Towards Model-Driven Self-Explanation for Autonomous Decision-Making Systems

Author(s):  
Owen Reynolds
Author(s):  
Richard Ashcroft

This chapter discusses the ethics of depression from a personal perspective. The author, an academic who has worked in the field of medical ethics or bioethics, has suffered episodes of depression throughout his life, some lasting several months. Here he shares a few quite informal things about how these two facts about him are connected. He first considers the paradigm of autonomy and autonomous decision-making, as well as the problem with functional accounts of autonomy with regard to depression. He then reflects on an approach to ethics and depression that involves thinking about the ethics of being depressed. He also highlights two aspects of the ‘ethics of depression’: treatment and the ethical obligation to talk about it.


Author(s):  
Siamak Farshidi ◽  
Slinger Jansen ◽  
Sven Fortuin

AbstractModel-driven development platforms shift the focus of software development activity from coding to modeling for enterprises. A significant number of such platforms are available in the market. Selecting the best fitting platform is challenging, as domain experts are not typically model-driven deployment platform experts and have limited time for acquiring the needed knowledge. We model the problem as a multi-criteria decision-making problem and capture knowledge systematically about the features and qualities of 30 alternative platforms. Through four industry case studies, we confirm that the model supports decision-makers with the selection problem by reducing the time and cost of the decision-making process and by providing a richer list of options than the enterprises considered initially. We show that having decision knowledge readily available supports decision-makers in making more rational, efficient, and effective decisions. The study’s theoretical contribution is the observation that the decision framework provides a reliable approach for creating decision models in software production.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 969
Author(s):  
Eric Cayeux ◽  
Benoît Daireaux ◽  
Adrian Ambrus ◽  
Rodica Mihai ◽  
Liv Carlsen

The drilling process is complex because unexpected situations may occur at any time. Furthermore, the drilling system is extremely long and slender, therefore prone to vibrations and often being dominated by long transient periods. Adding the fact that measurements are not well distributed along the drilling system, with the majority of real-time measurements only available at the top side and having only access to very sparse data from downhole, the drilling process is poorly observed therefore making it difficult to use standard control methods. Therefore, to achieve completely autonomous drilling operations, it is necessary to utilize a method that is capable of estimating the internal state of the drilling system from parsimonious information while being able to make decisions that will keep the operation safe but effective. A solution enabling autonomous decision-making while drilling has been developed. It relies on an optimization of the time to reach the section total depth (TD). The estimated time to reach the section TD is decomposed into the effective time spent in conducting the drilling operation and the likely time lost to solve unexpected drilling events. This optimization problem is solved by using a Markov decision process method. Several example scenarios have been run in a virtual rig environment to test the validity of the concept. It is found that the system is capable to adapt itself to various drilling conditions, as for example being aggressive when the operation runs smoothly and the estimated uncertainty of the internal states is low, but also more cautious when the downhole drilling conditions deteriorate or when observations tend to indicate more erratic behavior, which is often observed prior to a drilling event.


2014 ◽  
Vol 204 (1) ◽  
pp. 1-2 ◽  
Author(s):  
Peter Lepping ◽  
Bevinahalli Nanjegowda Raveesh

SummaryCurrent capacity-based legislation and practice overvalues autonomy to the detriment of other ethical principles. A balanced ethical approach would consider the patient's right to treatment, their relationships and interactions with society and not solely the patient's right to liberty and autonomous decision-making.


1989 ◽  
Vol 82 (5) ◽  
pp. 260-263 ◽  
Author(s):  
H J Sutherland ◽  
H A Llewellyn-Thomas ◽  
G A Lockwood ◽  
D L Tritchler ◽  
J E Till

The relationship between cancer patients’ desire for information and their preference for participation in decision making has been examined. Approximately 77% of the 52 patients reported that they had participated in decision making to the extent that they wished, while most of the remaining 23% would have preferred an opportunity to have greater input. Although many of the patients actively sought information, a majority preferred the physician to assume the role of the primary decision maker. Ethically, the disclosure of information has been assumed to be necessary for autonomous decision making. Nevertheless, the results of this study indicate that patients may actively seek information to satisfy an as yet unidentified aspect of psychological autonomy that does not necessarily include participation in decision making.


2016 ◽  
Vol 11 (2) ◽  
pp. 124-155
Author(s):  
Walaa Abd El Haliem Eid ◽  
Fouada Shaban ◽  
Safaa Zahran ◽  
Karima El Said

2021 ◽  
pp. 98-101
Author(s):  
Kisaye Natsuki

This poem speaks about African peoples surviving our cross-centuries experience of displacement and subjugation where notions of home can fee lost, empty or inaccessible. It culminates to show that through this experience, another parallel and interacting reality of agency, clarity and action is occurring and we are empowered beyond any imposed systems. I recognized my strength and clarity as well as my powerful autonomous decision-making despite an experience of migration to Canada where knowing my place is always dictated. This allowed me to see even moreso the presence of this strength throughout our ancestors and still in ourselves now.


2019 ◽  
Author(s):  
Wenjia Joyce Zhao ◽  
Russell Richie ◽  
Sudeep Bhatia

Information stored in memory influences the formation of preferences and beliefs in most everyday decision tasks. The richness of this information, and the complexity inherent in interacting memory and decision processes, makes the quantitative model-driven analysis of such decisions very difficult. In this paper we present a general framework that is capable of addressing the theoretical and methodological barriers to building formal models of naturalistic memory-based decision making. Our framework implements established theories of memory search and decision making within a single integrated cognitive system, and uses computational language models to quantify the thoughts over which memory and decision processes operate. It can thus describe both the content of the information that is sampled from memory, as well as the processes involved in retrieving and evaluating this information in order to make a decision. Furthermore, our framework is tractable, and the parameters that characterize memory-based decisions can be recovered using thought-listing and choice data from existing experimental tasks, and in turn be used to make quantitative predictions regarding choice probability, length of deliberation, retrieved thoughts, and the effects of decision context. We showcase the power and generality of our framework by applying it to study risk perception, consumer behavior, financial decision making, ethical decision making, legal decision making, food choice, and judgments about well-being, society and culture.


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