Abstract
The rapid advancement of algorithmic trading has demonstrated the success of AI automation, as well as gaps in our understanding of the implications of this technology proliferation. We explore ethical issues in the context of autonomous trading agents, both to address problems in this domain and as a case study for regulating autonomous agents more generally. We argue that increasingly competent trading agents will be capable of initiative at wider levels, necessitating clarification of ethical and legal boundaries, and corresponding development of norms and enforcement capability.
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Notes
It is easy to find statements predicting a singularity around the corner (Kurzweil 2006), as well as those denying its inevitability (Walsh 2016) or even the possibility of ever achieving human-level AI. Most expert opinion considers superintelligence plausible this century, with significant disagreement about whether many humans alive today will meet machines exceeding their intelligence across the board (Müller and Bostrom 2016).
A long position is created when a trader buys a security, generally expecting to sell it later at a higher price. A short position is created when a trader sells a security in anticipation that its price will fall, planning to profit in buying it back later at a lower price.
As Davis et al. (2013) point out, the ethical responsibilities of traders, computer engineers, and quantitative analysts are each determined by separate professional organizations, creating a need for an organizational-level understanding of standards.
Schuldenzucker (2016) proposes a related theorem-proving approach, where starting from contract descriptions expressed in a formal logic, the prover uses no-arbitrage principles to derive inequality relations on security prices. If the inequalities are violated in the market, then an arbitrage opportunity exists.
The Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system maintained by the SEC is a system for filing (and subsequent retrieval) of electronic forms by public companies in the US. The database is freely available to the public, including investors (www.sec.gov/everythingedgar).
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Based on motivations and developing concepts of our ongoing project “Understanding and Mitigating AI Threats to the Financial System”, supported by a Grant from the Future of Life Institute.
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Wellman, M.P., Rajan, U. Ethical Issues for Autonomous Trading Agents. Minds & Machines 27, 609–624 (2017). https://doi.org/10.1007/s11023-017-9419-4
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DOI: https://doi.org/10.1007/s11023-017-9419-4