Keynote: Yeshimabeit Milner
5:55PM Jul 28, 2020
to hackers on planet Earth, the pandemic edition.
today's two o'clock keynotes and I'm so excited to do so. Introducing Yoshi Milner, who's the founder and executive director of data for black lives. She really has such an interesting profile. And in fact, the Financial Times wrote this fantastic piece about her recently and I recommend that you go look it up and one of the things about that profile is that it features a very hackish story. When she was in high school she got suspended. And, like maybe many of us and, and then what she did next was so interesting she decided to collect data about who was getting suspended. And lo and behold, she found that black children like her and this is a quote from the Financial Times were four times more likely to be suspended than white children. This was the beginning of her life as a data activist. And indeed, that's where she built her kind of lifelong commitment to movement building and data activism she has married the two together in this phenomenal organization I think you should definitely look up data for black lives. There's so much more I can say about her and what she's done and what she's accomplished. But I think you're here to listen to her and not me. So please join me in a virtual welcome, and I turn it over to Yoshi Milner for today's hope keynote.
Thank you Dr Coleman, and thank you
to everyone who's been a part of the process of organizing this
conference. I'm so honored to be part of the host conferences here. Sadly I can't be with you all in person, but I'm really really glad to be able to share more about the work we're doing and data for Black Lives data for Black Lives
is a movement, over 4000 scientists
and activists, committed to harnessing the power of data, and technology to make concrete and measurable change in the lives of black people data for black cars began with a vision, my vision, a bold ambitious, but very possible vision of changing the role that data plays in public life in the lives of historically oppressed people, and in particular in the lives of black people. We launched the organization officially with a conference at the MIT Media Lab november of 2017, and three years in this vision has grown into a powerful source force of scientists and activists, equipped with the skills, empathy, and the ability to create a new blueprint for the future. And we are continuing to grow. This year, we will be responding to the urgency of the political moment, but also the request of people all over the US and globe to bring the data for Black Lives mission where they live. The mission to make data a tool for social change, instead of a weapon of political oppression. This talk is entitled abolish big data. It's the name of the talk that I've been giving for the past year and a half. It's also the name of my forthcoming book. And it's so exciting to see in this moment the word abolition and abolition as a, as a political unnecessary process has emerged the mainstream abolition by definition means to recognize that reform is not enough. And abolish Big Data is a call to action that recognizes that the bullets police dogs and fire hoses of the past have become the predictive policing algorithms voter suppression apparatuses and facial recognition systems are the present algorithms and other big data technologies are the engines facilitating the evolution of chattel slavery into the prison industrial complex and have created the conditions for the crisis that we face now. The prison abolition movement asked the question, how do we create solutions in our communities, without recourse to prisons in this talk I apply the same lens to big data, how can we reimagine
structures and industries that concentrated data into the hands of a few.
And how can we abolish the structures that turn data into a powerful and deadly weapon.
This is not a call to end use of all data quite the opposite.
The call to abolish prisons and to abolish the police is not a call to abolish accountability. But to get rid of for once and for all, a punitive violent system that simply is not working for society, the call to abolish Big Data is to dismantle the oppressive structures and industries that surrounded to use big data is more than a collection of technologies, a vast amount of information in different types of it. It is more than a revolution in measurement and prediction. It has become a philosophy and ideological regime about how decisions are made and who makes them. It is given legitimacy to a new form of social and political control. That is taken the digital artifacts of our existence and found new ways
to use them against us,
and big data is not new. It is not novel, or as revolutionary. As we often worship it to be, but it is a part of a long and pervasive historical legacy and technological timeline of scientific oppression, aggressive public policy, and the most influential political and economic system that continues to shape this country's economy chattel slavery. I believe that what we face today. And what we must name is a data industrial complex, where zip code is destiny. We're debt becomes a ball and chain weaponized by complex and obscure financial systems were data is a strategy to rob people of political power by manipulating elections, a system and culture were persistent archaic and racist notions of risk persist narratives more powerful and pinchable than any prison cell that could ever be built
data for Black Arts was founded on the belief
that we have the opportunity with data to abolish reimagine, and create new structures of knowledge production, new forms of decision making. And that, that the ways in which we were able to create new forms of relating to each other. The possibilities are infinite. Because of the enormity of the threat that is scary and unprecedented
this discourse has been very negative and fatalistic. This does not reflect the agency of our communities
and our movements. We don't want people to get up give up and get overwhelmed. We want to create alternatives. I first learned to collect, analyze, and use data as a high school student because early on I realized that alone we could be ignored but that there was power in a number. This video shows something that happened at a neighboring high school. The school that I was
supposed to be a part of according to my address that my
sister went to my friend from elementary school, went to
students to organize a peaceful protest in response to a school administrator putting a ninth grader in a headlock. It made national news but not in the way that it would today. I will never forget seeing footage of SWAT team units for the school of police shoving the small frames of students I grew up with against police cars on CNN and local news there were headlines read Riot at Miami Edison senior high. I knew that unless we found new ways to be heard, to disrupt narratives that facilitated this level of abuse my future in the futures of many other people, young people would be at stake. When we were turned away from public hearings at the school board and totally dismissed by then, Superintendent Rudy crew. We hit the ground running and surveyed 600 students about their experiences with suspensions and arrest in schools. For many of these young people surveyed, that was their first time ever being asked about their experiences in schools. At that moment they had realized they weren't bad kids because they've been suspended for forgetting their school ID or wearing the wrong color t shirt with their uniform, but this was a statewide problem and a national problem and it was known as the school to prison pipeline.
after graduating from college.
I returned to Miami, with a renewed sense of purpose and Arsalan skills and data collection and research that was urgently needed. I was asked to lead a reproductive justice campaign to address the black infant mortality crisis. And although in my head and nationally the infant mortality rate has decreased steadily over the past 50 years the black maternal
the black infant mortality rate has remained constant black babies were three times
more likely to die before their first birthday than white babies mothers in the community knew that this tragedy was connected to hospital policies and practices such as the aggressive marketing of infant formula, and the unnecessary use of procedures that were costly and dangerous like C section. zerion section, but without data community outcry was ignored, with a small team of moms I surveyed 300 mothers on their experiences, giving birth in Miami in particular at Jackson Memorial Hospital, our public hospital in
the largest hospital in the country.
We weren't able to bring 300 mothers into the boardroom with this we finally had a meeting with the hospital, but the CEO and the rest of this staff could not deny the data that we collected a campaign that had taken up to that point years to even push through took only a few months to win. And today the lives of hundreds of mothers and babies have been impacted by the policies that we fought for. And that same summer while I was working on this campaign and still
continuing to fight for restorative justice
Trayvon Martin's murderer george Zimmerman was acquitted. Based on stand your ground laws, when we found out the news in Miami a group of us young people led by the group Dream Defenders drove up to Tallahassee, Florida,
the Capitol and occupied the state capitol.
We spent over a month sleeping on the floor. The cold marble floor of the state capitol not because we wanted to make a blanket political statement, but because it had become legal effectively in the state of Florida to kill a black child with impunity. According to stand your ground laws, which was a codification of perceived threat. In
all of these experiences, whether it was in the hospitals, whether it was my original experience in school,
whether it was us, literally, camping out in
the state capitol for 3030 days. I knew that what we were fighting against were not just the institutions whose policies and practices sought to undermine our lives. But behind those policies and practices the narratives that justified endorse and encouraged the civil rights and human rights abuses narratives grounded in data. That must also be abolished while we do the work of dismantling the structures that perpetuated them. And perhaps the most harmful narrative surrounds the notion of risk, the very first time I even heard the word at risk was actually in the fourth grade, it was, coincidentally, in a computer class I also got to
spend it in sixth grade
that computer class I think that was a sign that maybe that I was on the right track in terms of some of the work I was doing. I always believed that you face opposition when you're on the right track friction right that's a law of physics but anyway.
I was talking to another student and she was telling me that she was at risk that we were all at risk. You know, I'm nine years old and I'm afraid I'm like what's going on where are you at risk and she said she's a part of after school program while she really liked the
program that it was for at risk students.
Children who are at risk of going to prison of having an unwanted pregnancy to early age, or even dying early.
Again she liked that program.
But it was almost like being a part of it was a self fulfilling prophecy.
It was as if these programs in this language foreshadowed
the narrow options for not just what we could do after school every day but also who would we be who we would become.
And for me, As someone who I always
say survive the school to prison pipeline. Again, in a lot of ways that term has become a self fulfilling prophecy.
So how are the word risk which finds its
origins in finance and business insurance loss
profession, prevention and become a label operationalize through policy and weaponizing and young people like me and my friend. This is one of my favorite examples here of machine learning, and probably one of the most useful, I would say, autocorrect right in this we see the word risk and the synonyms. Danger Jeopardy peril hazard menace threat.
How did these terms become used against young black people.
How do they become used in order to push narratives that have been uh now condone the deaths of people like brother George Floyd, and have allowed it to that we've gone so long without any justice for Briana Taylor.
These are present their cultural, but they're also driven
by the weaponization of data and statistics.
With the end of the Civil Rights Movement the war on drugs, also known as the war on communities, black communities specifically, and the introduction of massive legislation to push for the most violent civil rights and human rights assaults of our left of our lifetime mass
incarceration came a wave
of research and data to justify the targeted and coordinated efforts to warehouse entire communities into prisons. The term super predator was introduced by social scientists and bush administration advisor john de Luna 75. Do we will create entire theory around the notion that a new generation of street commandos is upon us, the youngest biggest and baddest generation any society has ever known. Based on what we have witnessed research and heard from people who are close to the action. He wrote with two co authors here's what we believe. America is now home to thickening ranks of juveniles super predators radically impulsive brutally more merciless youngsters, including evermore pre teenage boys who murder assault, rape bra fertilise deal deadly drugs, jump, join gun toting gangs and create serious communal disorders. At the core, he said. The problem is that most inner city children grow up, surrounded by teenagers who are themselves deviant delinquent and criminal. The point of this was to spark panic. The point of this was to feel vitriol and hatred and take the emotions of suburban white people. Other factors of society, and to harness that to power, tough on crime policies and practices that proved to be 100% successful in criminalizing black people for the next few decades.
It took years eventually for Julio to admit what we all know to be true, right. But none of this none of these predictions that he claimed. Not only were they wrong. They were the exact opposite of
what was happening in quote unquote inner city neighborhoods across the nation.
But by the time he admitted in 2001 years later, after converting to Catholicism and wanting to do the right thing, so to speak. These policies had already been emotion, had been automated into the American imagination. And another example john Mueller was not alone in the 1980s wobble for Super predator dr Ira chesnoff built an entire career off of the crack baby myth, which is based on a flimsy study comprising of
participants. It was based on a hypothesis that was in lockstep with the most racist political intentions, a fear that one day a generation of children will grow up to be cracking down in a burden to society. All of this was wrong. And as researchers, we know that the sample size 23 is put it's been 23 babies should have refuted the validity of this study alone, but it was not. And similarly the reality was true, right. Later on, whose New York Times kind of Expo say that follows one of the quote unquote crack babies featured in this poor poo poo participated in the study.
One of the babies,
who's now, a young woman today grew up to be a healthy functioning, and quite exceptional young woman. The first in her family to graduate from college, poverty, rather than crack addiction, has been found to be way more harmful in the child's life. And lastly the welfare queen myth right, which is which is used and it's continued to be used, what now in this moment of COVID-19 recovery right. This has been used to dismantle our country's safety net to privatized social services and siphoned resources away from the very communities who need them and who pay for them with taxpayer dollars. Meanwhile, the real welfare queens are the corporation's who benefit more from government subsidies than all of the individual food stamps, Medicaid, unemployment benefits combined recipient benefits benefit recipients excuse me combined,
especially right now with so many people
are being crushed under the weight of the absence of a
safety net that they're very tax dollars should have been paying for.
In the age of big data, unless we are aware of this history and this is just reason history,
this is, I'm 30 years old. This is all in my lifetime
right, unless we were aware of this history we risk repeating it. And I think that's a bit of a more appropriate term or the view
of the use of the term risk.
So before we go into more modern, contemporary examples again, talk before we talk about algorithms and machine learning and the ways in which these myths are being reinforced and perpetuated in this moment, we must first discuss the history big data, we have to tell its origin story. What are the economic imperialistic and colonial contexts that require the level of record keeping, accounting and surveillance that have come to the vine. The Big Data practices of today. Contrary to popular belief, slavery was not the antithesis to business innovation, and much of what we know about scientific management. Management Science, finance, does not come from the factory floor. The railroad or the steam engine. The Big Data Systems, we're familiar with today, used to control surveillance at violence to maintain power structures and ensure profit on a global scale originated during slavery in the 1600s and 1700s. The Dutch East and West India companies were the largest commercial enterprises in the world. With hundreds of ships thousands of employees countless offices in Asia in the Americas. The voc and WCS operations were mirrored all over the Atlantic and brought to the US. These were the most powerful corporations in the world. In proportional terms, they were wealthier and more powerful than Apple, Google and Facebook combined these companies pioneered colonialism created the blueprint for globalization and develop new data practices
maintain this massive operation.
And although this history has been largely ignored and erased. These sophisticated Big Data practices predate the analytical tools we use today. Big Data practices were not invented out of creativity or innovation. This wasn't new in sitting under a tree and an apple falling on his head. But in the deeply violent transatlantic slave trade, which traffic 12.5 over 12 point 5 million enslaved African people to the Americas. Dr Caitlin Rosenthal, author of accounting for slavery masters in management rights that planters control over and say people made it easier for them to fit their slaves into neat empirical rows and columns extraction of the catastrophic loss of life. And the necessary torture required to maintain plantations was needed to serve the owners who were room so far removed from the daily use of literal rows and columns and rows and fields
of the sugar cotton and tobacco plantations they owned data moves up and down hierarchies akin to the way in which
CEOs and boards are today responsible for, but never
accountable to the violence they inflict, big data was necessary to distance oneself from the violence and the gore capitalism of slavery, the standardized
used to count for slavery. Perfect the legacy of the thorough record keeping, of the Dutch Empire, and can be found in a report from British guy and later in South America. This hits home for me. Because British hyaena was where my family and my own ancestors were traffic to an enslaved.
So this is a monthly abstract for a plantation
disturbingly named hope and experiment literally the name of the plantation is hope and experiment. And it reveals the regular shape calculated operations for each month.
There was one line for each day with columns for the many different categories of men,
women and children. They include in the field watchmen how servants carpenters invalid and runaways during slavery was essential to the operations of their plantation of the plantation and their role was justified by the brutal logic of capitalism, and I quote one slave owner, the hand of an eagle child is best calculated to extract the weed and grass. This daily process of dehumanization was deeply numerical and below the monthly abstracts for ideal identical reports for livestock Negro account and livestock account use the same methods of taking an inventory, calculating increase in decrease purchase sales birth, death slaughter murder, with very little difference, made for women man child oxen boat and cattle. But the most necessary form of accounting used and operationalized, and it's so similar to what's happening today was in the wielding of information as a weapon to create fear distrust and to neutralize collective action a month enslave people from a movement from removing verses in tech, such as the Bible that rejected slavery and using amputation, wiping in torture to ensure that no one can even read and write or communicate at all. Information Systems developed during slavery, were created with the intention of eclipsing the networks that allowed enslaved people, black people to assert their strength in numbers to become educated and informed to escape to organize and to fight back. All of these examples, indicate the ways in which big data was born out of bondage. There's so many other examples, you're all going to have to wait for the book to come out and some more materials to read more about it but there's so many examples and make this connection. And I think there's so many examples because of course this history has been largely
We're not taught this in
schools and we certainly aren't taught this when we're learning about technology, whether it's school or on our own or whatever.
But this emphasizes very earlier point that big data is a new word innovative as we worship to be it to be, but it's a part of this longer historical legacy. We often say that no algorithm is neutral. That algorithms are opinions embedded into code. And this history reveals the extent to which
this is true.
So by definition an algorithm is a step by step function. A set of instructions to solve a problem recipes an algorithm. It's instructions on how to make the dish. The ingredients that make up the dish. And the result, based on what we define
from from the beginning of the recipe of success,
whether we want to focus on making something healthy or something that tastes good. Regardless of health benefits. These decisions are informed by question, what are we optimizing computational algorithms are layered complicated and their ingredients are not just the raw data that is fed into them. And the result is not simply is not as simple as the outputs that come from them. Scores ratios, GPS routes and Netflix recommendations, but as the chart demonstrates histories and values are what influence inputs and outputs, and most importantly the very models that are trained and develop the algorithms themselves.
One example are FIFO credit scores. So Contrary to
popular belief FIFO is on a federal agency it's the Fair Isaac company, a for profit entity started by William Earl and William Fair Isaac, and who 25 years ago, wanted to disrupt your skin lending, through the creation of an algorithm, and through the use of machine learning. And as we're
the inputs of the FileMaker algorithm are the debt we have, or miss number of the percentage of Miss payments. How many credit cards we have etc. And this information our data is provided through a collusion of data brokers, Equifax, Experian and TransUnion, and then fed into the FICO algorithm. And while we were told that certain
behaviors and financial characteristics compromise
your credit score, we aren't able to verify because
fake was a proprietary algorithm, a black box devoid of transparency with the purpose of displacing accountability, away from the for profit companies of profit from our data at will and if obviously at our expense and fica credit scores reflect our one algorithms that reflect the tremendous power that these algorithms hold over our lives. At this very moment there are students who will have to drop out of school because they cannot qualify for subsidized student loans, there are people struggling to afford rising public transportation costs, because they cannot afford subprime car payments, and even hard working families, facing homelessness, because they can't rent an apartment. All because of a three digit number. And these this three digit number will increasingly decide whether we get hired for the job. And even if we somebody do not resist whether or not we have the right to the same citizenship or be deported. While it is in violation of federal law to deny people housing, employment, education based on race, you can't to an algorithm and private companies like FIFO, which I must also mention is in their highest and the best just to make sure that some people have low scores and others don't argue that their algorithms don't discriminate. They say nowhere in the algorithm or their input this race value variable. But we know the based on the history of this country, how our neighborhoods and municipalities are organized. You don't need races of variable redlining the legacy of slavery had made the coast proxies for race, only seven generations several generations after slavery. 6 million African African Americans left the south for the National centers of the North Midwest and west coast of this country there what is known as the Great Black migration as black people contributed tremendously to the growth of the manufacturing industry, and to the culture and politics of Metropolitan Life, our federal government responded through policies that sought to institutionalize racist sentiments and permanently entrench black communities into a caste like status policies at foregrounded are four grounded in one of the most essential parts of economic mobility homeownership in 1933. As part of the green New Deal, the homeowners loan Corporation developed a grading system that deemed Samad areas desirable while others hazardous, it did not matter that federal law ruled racial joining unconstitutional. The creation of security maps and the redlining of black communities encouraged the practices of real estate boards neighborhood associations and white mob violence that made it possible for black people to own homes. People would bring your 1930s was hardly a science, but programs.
Scientific trappings that
helped turn popular racial knowledge into real world
consequences as NPV Collier historian writes today, 74% of the areas that were deemed hazardous in 1933 remain the low income under resource and neglected neighborhoods of today. And this is a map here of where I'm from in Miami, but I want to be clear, this was not just happening in the south and if you go on our website you'll see a blog post that I wrote around the time of the riots after dirt floods murder. One of the things that really defines Minneapolis, St. Paul and actually makes it the fourth worst city in the country for black people to live in based on metrics such as
high school graduation rate and wealth was the fact that black people were barred using violence right violent like terror, as well as legal legal ease right embedded into contracts of most houses still today in Minneapolis, St. Paul, our racial covenants that prevent black people and other races from buying and own and renting and homes. And that's why today black people have been kind of segregated into two neighborhoods in Minneapolis near north and southern Minneapolis which is actually Southern Minneapolis corridor. Business corner where all the black businesses where is where George Floyd was murdered for allegedly paying with a fake $20 bill for a bounced check, don't know which one of those but either way it shows the ways in which something that happened in 1933. And that was embedded and decoded into legal language and therefore data and it's mapped still has implications for today.
And this is an example from Chicago, right. So zip codes in the 20th century were actually organized to create, to, to, to organize the country you created to organize the country and to postal for the purposes of postal delivery. But, you know, through the creation of zip codes what was done, unintentionally, I think, was was the creation of these digital numerical artifacts of the right, the history of redlining, and it has been essential to extending the shelf life of racist policies of the past. So, how does that happen right. We know that, just as I described in Minneapolis example, or in the fact that 70% of the neighborhoods that were hazardous then are the disinvested over policed over criminalized neighborhoods of today, when you introduce zip codes and you bring zip codes and use it as an input in any research right and I'm a researcher, usually the best data that we have. It's amazing if we can get our hands on zip codes. But this is a warning right this is a caution that, especially when you're creating things like car insurance algorithms FICO credit scores rental application algorithms job applications and you're using zip code. So many times that it will serve as a proxy for race because of the ways in which, where you live, can most likely determine your race in the United States due to segregation. And this is in
where literally if you look on the map right, the hazardous area of 1933 are the areas where this most expensive car insurance premiums right propublica did this amazing study where they showed that even if you know for a white man who lived in downtown, where there's actually higher crime, because it's a commercial area and driving a sports car which is a more, quote unquote, expensive riskier car to drive. He had hundreds of dollars less in insurance premium payments than a working class father who lived in a working class. Mixed neighborhood and drove a regular car, and etc etc right and that's a lot of the reason is because of zip code, and how zip code is not only meant race but also how it comes into come to denote risk because race and perceived threat also influenced risk. And those perceptions. But to be clear, zipcode aren't the only proxies for race right beyond zip code. There are so many other examples of how big data perpetuates racism without racist. This is an example of the company's risk assessment questionnaire risk assessments are being used to determine how long someone can is sentenced for jail, especially in a criminal justice criminal legal system actually be very intentional about language, where people often don't go to go to trial, right. So, in this case, and you know you you you read some of these questions, and it's no wonder that a white career criminal who is multiple Connect convicted felonies, has it has gotten, you know, according to the propublica study got a lower sentence than a 15 year old girl who got into like a neighborhood tuffeau which is like a typical teenage kid thing right or was arrested for stealing a bike, right, look at these questions right how many of your friends, acquaintances have ever been arrested.
How often have
you moved in the last 12 months, multiple times.
Were you suspended or expelled from school, yes I described two
times that I got suspended already
hungry person has a right to steal strongly agree or strongly disagree. How often do you feel bored. So I mean according by all standards according to this risk assessment I should be in prison right now right. Who who's arrested in this country disproportionately black people who suspended, where I'm from in Miami and nationally black students are between five to
some places 10 times more likely to
be suspended than white students. Right.
So these are all
proxies for race and these are, these are the ways in which data has taken. What is most violent what is most dangerous about racism and been able to really amplify and exponential eyes, the impact of the harms.
And for these reasons,
we assert I assert the call to action to abolish big data to attract and dismantle the structures of concentrated
power into the hands of a few. And to put
the power of data into the hands of those who needed the most. The refugee. The prisoner, the activists, the most vulnerable and the least powerful it gets the enormity of the carceral criminal and capitalist apparatus, given what we know, the call to action to abolish big data, the call to action to be abolitionists in this era of big data and again this is a call to action I've been making for years now. As our work is grounded in the black radical tradition. Okay, we shape the data for Black Lives movement. After the contemporary movement to abolish prisons, as well as the primordial the original revolutionary movement of this country, which is a movement to end chattel slavery, which in many ways an unfinished project, and a legacy that we take on it's a torch, that I accepted. And that we handle. It is an obligation to become an abolitionist in this era, not simply a political choice, but an ethical obligation. And it's an obligation that's ultimately grounded in critical vision. And this vision is what guides our work. We believe that we are doing what our ancestors dreamed we would do web deploys dreamed would happen right when he took a team of young black people students and alumni of Atlanta University, and created data portraits
and did sophisticated rigorous data analysis and presented it in a world platform. So that
all of these
myths and ideas that were being perpetuated through statistics at that time, such as the idea that black people would eventually be extinct due to racial inferiority. No, he took that and showed not only were white people as a population growing in the US, but that any opposition that they were facing was because of structural issues. And this is the legacy again that we work in to reclaim data's protest data accountability and data as collective action. So I'm going to talk a little bit about the time I have left what we've been up to there so much as i mentioned data for Black Lives we've been in a moment of growth and expansion in the last year, and I'm so glad we decided to make this choice to hire new
staff beef up our programs
because I didn't predict COVID-19 to hit. But I certainly knew that what we were preparing for were the worst possible tragedies and disasters, given the state of the world, and the already precarious state in which black people in this country live. When we found out that COVID was coming to the US. And once I saw the headlines were being shared that black people were disproportionately impacted by COVID-19. We kind of sprung into action and we literally scraped every single open data portal in the city, in this whole country. To get a better sense of what these disparities were looking like right. And we've begun to track
This is an example of this was the first thing that we did where we just started to track death cases and death by states that had been reporting. We were pushing states to actually report and to do it accurately and to also implement conditioning testing protocols. And this is a next level of visualization that we did with our research team, but it's going to be launched into a bigger kind of platform where folks can not only learn more about what's happening but again coordinate organize and mobilize, but most importantly we knew that it was it was it was possible for us to only talk about the data, especially as we saw narratives being formed around personal responsibility going back to what I said about deploy in racial inferiority versus a focus on the structural issues right. So in addition to collecting
the data. We did exactly what a
movement would do in this moment, we said let's bring the voices of people directly impacted who are living on the frontlines to the forefront. Right. And so we organized a movement post check with like epidemiologists black doctors
folks from the UN African
committee on people of African descent.
You know organizers from Houston Texas folks more Atlanta hub to talk about what was happening
why it was happening and most importantly, how can we launch and deploy a response. And it was awesome and folks can read the report online at T for Bo. org slash reports, and we're going to be doing some more we've had other post checks to talk about things that's happened, but really right now, it's about tracking the state state of holding states accountable working with state CEOs and local studios, but also
equipping our folks
on the ground to do their own data collection, because we know that there's gaps in what's being collected on the state level.
Another piece of our work is
in the research area that we're working on now so a couple of years ago I wrote a year ago I wrote an open letter to Facebook, on behalf of the data for Black Lives movement. And in that you know I laid out three basic demands. Right. The first is to hire more black data scientists to work with technologists advocates and ethicists to establish a data code of ethics because Facebook uses our collective data to literally publish peer reviewed reports on research.facebook.com, And they did not have to be accountable to any kind of Institutional Review Board, or any outside third party external review board right. So at the very least, the code of ethics, but most importantly, I demanded that Facebook Connect commit anonymized data to a public data trust and why. Because I know you know I knew but came to analytical when I was working in color change on election stuff. This is really just a part of how elections work at this point. Creating surveys personality profiles whatever data mining data brokering that can happen to push votes, and to push narratives. But I also knew that, you know, while the likes of Christopher Wiley and Alexander Cogan had unfelt. You know, you know, just just unlimited access to Facebook data to you if they wanted. Black data scientists and researchers and allies in our network would never have that kind of access, even though they're doing research on things that are demonstrably and urgently more important than anything related to kind of trying to change the US election, especially to create the conditions that we're facing now. And so that's
where the idea for
the data trust comes from right now and moving beyond Facebook, what is it what does data
governance mean in this time. What does data sovereignty mean,
really, firing, and and and and gaining inspiration from indigenous data sovereignty and data rights movements that are emerging all over us right now and all over the world right how, you know, do we not only take collect individual but collective
ownership of our data
in a system again that's extractive that
capitalist. And there's also
weaponizing Set Data against us, right, so this is some more information around our data trust work, there's folks who are working in the UK, and people in places again like the UK and EU where there's a lot more political support around data governance and data accountability, but this is our solution right.
How can we
essentially a data trust is by definition.
It's a structure
where data is placed under control of a board of trustees, with a fiduciary responsibility to look after the interests of the beneficiary So you mean society, and using all of them offers us a greater say into how our data is collected accessed and used by others. So we have different examples of this and please stay tuned, or if you want to be involved. We're exploring the use of different technical structures, k anonymity, with any folks who have a lot of experience in encryption in security data storage servers please reach out to me, because I do want to talk to you so we can threat model and we can also talk more about how we can. Once we make demands around data or let's say we have folks in our network opt in and commit credit score data genetic state or whatever, how do we make sure that's secure because as you probably realize there's lots of corporate company corporate and corporate interests who really want black data in order to get a better sense of
how to fulfill their agendas, that's all I'll say.
And finally, one of the things that we're working on now around our policy work in addition to COVID is a no more data weapons campaign, and we're so inspired again and moved excited by the mass support that people have given to existing efforts to defund the police and abolish the police. We want to make sure that
algorithms will not replace police officers right
cities like Camden, New Jersey, had already begun defunding, the police after 911 because so many cities are actually going broke, and instead of. And while they've been happy to fire, police officers, a lot have been running towards adopting new technology and even saying that you know this new technologies reduce human bias which we know is not to be true they reinforce it. So we are working on a big project right now that I can't talk a lot about again security reasons, I'm sure you all understand. But we are looking for volunteers folks who want to be part of this tracking the development of data weapons across the country right data weapons are as obvious as facial recognition which work for people know about risk assessments policing x rays shot spotters sting rays. real time crime centers domain awareness system, but also things that are kind of more emerging right, look, I even think that Elon Musk is neuro link is is a data weapon. Okay, planting AI chips into people's brains. Working with Brown University my alma mater is braingate, where are we going right how do we make sure that these, these in the wrong hands. Political
in the hands of people
with a certain political agenda that they're not being used for harm right we have to make sure that. And the way that we make sure that is by dismantling, but most importantly by putting the data into the hands we will need the most training of people in order to do that and I think that goes back to the real meat and potatoes of our work right. The policy changes great, the Federal changes great but none of that is possible without the work of changing the cast of characters right 90% of the data in this world was created in the last two years in a lot of ways we don't need any more data, but we need data that is ethical just and useful right how do we go about that we need to change, who is doing data
collection who's doing analysis and who's disseminating it, who is in
power what agendas what what ideas are determining how data is collected, who's at the forefront. And that's why we're we've been in this very intense process of launching hubs programs all over the world. So far we have five cities including Atlanta, Atlanta Pittsburgh, San Francisco DMV in Minneapolis, St. Paul, and we have 50 cities in a waiting list and the whole purpose right now is to really, again, deploy real time, rapid response, but on also ongoing and and impactful data capacity to the ground. In order to not only fight these harms but again, to create a new blueprint for the future and to make data tool, instead of a weapon.
Also, this was a
save the date for our conference. We are actually postponing this conference to July 2021 but please stay in touch. For more information about some ongoing activities and events we have coming up. And finally, I'd like to leave you all with a last thought, you know what are we optimizing. That was a question that I asked earlier as we talked about data science, but what are we optimizing. A future where and Justices of the past are automated and reinforce a path defined by slavery dehumanization greed and violence and control or a future vested in justice, fairness solidarity. A world where the needs of all people are met. Dylan Rodriguez to stop defines abolition as a dream towards at the best of insurgent counter civilization civilizational histories genealogies of collective genius that perform liberation, under conditions of duress abolition is a process not an end goal. It is the rejection of prisons, or police or criminalization or control as the answers to our most pressing social problems, and the process of evolution begins in our minds and our organizations or academic institutions, is a new way of understanding the world. I believe that evolution is against certainty abolition is against permanence. The permanence of the prison cell, the guard tower the weapon and its factory abolition is about asserting life in a system that demands death. Casualties human bodies is its tribute abolitionists for us right now, while simultaneously. Being for generations to come. People we may never meet. See, but we must will into existence, just as our ancestors will does. And I'm confident that a new world is possible. A world that we can begin building right now, right here, right at this very moment, and I invite all of you to join us in this effort. I hope you can be a part of what we are building. Thank you so much hope
conference. Have a good day.