Philosophical approaches to ethical decision making

Introduction The main topic of the article is the Western metaphilosophy of the last hundred years or so. But that topic is broached via a sketch of some earlier Western metaphilosophies.

Philosophical approaches to ethical decision making

From Nash to Dependency Equilibria Just Machine Learning Closing Transparency of Classical and Quantum Mechanical Artificial Intelligence Hans Briegel In the first part of the talk, I will review recent work on the classical model of projective simulation PS for learning and agency, including its applications in robotics and quantum experiment.

The model can be quantized, leading to a speed-up in the decision-making capacity of the agent. In the second part, I will address the problems of transparency and interpretability of learning systems.

I will discuss these problems in the specific context of the PS model but also beyond, including quantum models for artificial learning agents. Preserving AI Control via the Use of Theoretical Neuroinformatics in Empirical Ethics Zoe Cremer It will be crucial to remain in control of the values implemented by autonomous, artificially intelligent agents.

This proposal shows how neuroinformatics could be applied to conceive of a quantifiable decision model, that can guide AI systems to remained aligned with empirically derived human ethics. The combination of machine learning and non-invasive brain imaging can abstract a shared cognitive space in ethical decision-making across humans, directly from neural computation.

This shared space can be used to build a model of human ethics and assumptions can be verified by reverse inference. The experimental paradigm is theoretically capable of processing naturalistic stimuli, reducing biases in theory selection and improving decision-making, by empirically estimating the Coherent Extrapolated Volition, while still retaining AI alignment.

Some examples of probabilistically fair measures here include precision parity, true positive parity, and false positive parity across pre-defined groups in the population e. Most literature in this area frame the machine learning problem as estimating a risk score. Recent papers -- by Kleinberg, Mullainathan, and Raghavan arXiv: I take a boarder notion of fairness and ask the following two questions: Is there such a thing as just machine learning?

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If so, is just machine learning possible in our unjust world? I will describe a different way of framing the problem and will present some preliminary results.

The answer to this question is famously thought to depend on whether y obtains in the most similar world s in which x obtains. One limitation of the resulting conception of similarity is that it says nothing about what would obtain were the causal structure to be different from what it actually is, or from what we believe it to be.

In this paper, we explore the possibility of using graphical causal models to resolve counterfactual queries about causal structure by introducing a notion of similarity between causal graphs. Principle of Independence of Mechanisms in Machine Learning and Physics Dominik Janzing Understanding science by identifying mechanisms that work independently of others is at the heart of scientific methodology.

The idea that every causal conditional in this factorization represents an independent mechanism is widespread in the literature, but our research suggests that the implications need to be further explored: In causal inference, it suggests entirely novel approaches.

In particular, the principle that P cause and P effect cause contain no information about each other sometimes allows to distinguish between cause and effect in bivariate statistics [1].

Further, the principle suggests new methods for detecting hidden common causes [2]. Roughly speaking, it also suggests that semi-supervised learning only works in 'anticausal' direction, that is, when the cause is predicted from the effect.

In causal direction, that is, when the effect is predicted from the cause, unlabelled points are pointless because knowing more about P cause does not help to better infer the relation between cause and effect [3]. When joint distributions change across different data sets, some causal conditionals may have remained constant, which can be helpful for machine learning in different environments [1].

Elements of causal inference, MIT Press Detecting non-causal artifacts in multivariate linear regression models, ICML On causal and anticausal learning, ICML Algorithmic independence of initial condition and dynamic law in thermodynamics and causal inference, NJP On the entropy production of time series with unidirectional linearity, JSP How can such moral judgments be cognitively represented?

According to it, an agent represents his or her moral judgments in terms of a universal betterness ordering over the options that he or she might encounter and then takes the morally permissible options in each context to be the most highly ranked feasible ones.

Metaphilosophy, Contemporary | Internet Encyclopedia of Philosophy

Although this approach constitutes a clear improvement over the purely extensional approach, it still has significant limitations. First of all, consequentialist representations of moral judgments are not always possible, because of the non- consequentialist or relativist nature of those judgments; and secondly, consequentialist representations are cumbersome and not very illuminating, especially when the number of possible options is large.

This way of representing moral judgments not only offers greater power and flexibility, but it also suggests a plausible mechanism for moral learning: Humans are slow, expensive, unreliable, and highly error-prone — in quite systematic but still unpredictable ways.Similarly, in ethics, no school answers all the problems raised by social living.

In most cases, all three schools need to be considered in order to reach the best ethical decision. Ethical and Legal Dimensions of Benzodiazepine Prescription. by Harold J. Bursztajn, M.D. and Archie Brodsky, B.A. From the Department of Psychiatry, Harvard Medical. “Ethics must begin at the top of an organisation.

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It is a leadership issue and the chief executive must set the example.” – Edward Hennessy The world of business is full of ethical dilemmas, from where to direct scarce resources to serving the local community. The ethical action is the one that provides the greatest good for the greatest number.

The Rights Approach The second important approach to ethics has its roots in the philosophy of the 18th-century thinker Immanuel Kant and others like him, who focused on the individual's right to choose for herself or himself. The ethical action is the one that provides the greatest good for the greatest number.

The Rights Approach The second important approach to ethics has its roots in the philosophy of the 18th-century thinker Immanuel Kant and others like him, who focused . May 03,  · Five Basic Approaches to Ethical Decision-Making.

By: Dr. David Meeler.

Philosophical approaches to ethical decision making

The Rights Approach. An important approach to ethics has its roots in the philosophy of the 18th-century thinker Immanuel Kant and others like him, who focused on the individual’s right to choose for herself or himself.

According to these philosophers, what.

Philosophical Approaches to Ethical Decision Making Matrix