But  first,  I  wanted  to  welcome  everyone. My  name  is  Katherine  Manti  from  the  Georgia  Tech  Library. A  few  things  before  we  get  started. We  do  have  the  Q  and  A  open  today. If  you  have  questions  for  Professor  Wendy  Wong, as  we  go,  you're  welcome  to  put  questions  in  the  Q  and  A. We'll  have  a  little  bit  of  time  at  the  end. We've  also  enabled  captioning, which  you'll  find  along  the  bar, along  the  bottom  of  your  zoom  to  be able  to  follow  along  with  that. I'll  pass  it  to  Dr. Asha  Johnson  from  the  Georgia  Tech  Library  to  welcome  us. Hello.  Hello  everyone,  and  welcom. I  am  Dr.  Asha  Johnson, Associate  Dean  for  Academic  Affairs and  Outreach  for  the  Georgia  Tech  Library. Thank  you  all  for  being  with  us  this  afternoon. I  hope  you  are  as  thrilled  as  I  am. So  let's  introduce  Dr.  Wang. Dr.  Wendy  Wong,  a  professor  of  political  science, focusing  her  studies  on  global  governance. She  is  the  author  of  award  winning  books, Internal  Affairs  and The  Authority  Trap,  with  Sarah  Stroup. As  a  scholar,  she  has  penned  dozens  of peer  reviewed  articles  and  chapters  and have  appeared  in  outlets  such  as  CBC, The  Global  and  Mail, the  Toronto  Star,  and  The  Conversation. Dr.  Wang  has  also  been  awarded  grants  from Social  Science  and  Humanities  Research  Council  of  Canada and  Canadian  Institute  for  Advanced  Research, among  many  other  granting  agencies. Today,  we  are  honored  for Dr.  Wang  to  share  and  discuss  her  book, The  Data  Human  Rights  in  the  Digital  Age. Published  by  MT. Press  in  October. The  data  has  been  shortlisted  for the  2024  Gilbert  Prize  and  was named  by  the  Journal  of  Democracy's favorite  books  of  2023. This  work  serves,  of  course, as  a  rallying  call  for extending  human  rights  beyond  our  physical  selves. Delving  into  critical  needs  to  reboot  rights  in our  data  intense  world  in the  exploration  of pervasiveness  and  data  collection  and  tracking. Professor  Wang  reminds  us  that  we all  indeed  are  stakeholders  in  this  digital  world, yet  many  are  being  left  out  of crucial  conversations  around  technology, ethics,  and  policy. Let's  all  welcome  Professor  Wong. Thank  you  so  much  for  that,  Dr.  Johnson. Let  me  share  my  screen. Thank  you  all  for  being  here. Thanks  to  Katherine  Manthy  for  the  wonderful  invitation. It's  so  nice  to  be  speaking  virtually  at a  library  as  you'll  see  later  today. To  my  mind,  libraries  are core  part  of  helping  us  adapt  to our  data  intense  reality and  I'll  come  to  that  at  the  end  of  my  talk. I'm  also  so  honored  actually  to  be  giving this  talk  for  the  Love  Data  Week  here  at  Georgia  Tech. And  of  course  we  all  know  Georgia  Tech  is a  leader  in  developing  and  thinking  about  tech  issues. It's  especially  important  to  be  thinking about  the  intersections  of  tech  in  society. When  I  got  the  invitation  from  Katherine, I  was  thinking  about  what this  idea  of  love  data  week  means. What  is  love  data? I  thought,  yes,  I  think  I  do  love  data. But  I  think  there's  a  caveat  with  the  way  I  love  data. That's  really  what  we're  going  to be  talking  about  today  because  I think  that  there  are  things  about  digital  data, not  data  in  general,  but  digital  data  that  enable  us  to record  things  about  people  and their  activities  through  online  devices. That  should  give  us  all  pause  and  think about  how  that  capability actually  really  fundamentally  changes our  lives  in  terms  of  how  we  experience  our  lives. I  also  wanted  to  reflect  a  little  bit on  the  theme  of  my  kind  of  data. I  think  this  is  such  an  important  idea  to  think  about because  as  I  hope  will  become  clear  today, the  idea  of  my  kind  of  data  is  not  so  simple  once  we think  about  it  in  the  context  of the  interconnected  societies  in  which  we  live. I  really  like  the  way  Dr.  Johnson  set  up  the  talk, and  I  will  do  my  best  to really  help  convince  you  and  maybe  give people  a  more  concrete  framework to  think  about  what  data  stakeholdership  means. Those  are  my  provisos, But  today  I  will  be  talking  about a  book  that  was  published  by  MT  Press. It  is  the  same  name  as  this  talk  and  it's  really  a  that, although  I'm  a  political  scientist, I  do  international  relations, I  really  was  writing  a  book for  a  much  more  general  audience. In  part  because  I  think  that  data  issues  are  so important  outside  of  my  own  home  field, but  also  because  so  much  has  been written  by  non  political  scientists. And  in  fact,  a  lot  of  my  ideas  draw  from outside  of  the  field  that  I'm  most  familiar  with. I  looked  a  lot  at  law. I  looked  at  people  working  in tech  fields  and  what  they  had  to  say. I  looked  at  some  humanities  fields. I  looked  at  the  social  sciences  writ  large. I  thought  about  this  really through  the  lens  of  human  rights. Society  and  global  governance. Because  that's  really  the  material  I'm  most familiar  with  and  that  I've  been  working on  for  two  decades  now. Going  on  two  decades in  a  time  when  artificial  intelligence, or  AI,  is  a  topic  that gets  headlines  at  least  once  a  week. I  think  it's  really  important  to  highlight the  role  of  data  in  society  because it's  important  to  remember  that  AI  needs three  things  to  be  useful  or  to  be  successful. As  a  technology,  AI  needs  compute  computing  resources. Ai  needs  algorithms  to  give the  commands  to  use  the  compute  resources. And  it  needs  data. Current  models  of  AI, especially  the  things  that  are  out  there  right  now, Like  large  language  models  that  do  make  headlines, Those  types  of  AI  need  lots  and  lots  of  data. That's  really  a  general  statement  for  the  type of  technologies  that  AI  refers  to. Even  though  this  is  a  book  about  data, it's  actually  a  book  about  why  data  are  so  central  to AI  and  how  that  centrality  is  life  changing. For  us,  the  book  came  around, I  have  to  say,  right  before  the  pandemic. Actually,  the  timing  was  not  great. But  I  also  got  to  see  what  it  was  like for  all  of  us  living  our  lives. Going  mostly  face  to  face  to, all  of  a  sudden  being  locked  down  and  going onto  these  virtual  platforms  like  Zoom. Today  that  we're  on,  becoming a  lot  more  dependent  on  digital  technologies in  a  very  explicit  way. It  was  really  a  good  time  to  reflect  on  how our  lives  become  data in  the  short  time  we  have  today  together. I  really  want  to  just  talk  through some  of  the  main  takeaways  from  my  book. And  I'm  really  looking  forward  to our  conversation  after  I like  to  start  by  talking about  what  Amazon.com  Shark  Tank, the  reality  show  and  basketball  legend, Scheck  Quel  O'  Neil  have  in  common. The  thing  that  they  have  in  common  is  the  ring  doorbell. Now,  Amazon  owns  ring  company. The  product  was  initially  featured  on  Shark  tank. The  fortunes  for  the  company really  weren't  going  that  well  until, among  other  things,  Shak decided  to  become  rings  Pitchman. This  is  an  interesting  intersection  of these  popular  culture  items. I'm  sure  many  people  today  know  what  ring  is, or  other  video  doorbells  like The  Nest  or  the  Arlo,  or  the  Blink. These  are  things  that  have  become  very  ubiquitous, very  pervasive  in  our  lives. About  one  in  five  American  households have  one  of  these  products. During  the  pandemic,  video  doorbells  and other  remote  devices  also  surged  in  terms  of  sales. Video  doorbells  are  a  product that  allow  the  purchasers  the ability  to  monitor  and  record  the  area outside  of  their  doors  or wherever  they  end  up  placing  these  doorbells, they  pull  in  audio  and  visual  recording. They  allow  the  owners  of these  devices  to  speak  to  visitors  and  answer  the  door, even  when  they're  not  home, at  least  to  know  who's  coming  in  to  interact. The  thing  about  ring  is  that  they offer  a  bunch  of  different  types  of  products. You  can  get  the  doorbell, but  you  can  also  get  cameras  and  lights  and  hook  them  all together  in  a  security  system  for  your  property. Now,  why  am  I  talking  about  ring? Why  the  human  rights  issue? Increasingly,  everyday  objects  like door  bells  are  actually  raising  important  questions  about how  human  life  has  changed  and  therefore how  human  rights  have  changed  or  need  to  change. To  think  about  these  shifts as  our  devices  become  more  and  more  data  intensive. And  emerging  technologies  like AI  have  come  to  rely  on  massive  pools  of data  about  people  order to  work  and  function in  the  ways  that  we've  come  to  expect. More  and  more  of  what  I  call mundane  activities  of  our  lives  become  data. I'll  talk  more  about  this  mundaneness  in  a  few  minutes, but  I  want  to  put  it  in  the  sense that  data  are  being  taken  from  us, about  us,  often  very unexpected  and  mundane,  or  everyday  ways. When  we  think  about  how  the  ring  works  and the  implications  of the  audio  and  visual  detection  and  recording  abilities, it  really  changes  the  terms  of  who  might  be  surveying. I  think  in  this  day  and  age  we  are, we  understand  the  purpose of  some  of  the  closed  caption  or closed  circuit  TV  monitoring  that  happens  in public  spaces,  often  by  government. We  know  that  there's  a  lot  of  surveillance in  semi  public  places  like  malls. Those  are  places  where  we  might  expect  surveillance. But  ring  products  are  actually  in placed  on  private  homes  which  are facing  streets  that  are  very much  public  and  often  not  surveyed. The  surveillance  is  being  done  by homeowners  for  private  purposes. Those  of  us  who  walk  by  these  devices, our  voices,  our  images, our  gates  are  being  caught  in these  snippets  through  audio  and  visual  data. These  data  are  available  for analysis  by  those  who  have  the  data. Actually,  ring  has  gotten  into some  controversy  because  it's  signed  agreements with  thousands  of  law  enforcement  agencies to  share  ring  camera  data, often  without  the  knowledge  or consent  of  the  doorbells  owners. In  turn,  doorbell  owners, if  they  are  paying  for  a  subscription, can  download  video  and audio  that  their  device  is  captured. There  are  a  lot  of  folks  who  can actually  access  these  data. Sometimes  though,  I  think  it's  also worth  thinking  about  how  the  capacities of  ring  doorbells  can be  turned  against  those  who  are  doing  the  surveillance. There've  been  a  number  of  high  profile  cases where  hijackers  actually  or  hackers  were  able  to hijack  the  camera  and  the  two  way  microphone on  cameras  or  on  doorbells  to  really  harass  the  elderly, to  stok  children  and other  unsuspecting  users  because  they were  able  to  hook  into the  online  connectedness  of  these  devices. I  also  want  to  speak  to  the  fact  that  we as  the  pedestrians  or  the  drivers  who  are pretty  unlikely  to  be  aware  of  these  devices  as we're  walking  around  in  our  neighborhoods or  driving  around. We're  not  really  consenting  to  those  kinds  of  activities. However  harmless,  however  mundane, we're  not  consenting  to  them  being  captured. Doorbell  owners  don't  always  consent  to  how  the  footage being  used  on  their  devices  is  being  shared. Because  I  think  practically  it is  very  difficult  to  do  all  that consenting  and  all  that  acknowledgment  given how  digital  data  are  used. Just  this  is  just  to  point  out, the  ring  is  one  of  many,  countless, what  we  call  smart  objects. Recording  and  sharing  data about  us  with  various  entities, they  corporate  or  government. These  entities  have  an  interest  in collecting  data  from  people. They  are  data  collectors. This  raises  several  questions  that  I really  want  to  focus  on  in  the  rest  of  my  remarks. First,  to  what  extent  are human  activities  and  human  existence  becoming  data? I  want  us  all  to  think  about  that  and  reflect  on  that. Second,  critically,  from  the  rights  perspective, how  are  our  rights  as human  beings  being  tested  and  perhaps violated  in  a  social  context  in which  data  intensive  devices  are  pervasive? They  are  ubiquitous.  We  are  all meeting  on  an  online  platform  today, and  I'm  sure  in  your  purses, your  bags  on  your  desks, we've  got  multiple  smart  devices  that are  there  these  days. We  hear  a  lot  actually, about  data  about  people  or  data  being  taken  from  people. And  we're  often  confronted  with  news  about how  companies  are  using  data  in  ways  we  may  not  like. We  might  find  troubling whether  that's  tracking  our  behavior  across the  internet  and  having  a  surprised  ad  show  up because  a  random  conversation we  might  have  had  with  a  friend. Or  being  part  of this  massive  generative  AI  system like  chat  PT  or  the  various  GPT's  that  are  being  created. Thinking  about  how  we  are  part  of  the  data, we  are  part  of  the  data  and  being  used as  part  of  these  AI  systems  for  training. I  think  it's  really  easy  to  then  think,  well, we  can't  help  but  fall victim  to  these  incidents  or  be  part of  this  process  because  of  how our  lives  are  structured  and  organized. Many  of  us  have  smartphones. We  depend  on  the  Internet  for  day  to  day  activities. We  engage  in  digital  technologies, whether  we  like  it  or  not, whether  that's  taking  public  transit or  patronizing  stores  that  use  loyalty  programs, which  are  of  course,  an  old  way to  track  people's  behaviors. Some  of  these  stores  even  use facial  recognition  technology  these  days. Or  whether  we're  having  our  purchase  histories being  analyzed  and  tracked  through  websites  and  apps. Or  walking  down  streets  with  houses  that  have digital  doorbells  and  feature digital  assistants  like  Alexa, our  lives  have  become  data  fied. That  is,  the  behaviors  that  are  revealing  of our  innermost  thoughts  and personal  activities  have  become  digital  data. Another  way  to  think  about  this  is  that a  big  part  of  our  lives  have  become data  that  could  mean  that  we  feel  like  data  subjects. This  is  the  first  takeaway I'm  going  to  be  talking  about  today. We  might  have  a  tendency  to  feel  like  we're subjected  to  this  data  making  process. That  we  might  feel  that  we  have  very  little to  say  about  whether  the  data  collection  process  happens. I  wrote  this  book  because  I  think  it's important  to  become  data  stakeholders, to  recognize  that  we  are  actually  all  data  stakeholders. To  think  about  how  human  rights  can get  to  that  point  of  recognition  of  our  stakeholdership. And  so  the  first  step  is  to recognize  the  importance  of our  role  and  the  creation  of  data. All  of  us  are  data  sources,  right? And  I  think  it's  important  to  think  about  this  role. It's  not  a  passive  role. We  don't  have  to  lose  to powerful  data  collectors  with  names  like  Google, Amazon,  Microsoft,  Apple,  and  Meta. It's  not  necessarily  the  case  that  they  get  to  dictate the  terms  of  how  data  are  made  to  be  a  stakeholder. It  really  means  making  our  voices  heard. And  there's  a  challenge  to  that, because  there  are  currently  billions  out  there, billions  of  Us  data  sources, and  there  are  very  few  companies, They're  very  wealthy  and they  have  a  lot  of  power  in  the  AI  space. But  I  think  part  of  the  issue  is  that  we're  not thinking  about  data  as  something  intrinsically  human. Instead,  I  think  we're  often told  to  think  about  data  as  a  commodity, something  to  be  bought  and  sold. Even  something  as  valuable  as  oil. We're  still  being  told  that data  are  something  that  we  can  trade. Just  this  morning  as  I  was  prepping  for  this  talk, I  was  reading  on  my  Twitter  feed  that the  University  of  Michigan  is licensing  data  from  speeches  and  student. Now  there's  no  mention  of  whether  people  know  they're  in this  dataset  or  if  they've consented  to  having  this  material  be  shared. But  there's  certainly  dollar  values  attached  to these  datasets  that  are  on  offer. This  is  I  guess,  consistent  with the  idea  that  we're  the  product  if  we're  not  paying. But  this  is  very  much  a  market  driven  idea of  what  data  about  people  are. By  contrast,  we're  sometimes  also  told that  data  are  by  products.  They're  not  important. In  fact,  I've  often  heard  people  talking  about  data as  dust  or  detritus  or  exhaust. Certainly  not  things  that  I  would attach  huge  dollar  values  to. Now  what  if  we didn't  just  think  about  data  as  part  of  the  market, but  what  if  we  thought  about  it  as  part  of  who  we are  part  of  being  human? Because  as  our  lives  become  data  fight, that's  exactly  what  I  think  is  happening. If  we  do  think  about  data  as  being  part  of  who  we  are, then  we  can  also  think  about  how  data  can  be subject  to  the  globally endorsed  framework  of  human  rights. Just  to  restate, stakeholdership  means  having  skin  in  the  game, but  it  also  means  having  entitlement  to speak  up  because  we're  all  part  of  the  game  already. Rather  than  sitting  back  and  being  subject  to data  collectors  policies  on  how  they  make,  store, and  analyze  data  about  us, we  need  to  start  directing  the  conversation  to  one where  we  can  talk  about the  future  of  data  in  terms  of  human  rights. Now  the  second  takeaway  is that  there  are  some  challenges. This  idea  of  using  human  rights  to  think  about  data, that's  because  data  are  sticky. This  is  a  framework  I  introduce  in  the  book because  I  think  it's  a  really  useful  image,  right? Data  are  sticky  like  gum  on  the  bottom  of  your  shoe. We've  all  had  that  unfortunate  instance where  we  step  on  gum  and  don't realize  and  grind  it  in  our  shoe. And  then  it's  really,  really  hard  to  take  it  off afterwards  when  we  finally  realize  what  we've  done. Now  I  think  in  a  similar  way, it's  actually  quite  easy  to  generate  data about  ourselves  because  of  how  we  live  our  lives. But  again,  it's  not  so  easy  to  be  rid  of  them. I  think  critically  different  from  gum, we  often  don't  even  know we've  stepped  in  it  or  we've  made  those  data. Okay,  and  that's  because  data  are  sticky. Now  before  I  go  into the  four  reasons  why  I  think  data  are  sticky, especially  data  about  people, I  do  want  to  point  out  that  one  of  the  great  things  about digital  data  is  that  they  are easily  copied  and  transferred,  right? They  are  easy  to  share  and  easy  to  move  around. Those  qualities  make  them  very  useful  for  us, but  they  also  make  them  problematic, and  they  contribute  to  this  idea  of  stickiness. The  first  reason  why  data  are  sticky  is  because the  great  majority  of  data  from people  that  are  being  collected  are  mundane  in  nature. It  means  they're  not  remarkable. We  often  can  think  about  them  as  not  being even  all  that  interesting  outside  of, maybe  perhaps  on  our  own  preferences. So  think  about  an  app  like  Straba  which records  the  length  of your  runs  and  the  time  and  all  that  that  maps  it  out. I  mean,  those  are  data  that  are  important  perhaps  to  us, but  really  are  mundane.  They're  every  day,  right? These  are  things  that  you  do  on a  daily  basis  or  on  a  regular  basis, and  now  you're  recording  them  for  yourself. There  are  all  these  different  things that  our  devices  are  collecting, about  our  locations,  what  we  do, our  little  behavioral  quirks. But  the  mundaneness  of  data  is  also really  important  to  point  out some  things  you  can't  change. You  can  change  your  jog, but  you  can't  change  your  face  that  easily. You  can't  change  the  way  you  walk  that  easily. You  can't  change  your  heart  rate or  your  heartbeat  patterns  that  easily. This  is  why  they're  mundane  there  every  day  and  there that  can't  or  don't  have  the  capacity  to  easily  change. The  second  reason  why  data are  sticky  is  because  they're  linked. This  is  really  just  referring  back  to this  idea  that  data  are  really  easy  to  copy  and  transfer. They  have  value  for  analysis. I  think  we  all  know  now  that  when  data  are  created, they're  not  just,  they're  in a  little  spreadsheet  or  in a  little  database  that  stays  closed. In  most  circumstances,  they're  being shared  and  bought  and  sold. You're  going  to  think  about  positive  things  that  might arise  from  that  thinking  in  terms  of  medical  data. Oftentimes  medical  professionals  wish  that  data  could  be shared  more  so  that  they  could  learn  more  about certain  diseases,  work  towards  cures. But  of  course,  there  are  negative  externalities, negative  effects,  when  we  do  share  health  data. Things  that  are  maybe  not  directly related  to  the  health  of  a  population  or  individuals. But  health  data  can  be  used  to  deny people  insurance  or  raise  insurance  rates, discriminate  them  in  other  ways. The  third  reason  why  data are  sticky  is  because  they're  effectively forever  once  created  because we  often  don't  know  that  they're  being  created. But  also  it's  actually  very  hard  to  verify the  deletion  of  data  because  they  are  so  easily  copied. I  think  it's  safe  to  assume  that data  are  effectively  immortal  as  soon  as  they're  created. They  last  for  a  long  time. The  last  reason  data  are sticky  is  that  they're  co  created. This  is  something  I  talk  about  quite  a  bit  in  the  book because  it  does  pose  some  issue  for  the  claims  around. I  often  hear  people  claiming  this is  my  data  or  this  is  your  data, or  these  data  belong  to  you. But  actually,  given  the  fact  that data  can  only  exist  if  there  is a  data  source  that's  all  of us  and  a  data  collector  that's  someone, a  company,  a  government that's  interested  in  making  those  data. This  is  the  co  created  process. Without  data  sources,  you  or  data  collectors, there  would  be  no  data  right  because data  don't  exist  in  nature. This  is  actually  a  problem  if we  think  in  terms  of  property  rights, for  example,  about  whose  data  they  are. What's  the  determination  of  to  whom  those  data  belong? Is  it  because  they're  about  you? You're  the  source,  so  they're  your  data, or  is  it  actually  the  company's  data? Because  they're  the  ones  who  are  actually collecting  information  about  what you're  doing  and  what  you're  thinking. That's  one  way  to  think  about  co  creation. I  think  the  other  way  to  think  about  it really  is  one  that forces  us  to  step  outside  of our  individual  experience  of  data  collection. I  want  to  draw  attention  to  the  fact that  data  are  often  actually  very  collective  in  nature. Think  about  explicit  examples, like  when  someone  posts  a  group  photo of  you  in  it  on  social  media. Or  we  can  think  about the  more  implicit  background  ways  that  data  works. The  reason  why  data  are  so  important  to data  collectors  is  because  they're  able  to generalize  about  people  like  you. They  make  new  categories, they  make  new  collectives  from  which to  sell  better  products  or  deliver  better  services. These  data  are  coming  from  individuals. We  all  experience  data  collection  as  an  individual. The  effects  of  those  data  are actually  very  much  collective. They're  not  about  just  our  experience, but  other  people's  experiences  that  are  like  us. We  probably  won't  know  to  what  extent  the  data  that are  being  taken  about  us  are affecting  someone  else's  experiences. When  data  about  us  are  created, it's  important  to  note  they're not  created  in  isolation  and that  they  have  both  collective and  individual  implications. Now  I'm  going  to  turn  to  how  human  rights  can  help, because  human  rights  is  another framework  where  we  have  to think  about  individuals  and  collectives. Let  me  get  some  water  before  I  start  that, we  often  hear  the  term  human  rights. I  think  it's  one  of  those  big  broad  ideas  that  has gotten  so  much  traction  in  the  last  75  to  80  years. I  want  to  point  out,  what are  human  rights?  How  do  we  think  about  them? The  political  scientist  Jack  Donnelly, who  has  written  one  of  the  most  important  textbooks out  there  about  human  rights, has  argued  that  human  rights  are  not  what  humans  are. Right  now,  the  point  of  human  rights  is  to  think about  human  beings  and  what  they  might  be  pump. In  that  sense,  we're  thinking  about  human  potential. Human  rights  are  safeguarding a  potential  about  human  life. Now,  some  of  you  might  be  familiar  with the  story  of  international  human  rights in  the  20th  century. Let  me  just  quickly  go  through  the  highlights  here. After  World  War  Two, the  UN  Charter  established  human  rights  as  one  of the  important  pillars  of  how the  international  sphere  was  going  to  operate  post  war. There  were  a  bunch  of negotiations  after  the  end  of  the  war. These  culminated  in  what's  called the  Universal  Declaration  of  Human  Rights, or  UDHR  for  short. In  1948,  through  the  years  of  negotiation, state  delegates  arrived  at  30  articles they  saw  key  to  the  establishment of  international  human  rights. They  agreed  that  those  rights  are universal,  unconditional,  and  interdependent. Now,  I  want  to  say  here  some  people think  about  ethics  and  human  rights  in  the  same  breath. I  think  they're  related,  but they're  different  in  an  important  way. Because  human  rights  are  entitlements  anyone  has against  states  are  responsible for  providing  or  protecting  human  rights. That's  what  makes  human  rights  different  from the  broader  idea  of  ethics  or  ethical  behavior, which  is  about  morality. Now,  some  examples  of  human  rights are  freedom  of  expression,  freedom  from  torture. But  perhaps  the  ones  that  we  pay less  attention  to  here  in North  America  are  the  right  to  education, the  right  to  choose  a  marriage  partner, the  right  to  a  fair  trial. Since  1948,  there  have  been, at  the  UN  level, the  United  Nations  level nine  main  human  rights  treaties  that have  been  signed  and  agreed  to  by  states. If  you've  heard  of  the  Genocide  Convention, or  the  Convention  against  Torture, or  the  International  Covenant on  Civil  and  Political  Rights, these  are  some  of  those. But  of  course,  there  are  more  legal  documents and  other  guides  at  the  UN, But  also  in  regional  organizations  like  the  EU or  the  Organization  of  American  States,  the  OAS. Okay.  There's  a  lot  of  human  rights  out  there.  Right? After  telling  you  all  that, I'm  going  to  say  in  our  data  five  world, we  want  to  think  about  how  all  these  rights, what  they're  actually  doing,  what  they're  trying  to tell  us  about  human,  human  life. Excuse  me.  On  this  slide  I have  what's  called  the  portico  of  human  rights. After  the  negotiations  over these  different  rights  happened  in  the  1940s, even  the  framers  of  UDHR  wondered, well,  how  do  you  fit  all  these  rights  together? Because  you're  talking  about  education  and you're  talking  about  choosing  a  marriage  partner. And  then  all  of  a  sudden  you're also  talking  about  privacy. What  holds  these  things together  other  than  we  think  they're  important? The  French  diplomat  and  lawyer  Rene  Cassin, who  later  won  the  Nobel  Prize, came  up  with  this  idea of  portico  for  a  Greek  temple  and  thought  about, you  have  all  these  rights  that  can  be organized  into  different  pillars  of  kinds  of  rights. As  you  can  see  on  the  slide. You  have  the  roof  that  they're  holding  up, which  is  like  the  duties  that  we have  to  one  another  and  why  human  rights  are important  for  upholding  those  ideas  of  a  common  humanity. And  you  have  the  steps  that  lead  up to  the  pillars,  right? This  is  where,  how  we  get to  these  ideas  around  certain  rights. I  just  want  to  point  us  to  the  foundation  here,  right? The,  the  entire  edifice,  the  entire  buildings. Actually  four  values  and  they  were  called  dignity, liberty,  equality, and  brotherhood  at  the  time  of  the  UDHR. Now  I  think  these  values  are  really  where  we need  to  focus  our  efforts  in thinking  about  data  fication  and  human  rights. Because  there's  been  arguments around  how  privacy  changes, how  freedom  of  expression  changes  as a  result  of  AI  or  as  a  result  of  big  data. But  I  really  think  it's  important  to  think about  why  do  we  care  about  the  freedom  of  expression, Why  do  we  care  about  privacy? And  so  I  think  these  values  are actually  what  helps  us  understand  that  better,  right? And  you  know,  in  so  far as  thinking  about  these  very  important  values, I  think  that  dignity  is  about  the  worth  of  a  person. Dignity  is  how  people  feel  as  having  worth  and also  how  we  treat  each  other  as  though  we  have  worth. The  idea  of  equality  is  really  important. It  speaks  to  a  desire  to be  treated  without  discrimination, and  that  we're  all  being  treated  to  the  same  baseline, not  arbitrary  baselines  in accordance  to  individual  characteristics. In  the  book,  I  talk  not  about  liberty, but  about  autonomy  because  I  think  autonomy  is a  very  important  idea  if liberty  is  about  being  able  to  act. Income  if  liberty  means  not  having  restraints. I  think  the  idea  of  autonomy  is  about  agency. It's  about  actually  acting  on  a  lack  of  restraint to  actually  be  able  to make  choices  and  act  on  them  freely. Autonomy,  I  think  takes  liberty  at  one  more  step. Finally,  I  updated  brotherhood, or  the  21st  century  to think  about  it  in  terms  of  community. Right?  Community  is  really  what  brotherhood's  about. It's  about  being  part  of  a  group. It's  about  membership  in  a  common  society. When  we  think  about  dignity  and  equality  and  autonomy and  community  worth,  things  haven't  changed. I  think  a  lot  of  our  debates  around  social  media or  about  what's  going  to  happen  with  deep  fakes. These  are  all  about  these  four  values. I  think  really  what  we  need  to  think  about  is that  when  the  framers  of  human  rights  in  the  1940s, the  UDHR  framers,  when  they  were  writing  that  document, they  were  really  thinking  about  physical  abuses  and physical  restraints  on  human  potential. We  have  to  think  about  how  the  digital  changes  that. We  have  to  think  about  how  the  digital  makes  it better  or  worse  in terms  of  encouraging  human  flourishing. But  we  have  to  embrace  the  fact  that  human is  physical  and  digital,  they're  not  separate. I  think  that's  really  a  key  thing  to  acknowledge. Now  I  also  want  to  spend  some  time  thinking about  big  tech  as  governor. I  can  talk  more  about  this  in  the  key  and  I have  a  special  interest  in  thinking about  non  state  actors as  governors  and  governing  in  the  world. But  let  me  just  start  off  with what  about  tech  means,  right? I  think  we're  usually  talking  about  tech. That  they're,  they're  big  because  they are  rich  and  they're  historically  wealthy. That's  what  gives  them  power. I  think  that's  correct.  In  a  certain  way. Money  is  a  way  to  exercise  power, but  it's  just  one  way. And  I  actually  think  that given  what  big  tech  is  giving  us, given  the  types  of  technologies  they're developing  and  their  role  as  data  collectors, I  think  that's  far  more  than economic  power  that  contributes  to  their  economic  power. But  it's  not  just  economics, they're  also  governing  in  ways  we're  used to  thinking  about  states  or  governments  doing. If  we  think  about  governing  from a  political  science  perspective, we're  talking  about  creating order  and  shared  expectations. That's  what  governing  is  all  about. That  means  we're  setting  rules and  finding  ways  to  enforce  those  rules. In  our  day  and  age,  we  do  expect  governments  to  govern. It's  far  less  expected  to  see other  types  of  entities  doing  that  work. But  I  think  more  and  more  we cannot  dismiss  the  fact  that  big  tech  is  governing. They  are  creating  and controlling  the  digital  platforms  through which  we  access  services and  create  social  and  political  connections. They  determine  how  those  platforms  work. They  determine  what  data  they  collect, when  and  how  they  use  those  data. These  data  are  underpinning  many  AI  functions  for  sure, but  also  non  AI  computing  functions  that  have  value  in human  societies  in  terms  of  creating order  around  shared  expectations. I'll  just  give  you  an  example  from  the  book. I  talk  a  lot  about  Meta's  oversight  board. Meta  started  this  board when  they  were  still  called  Facebook. Basically,  they  actually  took it  upon  themselves  to  recognize the  importance  of  the  human  right of  freedom  of  expression and  they  actually  refer  to  international  law  around  it. And  they  made  it  a  goal  to  use  freedom  of expression  analysis  to  think  about what  types  of  content  to  either  keep  on  their  platforms, Facebook  and  Instagram,  or  to  remove. This  is  one  way  where  billions  of  people  are affected  by  the  decisions  of  one  company. Because  the  reach  of  Meta's  total  set of  products  which  are  not  just  Instagram  and  Facebook, but  also  Messenger  and  Whatsapp  varies  3-4  billion, depending  on  who's  counting. I  think  that  is  incredible  reach. There's  no  government  on  Earth  that  can  credibly claim  that  it  governs  three  to  4  billion  people. When  we  think  about  the  reach of  some  of  these  technologies  and the  self  designated  governing  roles  that  they're  playing, I  think  it  says  an  awful  lot  about  how  we  need  to expand  our  way  of  thinking  about big  tech  to  go  beyond  the  financial. I  want  to  close  with  encouraging all  of  us  to  think  about  data  literacy  as  a  human  right. Data  literacy  is  a  set  of  skills  and  concepts that  I  think  will  be  key  to  creating  data  stakeholders. We're  circling  back  to  the  first  takeaway. I  argue  in  the  book  that data  literacy  should  actually  be  a  part of  how  we  think  about  the  universal  right  to  education. That's  because  human  life  will continue  to  be  data  centric  as  it  is  already. As  such,  we  have to  start  thinking  about  how  learning  about  data, making  data,  using  data, and  the  implications  of  creating digital  data  have  become  core  human  experiences. If  that's  the  case, then  declaring  a  human  right  to  data  literacy creates  a  universal  entitlement  which  allows  us  to write  the  imbalance  currently  between data  sources  and  data  collectors  in  terms of  how  data  are used  and  perhaps  exploited  In  our  world  today, literacy  is  about  both  giving individual  skills  in  order to  function  in  a  data  driven  society, but  also  creating  societies  and  communities that  are  collectively  informed  about  data. And  can  at  least  understand  the  conceptual  leap from  things  existing  in nature  to  things  exist  as  datasets, to  things  existing  as  datasets  in  a  digital  format. Thinking  here,  what  does  it mean  to  realize  a  right  to  data  literacy? We're  not  saying  everyone should  be  a  data  scientist  here, I  think  we're  saying  people  need  to  have basic  ideas  around  the  premises  of  data  creation. Why  our  assumptions  about the  world  matter  when  we  make  data. And  how  our  choices  of  data  sources  matter for  how  and  what  we  learn  from  the  data. This  involves  curricular  changes, which  I  don't  want  to  talk  about  right  now. This  involves  community  organizations  that  have  run pilots  on  thinking  about  how  to  teach  people  about  data. But  let  me,  this  is  about  libraries. Okay.  This  is  about  reconceptualizing  and  I  think correspondingly  funding  libraries  to be  stewards  of  data  and  data. Literacy  libraries  are  foundational in  giving  people  linguistic  literacy  skills. They're  key  parts  of  literacy  campaigns  for  reading. There's  no  reason  actually  why  we  can't  think of  new  ways  to  fund  libraries  to give  us  wide  basis  for  bringing  about  data  literacy. Because  if  we  think  about  what  libraries  are  for, they  gather  information  and  they organize  that  and  tag  it  and  file  it  such  that  when  I, as  a  patron,  come  in, I  can  find  what  I  need. Librarians  are  often  very informed  about  their  collections. Often,  there  are  shortcuts  to  thinking  about what's  possible  to  learn  in  a  given  library. They  are  data  creators, data  collectors  in  a  very  direct  sense. I  want  to  end  with  some  thoughts  about  treating  people, data  from  people  and  what  that  means. And  I  think  we  need  to  really  recognize  that data  from  people  are  from  people. The  data  being  taken  from  living  beings. They  should  be  treated  accordingly. And  I  think  that's  a  really  important  conceptual  shift. Data  don't  come  from  nowhere, they  come  from  some  one. They're  made  in  a  co  creative  process that  we  currently  don't  fully  acknowledge. This  co  creative  process  is  laden  with  political, social,  cultural,  and  economic  concern. We  also  have  to  think  about  the  power  that  is  in that  process  and  why  it's  critical  to  understanding, in  some  ways,  the  current  state  of affairs  with  AI  and  AI  governance. If  we  think  about  that,  a  lot of  times  people  talk  about  privacy. I  don't  think  privacy  is enough  because  I  think  that  implies  that something  exists  and  you're  doing something  to  keep  others from  accessing  that.  Good,  right? You're  keeping  someone  from  accessing  data. But  if  you  think about  the  argument  I've  talked  about  today, if  you've  already  collected  the  data and  then  you're  promising  to  keep  someone's  privacy, that's  actually  quite  different from  not  collecting  the  data  at all  because  of  autonomy  concerns  or  dignity  concerns. Another  thing  I  hear  a  lot of  people  talking  about  is  consent. I  have  a  lot  to  say  about  this. Let  me  just  briefly  run  through  this  idea. As  a  human  subjects  researcher, someone  who  talks  to  people  as  part  of  my  work, I  have  to  seek  consent  all  the  time  from  participants, whether  it's  interview  data  or  survey  research  data. And  we're  forced  as  researchers  to  think  about the  processes  and  uses  of the  data  we  are  trying  to  collect  about. People  go  through  these  very  rigorous  processes. We  are  reviewed  by  multiple  bodies within  the  university  and  we  have  to  think  of ways  that  data  subjects  can appropriately  consent  and  take  away  that  consent. And  also  how  we  manage the  data  once  we  collect  them  and  how  we  destroy  them. This  is  not  a  process  that  I  see replicated  at  all  outside  of  the  university  context. I  think  this  is  a  problem  because  nowadays  it's  not  just social  scientists  and  medical  professionals who  are  dealing  with  human  subjects. It's  all  these  different  companies that  are  creating  AI  products, that  are  creating  data  intensive  technologies. There  is  something  to  be  said about  the  limits  of  consent, but  also  the  rigor  behind the  consent  that  we've  gotten  used  to  in  the  digital  age. To  conclude,  I  don't  think human  rights  are  actually  a  silver  bullet. I  think  that  the  challenges  of data  fication  on  humanity  are  broader  than  that. But  I  think  that  if  we think  about  the  values  of  autonomy, community,  dignity  and  equality, our  ways  of  thinking  about  data, I  think  it's  going  to  get  us  down  a  path  of  really valuing  human  potential  in  ways  that  are different  currently  from  how  we  talk  about  data. Thank  you  for  listening  and  I'll  end  my  remarks  there. Thank  you  so  much,  Professor  Wang. That  was  absolutely  informative and  just  amazing  approach  to  data, data  literacy  and  AI  as we  really  change  even how  we  perceive  information  in  the  21st  century.