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Trustworthy artificial intelligence

Authors:
Scott Thiebes at Karlsruhe Institute of Technology
Scott Thiebes
Sebastian Lins at Karlsruhe Institute of Technology
Sebastian Lins
Ali Sunyaev at Karlsruhe Institute of Technology
Ali Sunyaev
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Abstract

Artificial intelligence (AI) brings forth many opportunities to contribute to the wellbeing of individuals and the advancement of economies and societies, but also a variety of novel ethical, legal, social, and technological challenges. Trustworthy AI (TAI) bases on the idea that trust builds the foundation of societies, economies, and sustainable development, and that individuals, organizations, and societies will therefore only ever be able to realize the full potential of AI, if trust can be established in its development, deployment, and use. With this article we aim to introduce the concept of TAI and its five foundational principles (1) beneficence, (2) non-maleficence, (3) autonomy, (4) justice, and (5) explicability. We further draw on these five principles to develop a data-driven research framework for TAI and demonstrate its utility by delineating fruitful avenues for future research, particularly with regard to the distributed ledger technology-based realization of TAI.
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INVITED PAPER
Trustworthy artificial intelligence
Scott Thiebes
1
&Sebastian Lins
1
&Ali Sunyaev
1
Received: 13 May 2020 /Accepted: 9 September 2020
#The Author(s) 2020
Abstract
Artificial intelligence (AI) brings forth many opportunities to contribute to the wellbeing of individuals and the advancement of
economies and societies, but also a variety of novel ethical, legal, social, and technological challenges. Trustworthy AI (TAI)
bases on the idea that trust builds the foundation of societies, economies, and sustainable development, and that individuals,
organizations, and societies will therefore only ever be able to realize the full potential of AI, if trust can be established in its
development, deployment, and use. With this article we aim to introduce the concept of TAI and its five foundational principles
(1) beneficence, (2) non-maleficence, (3) autonomy, (4) justice, and (5) explicability. We further draw on these five principles to
develop a data-driven research framework for TAI and demonstrate its utility by delineating fruitful avenues for future research,
particularly with regard to the distributed ledger technology-based realization of TAI.
Keywords Trustworthy artificial intelligence .Artificial intelligence .Trust .Framework .Distributed ledger technology .
Blockchain
JEL classification M15 O30 A13 C80
Introduction
Artificial intelligence (AI) enables computers to execute tasks
that are easy for people to perform but difficult to describe
formally (Pandl et al. 2020). It is one of the most-discussed
technology trends in research and practice today, and estimat-
ed to deliver an additional global economic output of around
USD 13 trillion by the year 2030 (Bughin et al. 2018).
Although AI has been around and researched for decades, it
is especially the recent advances in the subfields of machine
learning and deep learning that not only result in manifold
opportunities to contribute to the wellbeing of individuals as
well as the prosperity and advancement of organizations and
societies but, also in a variety of novel ethical, legal, and social
challenges that may severely impede AI’s value contributions,
if not handled appropriately (Floridi 2019; Floridi et al. 2018).
Examples of issues that are associated with the rapid develop-
ment and proliferation of AI are manifold. They range from
risks of infringing individuals’privacy (e.g., swapping peo-
ple’s faces in images or videos via DeepFakes (Turton and
Martin 2020) or involuntarily tracking individuals over the
Internet via the Clearview AI (Hill 2020)), or the presence of
racial bias in widely used AI-based systems (Obermeyer et al.
2019), to the rapid and uncontrolled creation of economic
losses via autonomous trading agents (e.g., the loss of millions
of dollars through erroneous algorithms in high-frequency
trading (Harford 2012)).
To maximize the benefits of AI while at the same time
mitigating or even preventing its risks and dangers, the con-
cept of trustworthy AI (TAI) promotes the idea that individ-
uals, organizations, and societies will only ever be able to
achieve the full potential of AI if trust can be established in
its development, deployment, and use (Independent High-
Level Expert Group on Artificial Intelligence 2019). If, for
Responsible Editor: Rainer Alt
*Ali Sunyaev
sunyaev@kit.edu
Scott Thiebes
scott.thiebes@kit.edu
Sebastian Lins
sebastian.lins@kit.edu
1
Department of Economics and Management, Karlsruhe Institute of
Technology, Institute AIFB - Building 05.20, KIT-Campus South,
76128 Karlsruhe, Germany
Electronic Markets
https://doi.org/10.1007/s12525-020-00441-4
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