Uberveillance and Artificial Intelligence
I really enjoy giving guest lectures, especially in classes coordinated by my fellow collaborators. Today I had the great joy of sharing 30 minutes on conceptualising uberveillance in the context of artificial intelligence.
Additional Links:
Competing in the Age of AI
https://hbr.org/2020/01/competing-in-the-age-of-ai by Iansiti and Karim R. Lakhani (HBR)
National Builder: How Much are Governments doing with your Citizen Personal Information
https://www.katinamichael.com/media/2021/3/30/sa-liberal-partys-use-of-nation-builder-software
https://www.katinamichael.com/media/2021/3/30/political-parties-and-data-harvesting
Automating Higher Education - Giga-fying and Uberizing Education
https://slate.com/technology/2021/03/trolley-solution-shiv-ramdas-short-story.html
https://slate.com/technology/2021/03/trolley-solution-response-essay-automated-higher-education.html
Citation: Katina Michael, 1 April 2021, Uberveillance and Artificial Intelligence, in Rob Nicholls, COMM2050 Data Use and Misuse, University of New South Wales, Kensington Campus.
Zoom Transcription - brought to you by AI Software Speech-to-Text
* Better than nothing? Imagine putting this into a Machine Learning algorithm? Is more data better or is better data better? :-) Have a read.
WEBVTT
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Rob Nicholls: Well Christina thanks, very much for agreeing to talk to our group day, so this is come to 050 data use and misuse and i'm really pleased that.
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Rob Nicholls: Professor cortina Michael from Arizona State University has agreed to come and talk to us this morning on uber Valence and artificial intelligence identity location and condition, monitoring and i'll hand over to you thanks Katrina.
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Katina Michael: Thank you so much rob good morning everyone it's great to be with you i'm giving this talk on the Valence and artificial intelligence and I might take off my headset actually and.
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Katina Michael: The TOEFL look at.
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Katina Michael: The antecedents of uber violence attorney likely you haven't heard before and put it in the context of artificial intelligence.
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Katina Michael: And this process of dignifying so many of our business processes and government processes and what the fallout from that might will be going into the future and so uber Valence In summary, is the ability to garner someone's identity.
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Katina Michael: Their location and their condition and by using the census information.
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Katina Michael: to predict and to.
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Katina Michael: proactively states.
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Katina Michael: The context that somebody is in, so I want you to think about this, if I know who you are where you are what condition you're in I can probably in forgive state of mind.
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Katina Michael: And I could possibly inform your next actions and if I couple that with behavioral data that identifies touch points interactions both in the cyber world and the physical world.
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Katina Michael: Then I can know quite confidently how you may act or react to certain scenarios.
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Katina Michael: And so we've come of age when the term uber balance was conceived by md Michael back in 2006.
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Katina Michael: This big data was beginning to proliferate.
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Katina Michael: But it wasn't what I would call the onslaught.
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Katina Michael: Of the big data we have available today, so I came from an industry, I was working in network planning, I used a lot of telecommunications data.
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Katina Michael: With geographic information systems and also statistical data through the Australian Bureau of Statistics if I was working in Australia and other statistical bureaus across Asia for about six years.
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Katina Michael: And all the time, I will be marrying up customer data from telstra, for example, the product plans our future manufacturing.
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Katina Michael: equipment that will we would be selling to telstra and would couple that up with customer data, even the torture white pages at the time, even though that practice is now illegal.
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Katina Michael: But i'm talking about the MID 90s to late 90s when things started to become digital and digitized and i'd say around 2006 we had this explosion just before.
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Katina Michael: Empty Michael coined the term is surveillance, we started to see some big public systems in the form of social media in the form of dynamic websites what i'd call content two point O war multimedia rich and so, then the harvesting began the view of what we would do with that data began.
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Katina Michael: And so, if surveillance today in the context of artificial intelligence, which is a convergence of all of this different kind of computing stealth.
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Katina Michael: is causing a conundrum it's causing a dilemma it's causing can I go that far, am I allowed to do this practice, but this is where I would take the business process.
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Katina Michael: But as your home reading that Professor Nichols gave to you on artificial intelligence from the Harvard Business Review stated, it is about this disintermediation, it is about the Ai fide world it is about, do we really need humans in the loop.
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Katina Michael: And we what might happen when we remove humans from the loop when we remove the oversight bodies potentially when we removed the influence of what we call in business, the business world, a capability.
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Katina Michael: A dynamic capability and dynamic management capability.
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Katina Michael: So we know what the seas are we know what the mcs is is injection of the human as manager, to see a business process in a particular way, but what are our bounds well the law tells us what our bounds on perhaps our imagination tells us what our bounds.
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Katina Michael: But, deep down inside, how do we know when something is useful or really as a misuse.
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Katina Michael: And I refer back to one of my lectures at ut So when I was doing the bachelor of it program scholarship there back in the mid 90s.
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Katina Michael: He said we could use the TV test it smells fishy test the if I put myself.
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Katina Michael: In someone was recording my actual action would that change my action, the mom test, you know if I was doing this in front of my mom what would that mean we had all these different tests to look at legality and ethical it.
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Katina Michael: So something could be legal but unethical, perhaps it could be legal and ethical, it could be illegal, but ethical, it could be illegal or unethical and unethical.
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Katina Michael: So all of these different things I want you to think about when we go through the different case studies that i'll be sharing with you.
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Katina Michael: So I allows for the disintermediation of processes, perhaps escaping that middle person that would inter mediate an agreement.
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Katina Michael: A process and it allows us now to do things that we would never do before, because we have access to the data through the explosion of information around about the time of web two point o
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Katina Michael: We had the explicitness of what was in here, he being blurted out in the online world.
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Katina Michael: So previously, we take family photos but we wouldn't share them online We certainly wouldn't share them strangers.
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Katina Michael: But it has become a normalized activity, when I say what i'm doing I I go to a public website with a public persona that I possibly curated in a particular way container the academic container the family person container the one who has a Community interested in privacy, for example.
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Katina Michael: But we manage these different profiles, but how much we manage them is really an interesting thought I think many times they manage us.
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Katina Michael: And if you just go cold Turkey as i've done a little bit over the since November you start to realize how much you have shared on the line.
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Katina Michael: My personal website container market COM will will show you the depth and the breadth of my work over the last 15 years, but it also has some personal things on it.
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Katina Michael: So it's there to be utilized it's there to be managed it's there to be placed into some kind of machine learning algorithm it's then perhaps for the government.
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Katina Michael: To say oh this container model is an individual, we want her to vote for us next next election, I think our web scrape whatever I can in an offshore organization.
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Katina Michael: And maybe i'll use the electoral roll, as I am a political party and maybe marry up that data with her in a subject record.
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Katina Michael: And figure out what her sentiments might will be and I can do that now through text increasingly we have image analysis tools that allow us to look at images to denote what is happening.
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Katina Michael: and even more so, what we all should be thinking about is the video analytics that is taking place, which I talked about back in 2013, particularly when we look at the facts and temporary but that's another issue.
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Katina Michael: The main issue I want to get through to you today's if you're a business entity or a government agency, these two stakeholder times.
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Katina Michael: What are the limits of the potential use of data and when do we say it's misused, when do we say we're pondering or we're tearing on over Valence and so i've got a short presentation and then I go into a discussion.
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Katina Michael: So my journey began in 1994.
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Katina Michael: And for over 20 years i've been collaborating with md Michael.
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Katina Michael: Where we've been formally researching the social implications of marketing people, something that seemed quite bizarre to most people when I began my thesis.
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Katina Michael: But my honors thesis in my undergraduate degree was actually on the potential to look at the embeddable devices.
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Katina Michael: And what that might mean for identity and I found this wonderful lady Professor Jennifer edwards, who was a wonderful researcher at Uta she's still ETS as a professor emeritus and, at the time I was working in Andersen consulting which is now essential.
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Katina Michael: And I was offered a job, actually with Arthur Andersen which I declined to do further study would you believe so, I went to the Andersen consulting library, and I wanted to see what data was available on this idea of marketing people.
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Katina Michael: Believe it or not, I got support from the end some consulting librarian he says, I think I found something for you one Sunday and I was in the most weekends for that six month internship.
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Katina Michael: and, later on, while I was doing my PhD the company, I worked for not or networks for six years, a global manufacturer of telecommunications equipment.
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Katina Michael: sponsored the first cyborg one point O experiment which was an implantable experiment and, at the time, our CEO john Roth was telling us, while we've created smartphones.
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Katina Michael: And there was a nortel networks smartphone he said we're going to stop manufacturing the smartphone because I believe.
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Katina Michael: It won't be too long before we have a brain to brain interfaces and Lo and behold, today we are seeing the beginnings of murmurings about that, but I want to basically say to you.
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Katina Michael: that the human metaphor, that was defined by an internal employee of Anderson consulting and, here are some internal documents that I can only show you now, because the company does not exist, the human metaphor was moving to the end of technology, what does that mean.
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Katina Michael: And it was about eliminating the human computer interface.
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Katina Michael: In many ways of Ai does penetrate without an implantable the brain because of the things that I argue in terms of its ability to know your touch points with the online cyber world.
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Katina Michael: And so let's extend this and say Okay, the human metaphor is not really about the human.
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Katina Michael: it's not really about the elimination of technology it's about knowing the person within and potentially being able to predict.
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Katina Michael: Their thoughts their sentiments their ideas, based on both historical data.
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Katina Michael: And this amazing algorithmic approach through neural networks of machine learning, I give them machine something to look at I let it study it and either in a supervised way we're in an unsupervised the way.
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Katina Michael: I say go for it in a supervised way usually uses regression analysis in an unsupervised way it learns from the data set to determine the unlabeled and unstructured and untag data.
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Katina Michael: And so there are these two different views of machine learning, some of you may have heard of deep learning again but not many people are talking about the limits of these tools, but what we're going towards is almost the knowledge of what the person has within the scope.
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Katina Michael: Being able to be used in different business functions, for example, the marketing process, which is about price promotion and other PS, the four p's.
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Katina Michael: is about knowing how can I use the data that is emanating from cantina or containers online persona or personas.
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Katina Michael: to drive my next product development, so I know for a fact if I introduced a feature to my headset that that feature will be bought by a container or a type of container is that okay if we're using big data for service provisioning.
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Katina Michael: Is it okay if we're using big data or machine learning practices to manipulate or exploit the end user to buy more.
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Katina Michael: And so I say here are my attractive customers containers a big spender she came on last week, she did multiple purchases The week before, but I also know what time of day she comes online to buy.
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Katina Michael: And so i'm going to just strategically send her a micro targeted message about half an hour before she usually jumps online on a Friday night to do her spending therapy.
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Katina Michael: And what we found again and again and alibaba is mentioned in this Harvard Business Review, they are the King and kings of doing this because data is gold, I have heard senior people within the organization.
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Katina Michael: The organization of alibaba present at conferences and say we're really interested in the big spenders so the second T services for the rest.
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Katina Michael: But when we kick in with the pareto principle that 20% of your customer base spends.
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Katina Michael: 80% of your total revenue or is responsible for 80% of your revenue you start to realize the power.
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Katina Michael: of creating t's and classifying if any of you have ever traveled in the States you'll know that there's.
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Katina Michael: A row for the gold member of X and as a row for the platinum platinum and there's a row for the.
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Katina Michael: People who have gone in and bought online for the cheapest price for the ticket it's like seven, it is, and my kids are scratching their head sometimes when we're traveling to the States don't mom.
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Katina Michael: Do we really need this content just call out the Rose but no it's all got to do with the algorithms.
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Katina Michael: And so, when you jump online you're just not container Michael or whoever, you are rob Nichols.
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Katina Michael: Your container Michael with this value, like in principle behind you, the one who will spend that Friday night when we start to poker with micro targeted messages.
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Katina Michael: The one who potentially can be an influence and opinion leader within her peer group for brand awareness and so.
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Katina Michael: You know if I do something on social media and it looks like containers and dose this will 20 other people go, you know, we should buy this because container wiser, and so we are now going from this metaphor for the computer.
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Katina Michael: The human being to the end of the computer interface, how can I get you to the end of the shopping cart.
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Katina Michael: as quick as I can, to press that that button that says i'm buying what processes can I cut out from that buying experience.
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Katina Michael: So Kevin endo has never been more important and I guess Andersen consulting view of the world, or something like this is what the human metaphor was like going stick.
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Katina Michael: I can't read it, but top of your head i'm not talking to just a person guys and girls and everyone they knew exactly what was coming this explosion of data, this.
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Katina Michael: i'm going to take what I know thing i'm going to i'm going to write it out as a consumer.
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Katina Michael: i'm going to serve whether I think these products things i'm going to say whether I like something or i've had silly thoughts, this evening, or I had a date that broke up or whatever we explicitly state online.
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Katina Michael: But don't be fooled people are watching and this violence is what precedes the uber the exaggerated surveillance, the the above and beyond surveillance of what zip of course surveillance capitalism, but i'm going to say if a balance came a good.
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Katina Michael: time before surveillance capitalism.
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Katina Michael: So, as the end of the computer interface think about that we are in during this coven time we've been talking contactless we've been talking frictionless.
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Katina Michael: And when there is no friction, we end up swiping that card faster and faster was or continent prison i'm doing it from my from my home it doesn't feel like buying the reason hard cash being given over to the other side.
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Katina Michael: And so technology so sophisticated, it cannot be seen, or that pointed to me to embedded technology can't be seen it's not transferable is micro targeting at its best and it's a movement away from this notion, now we just did be done for aggregation.
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Katina Michael: We just did a big data, so we know what people do a collection districts, or at the statistical local area.
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Katina Michael: Or the household level no friends, this is now going beyond this sort of mass surveillance to this micro targeted reaching out because I know who you are perhaps not another human who knows who you are, but the machine, as you as one.
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Katina Michael: Article said, better than you know yourself, because he can categorize and cluster.
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Katina Michael: All those transactional points that we can't even remember we can't remember if we thumbs up something five weeks ago or six months ago, or three years ago.
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Katina Michael: But pulling this data together and inferring through the patents that are uncovered and and Eden, and are invisible the machine knows that, and can penetrate within that's where I take the human metaphor, and so this is the image are really want you to take away today.
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Katina Michael: These things, ladies and gentlemen.
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Katina Michael: Are in here.
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Katina Michael: We made for the time being beholding something and having to enter details in, but what is, what are we entering it's what he and so when Google says they want to be the third half of your brain it's a fascinating.
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Katina Michael: slogan, the third half of your brain, because if I know how your brain works, I can push the right buttons I can exploit you, and this is where I think we are grappling with machine learning practices.
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Katina Michael: How far do I go to push the buttons to predict and how far is it Okay, because I want my business to fly, and I want people to buy products that they need.
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Katina Michael: Rather than influencing them in a way, and recommending to them in a way, things that I know that are implicitly one.
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Katina Michael: they're like this, or give them more of this because more of this means more sales more attention economy more watching more sucked into my to my to my idea of the world.
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Katina Michael: And so, where are the limits and are we going to get to a place where we say there's nothing really wrong with the use of machine learning.
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Katina Michael: If it helps us to do better service provisioning and infrastructure, providing smart city designs more safety.
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Katina Michael: Because there are so many great things about machine learning that we can see, to do with limited resources to do with energy efficiency if we only had the capacity.
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Katina Michael: To come up with public interest technologies and machine learning was concerned there'd be no problem here, but we're seeing massive discriminatory practices take place.
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Katina Michael: When person X is perhaps taking a rideshare to a African American Community and so hyped up the process I don't want my drivers going there.
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Katina Michael: or I rented Katrina and her kids they're a bit loud in my rideshare the next time I pick her up i'm going to hope, the price because she's got a baby with a disability, whatever the question here is how are we manipulating the algorithms and how are they manipulating us.
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Katina Michael: So if the Valence again identity location condition inferring situate situational awareness towards predictive profiling.
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Katina Michael: I know who you are where you are when and what a movement away from mass surveillance to deliver violence which then starts to question and have consequences for human rights.
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Katina Michael: it's okay in the criminalisation space, but hopefully not taken to the point of minority report, where you have the cogs making preemptive.
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Katina Michael: choices about criminality, think about this now in the buying experience its container I preempt this i've used structured and unstructured data to determine this in the real time, if not real time.
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Katina Michael: to influence the decision making and so moving away from this total information awareness, to the specificity of what's in your skull what's inside this this picture, he called the brain.
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Katina Michael: And i'll leave you with this.
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Katina Michael: motif.
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Katina Michael: Think about where we're going as if it was a black box recorded in your head Professor Nichols who I admire so greatly had one sent me an article.
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Katina Michael: On the fight recorder that was being used by our Defense forces a little device placed on the back of a helmet or back on the back of a backpack that would be able to support the Defense personnel army officer, for example in knowing.
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Katina Michael: Whether we're located to support the management of troops, and this was a test case but that article you sent me hasn't really gone from my mind.
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Katina Michael: Except that energy model and I were talking about embedded devices why carry something that's transferable.
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Katina Michael: When something like this could be potentially implantable containers black box rob's black box your black box and what does that denote about patterns of movement, including the trade off between convenience and Karen control and even safety.
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Katina Michael: Now, where evidence was ahead of its time was in the definition of the access of access.
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Katina Michael: This is before we had the face and disinformation happening rife with social media mg Michael said, there are three fallouts.
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Katina Michael: misinformation the misinterpretation of data and perhaps the worst one of the more information manipulation I misinform you deliberately that's done a misuse and misinterpret the data that's not deliberate it's accidental perhaps.
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Katina Michael: But then I infer that you have something, for example, you bought a book for a friend and that book happens to be a best seller for the gay, lesbian community.
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Katina Michael: The system infers you yourself a gay or lesbian and the system has has been wrong in its interpretation.
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Katina Michael: of your buying behavior, this was an example that it was actually published in 2004 I think as an Amazon fallout back then.
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Katina Michael: And then information manipulation which is like the deliberate misuse.
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Katina Michael: And so what we're going to find with machine learning and Ai as we progress down this path and i'm not going to say up implantable just knowing more about the consumers mindset and context is how much of it will be accidental as opposed to deliberate.
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Katina Michael: As an employee as a programmer as a lawyer, as a business process period where do I see it, and when do I say now, this is becoming a little bit uneasy for me.
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Katina Michael: How do I manage this dynamic capabilities, for example in the field of management if i'm a manager and how do I ensure my customers are not purposely manipulated for the sole practice of profit maximization.
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Katina Michael: Now i'm going to share screen very quickly and allude to you to an article.
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Katina Michael: Just find that that came online for the South Australian Government and last week, I was interviewed by ABC Adelaide in South Australia.
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Katina Michael: Around the potential use of a of a platform called nation builder nation builder is a one stop shop integrated unified communication messaging and website system.
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Katina Michael: That was used during trump's election campaign was used during brexit 2016 was even used locally.
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Katina Michael: In New Zealand for the 2017 successful election of a turn So what we are seeing is that the majority of political parties and government agencies are relying on this nation builder platform that was built by Zuckerberg roommate at Harvard.
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Katina Michael: And he studied organization, but he also studied things to do with how do we take electoral roles, how do we take publicly.
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Katina Michael: Available data that consumers and citizens post online and then, how do we take sentiment analysis of different touch points, perhaps as they are interacting with the government website, in this case, it was the Prime Minister and cabinet website.
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Katina Michael: Somebody knows noticed in the status bar at the bottom a redirect to nation builder and everything and pretty much erupted about 48 hours ago Steve Marshall the state.
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Katina Michael: premiere had to come online the state Ombudsman came online I had to go talking about what potentially might be happening any what man will be innocent.
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Katina Michael: The Liberal Party may well be using the website to facilitate the dynamic a release of media relations as they are in government.
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Katina Michael: But the other possibility is that they are conducting data harvesting.
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Katina Michael: And so we're do we say enough is enough if this is the practice which is currently being investigated.
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Katina Michael: When do people have consent when did I have transparency when did they know that data is being crucified or data fight about them, how is that data being used to manipulate this sentiment.
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Katina Michael: And so, with one minute to go, I want to expose you and i'll put this in the chat and to wrap up, I also want to expose you to this notion of how much of higher education can be automated.
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Katina Michael: As you all gone through this with with Professor Nichols and myself as faculty.
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Katina Michael: it's a striking story that I respond to written by an Indian chief.
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Katina Michael: renders it talks about the trolley solution where a college Professor is pitted against an Ai machine the machine is called Ali and the Professor is supposed to have a go at competing with Ali for the best kinds of scores for the students.
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Katina Michael: But again it's about this this aggregation is disintermediation this versus this and i'm going to finish by saying to you i'm not here to demonize technology is never this or this.
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Katina Michael: it's this which we love and how can we.
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Katina Michael: play some kind of regulatory bounce around it, so that we can exploit it for good and not harm people so with that i'll stop and say thank you for the opportunity to talk and play some links in the chat and just hear from you in as we're closing rob.
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Rob Nicholls: Right, thank you very much indeed cortina That was really excellent, and I really enjoyed it and i'm.
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Rob Nicholls: really looking forward to working out whether i'm still going to be here next week or whether i'm going to be replaced by by Ai so i'll have a look at those those slight articles and i'll also note that.
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Rob Nicholls: Both both major political parties in Australia use that same system.
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Rob Nicholls: So that could be either there, so I thanks very much we were actually at times so.
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Rob Nicholls: What I suggest, if there are any questions that you've got for container if they're burning questions pop them in the chat box now.
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Rob Nicholls: Otherwise, we might collect them and I might might invite patina back to have a chat about them in the future if that's okay with you Christina.
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Rob Nicholls: And otherwise i'll see you, as I said, of having been replaced by an Ai at 10 o'clock next Thursday enjoy your long weekend it's public holidays on Friday and Monday here and throughout the whole of Australia and thanks, very much indeed Katrina Thank you.
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Katina Michael: Thank you have a lovely long weekend bye bye now.
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Rob Nicholls: bye folks.