On the Convergence of Artificial Intelligence and Distributed Ledger Technology: A Scoping Review and Future Research Agenda

Konstantin D Pandl,Manuel Schmidt-Kraepelin,Ali Sunyaev,Scott Thiebes

doi:10.1109/access.2020.2981447

Konstantin D Pandl, Manuel Schmidt-Kraepelin + Show 2 more

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https://doi.org/10.1109/access.2020.2981447

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 137	License type: CC BY 4.0

Affiliation: Karlsruhe Institute of Technology

Abstract

Developments in artificial intelligence (AI) and distributed ledger technology (DLT) currently lead to lively debates in academia and practice. AI processes data to perform tasks that were previously thought possible only for humans. DLT has the potential to create consensus over data among a group of participants in untrustworthy environments. In recent research, both technologies are used in similar and even the same systems. This can lead to a convergence of AI and DLT, which in the past, has paved the way for major innovations of other information technologies. Previous work highlights several potential benefits of a convergence of AI and DLT but only provides a limited theoretical framework to describe upcoming real-world integration cases of both technologies. In this research, we review and synthesize extant research on integrating AI with DLT and vice versa to rigorously develop a future research agenda on the convergence of both technologies. In terms of integrating AI with DLT, we identified research opportunities in the areas of secure DLT, automated referee and governance, and privacy-preserving personalization. With regard to integrating DLT with AI, we identified future research opportunities in the areas of decentralized computing for AI, secure data sharing and marketplaces, explainable AI, and coordinating devices. In doing so, this research provides a four-fold contribution. First, it is not constrained to blockchain but instead investigates the broader phenomenon of DLT. Second, it considers the reciprocal nature of a convergence of AI and DLT. Third, it bridges the gap between theory and practice by helping researchers active in AI or DLT to overcome current limitations in their field, and practitioners to develop systems along with the convergence of both technologies. Fourth, it demonstrates the feasibility of applying the convergence concept to research on AI and DLT.

Highlights

Artificial intelligence (AI) and distributed ledger technology (DLT) are among today’s most actively debated developments in information technology with potential for tremendous impact on individuals, organizations, and societies over the decades
We aim to address this apparent knowledge gap by asking and answering the following two research questions: RQ 1: What is the current state of research on the technological integration of AI and DLT?
FUTURE RESEARCH AGENDA ON AI FOR DLT we present our analysis of future research opportunities on the advancement of DLT using AI

Summary

Introduction

Artificial intelligence (AI) and distributed ledger technology (DLT) are among today’s most actively debated developments in information technology with potential for tremendous impact on individuals, organizations, and societies over the decades. A 2018 report from the McKinsey Global Institute estimates that the application of AI in various industries could deliver an additional global economic output of around USD 13 trillion by 2030 [1]. AI can nowadays already exceed human capabilities. Research in the health care domain has, for instance, shown that AI can analyze echocardiograms faster and more accurate than medical professionals [4]. DLT, on the other hand, can provide consensus over a shared ledger in untrustworthy networks containing, for example, unreachable or maliciously behaving nodes [3].

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