scholarly journals Statistically responsible artificial intelligences

2021 ◽  
Author(s):  
Nicholas Smith ◽  
Darby Vickers
Keyword(s):  
Artificial Intelligence ◽  
Moral Responsibility ◽  
Reactive Attitudes ◽  
Machine Ethics ◽  
Standard Account ◽  
Strong Ai ◽  
The Right

AbstractAs artificial intelligence (AI) becomes ubiquitous, it will be increasingly involved in novel, morally significant situations. Thus, understanding what it means for a machine to be morally responsible is important for machine ethics. Any method for ascribing moral responsibility to AI must be intelligible and intuitive to the humans who interact with it. We argue that the appropriate approach is to determine how AIs might fare on a standard account of human moral responsibility: a Strawsonian account. We make no claim that our Strawsonian approach is either the only one worthy of consideration or the obviously correct approach, but we think it is preferable to trying to marry fundamentally different ideas of moral responsibility (i.e. one for AI, one for humans) into a single cohesive account. Under a Strawsonian framework, people are morally responsible when they are appropriately subject to a particular set of attitudes—reactive attitudes—and determine under what conditions it might be appropriate to subject machines to this same set of attitudes. Although the Strawsonian account traditionally applies to individual humans, it is plausible that entities that are not individual humans but possess these attitudes are candidates for moral responsibility under a Strawsonian framework. We conclude that weak AI is never morally responsible, while a strong AI with the right emotional capacities may be morally responsible.

Introduction

2018 ◽  
Author(s):  
Christopher Evan Franklin
Keyword(s):  
Moral Responsibility ◽  
Free Will ◽  
Human Agency ◽  
Causal Role ◽  
Central Question ◽  
Agent Causation ◽  
The Right

This chapter lays out the book’s central question: Assuming agency reductionism—that is, the thesis that the causal role of the agent in all agential activities is reducible to the causal role of states and events involving the agent—is it possible to construct a defensible model of libertarianism? It is explained that most think the answer is negative and this is because they think libertarians must embrace some form of agent-causation in order to address the problems of luck and enhanced control. The thesis of the book is that these philosophers are mistaken: it is possible to construct a libertarian model of free will and moral responsibility within an agency reductionist framework that silences that central objections to libertarianism by simply taking the best compatibilist model of freedom and adding indeterminism in the right junctures of human agency. A brief summary of the chapters to follow is given.

Reactive Attitudes Revisited: A Modest Revision

2018 ◽  
Author(s):  
John Deigh
Keyword(s):  
Moral Responsibility ◽  
Free Will ◽  
Reactive Attitudes

The essay offers an interpretation of P. F. Strawson’s “Freedom and Resentment” on which attributions of moral responsibility presuppose a practice of holding people morally responsible for their actions, and what explains the practice is our liability to such reactive attitudes as resentment and indignation. The interpretation is offered to correct a common misinterpretation of Strawson’s essay. On this common misinterpretation, attributions of moral responsibility are implicit in the reactive attitudes of resentment and indignation, and consequently our liability to these attitudes cannot explain these attributions. The reason this is a misinterpretation of Strawson’s essay is that Strawson’s compatibilist solution to the free will problem requires that our liability to the reactive attitudes be conceptually prior to our attributions of moral responsibility.

Something Old, Something New, Something Borrowed, Something Blue: Part 3 – An Elephant Never Forgets

2017 ◽  
Vol 26 (3) ◽  
pp. 433-437
Author(s):  
Mark Dougherty
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Natural Systems ◽  
European Court ◽  
New Knowledge ◽  
The Right ◽  
Contextual Environment ◽  
The Brain ◽  
Index Services ◽  
Incomplete Picture

AbstractForgetting is an oft-forgotten art. Many artificial intelligence (AI) systems deliver good performance when first implemented; however, as the contextual environment changes, they become out of date and their performance degrades. Learning new knowledge is part of the solution, but forgetting outdated facts and information is a vital part of the process of renewal. However, forgetting proves to be a surprisingly difficult concept to either understand or implement. Much of AI is based on analogies with natural systems, and although all of us have plenty of experiences with having forgotten something, as yet we have only an incomplete picture of how this process occurs in the brain. A recent judgment by the European Court concerns the “right to be forgotten” by web index services such as Google. This has made debate and research into the concept of forgetting very urgent. Given the rapid growth in requests for pages to be forgotten, it is clear that the process will have to be automated and that intelligent systems of forgetting are required in order to meet this challenge.

scholarly journals Radiological CT findings and time evolution in acute stroke: case report

2021 ◽  
Vol 8 (2) ◽  
pp. 76-79
Author(s):  
Laio Bastos de Paiva Raspante ◽  
Laura Filgueiras Mourão Ramos ◽  
Uedson Tazinaffo
Keyword(s):  
Artificial Intelligence ◽  
Case Report ◽  
Emergency Room ◽  
Acute Stroke ◽  
Cerebral Perfusion ◽  
Imaging Finding ◽  
Clinical Suspicion ◽  
Perfusion Study ◽  
The Right ◽  
Optimized Treatment

Case report of a 95-year-old female patient that was admitted to the emergency room with a sudden weakness on the right who underwent propaedeutic imaging with cerebral perfusion study by CT using artificial intelligence (AI) software for clinical suspicion of acute stroke. The case illustrates a frequent and specific imaging finding for stroke and its disappearance in the control exam even without optimized treatment.

scholarly journals Are Artificial Intelligence (AI) And Machine Learning (ML) Having An Effective Role In Helping Humanity Address The New Coronavirus Pandemic?

2020 ◽  
Vol 17 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Disease Outbreaks ◽  
Hospital Capacity ◽  
Data Engineering ◽  
Clinical Presentations ◽  
The Face ◽  
Effective Role ◽  
Using Data ◽  
The Right

COVID-19 has become a pandemic affecting the most of countries in the world. One of the most difficult decisions doctors face during the Covid-19 epidemic is determining which patients will stay in hospital, and which are safe to recover at home. In the face of overcrowded hospital capacity and an entirely new disease with little data-based evidence for diagnosis and treatment, the old rules for determining which patients should be admitted have proven ineffective. But machine learning can help make the right decision early, save lives and lower healthcare costs. So, there is therefore an urgent and imperative need to collect data describing clinical presentations, risks, epidemiology and outcomes. On the other side, artificial intelligence(AI) and machine learning(ML) are considered a strong firewall against outbreaks of diseases and epidemics due to its ability to quickly detect, examine and diagnose these diseases and epidemics.AI is being used as a tool to support the fight against the epidemic that swept the entire world since the beginning of 2020.. This paper presents the potential for using data engineering, ML and AI to confront the Coronavirus, predict the evolution of disease outbreaks, and conduct research in order to develop a vaccine or effective treatment that protects humanity from these deadly diseases.

scholarly journals Perspectiva constitucional de las garantías de aplicación de la Inteligencia Artificial: la ineludible protección de los derechos fundamentales.

2020 ◽  
Vol 6 (2) ◽  
pp. 72-82
Author(s):  
Jorge Castellanos Claramunt ◽  
María Dolores Montero Caro
Keyword(s):  
Artificial Intelligence ◽  
Point Of View ◽  
Fundamental Rights ◽  
Judicial Decisions ◽  
Spanish Constitution ◽  
The Right ◽  
Judicial Protection

Artificial Intelligence has an undeniable effect on today’s society, so its study regarding its legal effects becomes necessary. And consequently, how fundamental rights are affected is of particular importance. Hence, the present paper studies the influence of algorithms in determining judicial decisions, especially from the point of view of how this issue would affect the right to effective judicial protection, recognized as a fundamental right in article 24 of the Spanish Constitution.

The Rise of Artificial Intelligence

2020 ◽  
pp. 1298-1313
Author(s):  
Robert Niewiadomski ◽  
Dennis Anderson
Keyword(s):  
Artificial Intelligence ◽  
Labor Market ◽  
Exponential Growth ◽  
Cognitive Abilities ◽  
Full Range ◽  
Rapid Expansion ◽  
Employment Opportunities ◽  
Strong Ai ◽  
Long Run ◽  
The Impact

Our inventions defined the work we engaged in for centuries; created new industries and employment opportunities around them. They, however, had often unforeseen consequences that affected the way we lived, interacted with each other, and redefined our societal rules. The established narration portrays the impact of major technological leaps in civilization on employment as temporary disruptions: Many finds themselves without employment taken away from them by efficient, laborsaving inventions, but, in the long run, through gradual adaptations, improved education and gaining higher qualifications, everyone benefits. In this chapter, the authors explore the impact of the rapid expansion of artificial intelligence (AI) in relations to the labor market. The authors argue that this rather optimistic, even naïve scenario, collapses while confronted with the exponential growth of AI; in particular, with the potential arrival of syneoids – robotic forms of “strong AI” possessing, or even exceeding, the full range of human cognitive abilities.

Decision Support Software

2009 ◽  
pp. 440-447
Author(s):  
John Wang ◽  
Huanyu Ouyang ◽  
Chandana Chakraborty
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Mathematical Logic ◽  
Decision Support ◽  
Support Systems ◽  
Scientific Methods ◽  
Simulation And Optimization ◽  
Business Software ◽  
The Right ◽  
Support Software

Throughout the years many have argued about different definitions for DSS; however they have all agreed that in order to succeed in the decision-making process, companies or individuals need to choose the right software that best fits their requirements and demands. The beginning of business software extends back to the early 1950s. Since the early 1970s, the decision support technologies became the most popular and they evolved most rapidly (Shim, Warkentin, Courtney, Power, Sharda, & Carlsson, 2002). With the existence of decision support systems came the creation of decision support software (DSS). Scientists and computer programmers applied analytical and scientific methods for the development of more sophisticated DSS. They used mathematical models and algorithms from such fields of study as artificial intelligence, mathematical simulation and optimization, and concepts of mathematical logic, and so forth.

Marketing and Artificial Intelligence

2021 ◽  
pp. 75-95
Author(s):  
Sujata Ramnarayan
Keyword(s):  
Artificial Intelligence ◽  
Customer Experience ◽  
Amount Of Information ◽  
Making Sense ◽  
Value Add ◽  
The Right

Technologies are changing marketing due to the amount of information available to consumers, along with information being generated by consumers. Marketers face a challenge with greater volume and variety of data generated at a faster rate than ever before along with fragmentation of channels. This data when combined with artificial intelligence presents an opportunity to marketers to provide value add at a granular level and a personalized customer experience round the clock 24/7/365. Treating customers as individuals by offering an optimized personalized offering, sending the right personalized message at the right time through their preferred channel is the promise of data fed into AI algorithms. Artificial intelligence has the potential to transform companies by making sense out of an insanely voluminous variety of data being generated with its ability to serve customers more effectively and efficiently, personalizing at scale.

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