Justice by Design: How Emerging Technologies, Privacy, and Social Justice Collide

Justice by Design: How Emerging Technologies, Privacy, and Social Justice Collide

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Hi there everybody, welcome to our  CPGE EDI webinar. I am thrilled   today to introduce you to my dear friend and  world renowned privacy expert, Ms. K Royal. I guess I could call you the honorable K  Royal since you are a licensed attorney,   but Kay has the entire alphabet soup of privacy  qualifications and is a prolific privacy author. She has over 60 news articles, is a featured  privacy tech columnist for The Association   of Corporate Counsel. She also initiated  the Association of Corporate Counsel's   Women in the House programming supporting  women in health counsel and the ACC elected K as their member of the Year in 2015,  and the recognition of her extensive   leadership. She is an executive board member  for the Center of Law, Science and Innovation   at Arizona State University as well as an  adjunct professor of privacy law, and she's won just about every award you could possibly  imagine for a pro bono service awards and   for her outstanding work as  an attorney and a privacy   expert and I'm super excited to hear your  presentation today K. Thank you. Welcome K

I'm wondering if this shows  everyone how you supplement your income by taking prolific bribes. No, thank you so much for having me  Darra was one of my absolute favorite   law students back when I worked at the  Arizona State University College of Law   running the student life and the pro bono, and she  actually impressed everyone on day one when one of the most famous and most argumentative  professors did a sample socratic method to   the entire entering class on the welcome  day and Darra gave it back to him just as   good as she got it and got the attention of  everyone: the professors to staff, everyone standing up. So, love being here, but okay  this isn't the K and Darra loves each other   show. So let's jump in, I'm going to share  my screen and this is absolutely an open  

conversation so if anyone has any questions  please please do not hesitate to ask any questions that you might  have. Jump in, interrupt us,   chat, whatever. Darra please  feel free to do the same.   I have no intention of killing everyone  with death by PowerPoint whatsoever. Okay, so today she introduced me, but my email  addresses are on the presentation as well. That   way you can make sure you can get hold of  me if you have any questions whatsoever.

I also co host a podcast is very popular  actually in privacy. Today we released   an emergency session on standard  contractual clauses out of the EU so   love it when things are published within 24  hours it means I do minimal editing work. So, let's give everyone kind  of a basics in what privacy is.   And if anyone, if everyone wants to speak  up and raise their hand and say yes we   already fully understand privacy, then we  can skip kind of doing a grounding in it.

Otherwise I'll give you a little bit of an  oversight and hopefully this will put it   in perspective as to why does privacy matter.  It's actually the hottest growing field both   in and out of law right now and it's my  understanding, I'm speaking to librarians, students, although that's not what  you call them. Data custodians. We have library students and information  science students. Information professionals   and sort of the big term for our field.  So this should really absolutely help.

So you may hear the term personal data,  personally identifiable information,   personal information. So, PI, PII. What does it  all mean? Well when you kind of look at it overall   all of it is kind of putting it into one  category although they actually do have different nuances, but essentially it means  information that's linked to a person.   And there is absolutely nothing in the  definition that says it has to be personal,   personal information it can be business  personal information, it can also be publicly available, personal information. There's  nothing that says it's confidential.   So a lot of times when I talk to sales  people at companies they'll say well we   don't have personal information  so we don't need to do all this.

Well, who do you talk to? Who do you call?  Who do you email? Who signs the contract?   All of that is personal information, and it  doesn't matter if you have the person's name. That is a critical thing to understand.  You don't have to have the person's name   in order for it to be personal information. It  merely has to be information that relates to   or is capable of being related to an  identified or potentially identifiable person, and I'll give you a wonderful example, very  common way of the identifying photos people.   Y'all tell me if you can tell who this is. Personal information, even if  it is commonly dei dentified.  

And this actually matters when it comes to things  like HIPAA when they're like, I'm taking pictures   of patients and hospitals, but you can't identify  who it is so it's not really protected under HIPAA. Well, is it a unique injury. Are you at a hospital where you  only take certain types of cases?   Is there an identifying mark on the individual  such as a tattoo or particular mole or birthmark   or something like that. If you can identify and  narrow down who that person is with information that is available to you then it's personal information and nowadays  information that is available to people come   from all over the place. You don't have to just  look at the databases within your own company,   there's information freely available  online or from other companies. So that really impacts it. Now, this is the law and I promise not to kill  you with the legal stuff, but you kind of need   to understand that in the United States,  the word privacy is not in our Constitution.

And people think it is, but it's not. It was not until the Griswold case in  1965, I believe, where they established   officially that the penumbra of the Bill  of Rights, specifically the first and the   third and the fourth and the fifth and the ninth  and the 14th amendments actually do mean your private, so you're not being forced to quarter  soldiers, therefore you have privacy of your home. And thank you, Darra just completely  keeping us updated with notes I love it. So these emanations of privacy. Thank you Darra,  that are in the penumbra has actually give us a   constitutional right to privacy. However there  are 11 state constitutions that include privacy  

in the constitution, California is one of them. Although California is was voted into  the Constitution, Arizona has it and   it was actually in the constitution when Arizona  became a state. It was put in there deliberately. There's also federal laws. The Electronic Communications Privacy  Act, Video Privacy Protection Act,   I love to throw out here especially the  video privacy one. That's an example of   privacy laws coming to fruition because  of something happening in the world. And quite often laws are passed in  reaction to something that's public outrage   and the video Privacy Protection Act came because  the video rental information was released or   breached, and it included the video rental  list of some of the US Congress people.

Therefore, it became a law that you  have to protect the information. So, but one of the other things is  to pay attention to you'll hear a lot   from the Federal Trade Commission . They're  an agency in the US, that you would not think   is actually protecting privacy, but there is  section five, which prohibits unfair defective or unfair or deceptive acts in trade. And  so what they particularly look at are the   privacy notices online for companies and if  companies say they do something and they don't,   or they say they don't do something and  they do, then it can become a deceptive trade practice, and it used to be that privacy  notices were very wordy, very flowery. Attorneys  

would get involved and say we protect your  data to the highest protection imaginable. Well as you can imagine that not true,  because all security can be broken.   And so now you need to make sure that  your privacy notices are merely factual,   and one of the interesting things is under the new  California Consumer Privacy Act and the soon to be in 23 California Consumer Privacy Rights Act  is companies have to disclose whether or not they   sell or share your data. Now sell is very broad.  It does not mean selling your data for money. It can mean exchanging your  data for something of value,   and a lot of companies say well we don't sell  the data so we're not going to put it on there.

They have to put in their privacy notice  whether they do sell the data or whether   they don't sell the data, and if they  do who do they sell it to giving the   very broad definition of exchange  of value not necessarily money. And as you can imagine if they get  it wrong. The FTC can come after them   for deceptive trade practices. So it's  very interesting conundrum going into. There's also tort law I don't get into it,  but people can sue for invasion of privacy   intrusions, highly offensive, there's  all kinds of things privacy's related to.  

Then of course the main federal acts here in  the US. HIPAA, which is the Health Insurance Portability and Accountability Act,  FERPA for education, GOBA for finance,   and then the Privacy Act of 1974 for  government data for public sector. One   of the interesting things to realize is the very  first privacy law in the United States or not even in the United States, in the world is recognized  as being 1970, I believe, and it was in a   province of Germany, and the first  country law was the one in Switzerland,   but it was at the same time that  the US started passing privacy laws. And so they say the US doesn't have good privacy   laws because we're unlike the rest  of the world and that's not true. There was actually just an Italian case that  came down about a doctor who published an   article about a patient, and it was  in a medical journal and the Italian   enforcement agency had to come down because  you didn't get the patient's permission to do it. He didn't identify the information. Europe is  all up in arms because you know this Enforcement   Act. Didn't the doctor violate privacy and  here in the US, there would be no question.

So, matter of fact, if the doctor tried  to publish it in a journal here in the US,   the journal probably would have de identified  it for him, and would have asked for a signed   permission from the patient to use it  so it's interesting to see how the US privacy law definitely butts  up against global privacy law. So let's move on just a little bit we've  talked about this little bit. GDPR is Europe   is the General Data Protection Regulation,. It is  actually driving privacy laws worldwide. Brazil   actually modeled there's after the  European Union's GDPR and now that the UK has exited the European Union,  the UK has their own version of the GDPR.   Canada has privacy laws although people  like to say they have no teeth, because   they don't do a whole lot of enforcement they  actually have a proposed privacy law now that they're looking at doing a whole lot more  sanctions and violations and having appeals   and being a lot more formal. And here in the  United States, Virginia actually passed a law,   just this past legislative season that's  modeled after the GDPR even use the terms controller, processor.

So with all that. Let's start  diving into what are the   specific pillars of privacy? What do you need  to do and we're again we're the aim of this   is to get to the artificial intelligence  and the social justice and how this works. So if I go too fast, please don't  hesitate to tell me to slow down   apparently I'm one of the fastest talking  Southern people most people I've ever met.

So, just feel free to say whoa stop explain  that a little bit and we're good. Darra jump   in if you got questions. So, under the privacy  pillars and these are pretty standard things   that happen under all privacy laws.  So you might not be able to comply or know all the privacy laws in the  world, much or the ones in the US,   but at least you can understand the general  principles of them. So transparency and  

notice means exactly what it says, tell  people what you're doing with their data. Now, my children who are much older than  I would like to admit they are right now   used to ask why do we write privacy  notices if we know people don't read them. Raise your hand. I don't even have to see  you raise your hand if you read the privacy  

notices of all the websites you go to, or the  privacy notices of all the apps you download. And if you reject certain permissions  and the app you download. Do you have   your phone set for automatic updates of those  apps because typically they go from anywhere   from 12 permissions you give them when you  initially install them to an average of about 120 on updates. So even though you  might have said no to permissions   if you're set to automatic updates  and you probably have it anyway. So transparency and notice,   why do we tell people, because it's  the only way we have of telling people. I mean I'm sorry absorb that very  simple statement, the only way we   have giving notice and telling people  is to give notice and tell people.

So it's a broken system, but it's one of the  only options we have. Consent is very touchy. You have to give people full information in order  to get consent from them and if you're going to   gain consent for something then you also have  to make it equally as easy to withdraw consent, and giving consent can be something  as easy as checking a box online,   but yet when you want to go back and opt out or  you want to withdraw your consent it's usually   write us at this email address and make it a,  you know, I don't know federal tracked package that requires a signature  and include three copies. It's not easy usually. And so you have  to make it easy individual rights,   we've always had rights under HIPAA. Ever since  it was passed, lot of laws now we're starting   to include them and one of the biggest ones  we're starting to see is the right for deletion and so you can generally request that your  data be deleted. And this is very important  

both to archivist and to data analysts is can you  delete data if it's going to break the database?   No, there are exceptions under  deletion including if the law requires you to keep the data you can tell them  no we're not going to delete the data. So a lot of things there. Privacy officers  having someone that knows privacy,   whether it's an attorney or a  non attorney. I've been in both  

roles I'm a licensed attorney, but  I'm in non attorney roles as well. Make sure someone actually understands  privacy. Vendor oversight make sure if   you're going to outsource either your customer  data that you process or your own data that   you have oversight over your vendors laws  are starting to require specific contracts in place with very specific language and  if you've got you know five different laws   with five different contractual  requirements and you're going to   have five different amendments on your contract. So why is it hard to get a contract in  place with a customer or an entity or an   outsource because all the laws that are in  place, so you know darn all those attorneys.  

Data purpose collection limitation means  only collect data for the reason you need to collect data for and it also means  don't use it for any other purposes.   A very common example of secondary use  of data is data that companies collect and then as they do software  improvements they test   the data on the data they have or they  test the software on the data they have.   Well the data they have was not collected  for purposes of testing software. If they collect the data in order to mail  a widget to someone. Well, that's why they  

collected the data. So purpose limitation would  say you can't then use it to test new software,   unless the second purpose is very  closely related to that of the first and who in their right mind would think testing  software is closely related to shipping a widget. So you might be able to explain it you  might be able to make those connections,   but you shouldn't have to so what do you need  to do, you need to disclose in your notice that   you're going to test it on your software  on their data whenever you have software improvements and nobody reads to notices anyway  so there you go now you have your permission.   Data integrity is just making sure  data can't be changed as it goes.   You keep data logs you make sure it's protected  during transmission and storage. Cross border

transfers and international requirements  is getting data from other countries and it   doesn't even have to physically move. If there  is a server in Germany and you're in the US   and you access that server even if you  don't download the data, you don't store it all you do is look at it, that is a cross  border transfer of data because looking at   it is considered processing. Processing  is anything you do today to including   deleting it or an anonymizing it that's  processing it, and then security, you've got to have security with privacy  you gotta have privacy with security.   No security is infallible it's going to  break and when it does what's going to   get you in trouble is going to be whether or  not you abided by the privacy requirements.

Do you have more data than you  should, is it not protected,   is it not redacted, is it not anonymized,  that's where you get in trouble and think   of all the data breaches that  you've heard of over the years. And you hear the CEO being fired, you hear of the  chief information security officer being fired.   You don't actually hear the Privacy  Officer being fired this because   most of the time they ignore us anyway,  because nobody wants to hear about privacy. It's kind of like insurance nobody  wants it, it's a necessary evil,   but it's there it is there for our protection  you just need to be aware of how it impacts you.

And one of the biggest things before we jump  into AI then is there is a difference between   a privacy breach, and a security breach. A  privacy breach could be impacting the data   and it doesn't have to be electronic  if you miss send an email if you lose a briefcase with patient records, those  are all privacy breaches. Security breaches   actually breaching the information security,  but it might not ever touch personal data. If you don't have personal data  in that system that was breached,   probably not a privacy breach,  but it would be a security breach. When you have them both. That's when you hear  about all the millions of records that are  

jeopardized and all those free credit checks  you've got for the next 20 years or something. Okay, so let's talk about artificial intelligence  and machine learning. Now in here, what is AI. So artificial intelligence or machine  learning is a machine that displays   intelligent behavior. It can reason, it can  learn it can process sensory perceptions. It involves tasks that historically been done  by people but can now be done faster, better,   and can actually learn things from what it  actually processes, and there are two types,   there are narrow AI, and then there's  artificial general intelligence, and they mean exactly what they sound like. The  narrow is limited to a very specific application,  

and the general is general  applications that it would have. The problem is, it happens within a black  box, and you can't explain it. So if under   the privacy laws people have the right to ask  you questions about how you process their data,   or how you came to a specific conclusion,  or what exactly you're doing to their data. You can't answer it if  it's AI, because you don't know. It happens outside our comprehension, we  don't know exactly what machines are doing. And so that is a very very touchy area when  it comes to privacy and it comes to individual   rights. The other thing that's touchy is  watching. Darra is a blockchain expert   and block chain is considered one of the  most secure ways of processing data however you can't change it. So how  do you do individual rights,  

deletion, amendments, corrections if you can't  actually change the data because it's immutable. So technology is both our friend and our enemy.   It gives us the ability to do certain things, to  innovate, to achieve amazing things in the world,   but it also offers complications when it  comes to very basic privacy protections. And it's no surprise that the first  privacy laws were passed in 1970 there   were some earlier ones in some very  specific areas right before that,   but it's because the first mass  marketed computer was sold in the 1960s.

And so now all of a sudden, it was different for  how you process data, how you compute, how you   share data, how data is stored. And  that started the whole thing about   privacy protections and that was  only a little over 50 years ago. So it's something that we're  just now starting to get into. So what are some of the ethical issues in AI. Well some of the general ethical  issues that people have: unemployment. So this is something we've always wondered when  there's machines. What happens after the jobs in,  

When they're done processing with they're going to  process, or when they take away jobs from people. Now that worries been around for a long  time and it hasn't really materialized as   machines replace people in jobs, more jobs  for people open up dealing with machines.   Data analysts is a perfect example of that.  Inequality. How do you distribute  the wealth created by machines.

Humanity. How do machines affect  our behavior and our interactions   and I'll show you a whole bunch of good  examples of these. Artificial stupidity. How do we guard against mistakes, and that's where  a lot of the social justice issues come in is the   mistakes that are being made. The common  word or phrase is garbage in, garbage out. But what if it's not garbage, that's going in. And that's one of the social justice  issues is the facts that are actually   going into the artificial intelligence,  they're real facts, it's not garbage.

The problem is the societal norms that created  those facts. And one of the examples can be it   is an absolute fact that there are more African  Americans in prison, then there are Caucasians. That's the fact. The backup to that is,  why are there more African Americans in   prison than there are Caucasians. And that  comes down to a whole lot of other social   justice issues that we have to deal  with and we need to fix as a society. But unfortunately, those are  the factors that go into the AI.  

And so if you've got AI watching  excuse me I have four dogs,   and apparently they decided they  wanted to be part of the presentation. Sorry. So if you're looking at security in a  mall or in a store and there used to   be those that were open and people would go to  malls and they walk around and they do things,   and the AI running would tell them they  need to watch the African Americans in the store closer than they watch the Caucasians   because African Americans are  more likely to break the laws. Not true. Just happens to be our societal injustices   coming through with the data that  goes into the biases that go into AI. And so that's where we really  need to see people that carry this   justice with them. We need more minorities  working in the programming and in the AI and  

in the technology to make sure that we're aware of  the biases that go in, because once you train AI according to the biases   you can't really untrained it so that question  about how do we fix artificial stupidity. So that's one of the social justice  issues. How do we keep, keep,   AI safe from adversaries, that's very hard. Some of the most corrupt countries in the world. And I say corrupt because that's the, that's  the gauge they're on is there's publications   about they look at the level of  corruption in certain countries. And some of them, part of what they figure  is in corruption is because they see security   protections own competitors or other entities  systems as a challenge, and they want to beat it.

And that's one of the legal things that we  take into account when we're doing law in China   is if we have a law firm in China, we just have  to understand that that data will be breached,   because that's a cost of doing  business in China is they, they love it they like doing it. It's a way of life there and so it's just one of  the things you take into account of doing business   and that's one of the first things to Chinese  law firms will tell you when you hire them. It's just know that your  data is going to be breached   by using us because that's  how we work here in China. And so, how do you protect  against unintended consequences.

You have to make sure that you're aware of the  biases in the data that's going into the AI. How do you stay in control of  a complex intelligent system   that is very difficult, and I'm looking  for the experts that can fix that one. And then how do you define the humane  treatment of AI, which is an interesting   question of robot rights, I have to admit  that's not one I get into very much. Any questions on this part so far. Darra  does this spark any questions with you?

All the questions. Okay. Well that was a good grounding,  that was the grounding and what   the conversation is going to be so  okay 28 minutes that wasn't bad. I'm really looking forward  to hearing you talk about how   privacy interfaces with all of this and  specifically from that social justice perspective. Then I am going to go straight into, you  know what let's go to the next slide. First,   just to give you a little peek  about how the world is treating AI,   and some of the laws that they have. So there are  countries that have discussed restrictions on the

use of lethal autonomous weapons. That  is a very controversial use of AI.   Regions that have permissive laws in place for  autonomous vehicles, and how those are used. And then I want to make sure that we talk about  biometrics before we actually jump into the AI.   So, I love this last one here that is the  face if you look at it sideways, it says wire.

And so this is one of the, the very easy ways to   understand the biometrics may not  always be what you think they are. So, love that and there are biometric  laws, some of them are private companies   only. Some of them also govern public  information are public entities and   one of the biggest controversies is law  enforcement use of facial recognition. And so, Illinois has BIPA, the  Biometric Information Protection Act.

Washington also has a biometrics law, Texas has  a biometric law, some of the new states that are   incorporating privacy laws include biometrics  in the definition of personal information. So it is protected from that, but typically  limited to biometrics use to identify a person,   the controversies with the law enforcement  use of biometrics, and this is AI is   recognizing people. We talked about the  biases that go into it. If AI was trained using the available student population and  the available student population when that   was created was overwhelmingly one gender  versus another, one race versus another then your AI is going to be trained on certain  things and so you can mis-identify people,   you can focus on the wrong people and  when police are using this in real time   to identify perpetrators at a scene, then  that's something you need to be careful of and we have some great news  stories around there so let me   move over this. One of my  professors that I work with,  

he and I teach the course on privacy biometrics  and privacy big data and emerging technology. And we actually did a presentation on AI,  just to give you some history here I'm not   going to give you all of this and I did send  this so it can be shared with y'all as well. So AI really started right  in, right before the 1960s,   but the boom has been this past decade or so  where you've really seen it coming and going. This is a PDF.

Let's go down to these examples so here we go. How  do you vote 50 million Google Images give a clue. So what is this show on your screen I just want  to verify that it moved it to the right screen. Yes. Okay. Perfect. Thank you very much. I want to make sure, yes. Okay, perfect. So this, what vehicle is most strongly  associated with Republican voting districts,   and it's extended tab pickup trucks for  Democrats, it is sedans. All of this came from AI. Your Roomba may be mapping your home and  collecting data that could be shared.

So I just got a Roomba, but in the past few  months before then I refuse to do so because   that's what it does it maps your house,  and that data can be breached and accessed. When AI can't replace the worker it  watches them instead and so cameras   watch the stations of workers and  see if they can meet their quotas. Can they violate your privacy  everything from speakers to   water meters are sending information to the cloud.

There's a murder trial was testing  the boundaries of privacy and home. Amazon Echo, Alexa, Google Home,  all of those are used to actually   capture transcripts. People can call the cops  using it even if they don't intend to do so,   and randomly I will walk through my house and just  say my husband's name is Tim just say stop Tim, stop Tim, don't break my leg. Oh, I'm bleeding  you hurt me. You're killing me. He's like,   shouldn't you be saying this with more  emotion. No, they just pay attention to   the transcripts not the actual audio recordings. And yes, they have used them in trials.

So that is it. Alexa call the police was another  one, they AI that can sense movement through laws. So when police are looking at assessing   houses and whether or not people are there  you can actually use AI for this as well.   It is helpful in good ways as well, don't  get me wrong here AI is very very positive. But for as many positive uses there are  negative uses. And until we can offset  

the outcomes of the negative uses. I mean  we have to be fair, as a society, hackers   are real obstacles for self driving vehicles  a lot of information that comes from there and they can hack them by the way yes they  can hack embedded medical devices so your   heart defibrillators your insulin pumps  things like that can be hacked and changed. AI also works in a lot of cases such as shopping  so there's an age old story that people who own   Macs would be shown hotel prices and car prices  a lot higher than people who own PCs, because   AI told them that people who own  Macs had more money to spend. Google's project Nightingale got the  personal health information on millions of   Americans and used it. Cameras with AI  brains, and we'll talk about how that goes   into deep fakes, so they can mine data very  much more specific than what you can capture own just software capturing data is the AI  can actually take information from that. Your bosses can read all of the company, emails,  AI can actually identify people who are potential   whistleblowers based on language they use  and it doesn't have to be language that says,   I'm going to blow the whistle on  this or I'm going to report them to a regulator, it can pick it up,  many many conversations before that,   just based on the wording that they use  and the types of emails that they send.

You can identify tweets sent under the influence  of alcohol so AI has learned what is a tweet look   like, what kind of words are there, what kind  of syntax do you use if you're drunk tweeting.   Facial recognition what we were  talking about before, these are just some of the ways. Some of the points  on the face that it pays attention to,   and how it does facial biometrics. Class action  file lawsuit against clear view AI startup.

And this was in Illinois under the Illinois  Act I was talking to you about and about   how they use facial recognition and whether  or not they got people's permission to use   their faces for their facial recognition  algorithms. Biased algorithm led to the arrest of an innocent person for a crime  he did not commit. So this was in Michigan,   and the facial recognition based on the AI and  the programming identified the wrong person. So when you talk about social justice  issues that's about as unjust as it gets. Can it predict your personality type by watching  your eyes, it can based on the information in.

It can also tell your political affiliation,  and then that connects to targeted behavioral   advertising and they can specifically  target individual people in the news   stories that those people are fed through  their social media or through their newsfeed that would either discourage  or encourage them to go vote. If your news stories are showing you on your  social media or your newsfeed on your device,   your laptop or your phone, that  the polling lines are backed up   for three miles and people are miserable  and people are passing out from the heat are you going to actually go physically  check to see if that's true or are you   going to choose not to go to the polls  and vote. That actually does happen. I may be paranoid, but paranoid  doesn't mean you're wrong. How China's using AI to fight the coronavirus  of very interesting ways that they implemented   that. Very successful processes in  most cases, their high tech police   they use facial recognition and a lot of  AI and a lot of the activities that they engage in. Emotion recognition algorithms  computers know what you're thinking.

Children's emotions as they learn. So can you watch children  actively learning and use AI,   and whether or not they're paying  attention whether or not they're engaged. Boost lip reading accuracy. Predict your own, that  was another personality one. Detects deception   may soon spot liars in real courtroom  trials now take that to the next step.

If you're using AI to detect whether or not  a witness is lying. That means you're using   real time AI in a courtroom. What if your  court is wrong, what if your AI is wrong. What if they're not lying. Is this  information they're going to give to the jury?   Is this information they're going to give  to the judge if it's not a jury trial?   Is this information shared to both prosecution  and defense or both sides of a civil trial.

And different issues like that and yeah  Darra I think you just brought up I think   that was you that just said that. So this  one about children learning and reading. How does that work with neuro diverse children. So, again, it's not necessarily garbage in,   it's just limited data in unless they're  actually including neuro diverse children   in these processes for the AI in equal levels  of how they're using non neuro diverse children. Then you're going to come out with the wrong   conclusions because they're  not using a full data set.

This one, your mind, you're the mind  reading AI can see what you're thinking,   and it can draw a picture  of it pretty fascinating,   but does everyone's minds work the same I don't  know even know what they would use to do that. Surveillance cameras to use computer eyes to find  pre crimes. Now how many of us have seen the movie   with Tom Cruise about the predicting murderers and  crimes that happened in preventing it from that.

Right. So that's another issue that we've got with the,  with the AI and the predictions. Is there still   always a human element there  always still a human element. Brain machine interfaces forged authenticity so   now we're getting into the deep  fakes and deep fakes are huge. I can't see a show of hands out there, but   think about deep fakes and how many of you  have had experiences, either watching the fakes   or even doing some of it yourself. There's very  popular apps where you can replace your face. In a video clip with a famous  movie clip or something like that.

And can you imagine what this, the implications  of this would be in courtrooms. So if a video   was introduced as evidence in a courtroom. Do  we have the right judicial measures in place   to stop false information from  being introduced as evidence. There's evidentiary procedures  to where you can challenge the   authenticity of certain things with this  AI on deep fakes is pretty, pretty big.

And it's pretty significant. And  you are allowed to produce a copy   of something if the original is not available,  I believe you can assess the original to see   if there is a deep fake. Some very very smart  people can go into the programming and assess it. But if it's a copy of it because  the original isn't available,   can you tell that the copy is a deep fake. Can you prove it.

And if you can't prove it. Do you have to let it in or can you eliminate  that from being evidence in a trial. Very, very controversial news, and  then the rest of these are just   good things. I'll stop here on these AI powered  cameras become a new tool against mass shootings. So, yes, AI was one of the things that  they used in the Boston Marathon bombing,   is they were able to identify people in  the, in the crowd that was there and who   was around and matched it also with witness  reports and security sightings and different things like that, but it was very  helpful in that. Also helpful in  

the school shootings that we've been  having lately. And so don't get me wrong,   AI is very very powerful, very much,  able to be used as a, as a powerful tool. And I will stop the presentation there. Let me stop sharing my screen and then Darra  let's talk about some of the questions that you   got with this really really brief, but  impactful insight into privacy and AI.

Well first I want to welcome all  the questions from our attendees,   because you and I can talk  anytime about my questions so. Absolutely well you had you posted one  yet for the archive is out there are we   going to have to evaluate AI generated records for   authenticity before they come into your  collections and how will you do that. That's a question for you? How will you do that,   if you're the keepers of history, how  do you know that the history is right. Well, and of course we've had as the archival  students can say we've had forgeries that's   where our whole field came from is looking  for forgeries, but you know and it's going   to be a problem I think for libraries  too and I think it's going to be a bigger piece of the whole dismiss information  problem that is so important to   the information profession and then for the  data, data analytics folks here, you know,   how are y'all going to be able to make sure that  the data that you're doing your work on is good. Right. And and again I get it. With the archivist,  

and maybe y'all can educate me on this. It's  not just written paper like you would think   of for a library and y'all are talking all  the information and how to archive that. And as part of your job is proving  it's correct. Does this mean you're   getting training in AI and  deep fakes and technology. Seems to be where we're moving, but   yeah so I will leave it to our wonderful  attendees now if they have any questions,   feel free to either raise your hand or to  talk or to type your question into the chat. Yeah, please do until I see  some questions coming through,   I'll just continue talking about  some of the ethical issues.

So, on the podcast we had a woman on  there one time that is a privacy engineer. And she was explaining how it's becoming  more common to make sure that engineers   are actually trained in not only privacy  and understanding what personal data is,   but in also understanding how does that feed  into the technology and what you need to be on the watch for. And so we've talked about  the, the underlying data that used to program   AI, and how if you don't have the right data  you can come out with the wrong conclusions. There's also intellectual property issues  with that. If you think of different   companies hiring the same AI company  to let's say just do contract review.

That's a good example. If Company A uses  it for you know 20,000 contracts and trains   it and then they're able to sell it to  Company B, Company YY, Company 1000, who   benefiting from the AI of that first company  who actually owns the intellectual property for that. And there was a company that was just  determined to have violated the IP of another.   And all of their patents invalidated  which means all the work they were   doing invalidated which means that all the  AI that they had that was training their product development. Where does  that go what happens to that. If, if the patent was actually owned by the  first company and has to go back to them.   Did they get all the AI training that came  from the companies that they sold it to. So there's a lot of ethical issues when it  comes to that the social justice one seems   to be the ones that are top of mind for most  people, and making sure there are some efforts   out there and making sure that one that  there are what they're calling inclusive programming.

So that is a movement now is inclusive it  by design, into the technology, making sure   that people of all different types are involved  in the programming and in the technology. And this doesn't just mean ethnicity and genders,   it means neuro diverse, it  means people with disabilities,   it means people from various locations in the  US that don't speak the same as the others. It means people have different heights. And   if you don't have that kind of diversity and  inclusivity and equality in the programming. You're going to come out with bias data  and implicit bias is a big focus in a lot   of fields nowadays and looking at that  and let's see we got one. Okay great.

Librarians are often in the position of  negotiating vendor agreements and contracts   without having recourse to legal counsel.  Oh my goodness didn't realize that. What is   happening in the field to empower librarians  to navigate this or is this an unmet need. I'm going to say from my  legal perspective is an unmet   need Darra you're much much closer to  this being an archivist and the lawyer. I'm not technically a lawyer  anymore and ethically I have   to point out that I let my license  lapse when I moved to Canada. Okay,   in our state you're still a lawyer,  you're just not a licensed attorney.

Okay. But yes, no, it's absolutely an unmet need and I  think for the privacy perspective, we've really   lost control of the ecosystem in the libraries,  and so, And I guess that's a good question K, is to build on Holly's excellent  question. Holly's one of my students.  We don't control the ecosystem anymore to a large  degree so how do we meet our privacy obligations   in an ecosystem where we only control part of it. And that is a growing concern  in a lot of fields, because,   as I talked to people about privacy and you know  you bring up privacy and people like that again. But it touches everything.

If privacy is dealing with personal data.  It touches, everything. Doesn't matter what   field you're in it doesn't matter if  you want to be hiding in the basement   typing in things all day long, no matter what  your end if you just want to be a transactional person doesn't matter. You're going to touch personal data somehow,   some way so how do you educate people  in the different fields about how to   use personal data and I'll give you a  great example of some of the differences.

So, if I was to tell you to tell  me if something was public data,   confidential data, or sensitive data, where  would you put membership in a trade union,   such as due to the librarians have  a National Librarians Association. We have the American Library Association, perfect.  So where would you put take out the American   because we don't want to specify a country, but  let's say it's the global librarians Association,   would you consider membership of  that to be public, confidential, or highly sensitive.

Oh it is so contextual only  because you understand it. Everyone else, listen to that. And  what we would probably say is public,   because here in the United States, you could go  pay $5,000 and you could get a list of pretty much   every trade union out there right, American  Medical Association, the Bar Associations, even our voter registration roles,  which really irritates the Europeans. In Australia, that's considered highly sensitive  information membership in a trade union is high or   professional association they don't even say  trade union because that could have specific   interpretations, but membership  in a professional association is considered highly sensitive. What about  bank account information your routing number   and your account information, would we say  that is public, private, highly sensitive. We'd here in the USA that's  highly sensitive right? It's not in Europe, and it's not in most  countries that define what sensitive data is,   it's not even, it's not even hitting  the boundaries their finances know   where in there definition of sensitive data.

Do you have to protect it. Yes. Is it  sensitive data, no. One of the biggest ones   dichotomies that I just mentioned was  political. So in most countries with   privacy laws political opinions and beliefs are  considered highly sensitive data, their special categories, they must be protected to  the highest degree and here in the US.  

Good Lord you can you can go  buy a voter registration pole. Or you can have AI figure it out based  on what kind of car you drive and   trust me there are political groups out there  who do buy that data and they do use it. So one of the last ones I'll  give you is personality.

Now I love this I happen to  specialize in definitions of   sensitive data. In Israel personality is  considered sensitive personal information. So I'm all kinds of sensitive here clearly. And so in order to understand to fully put into  context the AI, the technology, the programming,   the underlying data, the social issues, it  might cause you actually have to understand   what is personal data and then what  is special or sensitive categories of personal data. And how do you get that kind of understanding out  to the people that are creating this technology,   reading the contracts to buy the technology,  determining whether or not the output is   accurate or authentic, you start  getting into some very complicated problems that are not easy for people to solve.  and it can't just be one field solving it. If people are relying on the lawyers to  solve this, it ain't going to happen. It really does take everyone who has a  part to play in this from the beginning   of creating the data sets and making sure  that they're all inclusive to how you use   the data. There are cities who have decided  that their police departments are not allowed

to use a real time facial recognition,  they can use it in review, such as if   they're reviewing all the people that were  at a crime scene afterwards and looking at   the video they can use facial recognition for  that, but they're not allowed to use it in real time. Because the potential for harm to an innocent  person is very big, very large. So unless   we're able to get the people from the very  beginning of the system to all the way to the end. How do we address this problem it's not easy. It's not easy and all of you absolutely  have a role to play in that I'm including   the question on how do you read the contracts  for it because y'all aren't trained in law. You're not trained and most lawyers aren't  trained in privacy let's be clear here this is a   this is a very very small field,  although when the GDPR in Europe.

Went in effect three years ago it was past five  years ago, went into effect three years ago. The IAPP International Association  of privacy professionals predicted   that the world would need about 75,000 more  privacy people now I've been privacy a long time. And they predicted the world  would need about 75,000,   when they went back. I think two years after  the GDPR was passed, there were over 500,000   data protection officers registered with  the data protection authorities in Europe. Now that doesn't mean all the  people working in privacy,   it means the data protection officers  which are like your chief privacy officers. 500,000.

That's a lot. And those are lawyers, those are non lawyers,  those are people from every walk of life that   in their company was decided to be the  person that knows how to govern the data. It could be a data analyst,  it could be an archivist.

It could be about whoever  is in charge of the data. So is this a field for our students.  This is lit a fire under anyone they   found a passion for privacy, the  privacy bug bit them and they became   passionate about it yes this is actually  as I mentioned earlier, and I'm not joking.

This is the hottest growing  field, both in and out of law,   but you do need to make sure that you have the  right skill set to fit well into privacy there's   a lot of people that they're in privacy, they  have the jobs and privacy, they're not good at it. And the reason they're not good at it  is they're focusing either strictly   on exactly what they're doing  and so they're very inflexible,   or they don't understand all the ways that  privacy touches our lives and what it does. In other words, if you can't see that AI is  problematic from the data that comes in it   and before that the social justice issues that  impact the data that impact that goes into AI   to the outcomes and the deep  fakes and the authenticity. If you can't see that whole roadmap  and understand what the very very broad   mind that this is a problem, then yeah you're  probably not going to do good in privacy. Do you have to be all knowing and have  a law degree No. As a matter of fact,  

a lot of lawyers don't work well as privacy  people because privacy is is kind of   questionable now for me to say it's all shades  of grey, but there's very, very few hard lines in privacy. Unlike other areas of law where you  can move a comma and change the meaning of a   sentence, you know 15 different ways in privacy,  all of those meanings could still be right. Doesn't make one wrong versus another you can take  out an entire paragraph, explaining privacy law   replace it with something completely  opposite and they would both still be right.

So you've got to have that flexibility of  thinking and be willing to be creative,   but then also know where to  put your foot down and go No,   sorry that one is a big hard black bar  laying across your way and you ain't passing. There we do have a few of those. So we got about four minutes left with K. Does  anyone have any burning questions that they   want to get off their chest, well you have the  chance, absolutely happy to hear from anyone. And you're absolutely welcome to  contact me after with questions   if you didn't catch my email address  Darra knows how to reach me, trust me.

And in privacy I definitely  believe in the transparency part. So you can find me easily on social media,  just make sure you spell my first name with   one letter K there's not a dot after the  K there's no y. I'm as easy to find me. Thank you for doing that Darra just shared that  if you're interested in working on these issues,   check out the Library Freedom  Project is open to students.

Oh, thank you for that suggestion Holly  love that so please do check that out,   feel free to reach out to me find us.  If you want to know about privacy,   you're also welcome like I said  to go listen to the podcast. This season we shortened it to an average of about  30 to 35 minutes because people told us that 50,   five zero minutes was too long  to walk their dogs or exercise,   but the one that was released today on the  new standard contractual clauses out of Europe that are hot off the presses,  and it's almost an hour.

Sorry. But absolutely, you can go back through the things  we actually talked about social justice and AI   in some of the episodes so please feel free.  I'm not just being selfish and plugging here. It's just good information if  you're looking for a quick resource   on how to understand what it is if you have  a question that's an easy way of doing it. We don't talk from a very  legal perspective whatsoever.

Trust me nothing with me is  going to be a legal perspective.  In Spring of 2022 we have a new course on  privacy, technology, and law in iSchool. I wrote the course I don't  know if I'll be teaching it.   Beautiful she's actually my reviewer. One of my  reviewers my PhD is on privacy in universities   in the US and all the different privacy laws that  impact universities, people have no idea that here in the US, you might think it's FERPA,   which is the Family's Education Records  Protection Act or something like that. 

It's no the only one that  applies to the universities.  Pretty much every privacy law out  there would apply if you're doing   the right activities and that's another  thing to understand about privacy so   with that I won't make you run to the actual  hour. Thank y'all so much for having me. I hope you enjoyed the conversation, and have  some insight into why AI can be so problematic   for social justice and discrimination issues.

Thank you so much K. It was a real pleasure to  have you. We were very very lucky to have your   time and expertise. Thank you K. And thank ya'll  for listening to two southerners run the program.   Ya'll take care. Bye ya'll.

2021-07-22 13:17

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