S A LOT OF WORK GOING INTO
THAT SO HOW COULD WE I'M KIND OF
BEST DESIGN MODELS IN THAT WAY.
ON THE LAST POINT I'LL TOUCH ON
IN THIS IS RELATED -- TO BILL
THAT YOU.
OPPOSE CENTER ON BURKE IS THIS
IDEA OF HOW CAN WE BE MORE
TRANSPARENT ABOUT WHAT THE MODEL
OR WHAT THE DATA SETS ARE
ACTUALLY COMPRISED OF AND WHAT
THEY'RE LEARNING.
ON NEW WE CALL THESE DATA CARDS
WERE MODEL CARDS AND SOMETIMES
PEOPLE HAVE CALLED THEM
NUTRITION LABELS FOR DATASETS OR
NUTRITION LABELS FOR MODELS SO
THE SAME WAY AS YOU CAN SAY THIS
HAS YOU KNOW AX GRAMS OF FAT OR
SUGAR.
OR VITAMIN A AND WE'VE BEEN
WORKING TO TRY TO SAY OKAY FOR
THESE DATA SETS THAT WE'VE
LEARNED FROM YOU LET'S SAY IT'S
AN IMAGE DATA SET WHAT
PERCENTAGE ARE ANIMALS WHAT
PERCENTAGE OUR CARS WHAT
PERCENTAGE OUR FOOD JUST TO GIVE
PEOPLE A SENSE OF WHAT'S INSIDE.
WHERE DID THE DATA COME FROM
OKAY IT'S 60% AND 40% WOMEN YOU
KNOW 60% FROM THE U. S. 40% FROM
OTHER PARTS OF THE WORLD?
AND WE'VE BEEN REALLY WORKING TO
TRY TO PUT TOGETHER THESE%
NUTRITION LABELS WE'VE TESTED A
FEW ALREADY WE PUBLISHED. ONE
ONLINE FOR AN IMAGE DATA SET
THAT WE HAVE AND WE'RE REALLY
WORKING TO DO MORE IN THAT AREA
THE SAME THING FOR MODEL'S WE
FEEL LIKE THIS IS AT LEAST A
GOOD START TO PROVIDING SOME
TRANSPARENCY.
SO FOR THESE MODELS HOW DO THEY
WORK WHAT IS THEIR PERFORMANCE
ON DIFFERENT TYPES OF
POPULATIONS WHAT IS THEIR
PERFORMANCE I'M YOU KNOW WHAT IS
THEIR ERROR RATES -- WHERE DOES
THE MODEL FEEL WE'RE SHOULD
PROBABLY NOT BE USED ON WE'VE
GOTTEN ONE EXAMPLE AS WELL OF A
MODEL CARD WHICH WE POSTED
ONLINE WE'RE LOOKING TO DO MANY
MORE?
WE'VE GOT A TEST THESE IDEAS
BECAUSE WE ALSO DON'T KNOW IF
WE'VE GOT ALL THE RIGHT
CATEGORIES ARE ALL THE RIGHT
INFORMATION ON BUT WE THINK.
MAY NOT INDUSTRY COULD REALLY
MOVE TOWARDS SO -- IT AND WE
DON'T NEED TO GET INTO THIS
TODAY BUT ALL THREE OF US SIT ON
JUDICIARY COMMITTEE AN ISSUE
THAT WE'RE WRESTLING WITH THIS
PRIVACY TRANSPARENCY.
THE RELATIONSHIP SO I I KNOW
THAT GOOGLE'S ALREADY AWARE OF
OF OUR INTEREST IN.
OUR COLLECTIVE CONCERNED SO --
ALL RIGHT OTHER QUESTIONS.
IS THE SERVER JUST INCIDENT WHEN
SENATOR RUSSELL.
YOU KNOW I THINK -- PREVIOUS
CAPACITIES OF COME TO KIND OF
PUSH IT DIFFERENT ROLES THAT
GOVERNMENT AND INDUSTRY HAVE --
AB AT AT FIRST BLUSH MIGHT LOOK
UPON INDUSTRY AS A PROFIT MOTIVE
A MOTIVATED -- ADVANCE ADVANCING
THE AREAS STUDY OR LEARNING --
GOVERNMENTS HOWEVER HAVE A
DIFFERENT SET OF PRIORITIES --
STRATEGIC BEING ONE OF THEM.
AND SO MY QUESTION TO YOU IS.
DO YOU DOES GOOGLE HAVE ANY
RECOMMENDATIONS ON HOW.
THE LEGISLATURE OR THE CITY
CALIFORNIA THROUGH THE EXECUTIVE.
CAN LISTEN TO WHAT ARE THE
RECOMMENDATIONS OF INDUSTRY
WE'VE HEARD FROM A LITTLE HOOVER
COMMISSION SO ON AND SO FORTH.
HOW DOES CALIFORNIA HOW DOES
AMERICA BUT SPECIFICALLY
CALIFORNIA?
HOW DO WE CATCH UP TO WHERE WE
SHOULD BE WHERE WE WANT TO BE?
DâN.
ARE THERE CERTAIN REGULATIONS
THAT ARE BETTER CREATING --
DIFFICULTY ARE THERE CERTAIN
INDUSTRY INCENTIVES.
AND COORDINATION -- THAT -- WE
CAN BE A PART OF ANY VERY
SPECIFIC RECOMMENDATIONS YES AND
AND WE'VE ACTUALLY WRITTEN A
PAPER ON THIS SO HAPPY TO SHARE
THAT.
I WAS CAN YOU AFTERWARDS IT'S
GOT A LOT OF DETAILS IN THERE --
I WOULD SAY -- IN TERMS OF
SPECIFIC I'LL JUST NAME THREE
RIGHT HERE ON THE FIRST IS
REALLY IN TERMS OF CALIFORNIA
INVESTING CATCHING UP I'M REALLY
AND I THINK BEING ABLE TO MAKE
THOSE INVESTMENTS IN STUDENTS.
I AND AND YOU KNOW WHETHER IT'S
K. THROUGH TWELVE AT THE COLLEGE
LEVEL.
OR EVEN AT THE GRADUATE LEVEL
AND WHAT DO THOSE INVESTMENTS
LOOK LIKE WHAT ARE THE RIGHT
TYPES OF EDUCATION THAT STUDENTS
SHOULD BE LEARNING WE THINK OF
COURSE TEMAS IMPORTANT COMPUTER
SCIENCE IS IMPORTANT.
AND YOU KNOW MACHINE LEARNING IS
IMPORTANT BUT EVEN MORE THE
ABILITY TO LEARN TO LEARN THE
ABILITY TO ADOPT WHAT DO THE
SPECIFIC COURSEWORK LOOK LIKE
I'M NOT SOMETHING THAT WE'VE
OUTLINED IN IN.
HE TELLS YOU AS USEFUL IN TERMS
OF NUMBER TUNE TALKED ABOUT SOME
REGULATIONS A BEGINNING THE WAY.
AND WE'VE BEEN WORKING A LOT
WITH THE FEDERAL GOVERNMENT ON
ON HIP A REFORM WE'VE TALKED A
LOT WITH CALIFORNIA STATE AS
WELL UCSF AND SOME OF THE OTHERS.
YOU KNOW WITH SO MUCH PROMISE IN
THE MEDICAL FIELD THERE'S ALSO A
LOT OF ROADBLOCKS IN TERMS OF
BEING ABLE TO LEARN FROM PATIENT
DATA AND IN TERMS OF BEING ABLE
TO ADEQUATELY PROTECT PATIENT
DATA WALL MACHINE LEARNING
MODELS ARE ABLE -- TO KIND OF
SURVEY AN ENSEMBLE OF RECORDS TO
MAKE BETTER PREDICTIONS FOR
EVERYBODY -- COULD I THINK ALL
AGREE IN LONG RUN THAT KIND OF
THING WOULD BE VERY USEFUL --
TERMS OF PREDICTING DISEASE
EARLIER SAVING MONEY ON
PROMOTING HEALTH YOUR LIFE'S BUT
THERE ARE A LOT OF NEEDS TO BE
WORKED OUT THERE.
AND SO I WOULD SAY LOOKING AT AT
HEALTH CARE LEGISLATION LOOKING
ACCESS TO DATA LOOKING AT
PROTECTIONS FOR DATA WOULD BE IN
THE AREA THAT.
I'M IS QUITE IMPORTANT -- AND
THEN THE THIRD I WOULD SAY AT IS
REALLY JUST THINKING ABOUT.
I'M HOW GOVERNMENTS CAN PROMOTE
AND THIS CAME UP IN.
ASSEMBLY MEMBER NOVICE AT THIS
MONEY AS WELL HOW GOVERNMENTS
CAN REMOTE KIND OF HEALTHY AND I
GUESS ATTITUDE TOWARDS YEAH.
I'M NOT YOUR BUT NOT -- YOU KNOW
OVER POLLYANNA ISHE I GUESS
EITHER JUST REALLY INCREASING
PUBLIC PUBLIC EDUCATION SO THERE
AREN'T CRAZY PRESSURES ONE WAY
OR ANOTHER THING LIKE -- WERE
FREED OF THIS -- OR WE DON'T
WANT DAIS OR YOU KNOW WE'VE GOT
TO GO THIS WAY I THINK LOOKING
AT IT IN.
AT QUITE A NUANCED WAY ON SO
THAT EVERYBODY IS ABLE TO MOVE
FORWARD LIKE TO SEE THAT THE YES.
SHARE COPY THANK YOU THANK YOU
SIR BORDERS SIR RUSSELL.
YES THANK YOU MISTER CHAIR I'M
NOT SURE IF THIS IS THE RIGHT
TIME ON THE AGENDA BUT I'D LIKE
TO GET YOUR THOUGHTS ANYWAY ON A
ON A FEW THINGS -- ONE IS WITH
REGARDS TO THE IMPACT ON THE
FUTURE WORK -- AND HOW OLD.
YOUR COMMITMENT AT LEAST
GOOGLE'S COMMITMENT TO BE
SOCIALLY BENEFICIAL.
HOW DOES THAT -- HOW DO YOU MAKE
SURE THAT PART OF BEING SOCIALLY
BENEFICIAL?
IS OF A WORK FORCE YEP THAT IS
READY.
THAT IS COMPARED.
THAT IS PROACTIVELY.
EDUCATED -- AND THAT SHOULD END
UP IN BROAD TERMS.
OF IN IN OUR SOCIETY BEAN.
OF BENEFITING IN A WAY THAT'S
NOT JUST.
CRAMMING OUR LIVES IN WITH MORE.
TECHNOLOGY WITH.
I MEAN BECAUSE SEEMS LIKE THE
MORE TECHNOLOGY WE HAVE INSTEAD
OF BECOMING A SOCIETY THAT
ENJOYS LIFE MORE.
WE ARE BECOMING A SOCIETY IN
WHICH WERE CRAMMING MORE INTO
OUR DAY -- AND IT IS A COULD BE
A SOURCE OF FEAR OR IN SECURITY.
FOR PEOPLE IN TERMS OF WHAT
KINDS OF JOBS DOES THIS MEAN
WHAT KIND OF CAREERS DOES THIS
MEAN.
SO INSTEAD OF IT BEING A WHAT IT
IS WELCOME BUT INSTEAD OF BE
WELCOME ON EVERY.
IN EVERY ASPECT OF OUR LIVES.
IT SEEMS TO BE WELCOME BECAUSE
WE'RE EXCITED ABOUT THE
TECHNOLOGY BUT ARE WE EXCITED AS
FAR AS WHAT IT BRINGS TO OUR
FUTURE.
AS THE FUTURE CAREERS AND FUTURE
WORK FORCE FUTURE NEEDS SO JUST
ANY THOUGHTS ABOUT THAT OR HOW
WE COULD TACKLE THAT BECAUSE I
DON'T.
THINK ANYBODY HAS THE EXACT
ANSWER YEAH DEFINITELY THIS IS
SOMETHING WHERE A LOT OF
DIFFERENT TEAMS NEED TO PUT
THEIR HEADS TOGETHER.
I'M FROM GOOGLE I'D SAY WE DO
YOU THINK ABOUT THIS A LOT YOU
POINTED OUT THAT WE'VE GOT OUR
PRINCIPLES WE SAY A I SHOULD BE
SOCIALLY BENEFICIAL.
WE ALSO POINT OUT IN OUR RED
LINES OF APPLICATIONS WE WILL
NOT PURSUE WE WON'T PURSUE
APPLICATIONS THAT ARE LIKELY TO
CAUSE OVERALL HARM WE PUT THIS
ONE IN THERE IT'S QUITE.
AN I THINK BROUGHT SO THAT WE
ARE ABLE TO MAKE DECISIONS AS TO
CIVIC THINGS COME UP OFTENTIMES
PEOPLE THINK.
PHYSICAL HARM OR AND MAYBE
SAFETY AT IT MAYBE M. CHEMICAL
HARM THINGS LIKE THAT WE'VE ALSO
INCLUDED IN THAT NOTION ECONOMIC
HARM SOCIETAL HARM SO THAT IS
SOMETHING THAT WE ABSOLUTELY
THINK ABOUT.
I JOIN GOOGLE IN TWENTY FOURTEEN
IN THE FALL SO ALMOST FIVE YEARS
AGO AND IT'S INTERESTING BECAUSE
THE COMPANY HAS CHANGED A LOT
SINCE THAT TIME.
WHEN I FIRST JOINED ACTUALLY
ONLY A SMALL FRACTION OF EVEN
ENGINEERS HAD MACHINE LEARNING
TRAINING I'M THAT'S COMPLETELY
DIFFERENT TODAY WE'VE HAD MORE
THAN THIRTY FIVE THOUSAND
ENGINEERS GO THROUGH MACHINE
LEARNING TRAINING COMPANY?
SO EVEN WITHIN THE MICROCOSM OF
GOOGLE I SEE PEOPLE'S JOBS HAVE
CHANGED YOU THE SKILLS THAT
THEY'VE DEVELOPED HAVE HAD TO
CHANGE AND YOU KNOW MAYBE A LOT
OF TIME FIVE YEARS AGO USED TO
DO A LOT OF HAND PROGRAMMING AS
I WAS MENTIONING.
EARLIER NOW IT'S A LOT MORE
COACHING AND TRAINING AND
LEARNING FROM EXAMPLE AND SO
THOSE TYPES OF JOBS.
HAVE CHANGED WE'VE HAD PEOPLE
FROM ALL SORTS OF OTHER
FUNCTIONS TO LEGALSALES
BUSINESS ETCETERA I'M HAPPY WITH
YOUR MACHINE LEARNING TRAINING
AS WELL TO ADAPT TO THE WAY THAT --
YOU KNOW THE TECHNOLOGY AND THE
COMPANY IS CHANGING I'M WE WE
ANTICIPATE THIS WILL BE THE CASE
IN THE OUTSIDE WORLD AS WELL I
THINK WE'RE ALREADY STARTING TO
SEE THAT SO.
WHAT ARE WAYS THAT DIFFERENT
PEOPLE'S JOBS NEED TO CHANGE
INSIDE THE COMPANY I MENTIONED --
WE ACTUALLY HAD AN EDUCATION
TEAM THAT BUILT A MACHINE
EARNING COURSE THAT WE'VE HAD
THIRTY FIVE THOUSAND ENGINEERS
I'M GO THROUGH. TWO YEARS AGO WE
OPENED THAT COURSE UP SO ANYBODY
CAN TAKE IT AND IT'S IN MORE
THAN ELEVEN LANGUAGES I BELIEVE
RIGHT OUT.
I'M SEE EXACT SAME COURSE THAT
OUR OWN AND EMPLOYEES LEARN FROM.
SO WE'VE OPEN THAT UP EXTERNALLY
THAT SEEM EDUCATION TEAM HAS
ACTUALLY LOOKED ACROSS A WIDE
VARIETY RIGHT I THINK THE FIRST
COURSE WAS TARGETED TOWARDS
ENGINEER SPECIFICALLY.
I'M BUT WE RECOGNIZE THERE'S
LOADS OF DIFFERENT PEOPLE THAT
ARE GONNA NEED TO LEARN THIS AND
THEY MIGHT NOT NEED TO BE CODING
INTENSE OUR FLOOR PYTHON OR ANY
OF THOSE TYPES OF LANGUAGES
MAYBE THEY JUST NEED TO LEARN
HOW TO OPERATE SYSTEMS ARE.
NEED TO LEARN THE BASIC CONCEPTS
THAT KIND OF THING I'M SO WE'VE
RELEASED A WHOLE SET OF
MATERIALS CALLED LEARN WITH
GOOGLE A AYE.
ON OUR WEBSITE I'M AND WE'VE
SEEN EVERYONE FROM ELEMENTARY
SCHOOL AGE CHILDREN I'M LEARNING --
FROM THE COURSES AND TAKING THEM
THERE THE INTERACTIVE AND FUN
ALL THE WAY UP THROUGH PEOPLE
WHO ARE LOOKING AT SECOND THIRD.
FOURTH CAREER SO I THINK THERE'S
A LOT OF IMPORTANCE THERE IN
EDUCATION.
HON YOU TALKED A BIT ABOUT YOU
KNOW HOW DO WE MAKE SUE THAT
PEOPLE DON'T BECOME MORE
OBSESSED WITH TECHNOLOGY AND
MAYBE JUST MORE DRIVEN INTO
PHONES AND THINGS -- I THINK
THERE'S A LOT OF DIFFERENT
PERSPECTIVES ON ON A LOT OF
DIFFERENT PEOPLE THAT NEED TO
COME TOGETHER THEIR ONE EXAMPLE
THAT.
I'M I WILL GIVE FROM A GOOGLE
PERSPECTIVE THOSE WE'VE SEEN USE
OF MACHINE LEARNING FOR I'M
ACTUALLY I'M THE CREATIVE
INDUSTRY TO SPUR I'M BETTER
MUSIC AND ART OR ACTUALLY MAYBE
MORE DIFFERENT MUSIC AND ART SO.
WE'VE BEEN PARTNERING WITH A LOT
OF DIFFERENT MUSICIANS AND THE
FLAMING LIPS AND THEY'VE BEEN
SAYING YOU KNOW AT TIMES AS A
MUSICIAN YOU KNOW WE'VE GOT LOTS
OF IDEAS WE IMPROVISE WE DO.
INTERESTING THINGS BUT I'M THEIR
TIMES ARE WE GET A ROADBLOCK
GREAT I THINK YOU HEAR ABOUT
THIS FROM WRITERS TO WRITER'S
BLOCK OR ARTIST NOT SURE EXACTLY.
ON WHAT THEY WANT TO DO I'M
WE'VE WORKED WITH THEM TO
DEVELOP MACHINE LEARNING MODELS
TRAINED ON BARKER TREE NON
MOZART OR MAYBE TRAIN ON FLAMING
LIPS.
AND SONGS OR COMBINATION ON
CREATING KIND OF DIFFERENT
INSTRUMENT SOUNDS THAT DON'T
EXIST NOW -- BUT THEY CAN USE IT
AND PLAY AROUND WITH IT TO
ACTUALLY JUST GET NEW IDEAS
BURKE KIND OF CREATIVITY ARE
LIKE WHO I NEVER THOUGHT OF
THOSE NOTES IN COMBINATION
TOGETHER BEFORE THOSE
INSTRUMENTS OR THAT TYPE OF
RHYTHM AND THEN THEY'VE BEEN
ABLE TO TAKE THAT RIFF OFF OF IT.
AND COME UP WITH NEW SONGS NEW
PERFORMANCES AND SO I THINK
THAT'S JUST ONE EXAMPLE OF ON
THE WAY THAT AND MAYBE THIS
COULD HELP TRANSFORM A LOT OF
PARTS OF SOCIETY -- WHAT SEEMS
TO UNDERSCORE ALL OF IT IS
YOU'VE GOT TO GET LOTS OF
DIFFERENT PEOPLE INVOLVED IT
CAN'T JUST BE ONE COMPANY OR ONE
INDUSTRY SAYING THIS IS WHAT WE
THINK THE FUTURE LOOKS LIKE?
EDUCATION IS A KEY PART OF THAT
BUT SO IS PARTICIPATION I THINK
A LOT OF PEOPLE HAVE DIFFERENT
INTERESTS AND DIFFERENT VIEWS OF
WHAT THE FUTURE LOOK LIKE IF
THEY ALL HAVE A GOOD
UNDERSTANDING OF MACHINE
LEARNING -- I THINK WE MIGHT BE
ABLE TO BUILD THAT SOCIETY AND
THAT'S A BIT BETTER -- AND AGAIN
WHATEVER YOU MIGHT HAVE
INITIALLY AS YOUR RESPONSE AND
IN ANY -- DIRECTION THAT YOU
COULD GIVE US ON THIS IS.
HOW AS WE MOVE FORWARD WITH THIS?
BIG CHANGE IN OUR WORLD.
HOW DO WE MAKE SURE THAT IT IS?
EQUITABLY.
LEARNED AND TAUGHT.
BUT THROUGHOUT THE WORLD AND
THROUGHOUT OUR COMMUNITIES SO IT
DOESN'T BECOME SOMETHING THAT A
VERY ELITE GROUP OF PEOPLE.
KNOW HOW TO AND I DON'T MEAN THE
USE OF IT.
YEAH THE USE OF IT.
EVERYBODY SEEMS TO EVEN I CAN
PICK UP OF THE USE OF A LOT OF
THIS TECHNOLOGY I'M TALKING
ABOUT THE CREATED THE THAT
CREATORS -- BECAUSE THAT'S WERE
REAL STRENGTH IS YEAH IT'S IT'S
NOT JUST IN THE USERS THE
PASSIVE.
UP PART OF IT IT'S WHAT ABOUT
THE CREATOR SO.
IT REALLY I THINK IT'S REALLY
IMPORTANT FOR COMPANIES LIKE
GOOGLE. TO BE ESPECIALLY
VIGILANT AND PRO ACTIVE.
IN MAKING SURE THAT.
OF THE THE FRONT END THE FRONT.
PART YES -- THIS NEW LEARNING
AND TECHNOLOGY AND AND AI.
IS REALLY TAKEN EQUALLY OUT OUR
COMMUNITIES AND THROUGHOUT
DIFFERENT PARTS OF THE WORLD
THIS OTHERWISE WE JUST
PERPETUATING.
A LOT OF YOU KNOW BAD ECONOMICS --
SEGREGATION IN YOU KNOW IN THE
BIG USE OF OF THE TERM SO I GET
REALLY CONCERNED ABOUT THAT --
THAT.
WERE JUST NOT MAKING SURE.
IT'S GETTING OUT THERE AND IT'S
ADVANCING SO MUCH.
AND MANY COMMUNITIES ARE GETTING
LEFT BEHIND MANY COUNTRIES ARE
GETTING LEFT BEHIND SO.
HOW DOES GOOGLE ADDRESS THAT
YEAH?
I THINK THAT'S SOMETHING THAT
WE'RE CONCERNED ABOUT AS WELL I
MENTIONED IT A LITTLE BIT
EARLIER.
IN MY REMARKS ON SO COUPLE OF
DIFFERENT POINTS ONE IS ACTUALLY
COMPARED TO EARLIER TECHNOLOGIES
THAT HAVE EXISTED IF YOU LOOK AT
AND MAYBE CHEMISTRY OR
BIOTECHNOLOGY OR SOME OF THE
OTHERS.
AND YOU KNEW THAT THE BARRIER TO
ENTRY FOR ARTIFICIAL
INTELLIGENCE IS ACTUALLY QUITE A
BIT LOWER YOU DON'T ACTUALLY
NEED A FANCY LAB OR ACCESS TO
EXPENSIVE CHEMICALS.
OR BIG MACHINES LIKE IN NUCLEAR
MAGNETIC RESONANCE OR OR X. RAYS
ARE MICROSCOPES OR THINGS LIKE
THAT THE BARRIER TO ENTRY
ACTUALLY FOR ANYBODY TO LEARN
HOW TO CODE IS MAYBE.
A LAPTOP WERE ON A PHONE --
THERE'S LOTS OF MACHINE LEARNING
MODELS ACTUALLY OPERATE DIRECTLY
ON PHONE I'M WE'VE ACTUALLY I'M.
L. AMONG OTHERS BEEN PUTTING OUT
SOME KIND OF TOOLS THAT ARE EVEN
MADE OUT OF CARDBOARD BOXES BUT
HAVE A LITTLE RASPBERRY PI
CIRCUIT INSIDE.
EITHER FIFTY DOLLARS THEY'RE NOT
FREE BUT THEY ARE SOMETHING
WE'RE CALLING THEM A AYE WHY
KIDS THE SAME IDEAS LIKE D. I.
Y. BUT A AYE WHY SO I'M SCHOOL
CHILDREN CAN ACTUALLY.
BUILD THEIR OWN YOU KNOW SPEECH
TO TAX OR IMAGE RECOGNITION OR
THINGS LIKE THAT MODELS ON
THINGS THAT ARE DONE ON PHONES
OR ON COMPUTERS COULD BE
VIRTUALLY FREE AS LONG AS YOU'VE
GONE INTERNET CONNECTION OR
ACCESS TO THE SITE SO I THINK.
THE BARRIER TO ENTRY COMPARED TO
PREVIOUS TECHNOLOGIES IS QUITE A
BIT LOWER.
THAT BEING SAID PEOPLE STILL
HAVE TO KNOW ABOUT HE
OPPORTUNITY TO USE THESE
TECHNOLOGIES AND TOOLS
OPPORTUNITY TO LEARN ABOUT THEM --
WORK TRYING TO DO THAT THROUGH A
LOT OF DIFFERENT WAYS I TALKED
ABOUT EDUCATION AND WE'VE GOT
PROGRAMS IN CLASSROOMS IN THE U.
S. IN CALIFORNIA AND AND AROUND
THE WORLD.
AND JUST IN AT LAST OCTOBER WE
ANNOUNCED A CHALLENGE CALLED THE
GOOGLE TWENTY FIVE MILLION
DOLLARS A AYE IMPACT CHALLENGE
WHERE WE PROVIDED AT AN OPEN
CALL TO ANYBODY AROUND THE WORLD.
TO TRY TO THINK ABOUT WAYS A I
COULD ADDRESS PROBLEMS THAT
THEY'RE WORKING ON JUST IN MAY
SO JUST LAST MONTH WE ANNOUNCE
THE WINNERS OF THOSE.
I'M INCLUDING NINE FROM THE US
ONE FROM ALIFORNIA.
I'M REALLY LOOKING AT INNOVATIVE
WAYS THAT PEOPLE CAN.
USE THE TECHNOLOGY.
THE TEAMS DID NOT HAVE MACHINE
LEARNING EXPERIENCE OR EXPERTISE
SO THEY HAD IDEAS OF HOW THEY
MIGHT BE ABLE TO USE IT BUT
DIDN'T HAVE HANDS ON I'M KIND OF
KNOWLEDGE DATE PROPOSED THEIR
IDEAS AND I WAS SOMETHING THAT
WE THOUGHT WAS.
I'M REALLY EXCITING WE'VE SEEN
THEM ALREADY IN THE PAST FEW
MONTHS MAKE SIGNIFICANT GAINS ON
THEIR PROJECTS WE BROUGHT THEM
INTO GOOGLE LAST MAY FOR I'M
KIND OF A WHOLE WEEK WE CALLED
IT A BOOT CAMP I'M TRAINING IN.
MACHINE LEARNING PAIRED WITH I'M
EXPERTS I'M HANDS ON MENTOR SHIP
THINGS LIKE THAT BUT I THINK
THEY ARE GREAT EXAMPLES AND
WE'RE STARTING TO SEE A LOT OF
OTHERS HIGH SCHOOL STUDENTS ON
PEOPLE IN AND COMMUNITIES AND
OTHERS.
WHO ARE LEARNING A LOT OF THIS
ON THEIR OWN THROUGH THREE
MATERIALS THROUGH A LITTLE BIT
OF MENTORSHIP A LITTLE BIT OF
HELP A LITTLE BIT OF -- SEED
FUNDING SO I THINK THERE'S A LOT
OF EXAMPLES OUT THERE PEOPLE WHO
CAN ACTUALLY LEARN THIS THEY
DON'T NEED TO BE EXPERTS DON'T
NEED A PHD I'M BUT DO YOU NEED
TO BE WILLING TO INVEST A LITTLE
BIT OF TIME -- AND EFFORT INTO.
LEARNING AND KIND OF PRACTICING
BUT YEAH I THINK THERE'S A LOT
OF OPPORTUNITIES HERE
[inaudible]
THANK YOU.
YOUR CHILD THANK YOU VERY MUCH
MOST INTERESTING TESTIMONY AND
I'M SURE THAT OUR PATHS WILL
CROSS AGAIN HERE.
THANK YOU ALL RIGHT NEXT WE HAVE --
DOCTOR JOSH WILL CRAWL ON DOCTOR
KROLL IS THE POST -- DOCTORAL
RESEARCH SCHOLAR IT.
THAT IS THE RELATIONSHIP BETWEEN
GOVERNANCE PUBLIC POLCY AND
COMPUTER SYSTEMS DR CROLLES
RESEARCH FOCUS ON HOW TECHNOLOGY
FITS WITHIN A HUMAN DRIVEN
NORMATIVE CONTEXTS.
HE IS MOST INTERESTED IN THE
GOVERNANCE OF AUTOMATED DECISION
MAKING SYSTEMS ESPECIALLY THOSE
USING MACHINE LEARNING.
DOCTOR CLOSE PREVIOUS WORK SPANS
ACCOUNTABLE ALGORITHMS
CRYPTOLOGY CRYPTOGRAPHY.
SOFTWARE SECURITY FORMAL METHODS
BIT COIN IN THE TECHNICAL
ASPECTS OF CYBER SECURITY.
DOCTOR CROW HOLDS A MASTERS AND
A PHD IN COMPUTER SCIENCE FROM
PRINCETON UNIVERSITY WHERE HE
RECEIVED THE NATIONAL SCIENCE
FOUNDATION GRADUATE RESEARCH
FELLOWSHIP IN.
TWO THOUSAND ELEVEN DOT CROLLES
GOING TO SPEAK TO US ABOUT HIS
SOME OF HIS RESEARCH.
AND SOME LEGISLATIVE
IMPLICATIONS FOR ARTIFICIAL
INTELLIGENCE THANK YOU DOCTOR
CROW FOR BEING HERE CREATION.
THANK YOU CHAIRMAN AMBERG
SENATOR -- OTHER MEMBERS OF THE
COMMITTEE -- FOR THE OPPORTUNITY
TO SPEAK ARE I GUESS I CAN SKIP
OVER MY BIO BECAUSE YOU'VE GIVEN
EVEN MORE THANI HAD PLANNED.
TO OUR MY WERE QUITE IMPRESSIVE
THOUGH SO THANK YOU.
YEAH WELL THANK YOU -- MY WORK
FOCUSES AS YOU MENTIONED ON THE
NEED TO DESIGN COMPUTER SYSTEMS
TO SUPPORT HUMAN VALUES SUCH AS
FAIRNESS PRIVACY SECURITY AND
LEGAL COMPLIANCE WHEN COMPUTERS
ARE USED TO MAKE LIFE ALTERING
DECISIONS SUCH AS WHO WINS AN
ELECTION.
WHO GETS ACCESS TO FINANCIAL
PRODUCTS ARE AND WHETHER SOMEONE
SHOULD BE INCARCERATED OR
WHETHER A DIAGNOSTIC IMAGE SHOWS --
EVIDENCE OF DISEASE.
AS WE MOVE INTO A WORLD WHERE
ARTIFICIAL INTELLIGENCEINCREASES THE NUMBER STEAKS AND
SPEED OF THESE DECISIONS IT IS
ESSENTIAL THAT WE DESIGN SYSTEMS
TO SUPPORT HUMAN VALUES AND TO
BE SUBJECT TO ROBUST GOVERNANCE.
SO THAT WE CAN ENSURE THAT
PEOPLE AND ORGANIZATIONS.
COUNTABLE FOR THEIR ACTIONS.
HERE I USE THE TERM ARTIFICIAL
INTELLIGENCE SLIGHTLY
DIFFERENTLY THAN THE OTHER
WITNESSES TO MEAN ANY BEHAVIOR
BY MACHINE THAT A PERSON WOULD
CONSIDER TO BE INTELLIGENT
REGARDLESS OF WHETHER THAT.
I WANT TO MAKE THREE POINTS
TODAY.
FIRST WELL THEIR MECHANICAL
COMPUTERS SHOULD NOT BE
CONSIDERED OBJECTIVE.
SECOND THERE EXIST BOTH
TECHNICAL AND NONTECHNICAL
METHODS FOR CONTROLLING SOFTWARE
BASED SYSTEMS AND HOLDING THEM
TO HIGH STANDARDS OF FITNESS FOR
USE.
I INCLUDING APPROPRIATELY
ACCOUNTING FOR VALUES SUCH AS
FAIRNESS AND SECURITY AND
VERIFYING TO REGULATORS
OVERSIGHT ENTITIES AND THE
PUBLIC AT LARGE THAT THESE
STANDARDS ARE BEING MET.
AND THIRD WELL THERE IS NO
UNIVERSAL WAY TO UNDERSTAND THE
IMPACT AND CONSEQUENCES OF A
PARTICULAR COMPUTER SYSTEM.
GOVERNANCE REGIMES BASED ON
ROBUST ACCOUNTABILITY HOLD THE
GREATEST PROMISE OF ENABLING THE
BENEFITS OF TECHNOLOGY WHILE
MINIMIZING HARMS. TO MY FIRST
POINT ALTHOUGH COMPUTERS ARE
OFTEN DESCRIBED AS MECHANICAL
AND THEREFORE OBJECTIVE WE MUST
UNDERSTAND THAT ALL TECHNICAL
SYSTEMS ARE IN TRUTH SO SHOULD
TECHNICAL SYSTEMS MEANING THEY
INCLUDE PEOPLE ORGANIZATIONS
INSTITUTIONS AS WELL AS LEGAL
AND SOCIAL.
THE IMAGINED OBJECTIVITY OF
COMPUTERS DERIVES FROM THEIR
MECHANICAL NATURE AND THEIR
RELIANCE ON DATA ABOUT THE WORLD --
BUT CHOICES ABOUT WHICH DATED TO
GATHER WHICH DATED TO USE AND
THE NATURE OF THAT USE WORK
TOGETHER TO CAPTURE EXISTING
SOCIETAL INEQUITIES.
DATA RESULT FROM PROCESS OF
MEASUREMENT AND CAN
SYSTEMATICALLY DEVIATE FROM THE
UNDERLYING PHENOMENON OF
INTEREST A PROBLEM KNOWN
TECHNICALLY AS THE PROBLEM OF
BIAS.
MEASUREMENT CHOICES ARE JUST ONE
EXAMPLE OF THE DESIGN CHOICES
MADE WHEN AND I SYSTEMS ARE
CONSTRUCTED OR DEPLOYED INTO THE
WORLD.
NO DECISION IS PURELY TECHNICAL
OR ENTIRELY FREE OF POLITICAL
CONSIDERATIONS AND NO COMPUTER
SYSTEM.
SHOULD BE CONSIDERED TO REVEAL
OBJECTIVE TRUTH EVEN SYSTEMS
THAT ARE BASED ON DATA ABOUT THE
WORLD AS MANY I SYSTEMS ARE.
INDEED S. SYSTEMS CAN AND DO
REFLECT AND REINFORCE EXISTING
SOCIAL STRUCTURES AND BIASES
DISCRIMINATING AGAINST
VULNERABLE PEOPLE AND OFTEN --
INADVERTENTLY TREATING.
GROUPS LESS WELL THAN
HISTORICALLY ADVANTAGE GROUPS.
MACHINES PLAY FORWARD THE
POLITICAL CHOICES MADE DURING
THEIR DESIGN AND CONSTRUCTION.
WHEN SYSTEMS ARE BASED ON
HISTORICAL INFORMATION THAT
REFLECTS DISCRIMINATION?
THE CHOICE TO USE THIS
INFORMATION REFLECTS A
PARTICULAR PERSPECTIVE ON HOW
SUCH SYSTEMS SHOULD WORK. FOR
EXAMPLE RESEARCH HAS SHOWN THAT
FACE DETECTION SYSTEMS WHICH
IDENTIFY WHETHER A PHOTOGRAPH
HAS A FACE IN IT WORK LESS WELL
FOR DARK SKINNED PEOPLE THAN FOR
WHITE PEOPLE AS WELL AS LESS
WELL FOR WOMEN THAN FOR MEN.
AND THE PERFORMANCE FOR DARK
SKINNED WOMEN IS EVEN WORSE
TRANSFORMING A MOSTLY FUNCTIONAL
BUT OCCASIONALLY AIRING SYSTEM
THAT WORKS FOR NINE OUT OF TEN
PEOPLE INTO A BROKEN ONE THAT
WORKS ONLY TWO FOR ONLY TWO OUT
OF THREE I OTHER RESEARCH TO
WHICH I CONTRIBUTED.
DEMONSTRATED THE POTENTIAL FOR
FALSE MATCHES IN FACE
RECOGNITION SYSTEMS.
WHICH ASSOCIATE AN IDENTITY WITH
A DETECTIVE FACE.
ARE THESE FALSE MATCHES INCLUDED
NEARLY TWICE AS MANY FALSE
MATCHES FOR DARK SKIN FACES AS
FOR LIGHT ONCE.
BOTH KINDS OF UNEQUAL FAILURE
CAN BE ATTRIBUTED TO A
COMBINATION OF THE DESIGN
EVALUATION WORK FLOWS OF THE
SYSTEM'S NOT CONSIDERING
SUFFICIENTLY DIVERSE DATA.
AND DECISIONS IN THE EARLY
HISTORY OF PHOTOGRAPHY ABOUT HOW
TO BUILD A AND DEVELOP CAMERAS
AND FILM TECHNOLOGY THAT WOULD
CAPTURE WHITE FACES ACCURATELY.
EVEN IF WE STIPULATE THAT A FACE
PROCESSING SYSTEM COULD WORK
PERFECTLY.
I ITS USE WOULD TEND TO ENABLE
SURVEILLANCE AND POLICING.
BOTH A PRACTICES THAT HAVE BEEN
DEPLOYED HEAVILY IN THE PAST
AGAINST MINORITY GROUPS FOR
WHICH THE TECHNOLOGY IS ALREADY
LESS ACCURATE -- SO MAKING IT
MORE ACCURATE WOULD CAUSE THOSE
GROUPS TO BE POLICE -- TO AND
SURVEILLED MORE HEAVILY I AND A
BILL LIMITING THE USE OF FACE
SURVEILLANCE AND POLICE BODY
CAMERAS IS CURRENTLY PENDING
BEFORE THIS BODY AS A B..
TWELVE FIFTEEN IT IS.
IN A DIFFERENT CONTEXT RESEARCH
BY JOURNALISTS AT PROPUBLICA IT
DEMONSTRATED THAT A TOOL USED TO
ESTABLISH THE RISK OF COUNTY
FLORIDA FALSELY RATED BLACK
ARRESTEES AS HIGH RISK FOR
FUTURE CRIME AT NEARLY TWICE THE
RATE.
OF WHITE ARRESTEES EVEN WILL
CORRECTLY ESTABLISHING THE RISK
OF FUTURE REST FOR BOTH GROUPS.
THIS COUNTER INTUITIVE RESULT
CAN BE ATTRIBUTED TO THE FACT
THAT BLACK PEOPLE IN BROWARD
COUNTY ARE ARRESTED AS
SUBSTANTIALLY HIGHER RATE THAN
WHITE PEOPLE.
MATHEMATICALLY GUARANTEEING THAT
CALIBRATING RATINGS TO RISK
WOULD LEAD TO UNEQUAL AIR
DISTRIBUTION IT'S REPUBLICANS
STUDY HAS SPAWNED MUCH RESEARCH
ON BIAS AND DISCRIMINATION AND I
SYSTEMS.
RECENTLY PASSED AND NOW RECALLED
SB TEN MANDATES THE USE OF
SIMILAR RISK ASSESSMENTS TO
DETERMINE PRE TRIAL SANCTIONS AS
PART OF THE LAUDABLE GOAL OF
ELIMINATING MONEY BACK.
BUT WITH FEW CONTROLS ON WHETHER
THESE TOOLS PROMOTE JUSTICE DUE
PROCESS OR THE EQUITABLE
ADMINISTRATION OF CRIMINAL
PROCEDURE RISK ASSESSMENT TOOLS
LEAD TO IMPORTANT NEW GOVERNANCE
QUESTIONS.
ON THAT WE DON'T YET HAVE
ANSWERS TO ALTHOUGH I DID
CONTRIBUTE TO A REPORT BY THE
AIR RESEARCH COMMUNITY THAT WAS
COORDINATED.
I AM RELEASED BY A MULTI
STAKEHOLDER GROUP CALLED THE
PARTNERSHIP ON A AYE FOR THE
BENEFIT OF PEOPLE IN SOCIETY.
WHICH LOOKS AT THE GOVERNANCE OF
SUCH RISK ASSESSMENT SYSTEMS AND
LAYS OUT A BASELINE OF TEN
ISSUES.
WITH WHICH A RESPONSIBLY
GOVERNED RISK ASSESSMENT --
APPROACH MUST GRAPPLE.
EVEN DECISIONS ABOUT WHAT
COMPUTER SYSTEMS TO BUILD OUR
POLITICAL DECISIONS.
STUDIES HAVE SHOWN THAT SIMPLY
REMINDING PEOPLE OF THEIR COURT
DATES FOR EXAMPLE BY TEXT
MESSAGE SIGNIFICANTLY IMPROVES
APPARENT IMPROVES APPEARANCE
RATES WITHOUT COMPARING
ALTERNATIVE APPROACHES AND
STARTING FROM THE PERSPECTIVE OF
WHAT A SYSTEMS GOALS ARE.
WE RISK CEDING CONTROL OVER
IMPORTANT PUBLIC FUNCTIONS TO
PLACES BEYOND THE REACH OF
GOVERNANCE.
DECISIONS ABOUT WHO WILL BE
RELEASED DURING THE PRE TRIAL
PERIOD AND WHO WILL BE DETAINED
STAND TO BE INFLUENCED MORE BY
DATA SCIENTISTS AND BY JUDGES.
AND THE SCIENTISTS ARE NOT
CONNECTED TO THE PUBLIC POLICY
MAKING PROCESS.
THE FACT THAT JUDGES HAVE THE
FINAL SAY ON THESE COMPUTER
GENERATED RECOMMENDATIONS IS
COLD COMFORT IN LIGHT OF
RESEARCH ON AUTOMATION BIAS THE
DIFFERENCE OF HUMANS TOWARDS
MACHINE GENERATED DECISIONS.
AND RESEARCH REVEALING THE
MANIPULATION OF SCORES BY COURT
CLERKS ARE OTHER PROFESSIONALS
IN THE CRIMINAL JUSTICE SYSTEM
WHO GATHER AND ENTER THE DATA.
FROM WHICH THE SCORES ARE
CALCULATED.
MY SECOND POINT IS THE TECHNICAL
TOOLS AND NONTECHNICAL
INTERVENTIONS CAN HELP US
CONSTRUCT SOFTWARE THAT IS
RELIABLE.
BOTH FIT FOR PURPOSE AND SOME.
THIS REQUIRES A PARADIGM SHIFT
AWAY FROM A MINDSET THAT WE
BUILD COMPUTER SYSTEMS AND ONLY
THEN ASSESS THEIR IMPACTS ON
SOCIAL AND POLITICAL VALUES.
I AND THEN CONSIDER MODIFYING
THEM BASED ON THAT ASSESSMENT.
INSTEAD THE SYSTEMS MUST BE
DESIGNED FROM THE START TO
REFLECT OUR VALUES IN THEIR
REQUIREMENTS REQUIREMENTS ARE
CRITERIA ESTABLISHED AT THE
BEGINNING OF A SYSTEMS LIFECYCLE
DESCRIBING WHAT IT SHOULD AND
SHOULD NOT DO.
I AND EXPLICITLY INCLUDING THESE.
GOALS AND CONSTRAINTS SUCH AS
PROTECTING PRIVACY OR ADVANCING
FAIRNESS.
COMMON INDUSTRY PRACTICES SUCH
AS SOFTWARE TESTING CODE REVIEW
AN EXPLICIT TRACKING BUGS ALL
SERVE TO IMPROVE SECURITY
RELIABILITY IN VARIOUS WAYS AND
BRING US CLOSER TO THESE GOALS.
BUT EVEN WITH SUCH METHODS BUGS
IN VULNERABILITIES ARE PERCEIVED
AS INEVITABLE.
WELL NO SYSTEM CAN BE PERFECT
COMPUTER SCIENCE OFFERS A SUITE
OF RICHER AND MORE POWERFUL
TOOLS INCLUDING CRYPTOGRAPHY
SUFFER VERIFICATION.
AND MATHEMATICAL UNDERSTANDINGS
OF THE CAPABILITIES AND
LIMITATIONS OF MACHINE LEARNING
TECHNOLOGIES.
ALL OF THESE SUPPORT STRONGER
CLAIMS ABOUT THE RELIABILITY
FITNESS FOR PURPOSE AND
PRESERVATION OF VALUES SUCH AS
PRIVACY SECURITY IN FAIRNESS IN
COMPUTER SYSTEMS.
OF MY OWN WORK HAS DEMONSTRATED
A HOW TO BUILD ENHANCED AUDIT
LOGS FOR AUTOMATED DECISION
MAKING SYSTEM SO THAT CONSUMERS
TO RECEIVE.
SAY CREDIT SCORE CAN BE CERTAIN
THAT A COMPLETE JUSTIFICATION
FOR THEIR SCORE EXISTS MEANING
THAT THE FORMULA FOR GENERATING
SCORES REPORTED SOMEWHERE ALONG
WITH THEIR CREDIT HISTORY.
I AND ALONG WITH THE FACT THE
FORMULA APPLIED TO THEIR
PERSONAL CREDIT HISTORY
GENERATES THEIR PARTICULAR SCORE.
THESE TOOLS CAN ALSO BE USED TO
DEMONSTRATE THAT THE SAME
DECISION POLICY FOR EXAMPLE THE
SAME CREDIT SCORING FORMULAS
APPLIED TO EVERYONE.
ALL THIS IS POSSIBLE WHILE
PRESERVING THE PROPRIETARY
NATURE OF THE DECISION POLICY
FOR EXAMPLE THE SECRECY OF THE
CREDIT SCORING FORM.
A I SYSTEMS NEED NOT BE FAULTY
UNRELIABLE BLACK BOXES WHICH LIE
BEYOND HUMAN UNDERSTANDING AS
THEY ARE OFTEN PORTRAYED.
THIS IS A POLITICAL CHOICE.
SOFTWARE SYSTEMS CAN INSTEAD BE
DESIGNED TO FUNCTION CORRECTLY
IN ALL SITUATIONS I OR AT LEAST
TO CONTAIN FAILURES TO
PARTICULAR SUB SYSTEM SO THAT
THEY DO NOT IMPAIR THE OVERALL
RELIABILITY OR FITNESS FOR USE.
THE IMAGINED INSPIRED ABILITY OF
COMPUTER SYSTEMS STEMS FROM
DIFFERENCES IN KNOWLEDGE AND
POWER DYNAMICS BETWEEN SYSTEM
CONTROLLERS.
SYSTEM CONSUMERS AND SYSTEM
OVERSEERS.
ALTHOUGH LARGE OFFER PLATFORMS
OFTEN CLAIM THAT THEY CANNOT
EXPLAIN WHY A PARTICULAR
ADVERTISEMENT WAS SHOWN.
WHY A PARTICULAR SEARCH RESULT
WAS RANKED AS IT WAS OR WHEN AND
HOW OFTEN A PARTICULAR SOCIAL
NETWORK POST WILL BE VIEWED?
THE SAME COMPANIES ARE OFTEN
HIGHLY CERTAIN OF WEATHER
CHANGES TO THEIR ALGORITHMS WILL
INCREASE OR DECREASE REVENUES.
OR CHANGE THE BEHAVIORS OF THEIR
USERS IN PARTICULAR WAYS.
CERTAIN ASPECTS OF THE COMPUTING
ECOSYSTEM FOR EXAMPLE THE GOOGLE
HOMEPAGE HAVE BECOME SO
CONSISTENTLY AVAILABLE THAT
OUTAGES ARE NOW BECAUSE FOR NEWS
STORIES.
AND JUSTICE AIRPLANES ELEVATORS
AND BRIDGES HAVE BEEN IMPROVED
SO THAT YOU AND I CAN RELY ON
THEM WITHOUT A NEED FOR A DEEPER
DETAILED UNDERSTANDING OF HOW OR
WHY THEY WORK.
SO TO CAN SOFTWARE BE DESIGNED
AND BUILT TO MEET STANDARDS OF
PROPER FUNCTION IN A CONVINCING
WAY.
AND JUST AS THE FEDERAL AVIATION
ADMINISTRATION THE ELEVATOR UNIT
OF THE OCCUPATIONAL SAFETY AND
HEALTH DIVISION OR THE
DEPARTMENT OF TRANSPORTATION.
PARLAY THOSE TECHNICAL
ASSURANCES INTO THE TRUST OF
AVERAGE CITIZENS.
SO COULD AN APPROPRIATE
REGULATORY REGIME FOR SOFTWARE
PARLAY THE CERTAINTIES OF
SOFTWARE BASED SYSTEMS INTO
BROAD SOCIAL TRUST.
THIS BRINGS ME TO MY THIRD POINT
WHICH IS THAT HUMANS AND
ORGANIZATIONS MUST BE HELD
RESPONSIBLE FOR THE BEHAVIOR OF
COMPUTER SYSTEMS AND ESPECIALLY
A AYE SYSTEMS.
UNFORTUNATELY COMPUTER SYSTEMS
TEND TO UNDERMINE EXISTING
GOVERNMENT STRUCTURES
CHALLENGING ASSUMPTIONS ABOUT
THE NATURE OF FAILURES THE
ABILITY TO EXAMINE AND ANALYZE
DECISION MECHANISMS AND THE
SPEED AND SCALE OF DECISION
MAKING.
MERELY EXPLAINING SOFTWARE I
PUTS TO HUMANS IS UNLIKELY TO
HELP ON ITS OWN.
AND PLACING A HUMAN INTO THE
WORK FLOW ARTIFICIALLY LIMITS
THE PROMISE OF ECONOMY THESE
SYSTEMS OFFER WILL
SIMULTANEOUSLY PREVENTING THEIR
APPLICATION IN CERTAIN DOMAINS
WHERE THEY CAN BE
EXTRAORDINARILY VALUABLE.
FURTHER STILL WE KNOW THAT HUMAN
DECISION MAKING CAN BE FLAWED.
I AND YET WE TREATED AS A GOLD
STANDARD BUT COMPUTERS ARE
MACHINES WE CAN DESIGN THEM SO
THAT WE KNOW HOW THEY WILL
BEHAVE IN ALL CASES.
THAT'S WE CAN HOLD THEM TO
HIGHER STANDARDS OF PERFORMANCE
AND TRANSPARENCY THAN EVEN HUMAN
BUREAUCRACIES.
ALL TOO OFTEN COMPUTER SYSTEMS
FAILED TO REFLECT THE VALUES WE
DESIRE THEM TOPPLED.
SOFTWARE IS EXCELLENT AT
IMPLEMENTING CLEAR CUT RULES AT
HIGH SPEED ACROSS LARGE
POPULATIONS HOWEVER COMPUTERS
EVEN WITH THE ADVENT OF ADVANCED
AI.
ARE LESS APT TO DEALING WITH
SITUATIONS THAT REQUIRE
REASONING BEYOND STATED RULES --
OR THAT REQUIRE INTERPRETATION
THE APPLICATION OF THOSE RULES
FLEXIBLE STANDARDS ABSTRACT
PRINCIPLES AND THE NORMAL
INTENTIONAL AMBIGUITY IN
CONTRACTS AND LEGISLATION ALL
LIE BEYOND THE MECHANISTIC
OPERATION OF SOFTWARE.
WELL COMPUTER SCIENTISTS CAN CAN
CAN GUARANTEE THE FIDELITY OF
SOFTWARE -- TO ARTICULATED
REQUIREMENTS THE REAL WORLD
REQUIRESMORE FLEXIBILITY.
INSTEAD TO SUPPORT THESE HIGH
MINDED GOALS WE MUST HIGH HUMAN
INSTITUTIONS SUCH AS COURTS
JUDGES OVERSIGHT ENTITIES
LEGISLATIVE COMMITTEES -- INTO
COMPUTER SYSTEMS DESIGNING SO
SHE TECHNICAL SYSTEMS WHICH
IMPROVE UPON THE GOVERNMENT
STRUCTURES WE HAVE TODAY.
YET WITH THAT IN MIND POLICY
MUST NOT MANDATE THE DESIGN OF
TECHNOLOGY INSTEAD THE HUMANS
AND HUMAN ORGANIZATIONS TO
CREATE A ÁI SYSTEMS MUST BE
MADE RESPONSIBLE FOR THE SAFE
INAPPROPRIATE OPERATION OF THE
SYSTEMS.
THAT IS POLICY INTERVENTION
SHOULD SPECIFY WHAT THE
CONTROLLERS OF COMPUTER SYSTEMS
ARE RESPONSIBLE FOR RATHER THAN
THE MANNER IN WHICH THE SYSTEM
SHOULD ACHIEVE THOSE ASSURANCES.
PERHAPS SETTING MINIMUM
STANDARDS OR GUIDELINES FOR
PROCUREMENT ALONG THE WAY.
HOLDING THE CREATORS AND
CONTROLLERS OF A AYE SYSTEMS
RESPONSIBLE FOR THEIR BEHAVIORS
PRESERVES THE FLEXIBILITY FOR
INNOVATION WHILE PROVIDING
AVENUES FOR GOVERNANCE AND
OVERSIGHT.
SUCH RESPONSIBILITY WILL REQUIRE
THE DEFINITION OF AND OR THE
DEVELOPMENT OF NEW BEST
PRACTICES IN A AYE DEVELOPMENT
THAT TIGHT TECHNICAL AND
ORGANISATIONAL CONTROLS INTO THE
SUPPORT.
OF OPERATIVE HUMAN VALUES.
TOUGHER SYSTEM DEVELOPERS ARE
CURRENTLY UNANSWERABLE FOR THEIR
DECISIONS EVEN WHEN THOSE
DECISIONS CAUSE HARM.
STAKEHOLDERS RARELY HAVE ANY
PUBLIC FORUM IN WHICH TO EXPRESS
THEIR NEEDS AND CONCERNS.
WELL PROTECTIONS FOR PROPRIETARY
TECHNOLOGY AND INTELLECTUAL
PROPERTY INTERESTS HAVE TENDED
TO SHIELD SYSTEM DESIGNERS FROM
THE NEED TO RESPOND TO REQUESTS
FOR INFORMATION. ONE STUDY
APPLIED OPEN RECORDS LAWS TO
SMART CITY AUTOMATION PROJECTS
IN FORTY TWO JURISDICTIONS
ACROSS TWENTY THREE STATES
REPRESENTING DEPLOYMENTS OF SIX
DIFFERENT TYPES OF PREDICTIVE A
AYE SYSTEMS.
ONLY ONE COUNTY WAS ABLE TO
PROVIDE A LEVEL OF TRANSPARENCY
CONSISTENT WITH DECISION MAKING
BY GOVERNMENT AND HUMAN
BUREAUCRACIES RATHER THAN BY
PRIVATE SECTOR AND A AYE SYSTEMS.
WELL GOVERNOR A AYE REQUIRES A
MORE ROBUST PUBLIC SPHERE AROUND
THE SYSTEM DESIGN -- AND
DEPLOYMENT CONSIDERATIONS THAT
THE SYSTEM'S ENCOUNTER.
ALTHOUGH IT IS OFTEN SUGGESTED
AS A SOLUTION HOWEVER FULL
TRANSPARENCY OF SOFTWARE SYSTEMS
IS GENERALLY NEITHER NECESSARY
BECAUSE OF THE ASSURANCE
TECHNIQUES.
A MENTIONED PREVIOUSLY AND THE
DISCUSSION THAT -- WAS HAD WITH
DOCTOR CHAO ABOUT.
THE RELATIONSHIP BETWEEN
TRANSPARENCY AND THE SPECIFIC
THINGS THAT PEOPLE NEED TO KNOW.
OUR NORRIS TRANSPARENCY
SUFFICIENT BECAUSE SOFTWARE --
THAT IS NOT DESIGNED TO
FACILITATE ASSURANCE MAY IN FACT
BE IMPOSSIBLE TO ANALYZE FOR
TECHNICAL PERSPECTIVE.
THE TRANSPARENCY IS OFTEN
UNDESIRABLE IT PRESENTS RISKS TO
INDIVIDUAL PRIVACY IN TRADE
SECRECY WELL FACILITATING THE
STRATEGIC GAMING OF AUTOMATED
SYSTEMS.
OUGHT TECHNOLOGIES CREATING NEW
OPPORTUNITIES FOR GOVERNMENTS
THAT ARE STRUCK THAT ARE SUBTLER
AND MORE FLEXIBLE THAN TOTAL
TRANSPARENCY -- AND AND WE
SHOULD PURSUE THAT THAT ROUTE OF
COURSE THIS DISCUSSION ALLIED'S
A NUMBER OF IMPORTANT QUESTIONS
IN THE POLICY OF ARTIFICIAL
INTELLIGENCE.
THE I. INDUSTRIES HUNGER FOR
DATA ABOUT INDIVIDUAL CONSUMERS
AND CITIZENS LEADS TO NEW
THREATS TO PRIVACY.
THE USE OF STATISTICAL
TECHNIQUES TO IN FIRST SENSITIVE
INFORMATION SUCH AS HEALTH
STATUS WITHOUT ITS BEING
EXPLICITLY DISCLOSE CHALLENGES
THE ASSUMPTIONS OF EXISTING DATA
PROTECTION LAWS.
INCLUDING THE NEWLY ENACTED
CALIFORNIA CONSUMER PRIVACY. FOR
EXAMPLE ONE MAJOR RETAILER
REPORTEDLY DEVELOPED A SYSTEM
FOR PREDICTING WHICH OF ITS
CUSTOMERS WERE PREGNANT BASED ON
THEIR PURCHASE HISTORIES RAISING
THE SPECTER OF NEW FORMS OF
HEALTH BASED DISCRIMINATION.
FROM ACTORS WITH NO OVER ACCESS
TO HEALTH CARE INFORMATION.
THERE'S ALSO WIDE AGREEMENT THAT
IS A AYE AUTOMATES AN INCREASING
NUMBER OF TASKS THE NUMBER AND
NATURE OF JOBS REMAINING FOR
HUMANS WILL CHANGE DAMASCUS.
THIRD WILL CHANGE DRAMATICALLY.
AS NEW AND MORE AUTOMATED
SYSTEMS WORK DISPLACE EXISTING
HUMAN MEDIATED SYSTEMS OF WORK.
THE EFFECTS ON WORKERS AND THE
POLICY RESPONSES NECESSARY TO
MITIGATE THEM REMAIN IMPORTANT
OPEN QUESTIONS.
IN CONCLUSION AS POLICY IN
ENGINEERING PRACTICE INVOLVED TO
DEAL WITH THE NEW FOUND
IMPORTANCE OF SOFTWARE SYSTEMS
IT IS CRITICAL THAT WE DO NOT
ALLOW SOFTWARE SYSTEMS TO
OPERATE.
CHECKED BY DESIGNING A AYE
SYSTEMS SO THAT THEY BETTER LINE
WITH LEGAL AND POLICY OBJECTIVES
WE CAN IMPROVE THE GOVERNANCE OF
SOFTWARE SYSTEMS.
AND SOMETIMES OF EXISTING HUMAN
MEDIATED SYSTEMS BY EXTENSION.
THANK YOU AND I LOOK FORWARD TO
YOUR QUESTIONS.
THANK YOU [inaudible]
QUESTIONS [inaudible]
NO.
QUESTION BUT I TRY TO UNDERSTAND.
UP A LOT OF WHAT YOU WERE SAYING
BUT I THINK I GOT THE GIST OF
SEVERAL OF OF THE ISSUES.
WHICH KIND OF POINT.
TO HAVING.
KIND OF A OF SOMEONE WITH YOUR
EXPERTISE.
IN THE FRONT END [inaudible]
IN GOVERNMENT.
SO THAT AS WE DEVELOP POLICIES
THAT WE COULD NEVER IMAGINE
WOULD.
HAVE A NEGATIVE IMPACT OR WOULD
HELP TO CREATE BIASES -- OR
INEQUITIES THAT WE DON'T DO IT.
JUST ACCIDENTALLY WE WE SHOULD.
BE VERY CONSCIOUS OF THAT SO --
SHAPE.
I THINK I THE A LOT OF THAT.
THANK YOU -- THANK YOU SENATOR
RUSSELL I'M.
I HAVE NO QUESTIONS I THANK YOU
VERY MUCH DOCTOR KROLL FOR
COMING UP.
THANK YOU I KNOW WITH IT WILL
VISIT AGAIN -- I APPRECIATE YOUR
YOUR TIME EFFORT AND EXPERTISE --
MEMBERS OF THE PUBLIC WISH TO
EXPRESS POINTS OF VIEW.
THE S. -- SENATOR RUSSELL.
I ASK YOU TO CHAIR THE COMMITTEE
FOR JUST A FEW MOMENTS.
YOU CAN PASS AROUND US.
MADAM CHAIR SENATOR THANK YOU
VERY MUCH FOR HAVING THIS
HEARING SERRA FLOCKS IN THE
CALIFORNIA LABOR FEDERATION
THERE'S SO MUCH TO COMMENT ON
HERE BUT I WANTED TO FOCUS.
NARROWLY ON THE IMPACT OF WORK
CURSE -- THIS CAME UP SEVERAL
TIMES AND AND THERE WAS AN
ARTICLE RECENTLY THE NEW YORK
TIMES ABOUT.
HOW A ROBOT WON'T NECESSARILY
REPLACE YOUR JOB BUT THEY MAY BE
YOUR BOSS?
AND THERE'S A LOT OF
IMPLICATIONS AND POLICY
IMPLICATIONS WHEN ARTIFICIAL
INTELLIGENCE STARTS TO PERMEATE
THE WORK FORCE.
I'M ISSUES OF SURVEILLANCE AND
ISSUES OF DISCRIMINATION RIGHT
NOW A LOT OF WORKERS ARE
MONITORED BY ARTIFICIAL
INTELLIGENCE THERE SOME
COMPANIES.
REPORTEDLY LIKE AMAZON -- THAT
HAS ARTIFICIAL INTELLIGENCE THAT.
EVALUATES AND FIRES WORKERS THIS
RAISES ISSUES OF WEIRD YOU GO IF
YOU ARE RETALIATED AGAINST HER
FIRED AND THINK IT'S
DISCRIMINATORY.
DO YOU GO TO D. FBIH.
IS THERE A CLAIM OF A MACHINE
FIRES YOU FOR DISCRIMINATION ON
ANY BASIS -- SO I JUST A HOST OF
ISSUES DEALING WITH THE
WORKPLACE EVEN BEYOND HOW DO WE
DEAL WITH THE DISPLACEMENT OF
WORKERS.
I'M WE THINK THAT MOST LIKELY
ARTIFICIAL INTELLIGENCE
TECHNOLOGY WILL CHANGE THE
NATURE OF WORK IN WAYS THAT WE
NEED TO BE AWARE OF I'M
DISCRIMINATION ON THE BASIS OF
OF HEALTH STATUS THINGS LIKE
THAT.
AND THEN JUST QUICKLY WANTED TO
GO.
BACK TO THE SPEAKER FROM GOOGLE
WE VERY MUCH APPRECIATE THAT
THESE COMPANIES ARE DEVELOPING
ETHICS BUT AS SENATOR UMBERG
POINTED OUT.
PUBLIC PUBLIC SERVANTS ELECTED
OFFICIALS AND ADVOCATES HAVE
VERY DIFFERENT OBLIGATIONS BOTH
LEGAL AND FIDUCIARY -- PRIVATE
COMPANIES HAVE OBLIGATIONS TO
THEIRSHAREHOLDERS AND THEIR
INVESTORS AND A DIFFERENT MOTIVE
AND SO IT IS VERY IMPORTANT THAT
POLICYMAKERS.
HAVE ALSO SOME ETHICS AND
GUIDANCE AND REGULATIONS -- AS
ARTIFICIAL INTELLIGENCES IS
DEPLOYED IN THE PUBLIC AND THE
WORK FORCE THANK YOU VERY MUCH.
GOOD MORNING A REBEKAH MARK AS
REPRESENTING THE CENTER FOR
PUBLIC INTEREST LAW.
AS YOU MOVE FORWARD IN YOUR WORK
TO ADDRESS THE GROWING IMPACT OF
A AYE IN CALIFORNIA THE CENTER
FOR PUBLIC INTEREST LAW STRONGLY
URGES YOU TO CONSIDER FROM A
POLICY PERSPECTIVE.
THE IMPACT OF A AYE IN THE
CONTEXT OF THE LICENSE
PROFESSIONS SPECIFIALLY HOW DO
WE PROTECT CONSUMERS WHEN
MACHINES CAN DO THINGS AS OF NOW
WITHOUT REGULATIONS THAT HUMANS
NEED A LICENSE TO DO.
ON THE OTHER HAND HOW DO WE MAKE
SURE THAT THAT THE THE
PROFESSIONS THEMSELVES ARE NOT
PREVENTING ACCESS TO HIGHER
QUALITY AND CHEAPER SERVICES BY
DEEMING CERTAIN EMERGING
TECHNOLOGIES.
AS UNAUTHORIZED PRACTICE WHERE
THEY MAY HAVE PROTECTIONIST
MOTIVES AT HEART.
OUR CENTER IS CURRENTLY STUDYING
THESE ISSUES AND WE ARE MORE
THAN HAPPY TO ASSIST THE
COMMITTEE AS IT CONTINUES THIS
IMPORTANT WORK.
GOOD MORNING NANCY VARIAS FROM
SEIU LOCAL ONE THOUSAND
REPRESENTING STATE EMPLOYEES UP
AND DOWN THE STATE OF CALIFORNIA.
I JUST WANT TO THANK THE
COMMITTEE FOR HAVING THIS
HEARING ALSO SENATOR -- TO
SENATOR DRAWS -- FOR MENTIONING
THE ONE PIECE THAT I THINK WAS
MISSING FROM THE AGENDA WHICH
WAS THE WORK FORCE.
AND THE IMPACT ON HOW --
ARTIFICIAL INTELLIGENCE AND
TECHNOLOGY WILL BE IMPLEMENTED
AND HOW IT WILL AFFECT THE WORK
FORCE -- TECHNOLOGY FOR
TECHNOLOGY'S SAKE DOESN'T WORK
IN THIS STATE WE'VE SEEN THAT
HAPPEN MULTIPLE TIMES -- AND AS
ASSEMBLY MEMBER NAVA POINTED OUT
ON THE WORK FORCE HAS TO BE
TRAINED AND MORE IMPORTANTLY
THEY HAVE TO BE INVOLVED IN THE
IMPLEMENTATION OF THE TECHNOLOGY
IN THE ARTIFICIAL INTELLIGENCE
BECAUSE AS I MENTIONED WE ALL
KNOW WHAT HAPPENS.
WHEN THAT DOESN'T WORK AN ACTUAL
PEOPLE GET BLAMED -- FOR THE
LACK OF KNOWLEDGE ON HOW THE
TECHNOLOGY WORKS.
LASTLY I JUST WANTED -- TO POINT
OUT AS THE COMMITTEE MENTIONED --
THAT THE GOVERNOR HAS REALLY
TAKEN THE LEAD ON THIS I THINK
WITH THE OFFICE FORCED WORKS
FORCE COMMISSION -- AND YOU KNOW
WE APPRECIATE ALL THE
LEGISLATION THAT'S OUT THERE SO
WE LOOK FORWARD TO WORKING WITH
THE THE ADMINISTRATION AS WELL
AS THE LEGISLATURE GOING FORWARD
THANK YOU.
THANK YOU MISTER CHAIR ALREADY
BAYARDO SEIU CALIFORNIA JUST
REAL QUICKLY I THINK WILL ECHO
SOME OF THE THE COMMON THIRTY
MADE I THINK THE ISSUE OF
PRIVACY -- IS SOMETHING THAT
WILL WORK ON SEPARATELY -- BUT I
THINK THAT A CORE ISSUE FOR SK
YOU IS ALWAYS BEEN INCOME
INEQUALITY AND I THINK WHEN YOU.
LISTEN TO ALL THE THINGS ARE
SAID I THINK THERE'S A LOT OF
GREAT INNOVATIONS THAT ARE
OCCURRING BUT I THINK THAT ALSO
HAS THE POTENTIAL TO REALLY
DRAMATICALLY INCREASED.
THAT INCOME INEQUALITY THAT
ALREADY EXIST IN OUR SOCIETY SO
I THINK THAT THAT HAS TO BE ONE
OF THE CORE.
OF VALUES THAT WE HAVE AS OF
POLICY MAKERS WITH KEEP THAT IN
MIND AND MAKE SURE THAT THE
DECISIONS THAT WE MAKE DON'T
EXASPERATED PROBLEM THANK YOU.
THANK YOU I'M ANY OTHER COMMENTS
UP LET ME LET ME AGAIN THANK
THOSE WHO TRAVELED SO FAR AND
SPEND TIME.
INVESTIGATING THIS ISSUE -- AS
IS POINTED OUT BY NUMBER
WITNESSES THIS IS A HUGE AREA
AND NO DOUBT THERE ARE MANY MANY
OTHER ASPECTS THAT NEED TO BE
EXPLORED THE PURPOSE TODAY'S
HEARING WAS SORT OF OPEN THE
DOOR AND BEGIN THAT CONVERSATION --
IT IS -- AS ASSEMBLYMEMBER NAMA
POINT OUT.
IT IS CONCERNING THE THE
CALIFORNIA HAS NOT REALLY BEGUN
THAT CONVERSATION ORGANIZED
FASHION.
AND SO THAT'S WHAT THAT'S WHAT
WE'RE ABOUT THIS WILL BE THE
FIRST OF OF SEVERAL HEARINGS
THAT WILL BE HELD.
AND LET ME LASTLY EXPRESS MY
GRATITUDE TO US SENATOR ALSO
CENTER CHIANG AND SENATOR PORGES
FOR SPENDING SOME TIME TODAY'S
BUSY TIME LEGISLATURE.
SO WITH THAT WE WILL RECESS
UNTIL CALL THE CHAIR THANK YOU