Landscape of Machine Implemented Ethics
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Landscape of Machine Implemented Ethics Vivek Nallur1
© Springer Nature B.V. 2020
Abstract This paper surveys the state-of-the-art in machine ethics, that is, considerations of how to implement ethical behaviour in robots, unmanned autonomous vehicles, or software systems. The emphasis is on covering the breadth of ethical theories being considered by implementors, as well as the implementation techniques being used. There is no consensus on which ethical theory is best suited for any particular domain, nor is there any agreement on which technique is best placed to implement a particular theory. Another unresolved problem in these implementations of ethical theories is how to objectively validate the implementations. The paper discusses the dilemmas being used as validating ‘whetstones’ and whether any alternative validation mechanism exists. Finally, it speculates that an intermediate step of creating domain-specific ethics might be a possible stepping stone towards creating machines that exhibit ethical behaviour. Keywords Artificial intelligence · Robotics · Machine ethics · Autonomous systems · Implementation and design
Motivation Computers are increasingly a part of the socio-technical systems around us. Domains such as smart-grids, cloud computing, healthcare, and transport are but some examples where computers are deeply embedded. The speed and complexity of decision-making in these domains have meant that humans are ceding more and more autonomy to these computers (Nallur & Clarke 2018). Autonomy, in machines, can be defined as the effective decision-making power over goals, that influences some action in the real-world. For instance, smart traffic lights can autonomically change their timings, depending on the flow and density of traffic on the roads. The introduction of progressive levels of autonomy into software-enabled devices that * Vivek Nallur [email protected] 1
School of Computer Science, University College Dublin, Dublin D04 V1W8, Republic of Ireland
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interact actively with human beings implies that human society will be impacted by decisions made by such machines. Transport systems that decide on prices of tickets based on demand (Masoum et al. 2011), smart buildings that decide how much energy to be used at a particular time (Yoon et al. 2014), smart cameras that decide which persons to track (Lewis et al. 2014), cars that can change their routing priorities (Song et al. 2015), hospital machines that recommend a particular course of treatment (Lynn 2019), are all examples of machines being given autonomy, while decisively impacting human life. Autonomous machines, therefore, need to be imbued with a sense of ethics that reflect the social milieu they operate in and make decisions that are ethically acceptable to society. The notion of a general-purpose intelligence has been the quest of computer scientists ever since the dawn of computing. From Turing’s original essay on intelligence to recent developments in machine-learning where computers outp
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