scholarly journals Computing schizophrenia: ethical challenges for machine learning in psychiatry

2020 ◽  
pp. 1-7 ◽  
Author(s):  
Georg Starke ◽  
Eva De Clercq ◽  
Stefan Borgwardt ◽  
Bernice Simone Elger
Keyword(s):  
Machine Learning ◽  
Ethical Challenges ◽  
Hypothetical Case ◽  
General Introduction ◽  
Close Attention ◽  
Respect For Autonomy ◽  
Standard Clinical Practice ◽  
Potential Problems ◽  
Case Based ◽  
Do So

Abstract Recent advances in machine learning (ML) promise far-reaching improvements across medical care, not least within psychiatry. While to date no psychiatric application of ML constitutes standard clinical practice, it seems crucial to get ahead of these developments and address their ethical challenges early on. Following a short general introduction concerning ML in psychiatry, we do so by focusing on schizophrenia as a paradigmatic case. Based on recent research employing ML to further the diagnosis, treatment, and prediction of schizophrenia, we discuss three hypothetical case studies of ML applications with view to their ethical dimensions. Throughout this discussion, we follow the principlist framework by Tom Beauchamp and James Childress to analyse potential problems in detail. In particular, we structure our analysis around their principles of beneficence, non-maleficence, respect for autonomy, and justice. We conclude with a call for cautious optimism concerning the implementation of ML in psychiatry if close attention is paid to the particular intricacies of psychiatric disorders and its success evaluated based on tangible clinical benefit for patients.

scholarly journals A top-level model of case-based argumentation for explanation: Formalisation and experiments

2021 ◽  
pp. 1-36
Author(s):  
Henry Prakken ◽  
Rosa Ratsma
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Linear Models ◽  
Evaluation Studies ◽  
Data Sets ◽  
Machine Learning Applications ◽  
Level Model ◽  
Similarities And Differences ◽  
Further Development ◽  
Case Based

This paper proposes a formal top-level model of explaining the outputs of machine-learning-based decision-making applications and evaluates it experimentally with three data sets. The model draws on AI & law research on argumentation with cases, which models how lawyers draw analogies to past cases and discuss their relevant similarities and differences in terms of relevant factors and dimensions in the problem domain. A case-based approach is natural since the input data of machine-learning applications can be seen as cases. While the approach is motivated by legal decision making, it also applies to other kinds of decision making, such as commercial decisions about loan applications or employee hiring, as long as the outcome is binary and the input conforms to this paper’s factor- or dimension format. The model is top-level in that it can be extended with more refined accounts of similarities and differences between cases. It is shown to overcome several limitations of similar argumentation-based explanation models, which only have binary features and do not represent the tendency of features towards particular outcomes. The results of the experimental evaluation studies indicate that the model may be feasible in practice, but that further development and experimentation is needed to confirm its usefulness as an explanation model. Main challenges here are selecting from a large number of possible explanations, reducing the number of features in the explanations and adding more meaningful information to them. It also remains to be investigated how suitable our approach is for explaining non-linear models.

International responses to weather modification

1975 ◽  
Vol 29 (3) ◽  
pp. 805-826 ◽  
Author(s):  
Edith Brown Weiss
Keyword(s):  
International Cooperation ◽  
New Technology ◽  
International Community ◽  
Weather Modification ◽  
Weather System ◽  
The Past ◽  
Time Horizons ◽  
Weather And Climate ◽  
Potential Problems ◽  
Do So

In the past few decades we have been improving our understanding of the weather system and exploring ways to modify it. Over sixty countries have experimented with modifying the weather. The new technology of weather and climate modification will raise important political problems which will demand new responses from the international community. Whether states will be able to establish the cooperative measures necessary to develop and manage new technology depends upon whether there are sufficient incentives to do so. This article analyzes the historical patterns of international cooperation in meteorology, and then plots against several time horizons projected developments and capabilities in weather modification technology and the potential problems emerging from using the technology. It derives a tentative picture of the responsibilities demanded, compares the likely responses with those needed, and assesses whether they will be adequate for the problems projected.

scholarly journals Research on threat detection in cyber security based on machine learning

2021 ◽  
Vol 2113 (1) ◽  
pp. 012074
Author(s):  
Qiwei Ke
Keyword(s):  
Machine Learning ◽  
Cyber Security ◽  
Information Privacy ◽  
Machine Learning Techniques ◽  
Threat Detection ◽  
Vulnerability Detection ◽  
New Information ◽  
Learning Techniques ◽  
Potential Problems ◽  
Insight Into

Abstract The volume of the data has been rocketed since the new information era arrives. How to protect information privacy and detect the threat whenever the intrusion happens has become a hot topic. In this essay, we are going to look into the latest machine learning techniques (including deep learning) which are applicable in intrusion detection, malware detection, and vulnerability detection. And the comparison between the traditional methods and novel methods will be demonstrated in detail. Specially, we would examine the whole experiment process of representative examples from recent research projects to give a better insight into how the models function and cooperate. In addition, some potential problems and improvements would be illustrated at the end of each section.

The ‘Always Speaking’ Approach to Statutes (and the Significance of Its Misapplication in Aubrey v The Queen)

2020 ◽  
Vol 43 (1) ◽  
Author(s):  
Dan Meagher
Keyword(s):  
Statutory Interpretation ◽  
Close Attention ◽  
Modern Approach ◽  
Difficult Question ◽  
Do So ◽  
Legal Meaning

This article clarifies the nature and scope of the ‘always speaking’ approach to statutes in Anglo-Antipodean law. To do so is important. For whilst it is now considered interpretive orthodoxy to treat statutes as ‘always speaking’, what that entails in terms of doctrine and application is not always clear. It is, however, recognised that whether or not a statute attracts the operation of the ‘always speaking’ approach can sometimes be a difficult question to answer. In order to do so judges have at their disposal the interpretive tools (and method) provided by the ‘modern approach’ to statutory interpretation. Indeed, in these cases maybe close attention to the contextualism which lies at the heart of the ‘modern approach’ is a more satisfactory way of determining the legal meaning of a statute than to presume that it is ‘always speaking’.

Women Trafficking Problem in Assam

2021 ◽  
Vol 10 (3) ◽  
pp. 12-40
Author(s):  
Rupamjyoti Nath ◽  
Manjit Das
Keyword(s):  
Secondary Data ◽  
Close Attention ◽  
Common People ◽  
Eastern State ◽  
The North ◽  
North Eastern ◽  
Points Of View ◽  
The Government ◽  
Women Trafficking ◽  
Do So

The increasing numbers of newspaper reports on disappearing women from the north eastern state of Assam and especially from the economically backward areas of the state in recent years deserve close attention from both researchers' points of view as well as policy-level intervention of the larger community along with the government. This study makes an attempt to operate upon the menace area through the scalpel of game theory under the light of both primary and secondary data collected from the study area. It is an attempt to outline conscious human behaviour that leads to crimes such as women trafficking and identify the parameters controlling or affecting which types of crimes can be controlled. In order to do so, different distinct entities associated with the problem have been considered as different players leading to the concluding indication of prevailing flaws in the legal system of the country along with lack of employment opportunities and mass ignorance about the problem in hand among common people as the major reasons.

Methods of Software Quality Prediction With Similarity Measures

2017 ◽  
pp. 34-56
Keyword(s):  
Machine Learning ◽  
Software Quality ◽  
Similarity Measures ◽  
Fault Prediction ◽  
Estimation Accuracy ◽  
Case Based Reasoning ◽  
Quality Prediction ◽  
Software Fault Prediction ◽  
Software Quality Prediction ◽  
Case Based

To improve the software quality the number of errors or faults must be removed from the software. This chapter presents a study towards machine learning and software quality prediction as an expert system. The purpose of this chapter is to apply the machine learning approaches such as case-based reasoning to predict software quality. Five different similarity measures, namely, Euclidean, Canberra, Exponential, Clark and Manhattan are used for retrieving the matching cases from the knowledgebase. The use of different similarity measures to find the best method significantly increases the estimation accuracy and reliability. Based on the research findings in this book it can be concluded that applying similarity measures in case-based reasoning may be a viable technique for software fault prediction

Dimensions of Cultural Variation

2019 ◽  
pp. 67-92 ◽  
Author(s):  
Peter B. Smith
Keyword(s):  
Social Norms ◽  
Multilevel Modeling ◽  
Cultural Differences ◽  
Theoretical Framework ◽  
Social Contexts ◽  
Measurement Bias ◽  
Cultural Variation ◽  
Close Attention ◽  
The Social ◽  
Do So

To understand cultural differences, we need to find ways to characterize the variations in the social contexts in which people are located. To do so, we must focus on differences between contexts rather than differences between individuals. Most research of this type has examined differences between nations in terms of dimensions. Treating each nation as a unit, contrasts have been identified in terms of values, beliefs, self-descriptions, and social norms. The most influential difference identified concerned the dimension of individualism–collectivism, which has provided the theoretical framework for numerous studies. The validity of this type of investigation rests on close attention to aspects of measurement to ensure that respondents are able to make the necessary judgments and to respond in ways that are not affected by measurement bias. Where many nations are sampled, multilevel modeling can be used to show the ways in which dimensions of culture affect social behaviors.

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