AI for Good is happening.

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do you remember

what you wanted to be when you were a

kid

when i was seven i remember and

announced with a lot of pride

to my favorite teacher that i wanted to

be a nun

she rolled high broke my heart when i

was 13

i was fascinated with wildlife my heroes

were jango dol

tayan fosei i must say i was bullied at

school

so i was kind of upset with these stupid

human beings

and yes that be the plan i’ll fly to

ronda

or kenya i’ll be a vet and i spend my

entire life

protecting gorillas lions and their

habitats

today i’m working in the ai industry

and i am a big ai enthusiast ai for a

good enthusiast

how did that happen i’m going to take

you on a little journey

from my teenage aspiration to today’s

exciting perspective

growing up i eventually reconciled

myself with homoserpas

but i was still very disturbed by your

capacity to destroy a planet

and practice unfair treatments racism

sexism homophobia

so i will be a lawyer i will work in the

united nations

and i will defend human rights and

environmental rights

but in the end i didn’t become a vet

i didn’t become a lawyer no none

obviously

i started to work in the tech industry

why

i had such big ideas but i was

undeniably

attracted to this industry of doers

fearless entrepreneurs that were

changing our habits in decades

bill gates steve jobs wow

maybe we could leverage tech to do

something good in the world

so i’ve started my career in software

companies

these were super exciting time facebook

was exploding it was the beginning of

the internet of things

but yet i couldn’t reconcile

impact and tech so

i was about to move to another industry

when i got the chance

to start working in an ai startup

and i was blown away by the power of

this technology

so what is artificial intelligence three

notions to have in mind

one ai is a branch of computer science

that enables machine

to perform tasks that usually require

human intelligence

recognizing images understanding

language

solving problem make decision

to machine learning machine learning is

one approach to reach artificial

intelligence

through algorithm that analyze data

learn from them

find patterns or make predictions about

something in the world

number three deep learning

or deep neural learning is one of the

latest techniques to implement machine

learning

using algorithm designed like our human

brain

that can process an infinite number of

data

in such a short time ai

is so powerful it can solve problems

and find solutions where we human beings

will never be able to find on our own

think about alpha ford alpha ford

is a deep learning program developed by

deepmind in 2020. and basically

they’re solving one of the biggest

challenge in biology

predicting the shape of protein

did you know that each protein has a

unique shape that determines

there are literally billions of proteins

in human

living things and an infinite number of

configurations possible

alpha fod is able to predict the shape

of a protein with the same level of

accuracy than nor

dan lab in a few days versus a few

years with conventional methods opening

the door

to new treatment for diseases and to new

synthetic protein

able to digest waste produce biofuel

or make our plants more nutritious

while i was discovering the fabulous

world of ai

the united nations were announcing that

we were falling behind with regard to

achieving the sustainable development

goals in 2030

the sdgs are 17 goals adapted by the

united nations in 2015

as a universal call to protect our

planet

and poverty and make sure people live in

peace and prosperity

by 2030 that was it

i could finally reconcile tech and

impact

convinced that we could leverage ai to

accelerate progress towards the sdgs

i was so excited that i’ve decided to

turn it into my dream job

spotting and helping entrepreneurs

researchers scientists that are using ai

to help deliver unsustainable

development goals

that’s why today i want to share with

you

two areas that resonate with my teenage

questioning but also my current concerns

and where ai can help tremendously

climate change and equity and human

rights

i will show you through a pragmatic

example how

we are more informed and more empowered

thanks uai to make the right decision

and make our world a better place

let’s start with climate change ai can

help us

with the energy transition but also with

our biggest natural ally

for rest you know

that more than 70 of our carbon emission

are coming from the energy sector

that’s why we are decarbonizing it and

to do so

we’re shifting toward renewable energy

solar wind

this transition is coming with very

complex challenges

fortunately electric systems are a rash

of data

so ai can help substantially for

instance

to produce renewable energy you depend

on solar

and with conditions so operators have to

work

with standby polluting planes to avoid

shortages

which means that basically depending on

the time using energy during the day

you may be using dirty energy

by using machine learning to better

forecast

how much power is generated by renewable

sources

and how much power demand there is we

are able to reduce

dramatically the reliance understand by

polluting plants

for instance the technon profit what

time

is developing a solution named automated

emissions reduction

basically what they do is that they

forecast the grid emission

intensity in your region then they

connect with your smart device

smart freight smart car to help them

adapt the timing of the use of energy

to synchronize with clean energy and

avoid dirty energy

potentially we’re talking about a 40

reduction of carbon emission in the

coming years with this technology

greenhouse emissions are not only coming

from power plants

they’re also coming from the massive

destruction

of forest forests that do capture

carbon through photosynthesis here again

ai can help a lot

it can help to plan reforestation

and to monitor restoration program

so to plan reforestation you need to

know where to plant the trees

the causer lab from ethgeric university

carried out a study in 2019 to assess

how many trees the world could support

where they should be grown up and how

much carbon they could capture

they’ve been using ai to analyze

80 000 images from satellites

combined with viable such as topography

soil quality climate all over the globe

they came up with the three next results

one in a map a you can see the global

tree

cover which is basically the number of

tree the world can support

this equal to 4.4 billion hectares

on map b you can see the global tree

potential cover available for

reforestation which is 1 billion

hectares basically is the 4.4 billion

hectares

minus current forest minus agriculture

areas

the studies is telling us that this 1

billion

a hectare equal 1 trillion tree

and that this trillion tree is able to

capture

200 giga tons of carbon emissions

which equals to 100 years

of carbon emissions the third result is

also super interesting

half of these trillion trees are located

in the northern hemisphere

meaning that some of the richest

countries in the world usa

canada russia europe china

hold the power to reduce our carbon

emission by half

going further ai can help us with

restoration program

this is what the company pachama is

doing

they’re using deep learning combined

with images from satellite and drones

to assess from the shape of the forest

the level of carbon capture and the

level of biodiversity and wildlife

let’s take an example here in brazil and

on the left

you can see the monitoring work of

pachama and here they’re assessing

the level of carbon capture from the

project

through the years compared to the region

this kind of tool

are super important because today

only two percent of the fundings coming

from the credit card

markets are going to restoration program

so the more assessment tools we have

the more clarity and transparency we’ll

have and potentially

hopefully we’ll be able to drive more

funding to these restoration projects

now another area that is really dear to

my heart is how we can

fight against unfair treatment racism

homophobia

sexism how can we fight again these bias

racial buyers gender buyers that follow

us from

very old time and that are like kind of

hardwired in our brain

it’s interesting because we’ve never

been so talkative

and aware of this bias this day though

they’re supposed to be unconscious

because we’re so afraid to see them

perpetrated in our ai systems

let’s come back on the mechanism to do

machine learning you need data

and you need algorithm the algorithm is

the logic

applied to the data so basically we are

transferring our bias

consciously or unconsciously through

data sets and to algorithm so indeed

we are at risk that ai may reproduce

amplify and automate our bias that can

be frightening right

think about the former recruiting

algorithm of amazon

that was biased against women think

about this sentencing algorithm

in the u.s that were clearly biased

against black people

the good news is that we are aware of

this and that the ai community is

working to reduce it

i will even say that one of the most

interesting

and efficient solution to reduce this

bias

lies in ai itself because

with ai we can work at building

fair algorithm that will take over on

our unfair decision makings

and second we can use ai

to reveal and predict our level of

fairness

so we can act upon it that’s pretty

interesting because

if we rely on mentality to change it’s

gonna take

centuries the world economic forum is

telling us that it will take 130

years to close the global gender gap i

don’t know about you but i want to see

that in my lifetime

and i really think we can hack

mentalities for good with ai

so how do we do this how do we build

fair ai

three answers here one we need diversity

in engineering team that are building

algorithm today

it’s always the same kind of population

young

white male we need more ethnic

diversity we need more gender diversity

with engineers so they are able

to identify very early in the process

buyers that may be

deployed in their work second

we need to systematically use bias

auditing tools there are plenty of them

on the market

basically it’s like when you release a

car you check that it’s safe

let’s do the same with algorithm number

three

we need to make sure we have enough data

about underrepresented population in

data sets

in other words we need to be careful

when we use

historical data because this is where

the buyers are hidden

let’s take amazon again their algorithm

was basically

doing what it was supposed to do learn

from 10 years of recruitment at amazon

find a pattern

and make a recommendation on this of

course those 10 years of recruitment

were a majority of men

so obviously the algorithm will favor

men now if you train this algorithm

with performance data rather than

historical data

you may be able to reduce the risk

this is what the company pi metrics is

doing they’re developing a talent

matching platform

and they use ai to assess the soft skill

of candidates

they will assess the level of generosity

fairness

empathy and they will do the same job

with employees from the company that is

recruiting

and then they will compare the score the

candidates

whose skills are the closest to the most

performing employees

who will move forward in the process

another way to answer is how can we use

ai

to reveal and predict our level of

fairness so we can act upon it

i’m going to take here two examples in

the justice system

the stanford computational policy lab is

helping prosecutor

in san francisco to make race blind

charging decision on

incoming felony cases what does that

mean

basically they train an algorithm

to identify race related information

within policy policing electronic

records and to remove them

so basically in the example you see the

algorithm

has identified and removed the name of

the victim

in the indication related to the hair

color

skin color or neighborhood

now last example and this is one of my

favorite we can use

ai to assess the furnace of trials

trial watch is an ai powered platform

developed by microsoft and the clooney

foundation whose mission

is to build assessment tools for

fairness in trial

and protect vulnerable vulnerable groups

such as lgbt

women political opponents or journalists

whose right are at risk to be violated

during the justice process

so on this platform they’re gathering

data from trials all around the world

the ai will transform the records into

text

translate in different languages and

make it comparable so it can

identify pattern assess the trials and

grade the fairness

this tool is essential because basically

it enables us

to denounce publicly in the right time

any injustice

making the world kind of a witness into

the courtrooms

so you see there are a lot of different

ways to do ai for good

within our within our community we have

more than 200 projects

but every day we’re meeting new

entrepreneurs new projects

new brilliant ideas ai can be used to

speed up drug discovery

fight again coveted cancer balleria ai

can be used to

promote a more sustainable agriculture

ai can be used to fight against

misinformation

or terrorism of course

ai is no silver bullet we need

regulation

we need political incentive so it’s used

responsibly

and to encourage the use of it for good

but from what i’ve been witnessing in

the last year

we’re going in the right direction and

we are more and more informed

and empowered thanks to ai to make the

best decision and solve some of the

biggest challenges we face as a

civilization

and the planet and when my kid

will start to wonder what they want to

do when they’re older

i would have hundreds of heroes role

models

entrepreneurs researchers scientists

activists

and i will tell them their story and i

hope they will be

inspired and convinced they can change

the world for good thanks to artificial

intelligence

to all of you students people working in

ai

from near or far up to you to act

now i choose ai for good what will you

do

thank you

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you