Despite an emerging international consensus on principles of AI governance, lawmakers have so far failed to translate those principles into regulations in the financial sector. Perhaps, in order to remain competitive in the global race for AI supremacy without being typecast as stifling innovation, typically cautious financial regulators are unusually allowing the introduction of experimental AI technology into the financial sector, with few controls on the unprecedented risks to consumers and financial stability. Once an unregulated AI software causes serious economic harm, a public and regulatory backlash would lead to over-regulation that could harm innovation of this potentially beneficial technology. Artificial intelligence is rapidly influencing the financial sector with innumerable potential benefits, such as enhancing financial services and improving regulatory compliance. This article argues that the best way to encourage a sustainable future in AI innovation in the financial sector is to support a proactive regulatory approach prior to any financial harm occurring. This proactive approach should implement rational regulations that embody jurisdiction-specific rules in line with carefully construed international principles.
This paper adds to the discussion on the legal personhood of artificial intelligence by focusing on one area not covered by previous works on the subjectownership of property. The author discusses the nexus between property ownership and legal personhood. The paper explains the prevailing misconceptions about the requirements of rights or duties in legal personhood, and discusses the potential for conferring rights or imposing obligations on weak and strong AI. While scholars have discussed AI owning real property and copyright, there has been limited discussion on the nexus of AI property ownership and legal personhood. The paper discusses the right to own property and the obligations of property ownership in nonhumans, and applying it to AI. The paper concludes that the law may grant property ownership and legal personhood to weak AI, but not to strong AI.
This article explores the legal and ethical implications of big data's pursuit of human 'digital thought clones'. It identifies various types of digital clones that have been developed and demonstrates how the pursuit of more accurate personalised consumer data for microtargeting leads to the evolution of digital thought clones. The article explains the business case for digital thought clones and how this is the commercial Holy Grail for profit-seeking big data and advertisers, who have commoditised predictions of digital behaviour data. Given big data's industrial-scale data mining and relentless commercialisation of all types of human data, this article identifies some types of protections but argues that more jurisdictions urgently need to enact legislation similar to the General Data Protection Regulation in Europe to protect people against unscrupulous and harmful uses of their data and the unauthorised development and use of digital thought clones.
This paper argues for a sandbox approach to regulating artificial intelligence (AI) to complement a strict liability regime. The authors argue that sandbox regulation is an appropriate complement to a strict liability approach, given the need to maintain a balance between a regulatory approach that aims to protect people and society on the one hand and to foster innovation due to the constant and rapid developments in the AI field on the other. The authors analyse the benefits of sandbox regulation when used as a supplement to a strict liability regime, which by itself creates a chilling effect on AI innovation, especially for small and medium-sized enterprises. The authors propose a regulatory safe space in the AI sector through sandbox regulation, an idea already embraced by European Union regulators and where AI products and services can be tested within safeguards.
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