DN18 | A Case for Data Dignity |Jennifer Lyn Morone | TheDataUnion.us
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About the Author: Jennifer Lyn Morone is an American-born natural person who incorporated her identity by founding Jennifer Lyn Morone™Inc in 2014, during her time as an MA student at the Royal College of Art. Since then Jennifer Lyn Morone's mission is to establish the value of an individual in a data-driven economy and Late Capitalist society, while investigating and exposing issues of privacy, transparency, intellectual property, corporate governance, and the enabling political and legal systems.
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DN18 | A Case for Data Dignity |Jennifer Lyn Morone | TheDataUnion.us
- 1. Hello!
- 5. Source: Dimension Data/National Geographic
- 8. CONTROL
- 9. Credit: Bryan Bedder/Getty/Concordia Summit
- 10. ADDICTION
- 11. Photo Illustration by Tracy Ma/The New York Times; Shutterstock (child and phone)
- 12. DANGER
- 13. Source: Future of AI
- 14. DISCRIMINATION
- 15. Source: Berkman Klein Center Harvard
- 16. REDUNDANT
- 17. Source: Technology Review Credit: Bob Al-Green/Mashable
- 18. Credit: Spencer Platt/Getty Images
- 19. 2013
- 20. Photo: Platon
- 21. JLM Inc Promotional Video, 2014
- 22. Embracing Extreme Capitalism Handbook, 2016
- 24. Jennifer Lyn Morone - JLM Inc, Hooked-Up Data Collection Diagram, 2014
- 25. JLM INC Data Packages, 2016
- 26. One version of Extreme Capitalism’s Economic Model, 2014
- 29. VISION
- 30. Star Trek Online - Age of Discovery
- 32. Josan Gonzalez
- 34. Microsoft
- 35. Google
- 36. Microsoft
- 37. REAL
- 41. Source: WiredSource: wired.com Jaron Lanier Glen Weyl
- 42. Source: HBR.org A BLUEPRINT FOR A BETTER DIGITAL SOCIETY For individuals and platforms, the future requires a fundamental economic shift. by Jaron Lanier and E. Glen Weyl
- 43. Principles for MIDs Fiduciary Duty Quality Standards Inalienable Provenance Benefit Sharing Competence & Professionalism Biological Realism Cognitive Realism Longevity (Mediators of Individual Data)
- 47. THANK YOU! The Data Union www.thedataunion.us @thedataunion Jennifer Lyn Morone www.jennifermorone.com www.jenniferlynmorone.com @jlmorone RadicalxChange www.radicalxchange.org @Radxchange
Editor's Notes
- A - INTRO Hi, It has been an inspiring couple of days. I hope you have all enjoyed yourselves. As we near the end of this conference, ready to go off with new tools learned and insights gained, full of excitement and inspiration, want to send us all off with some thoughts to consider about the things we build, why we build them and And what world we are working for.
- GOOD THINGS Looking back over the past days we have seen some wonderful examples of positive ways in which data, ai and machine learning improve our lives. -------NEXT SLIDE EMBODIED LABS-------
- We always like to see how machine learning can help us work less but better.
- How we can decrease disease and suffering by identifying patterns early on. Like we learned from Eduardo Peire, CEO of AI scope
- How we can keep each other and our fellow habitants safe. Tracking to stop poachers
- ------MY FAVORITE EXAMPLES------- How it can help us be more COMPASSIONATE Embodied labs is an example that uses VR to better treat patients and loved ones by stepping in their shoes and experiencing some effects of their disease, prognosis or their last days of life. 1.5 min -------BAD THINGS NEXT--------- BAD THINGS We are also all aware of some of the negative aspects these technologies can bring too.
- BAD THINGS We are also ALL aware of some of the negative aspects these technologies can bring too. -------NEXT DEMOCRACY UNDERMINED------
- CONTROL – This past year we’ve seen How democracy can be undermined for political power Through the exploitation of businesses who have commodified our data for their financial gain. EXAMPLE -
- The obvious example is How the Political consulting firm - Cambridge analytica used Facebook ads to influence elections Brexit Trump
- Another negative outcome we’re seeing is ADDICTION – And how programs and applications are made with the explicit purpose to addict us and children
- Meanwhile, the people developing them Go to great lengths to keep themselves and their families away from these exact products
- There is DANGER as Automation continues to be a concern. ----------LAST YEAR -------TOBY WALSH
- Last year some Toby Walsh warned about autonomous weapons, also called “killer robots”.. -------NEXT-------Virginia Eubanks----------
- We’re seeing Discrimination becoming a problem ----------Virginia EUBANKS------
- Social Scientist Virginia Eubanks, enlightened many with her book ‘Automating Inequality’ – which investigated the impacts of: data mining, Policy algorithms and predictive risk models on poor and working class people in America.
- REDUNDANCY worried about being replaced in the labor market and how to pay for life. ----------REPLACING HUMAN LABOR---------------
- Almost every sector except for data scientists are at risk - from factory workers, artists, lawyers EXAMPLE Recently, top lawyers in the US battled artificial intelligence in a competition to interpret contracts — and they lost.
- Taxi Drivers in Nyc Have been going to extremes to protest platforms like uber and lyft By committing suicide to draw attention to the issue -------------------------------- CONSEQUENCES The consequences are real and undeniable. And It’s hard to see what the goal is
- ----------B - PART 1 – MY WORK !!!! NEW PART------------- As an artist and speculative designer, I am interested in visions. I look at technologies and systems and imagine what impacts they might have on society. 5 years ago, I was questioning where these digital technologies were taking us and what they were doing to us.
- During that time Snowden came out with his revelations and I began looking at who else was collecting data and why Found many corporations and a growing industry. My concerns then were and still are economic inequality and the future of work. I saw potential and an opportunity in this data economy in that apparently…. Everyone created something of transactional, economic, value just by being. So as a response to the negative consequences of the incessant technology. I set out to gain control of my data, or try to, and explore and expose what data are valuable, to whom and for what. And critically establish a new way of “working” by living But I did so in a certain way, as a protest to data exploitation.
- This is a video that announced the start of this protest. --------PLAY VIDEO--------------- 10 min This quickly became an all-consuming task and a difficult one at that – - Learning the ins and outs of corporate personhood ---------- PHOTOS OF WORK NEXT------------ (Talk about project as you go through photos)
- Looking at life from a purpose and mission standpoint Creating value for others Producing more than consumind Self-governance
- Imagining how a society of data creators would gain control of their data by using the corporate container and treating it like intellectual property. And how we would be able to bring that data to market – here you have the intermediary being a cooperative data broker owned by the data creators.
- We set out began developing an application to collect as much data as we could from the individual standpoint.
- Even made the data bundled into packages and available in tangible form
- The idea - as said in the video – was to find out how I would be used, andto gain control of my data. The model that was aimed for was some kind of gamified version of life on one hand and a passive data income stream on the other. --- BREAK RHYTHM-------Stop talking about project, Summarize ---- My objective through this all was and still is a world where people, data creators, are treated with dignity and given control over their data and share in the wealth they are part of creating.
- Of course, I did not expect this to be the way this objective would be achieved. I was not expecting everyone in the world to become a corporation. But, it got me thinking about corporate goals and visions. And I started wondering the past couple of years what exactly is the goal of all this data acquisition and AI, there must be an objective.
- Q - @ Company So, I went to One of the biggest technology companies in the world to sit down with people working on AI and machine learning and find out what they were working on and what the goal was. ----------Talk about how you really spoke to them-------- Many didn’t have an answer and looked puzzled by the question. Others could give only a narrow presentation around their research or product. And Some flat out said “I don’t know, but I don’t think it looks good.” Quickly came to realize there really was no….
- C - VISION …Vision Well, not really -----DO NOT BRING UP CONSEQUENCES------
- Fantasy Star Trek – ultra utopian – man bows before the technological enterprise There was one person who described what he thought the goal was. left this planet and travel around and live forever. But this absence of vision among the employees of the companies that are creating the world around us Was really startling. Of course -----DO NOT BRING UP CONSEQUENCES------
- we have an endless amount of dystopic visions, ever since the industrial revolution… Example EM Forster – ultra negative but can’t deny there are parallels with reality In 1904 EM Forster published The Machine Stops, which is a vision of a world whose society is isolated from each other each with a basic theme to teach each other over a cable and through a video box – sound familiar? Internet and video chatting.
- -=DYSTOPIC visions------------------------------------- We seem to know how we don’t want to live, even though we get shockingly close to these visions So I began hunting for positive visions but could only, for the most part, find corporate ones…. -----DO NOT BRING UP CONSEQUENCES------
- And Of course, these companies are heavily invested in me believing in these kinds visions of the future. Drones delivering food -----DO NOT BRING UP CONSEQUENCES------
- Of a world of abundant displays -----DO NOT BRING UP CONSEQUENCES------
- That is interconnected And we live forever Via their clouds -----DO NOT BRING UP CONSEQUENCES------
- -----DO NOT BRING UP CONSEQUENCES------ Now, of course there is a connection between the profit motive and the positivity with which they can think about the future. But a lot of the negative consequences of data use and ai are because of the profit motives. --------IMPORTANT--------REPEAT IN CONCLUSION-------
- D – PRACTICAL EXAMPLES RELATED TO DATA THAT AREN’T FOUNDED ON PROFIT MOTIVE Fortunately, there are some positive examples of common goals emerging even in this absence of common visions.
- For example - VTC After Uber cut fares across Paris, some of its drivers created a competing service, VTC Cab. Which is Modeled after Uber, but this ride-sharing platform aims to give drivers more control over their business and provide passengers an opportunity to support a French company. As the app’s founder, Mohammed Radi, told the Verge, "We want to re-establish and regain our rights over Uber. Uber is not representative of our community... They are a technology company which has no connection with the world of transportation. So they treat human beings like a number — you know, like a figure on a computer. And being a number, as a driver, it's a very bad feeling."
- Airbnb has sent a comment letter to the U.S. Securities and Exchange Commission, asking it to allow the home-sharing company to give equity to its hosts. Perhaps soon we will see a world where hosts and guests are the shareholders.
- MiData is an example of the kind of vision to achieve data dignity: They are a cooperative personal health data bank that returns the value to the individuals and the community and not third parties (e.g. shareholders) The cooperative is owned and controlled by its members and not by shareholders (of Google, Facebook, etc). And Profits are invested according to the member’s needs And as a Cooperative, the company cannot be bought
- Two visionaries who are working the offer up potential solutions are Glen Weyl and Jaron Lanier-
- They recently published a paper that lays out a vision for achieving data dignity through the use of 8 principles
- These principles would be applied to MIDs (mediators of individuals data ) They are as follows: Fiduciary duty – do what is in the best interest of the data creator Quality standards – like bbb Inalienable provenance – differential privacy Benefit sharing - regulations that 70% of value of data is returned to the creators of that data. Competence and professionalism - expertise and a clear mission. Biological realism - realism - strive to create outcomes for members that benefit them over their lifetime - like a portfolio - diversify royalties and income and grow it like a retirement fund. Cognitive realism - maximizing the agency and dignity of members by having clarity and giving the member control - setting their price with simple systems. Longevity - Shouldn’t last forever, but past a humans lifespan, like insurance companies. “MIDs will be the guardians of intergenerational digital wisdom and context.”
- Via this pursuit of postive visions and developing my own vision of a society that achieves economic stability via things like data, Connections started being made glen and I met And together with james felton keith Founded the Data union for the USA Of which we will apply the principles to MIDS Talk about what else the union will do and lead up to people coming together
- Talking about visions and working on overcoming inequality brought even more people together – Earlier, this fall, we founded Radicalxchange - an idea driven movement, inspired by ideas from this book We have come together as artists, communicators, researchers and academics, technologists and entrepreneurs, activists and people in government to harness market mechanisms to challenge outmoded rigid forms of capitalism and unresponsive politics. In march we are going to come together for the first time to collaborate, imagin, innovate and create a more inclusinve future. This is actively coming up with visions. 22 min -----------E – CONCULSION---------------
- E – CONCULSION The absence of visions is striking but the tide is turning. We have and will see good and bad examples Corporations will continue to infiltrate our excpectations with their visions of the future. But we should remember that these positive portrayals have a profit motives for accumulating wealth; Which we have to be wary of; But we saw and will continue to see positive and practical examples of companies that adopt business models that can drastically change the outcome to one that is good for all. So, as we end this conference please be conscious of what we work on. If doesn’t lead to a future that we imagine to be a good Then we shouldn’t do it. --------POINT------- STRIKING BUT NOT GRANDIOUS---------DIGNIFIED-------------- A vision of the future is not going to work out when data is used to increase consumption, profit or control. A dignified vision will be one that is collective and shared.
- THANK YOU CONTACT PAGE