Makokha, J. M. (2021, July), Artificial Intelligence Paradigms and the Future of Learning: What a Partial Review of Half a Century of AI Conceptualization Suggests  Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36700

\bibitem{asee_peer_36700}
  Makokha, J. M. (2021, July), \emph{Artificial Intelligence Paradigms and the Future of Learning: What a Partial Review of Half a Century of AI Conceptualization Suggests}
  Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference.
  10.18260/1-2--36700

Joseph Maloba Makokha.  "Artificial Intelligence Paradigms and the Future of Learning: What a Partial Review of Half a Century of AI Conceptualization Suggests".  2021 ASEE Virtual Annual Conference Content Access, Virtual Conference, 2021, July.  ASEE Conferences, 2021.  https://peer.asee.org/36700 Internet.  02 Oct, 2024

\bibitem{asee_peer_36700}
  Joseph Maloba Makokha.
  "Artificial Intelligence Paradigms and the Future of Learning: What a Partial Review of Half a Century of AI Conceptualization Suggests".
  \emph{2021 ASEE Virtual Annual Conference Content Access, Virtual Conference, 2021, July}.
  ASEE Conferences, 2021.
  https://peer.asee.org/36700 Internet.  02 Oct, 2024

@INPROCEEDINGS{asee_peer_36700
author = "Joseph Maloba Makokha"
title = "Artificial Intelligence Paradigms and the Future of Learning: What a Partial Review of Half a Century of AI Conceptualization Suggests"
booktitle = "2021 ASEE Virtual Annual Conference Content Access"
year = "2021"
month = "July"
address = "Virtual Conference"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/36700}
number = {10.18260/1-2--36700}
}

TY  - CPAPER
AB  - A close examination of Human-Artificial Intelligence (H-AI) research and application shows that there is a wide gap between expectations and implementation outcomes arising from several factors, most importantly the assumptions and guiding principles that creators have about users on one hand, and those of users on the other. In this paper, a review of literature - publications and intellectual property - from the first (1970s) and last (2010s) decades of the past half century was conducted to explore and highlight the driving factors on artificial intelligence (AI) research and application, the resulting implementation, and corresponding response from the AI community. Initial results reveal four general paradigms guiding research and development of AI - replacing the entire human with AI; replacing some part of the human with AI; augmenting the human with AI; and finally keeping AI out of the loop. Each of these paradigms lead to vastly different conceptualization of the human interaction with AI, affecting how we learn from, with, and by AI; what we trust AI to perform; perceptions of AI among different groups; and how well we view AI’s performance relative to our assumptions and expectations. Findings from this review will help practitioners in the human-AI field in recognizing and aligning their paradigms on AI with their goals, leading to better outcomes and fulfilled expectations across the spectrum from researchers to users of AI.
AU  - Joseph Maloba Makokha
CY  - Virtual Conference
DA  - 2021/07/26
PB  - ASEE Conferences
TI  - Artificial Intelligence Paradigms and the Future of Learning: What a Partial Review of Half a Century of AI Conceptualization Suggests
UR  - https://peer.asee.org/36700
DO  - 10.18260/1-2--36700
ER  -