Word Meaning in Legal Interpretation

Professor Sinnott-Armstrong argues against the arguments published by Professor Prakash and Professor Alexander in an article on legal interpretation in which they defended the thesis that all interpretation properly so-called seeks to uncover the intended meaning of the author(s). Against their arguments, the Author defends coherence and importance of word meaning. In Part I, he more precisely defines the these that Alexander and Prakash deny and Professor Sinnott-Armstrong defends. In Part II, he will show why Alexander and Prakash\u27s arguments fail to rule out word meanings. In PArt III, he will put these debates in a larger theoretical context and show why word meaning is important to legal interpretation

AI Methods in Bioethics

Commentary about the role of AI in bioethics for the 10th anniversary issue of AJOB: Empirical Bioethic

I’m not the person I used to be: The self and autobiographical memories of immoral actions

People maintain a positive identity in at least two ways: They evaluate themselves more favorably than other people, and they judge themselves to be better now than they were in the past. Both strategies rely on autobiographical memories. The authors investigate the role of autobiographical memories of lying and emotional harm in maintaining a positive identity. For memories of lying to or emotionally harming others, participants judge their own actions as less morally wrong and less negative than those in which other people lied to or emotionally harmed them. Furthermore, people judge those actions that happened further in the past to be more morally wrong than those that happened more recently. Finally, for periods of the past when they believed that they were very different people than they are now, participants judge their actions to be more morally wrong and more negative than those actions from periods of their pasts when they believed that they were very similar to who they are now. The authors discuss these findings in relation to theories about the function of autobiographical memory and moral cognition in constructing and perceiving the self over time

How stable are moral judgments?

Psychologists and philosophers often work hand in hand to investigate many aspects of moral cognition. In this paper, we want to highlight one aspect that to date has been relatively neglected: the stability of moral judgment over time. After explaining why philosophers and psychologists should consider stability and then surveying previous research, we will present the results of an original three-wave longitudinal study. We asked participants to make judgments about the same acts in a series of sacrificial dilemmas three times, 6-8 days apart. In addition to investigating the stability of our participants' ratings over time, we also explored some potential explanations for instability. To end, we will discuss these and other potential psychological sources of moral stability (or instability) and highlight possible philosophical implications of our findings

How AI can AID bioethics

This paper explores some ways in which artificial intelligence (AI) could be used to improve human moral judgments in bioethics by avoiding some of the most common sources of error in moral judgment, including ignorance, confusion, and bias. It surveys three existing proposals for building human morality into AI: Top-down, bottom-up, and hybrid approaches. Then it proposes a multi-step, hybrid method, using the example of kidney allocations for transplants as a test case. The paper concludes with brief remarks about how to handle several complications, respond to some objections, and extend this novel method to other important moral issues in bioethics and beyond

Adapting a Kidney Exchange Algorithm to Align with Human Values

The efficient and fair allocation of limited resources is a classical problem in economics and computer science. In kidney exchanges, a central market maker allocates living kidney donors to patients in need of an organ. Patients and donors in kidney exchanges are prioritized using ad-hoc weights decided on by committee and then fed into an allocation algorithm that determines who gets what--and who does not. In this paper, we provide an end-to-end methodology for estimating weights of individual participant profiles in a kidney exchange. We first elicit from human subjects a list of patient attributes they consider acceptable for the purpose of prioritizing patients (e.g., medical characteristics, lifestyle choices, and so on). Then, we ask subjects comparison queries between patient profiles and estimate weights in a principled way from their responses. We show how to use these weights in kidney exchange market clearing algorithms. We then evaluate the impact of the weights in simulations and find that the precise numerical values of the weights we computed matter little, other than the ordering of profiles that they imply. However, compared to not prioritizing patients at all, there is a significant effect, with certain classes of patients being (de)prioritized based on the human-elicited value judgments