The Democratization of Artificial Intelligence: Theoretical Framework

Author:

Costa Carlos J.1ORCID,Aparicio Manuela2ORCID,Aparicio Sofia3,Aparicio Joao Tiago3ORCID

Affiliation:

1. Advance/ISEG (Lisbon School of Economics & Management), Universidade de Lisboa, 1649-004 Lisbon, Portugal

2. NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal

3. Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal

Abstract

The democratization of artificial intelligence (AI) involves extending access to AI technologies beyond specialized technical experts to a broader spectrum of users and organizations. This paper provides an overview of AI’s historical context and evolution, emphasizing the concept of AI democratization. Current trends shaping AI democratization are analyzed, highlighting key challenges and opportunities. The roles of pivotal stakeholders, including technology firms, educational entities, and governmental bodies, are examined in facilitating widespread AI adoption. A comprehensive framework elucidates the components, drivers, challenges, and strategies crucial to AI democratization. This framework is subsequently applied in the context of scenario analyses, offering insights into potential outcomes and implications. The paper concludes with recommendations for future research directions and strategic actions to foster responsible and inclusive AI development globally.

Funder

FCT—Fundação para a Ciência e Tecnologia, I.P.

Publisher

MDPI AG

Reference49 articles.

1. Johnson, K. (2024, May 15). AI Democratization Depends on Tech Giants. Venturebit. Available online: https://venturebeat.com/ai/ai-weekly-ai-democratization-depends-on-tech-giants/.

2. Sudmann, A. (2019). The Democratization of Artificial Intelligence. Net Polit. Era Learn. Algorithms Transcr. Bielef., 1.

3. Against “Democratizing AI”;Himmelreich;AI Soc.,2023

4. Imaginaries of Democratization and the Value of Open Environmental Data: Analysis of Microsoft’s Planetary Computer;Lukacz;Big Data Soc.,2024

5. Open-Source AI: An Approach to Responsible Artificial Intelligence Development;Bildirici;REFLEKTİF Sos. Bilim. Derg.,2024

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3