Kenneth Arnold


Kenneth Arnold

Education

  • B.S. in Electrical and Computer Engineering, Cornell University, 2007
  • S.M. in Media Arts and Sciences, MIT Media Lab, 2010
  • Ph.D. in Computer Science, Harvard University, 2020

Professional experience

  • Microsoft Research New England, Cambridge, MA
    Research Internship Fall 2015
  • Luminoso, Cambridge, MA
    Co-founder, Researcher, Developer 2011 and Summer 2013
  • MIT Media Lab, Cambridge, MA
    Research Assistant August 2007–August 2011
  • IBM, Austin, TX
    Extreme Blue Intern Summer 2006
  • NASA Goddard Space Flight Center, Greenbelt, MD
    Nonlinear Signal Analysis Research Programmer Summer 2003 and 2004

Biography

I’m interested in research and teaching at the intersection of data science, people, and Christian faith. My main projects are around AI for Everyday Creativity, including:

  • Applying today’s large AI language models to help writers express their ideas in their own words
  • AI for instructors to see what students are learning
  • Helping everyone understand what AI can do, and accurately calibrating both our excitement and our concerns

Publications

Kenneth C. Arnold on Google Scholar »

Conference and Journal Papers
  • K.C. Arnold, K. Chauncey, and K.Z. Gajos. Predictive text encourages predictable writing. IUI 2020.
  • K.C. Arnold, K. Chauncey, and K.Z. Gajos. Sentiment bias in predictive text recommendations results in biased writing. Graphics Interface (GI) 2018.
  • K.C. Arnold, A. Kalai, and K.Z. Gajos. On Suggesting Phrases vs. Predicting Words for Mobile Text Composition. UIST 2016.
  • K.C. Arnold, K. Chang, and A. Kalai. Counterfactual Language Model Adaptation for Suggesting Phrases. IJCNLP 2017.
  • K.E. Boronow, H.P. Susmann, K.Z. Gajos, R.A. Rudel, K.C. Arnold, P. Brown, R. Morello-Frosch, L. Havas, J.G. Brody. DERBI: a digital method to help researchers offer “right-to-know” personal exposure results. Environmental health perspectives, vol. 125 no. 2, 2017.
Posters and Workshop Papers
  • K.C. Arnold, *A. M. Volzer, and *N. G. Madrid. Generative Models can Help Writers without Writing for Them. IUI Workshop on Human-AI Co-Creation with Generative Models, 2021.
  • K.C. Arnold and K.Z. Gajos. Effective Interactions for Personalizing Spatial Visualizations of Collections. UIST 2015.
Talks and Other Publications
  • Panelist at Philosophy Club roundtable discussion on AI, February 2023
  • “ChatGPT is not Magic” talk at Big Data Ignite meetup, January 2023
  • “AI and Writing: Laziness or Thoughtfulness?” talk at Association of Christians in the Mathematical Sciences (ACMS) conference, June 2022
  • Ceballos-Zapata, Abraham, Arnold, K.C., and *McCallion, Emma, “Future Visions in Language Pedagogy”, talk at Calvin World Languages Forum, Spring 2021
  • Kenneth C. Arnold. Faithful Text Prediction. Christian Courier, September 13, 2021

Awards

Patents
  • From my internship at Microsoft Research:
    Patents Interactive context-based text completions. Kenneth C. Arnold, Kai-Wei Chang, Adam Tauman Kalai. (US20180101599A1, pending).

  • From my internship at IBM (all list inventors as: Jacob C. Albertson, Kenneth C. Arnold, Steven D. Goldman, Michael A. Paolini, Anthony J. Sessa):
    • Controlling resource access based on user gesturing in a 3D captured image stream of the user. (US7971156 issued Jun, 28 2011).
    • Informing a user of gestures made by others out of the user’s line of sight. (US7725547 issued May, 25 2010).
    • Tracking a range of body movement based on 3D captured image streams of a user. (US7840031 issued Nov, 23 2010).
    • Warning a vehicle operator of unsafe operation behavior based on a 3D captured image stream. (US7792328 issued Sep, 7 2010).
    • Controlling a document based on user behavioral signals detected from a 3D captured image stream. (US7877706 issued Jan 25, 2011).
    • Controlling a system based on user behavioral signals detected from a 3D captured image stream. (US7801332 issued Sep, 21 2010).
    • Warning a user about adverse behaviors of others within an environment based on a 3D captured image stream. (US8269834 issued Sep 18, 2012).
    • Adjusting a consumer experience based on a 3D captured image stream of a consumer response. (US8295542 issued Oct 23, 2012)

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