Abstract
In the digital era, we witness the increasing use of artificial intelligence (AI) to solve problems, while improving productivity and efficiency. Yet, inevitably costs are involved with delegating power to algorithmically based systems, some of whose workings are opaque and unobservable and thus termed the “black box”. Central to understanding the “black box” is to acknowledge that the algorithm is not mendaciously undertaking this action; it is simply using the recombination afforded to scaled computable machine learning algorithms. But an algorithm with arbitrary precision can easily reconstruct those characteristics and make life-changing decisions, particularly in financial services (credit scoring, risk assessment, etc.), and it could be difficult to reconstruct, if this was done in a fair manner reflecting the values of society. If we permit AI to make life-changing decisions, what are the opportunity costs, data trade-offs, and implications for social, economic, technical, legal, and environmental systems? We find that over 160 ethical AI principles exist, advocating organisations to act responsibly to avoid causing digital societal harms. This maelstrom of guidance, none of which is compulsory, serves to confuse, as opposed to guide. We need to think carefully about how we implement these algorithms, the delegation of decisions and data usage, in the absence of human oversight and AI governance. The paper seeks to harmonise and align approaches, illustrating the opportunities and threats of AI, while raising awareness of Corporate Digital Responsibility (CDR) as a potential collaborative mechanism to demystify governance complexity and to establish an equitable digital society.
Original language | English |
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Pages (from-to) | 179-188 |
Number of pages | 10 |
Journal | Society |
Volume | 58 |
Issue number | 3 |
DOIs | |
Publication status | Published - 14 Jun 2021 |
Bibliographical note
Funding Information:This work was funded in part by the UK Engineering and Physical Sciences Research Council for the projects titled “FinTrust: Trust Engineering for the Financial Industry” (EP/R033595/1) and “Finclusion: verifiable credentials” part of Trusted Digital Infrastructure for Identification Systems Gates Foundation/Turing Institute (ESaPoNIS\100047).
Publisher Copyright:
© 2021, The Author(s).
Keywords
- Artificial intelligence (AI) governance
- Complexity
- Corporate Digital Responsibility
- Digital ethics and trust
- Equitable digital society
- Financial technology (FinTech)
ASJC Scopus subject areas
- Sociology and Political Science
- Social Sciences(all)