Autonomous vehicles —and accidents they are involved in—attest to the urgent need to consider the ethics of artificial intelligence. The question dominating the discussion so far has been whether we want AVs to behave in a ‘selfish’ or utilitarian manner. Rather than considering modeling self-driving cars on a single moral system like utilitarianism, one possible way to approach programming for AI would be to reflect recent work in neuroethics. The agent–deed–consequence model :3–20, 2014a, Behav Brain Sci 37:487–488, 2014b) provides a (...) promising descriptive and normative account while also lending itself well to implementation in AI. The ADC model explains moral judgments by breaking them down into positive or negative intuitive evaluations of the agent, deed, and consequence in any given situation. These intuitive evaluations combine to produce a positive or negative judgment of moral acceptability. For example, the overall judgment of moral acceptability in a situation in which someone committed a deed that is judged as negative would be mitigated if the agent had good intentions and the action had a good consequence. This explains the considerable flexibility and stability of human moral judgment that has yet to be replicated in AI. This paper examines the advantages and disadvantages of implementing the ADC model and how the model could inform future work on ethics of AI in general. (shrink)

As artificial intelligence technologies become increasingly prominent in our daily lives, media coverage of the ethical considerations of these technologies has followed suit. Since previous research has shown that media coverage can drive public discourse about novel technologies, studying how the ethical issues of AI are portrayed in the media may lead to greater insight into the potential ramifications of this public discourse, particularly with regard to development and regulation of AI. This paper expands upon previous research by systematically analyzing (...) and categorizing the media portrayal of the ethical issues of AI to better understand how media coverage of these issues may shape public debate about AI. Our results suggest that the media has a fairly realistic and practical focus in its coverage of the ethics of AI, but that the coverage is still shallow. A multifaceted approach to handling the social, ethical and policy issues of AI technology is needed, including increasing the accessibility of correct information to the public in the form of fact sheets and ethical value statements on trusted webpages, collaboration and inclusion of ethics and AI experts in both research and public debate, and consistent government policies or regulatory frameworks for AI technology. (shrink)

This book reconceives disability as a set of social relations and practices, as experienced embodiment, and as an emancipatory movement, as well as a biomedical phenomenon. The author brings new attention to complex ethical questions surrounding disability, looking at not only the biomedical understanding of impairment, but also its cultural representations and social organization.

What is the ethical impact of artificial intelligence assistants on human lives, and specifically how much do they threaten our individual autonomy? Recently, as part of forming an ethical framework for thinking about the impact of AI assistants on our lives, John Danaher claims that if the external automaticity generated by the use of AI assistants threatens our autonomy and is therefore ethically problematic, then the internal automaticity we already live with should be viewed in the same way. He takes (...) advantage of this paradox of internal automaticity to downplay the threats of external automaticity to our autonomy. We respond in this paper by challenging the legitimacy of the paradox. While Danaher assumes that internal and external automaticity are roughly equivalent, we argue that there are reasons why we should accept a large degree of internal automaticity, that it is actually essential to our sense of autonomy, and as such it is ethically good; however, the same does not go for external automaticity. Therefore, the similarity between the two is not as powerful as the paradox presumes. In conclusion, we make practical recommendations for how to better manage the integration of AI assistants into society. (shrink)