skip to main content
10.1145/2851581.2892591acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
research-article

After Death: Big Data and the Promise of Resurrection by Proxy

Published:07 May 2016Publication History

ABSTRACT

With the advent of Big Data and the possibility of capturing massive personal data it is possible to simulate some aspects of a person's personality. The imitation game is based on the observation that it is possible to convince a person of a fake identity if sufficient information is available about the identity being faked. Imitation is however not limited to a person who is alive but also a person who is not alive; the question of simulating a deceased person for the purpose of having the simulation interact with a person is addressed. Various challenges and background considerations for such an endeavor are discussed. The goal of the paper is to open up discussion on this subject and examine its feasibility.

References

  1. Eterni.me. http://eterni.me/. (????). Accessed: 201602--14.Google ScholarGoogle Scholar
  2. Muhammad Aurangzeb Ahmad, Brian Keegan, Jaideep Srivastava, Dmitri Williams, and Noshir Contractor. 2009. Mining for gold farmers: Automatic detection of deviant players in mmogs. In Computational Science and Engineering, 2009. CSE'09. International Conference on, Vol. 4. IEEE, 340--345. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Muhammad Aurangzeb Ahmad, Cuihua Shen, Jaideep Srivastava, and Noshir Contractor. 2014. Predicting Real World Behaviors from Virtual World Data. Springer. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Selmer Bringsjord, Paul Bello, and David Ferrucci. 2003. Creativity, the Turing test, and the (better) Lovelace test. In The Turing Test. Springer, 215--239.Google ScholarGoogle Scholar
  5. Jed R Brubaker and Gillian R Hayes. 2011. We will never forget you {online}: An empirical investigation of post-mortem Myspace comments. In Proceedings of the ACM 2011 conference on Computer supported cooperative work. ACM, 123--132. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Neil Caulkins. 2001. Trustee's Duties When a Celebrity Persona Is the Asset, A. J. Pat. & Trademark Off. Soc'y 83 (2001), 31.Google ScholarGoogle Scholar
  7. Henry Chen, Austin S Lee, Mark Swift, and John C Tang. 2015. 3D Collaboration Method over HoloLens and Skype End Points. In Proceedings of the 3rd International Workshop on Immersive Media Experiences. ACM, 27--30. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Scott H Church. 2013. Digital gravescapes: Digital memorializing on Facebook. The Information Society 29, 3 (2013), 184--189. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Andy Clark. 1998. Being there: Putting brain, body, and world together again. MIT press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Andy Clark and David Chalmers. 1998. The extended mind. analysis (1998), 7--19.Google ScholarGoogle Scholar
  11. Harry Collins. 2014. Gravity's Ghost and Big Dog: Scientific discovery and social analysis in the twenty-first century. University of Chicago Press.Google ScholarGoogle Scholar
  12. Hubert L Dreyfus. 2007. Why Heideggerian AI failed and how fixing it would require making it more Heideggerian. Philosophical psychology 20, 2 (2007), 247--268.Google ScholarGoogle Scholar
  13. Robert J Elliott, Lakhdar Aggoun, and John B Moore. 2008. Hidden Markov models: estimation and control. Vol. 29. Springer Science & Business Media.Google ScholarGoogle Scholar
  14. Chris Elsden and David S Kirk. 2014. A quantified past: remembering with personal informatics. In Proceedings of the 2014 companion publication on Designing interactive systems. ACM, 45--48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Niksha Federico, Tessya Federico, Francesca Federico, Gabriel Sternik, and Babak Esmaeli-Azad. 2014. Virtual Humans and Avatars-Healthcare Personal Agents in the Palm of Your Hand (LB855). The FASEB Journal 28, 1 Supplement (2014), LB855.Google ScholarGoogle ScholarCross RefCross Ref
  16. Nicholas Felton. 2007. Feltron Annual Report. (2007).Google ScholarGoogle Scholar
  17. Leon A Gatys, Alexander S Ecker, and Matthias Bethge. 2015. A neural algorithm of artistic style. arXiv preprint arXiv:1508.06576 (2015).Google ScholarGoogle Scholar
  18. Stevan Harnad. 1991. Other bodies, other minds: A machine incarnation of an old philosophical problem. Minds and Machines 1, 1 (1991), 43--54. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. James J Hughes. 2012. THE POLITICS OF TRANSHUMANISM AND THE TECHNO-MILLENNIAL IMAGINATION, 1626--2030. Zygon® 47, 4 (2012), 757--776.Google ScholarGoogle ScholarCross RefCross Ref
  20. Christof Koch. 2014. Does My Smartphone Really Love Me? Scientific American Mind 25, 4 (2014), 26--29.Google ScholarGoogle Scholar
  21. Jure Leskovec, Jon Kleinberg, and Christos Faloutsos. 2005. Graphs over time: densification laws, shrinking diameters and possible explanations. In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining. ACM, 177--187. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Karl F MacDorman. 2006. Subjective ratings of robot video clips for human likeness, familiarity, and eeriness: An exploration of the uncanny valley. In ICCS/CogSci-2006 long symposium: Toward social mechanisms of android science. 26--29.Google ScholarGoogle Scholar
  23. Michael L Mauldin. 1994. Chatterbots, tinymuds, and the turing test: Entering the loebner prize competition. In AAAI, Vol. 94. 16--21. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Maurice Merleau-Ponty and Colin Smith. 1996. Phenomenology of perception. Motilal Banarsidass Publishe.Google ScholarGoogle Scholar
  25. Jacquelyn Ford Morie. The AIJ Ultimate Selfie AI: Musings on the Future of our Human Identity. (????).Google ScholarGoogle Scholar
  26. Alexis Onanian. 2008. Texting: The New Form of Communication; Actually, the New Form of Everything. Artifacts (Journal) (2008).Google ScholarGoogle Scholar
  27. Cody Osterman. 2015. Black Mirror, Serial, and The Affair: Popular Culture's Obsession with Memory. (2015).Google ScholarGoogle Scholar
  28. Simon Parkin. 2014. Oculus Rift. Technology Review 117, 3 (2014), 50--52.Google ScholarGoogle Scholar
  29. prn2015. 2015. No Time to Talk: Americans Sending/Receiving Five Times as Many Texts Compared to Phone Calls Each Day, According to New Report. (25 March 2015). http://prn.to/1C7BsV9 Retrieved January 9, 2015 from PRN News.Google ScholarGoogle Scholar
  30. Hayes Raffle, Rafael Ballagas, Glenda Revelle, Hiroshi Horii, Sean Follmer, Janet Go, Emily Reardon, Koichi Mori, Joseph Kaye, and Mirjana Spasojevic. 2010. Family story play: reading with young children (and elmo) over a distance. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 1583--1592. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Antonius CGM Robben. 2009. Death, mourning, and burial: a cross-cultural reader. John Wiley & Sons.Google ScholarGoogle Scholar
  32. Abigail J Sellen, Andrew Fogg, Mike Aitken, Steve Hodges, Carsten Rother, and Ken Wood. 2007. Do life-logging technologies support memory for the past?: an experimental study using sensecam. In Proceedings of the SIGCHI conference on Human factors in computing systems. ACM, 81--90. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Thad Eugene Starner, Nirmal Patel, and Shumin Zhai. 2012. Touch-Based Text Entry Using Hidden Markov Modeling. (Sept. 30 2012). US Patent App. 13/632,042.Google ScholarGoogle Scholar
  34. Melanie Swan. 2013. The quantified self: Fundamental disruption in big data science and biological discovery. Big Data 1, 2 (2013), 85--99.Google ScholarGoogle ScholarCross RefCross Ref
  35. Sarah Tarlow. 1999. Bereavement and commemoration: An archaeology of mortality. Vol. 1. Blackwell Publishing.Google ScholarGoogle Scholar
  36. Alan M Turing. 1950. Computing machinery and intelligence. Mind (1950), 433--460.Google ScholarGoogle Scholar
  37. Luis Von Ahn, Manuel Blum, Nicholas J Hopper, and John Langford. 2003. CAPTCHA: Using hard AI problems for security. In Advances in Cryptology EUROCRYPT 2003. Springer, 294--311. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Joseph Weizenbaum. 1966. ELIZA a computer program for the study of natural language communication between man and machine. Commun. ACM 9, 1 (1966), 36--45. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Svetlana Yarosh. 2015. Designing technology to empower children to communicate with non-residential parents. International Journal of Child-Computer Interaction 3 (2015), 1--13.Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. After Death: Big Data and the Promise of Resurrection by Proxy

    Recommendations

    Reviews

    Sandhya Jane

    This interesting research paper touches on the consequences of personal data shared online, a sensitive yet largely unexplored area. For example, there is the possibility that massive personal data could be used for simulating a person's personality for good or bad. This issue at present is at a manual level; for example, people create fake IDs on social networking sites and source the picture and other details of a related profile to replicate the original. Sometimes it is done at a near perfect level, but technology applications might influence the outcome. The focus of this paper is to examine the feasibility of creating a fake identity of a deceased person, in order to interact with the "person" by simulating his or her ideas, thoughts, reactions, and other relevant information. The usage of big data will add massive input and can possibly simulate the fake person (or simulated ID) to have an interaction with one or more people in a group. In addition to this, the simulation can further be customized, for example, based on place, time, setup, or people present. According to the author, "It is possible to create a simulation of a person because each of us can anticipate what the other person is going to say, provided that we know them sufficiently well." The idea of this work came up when the author heard the news of his father's illness, which was terminal in nature; he was not going to survive for long. The author wanted to explore the possibility of his children interacting with his father after his death. The author used the Turing test, which is inspired by an imitation game, to check a few factors such as how the imitated, imitator, interlocutor, and medium of communication can influence the degree of success. Humans have created various ways to remember a deceased person through his belongings and thoughts, but this study may add value in complementing these by determining the way in which the deceased would have responded. The author of this paper seeks an open "discussion on the subject of interacting and conversing with simulations of the deceased," and the research sounds promising for dealing with psychological, social, and emotional issues in the future. Online Computing Reviews Service

    Access critical reviews of Computing literature here

    Become a reviewer for Computing Reviews.

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      CHI EA '16: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems
      May 2016
      3954 pages
      ISBN:9781450340823
      DOI:10.1145/2851581

      Copyright © 2016 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 May 2016

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      CHI EA '16 Paper Acceptance Rate1,000of5,000submissions,20%Overall Acceptance Rate6,164of23,696submissions,26%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader