scholarly journals The influence of algorithms on political and dating decisions

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249454
Author(s):  
Ujué Agudo ◽  
Helena Matute
Keyword(s):  
Artificial Intelligence ◽  
Daily Life ◽  
Personal Freedom ◽  
Decision Context ◽  
Institutional Initiatives

Artificial intelligence algorithms are ubiquitous in daily life, and this is motivating the development of some institutional initiatives to ensure trustworthiness in Artificial Intelligence (AI). However, there is not enough research on how these algorithms can influence people’s decisions and attitudes. The present research examines whether algorithms can persuade people, explicitly or covertly, on whom to vote and date, or whether, by contrast, people would reject their influence in an attempt to confirm their personal freedom and independence. In four experiments, we found that persuasion was possible and that different styles of persuasion (e.g., explicit, covert) were more effective depending on the decision context (e.g., political and dating). We conclude that it is important to educate people against trusting and following the advice of algorithms blindly. A discussion on who owns and can use the data that makes these algorithms work efficiently is also necessary.

Automating intellectual freedom: Artificial intelligence, bias, and the information landscape

IFLA Journal ◽  
2021 ◽  
pp. 034003522110571
Author(s):  
Catherine Smith
Keyword(s):  
Artificial Intelligence ◽  
Intellectual Freedom ◽  
Digital Information ◽  
Personal Freedom ◽  
Library Users ◽  
Human Operators ◽  
Information Landscape ◽  
Resource Description

Anxieties over automation and personal freedom are challenging libraries’ role as havens of intellectual freedom. The introduction of artificial intelligence into the resource description process creates an opportunity to reshape the digital information landscape—and loss of trust by library users. Resource description necessarily manipulates a library’s presentation of information, which influences the ways users perceive and interact with that information. Human catalogers inevitably introduce personal and cultural biases into their work, but artificial intelligence may perpetrate biases on a previously unseen scale. The automation of this process may be perceived as a greater threat than the manipulation produced by human operators. Librarians must understand the risks of artificial intelligence and consider what oversight and countermeasures are necessary to mitigate the harm to libraries and their users before ceding resource description to artificial intelligence in place of the “professional considerations” the IFLA Statement on Libraries and Intellectual Freedom calls for in providing access to library materials.

Taming Artificial Intelligence in Psychiatry and Pain Medicine

2020 ◽  
pp. 399-412
Author(s):  
Usef Faghihi ◽  
Sioui Maldonado-Bouchard ◽  
Mario Incayawar
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Health Care ◽  
Deep Learning ◽  
State Of The Art ◽  
Daily Life ◽  
Health Care Sector ◽  
Human Cells ◽  
Pain Medicine ◽  
Medical Field

Today, deep learning (DL) algorithms are intertwined with our daily life. This subdomain of artificial intelligence (AI) technology is used to unlock your phone by only detecting your face, find the best path from work to your home or vice versa, or detect anomalies in the human cells taken for lab tests. Yet, although AI technology is helping in many fields, whether it has done so in the medical field is debatable. DL lacks reasoning; it is unable to determine the causes of events. This is especially crucial when it comes to the health care sector. At this point, computers cannot help physicians with their duties. On the contrary, they are the cause of burnout in more than half of physicians in United States. One of the causes of burnout repeatedly pointed out by physicians is the digitalization of medicine. This chapter presents some of the AI approaches that could help physicians. It also discusses the current limitations and dangers inherent to many of today’s state-of-the-art AI systems. The authors provide some ideas about the future of AI in pain medicine and psychiatry.

Uber and the making of an Algopticon - Insights from the daily life of Montreal drivers

2020 ◽  
Vol 44 (2) ◽  
pp. 241-260
Author(s):  
Rabih Jamil
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Daily Life ◽  
The World ◽  
Taxi Industry ◽  
Platform Economy

Using machine learning and artificial intelligence, Uber has been disrupting the world taxi industry. However, the Uber algorithmic apparatus managed to perfectionize the scalable decentralized tracking and surveillance of mobile living bodies. This article examines the Uber surveillance machinery and discusses the determinants of its algorithmically powered ‘all-seeing power’. The latter is being figured as an Algopticon that reinvents Bentham’s panopticon in the era of the platform economy.

scholarly journals Application and Development of Computer Artificial Intelligence Technology

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Yu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Science Fiction ◽  
Daily Life ◽  
Science And Technology ◽  
Modern Society ◽  
Internet Technology ◽  
Tertiary Industry ◽  
The People ◽  
Artificial Intelligence Technology ◽  
Applied Artificial Intelligence

In the development of modern society, Internet technology has been popularized and applied. Artificial intelligence technology is not only found in science fiction movies, but has been widely used in industry, tertiary industry and people’s livelihood. Under the background of rapid advancement of science and technology, computer artificial intelligence technology will play an important role in the future. Due to a series of problems in the development of computer artificial intelligence technology, it is necessary for relevant personnel to strengthen research on the application and development of computer artificial intelligence technology. The paper mainly studies the application and development of computer artificial intelligence technology, and hopes to bring more convenience to the daily life of the people.

scholarly journals Mākslīgais intelekts un nākotnes regulējuma dilemma

2021 ◽  
pp. 174-182
Author(s):  
Ritvars Purmalis ◽  
Keyword(s):  
Artificial Intelligence ◽  
European Union ◽  
Daily Life ◽  
Civil Liability ◽  
Industrial Sector ◽  
The European Union ◽  
Further Development ◽  
Insight Into ◽  
Artificial Intelligence Systems ◽  
Operational Capacity

Digital innovations such as artificial intelligence systems, although limited in their current operational capacity, can be considered to be part of our daily life. Various ways in which these systems are implemented into day-to-day aspects directly affect not only the further development of the industrial sector but the society as a whole. The purpose of this article is to provide a brief insight into the current situation and the various initiatives of the European Union institutions in relation to the methodology for the application of civil liability in the case of damage caused by artificial intelligence systems, as well as to assess the content of future regulatory framework that has been published by the European Parliament, with whom it is intended to establish a common methodology throughout the European Union for the application of civil liability regime, if the damage is caused by artificial intelligence systems.

scholarly journals Governance, Risk, and Artificial Intelligence

AI Magazine ◽  
2020 ◽  
Vol 41 (1) ◽  
pp. 61-69
Author(s):  
Aaron Mannes
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Intelligent Agents ◽  
Soft Power ◽  
Daily Life ◽  
Physical Injury ◽  
Financial Loss ◽  
The Public ◽  
Hard Power ◽  
Governance Risk

Artificial intelligence, whether embodied as robots or Internet of Things, or disembodied as intelligent agents or decision-support systems, can enrich the human experience. It will also fail and cause harms, including physical injury and financial loss as well as more subtle harms such as instantiating human bias or undermining individual dignity. These failures could have a disproportionate impact because strange, new, and unpredictable dangers may lead to public discomfort and rejection of artificial intelligence. Two possible approaches to mitigating these risks are the hard power of regulating artificial intelligence, to ensure it is safe, and the soft power of risk communication, which engages the public and builds trust. These approaches are complementary and both should be implemented as artificial intelligence becomes increasingly prevalent in daily life.

scholarly journals Sentiment Perception in Articulation

2021 ◽  
Vol 9 (VII) ◽  
pp. 2803-2812
Author(s):  
Ganesh NagaVenkataSai Mohan Kancherla
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neural Networks ◽  
Daily Life ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Multi Layer Perceptron ◽  
Working Model ◽  
Initial Stage ◽  
Perception System

Emotion is quite prevalent aspect in daily life. Every individual has a inequity levels of anxiety in the finding the concealed emotion present in a speech or talk. So we had decided to procreate a new methodology in which every emotion which is present in a speech can be detected. The system we developed can detect any emotion with a great extent of efficiency. Any type of emotion will be detected using Machine learning algorithms in a effective way. We will utilize Multi-Layer Perceptron in the initial stage and then we will compare this with working model of Convolution Neural Networks. We want to develop an Artificial Intelligence perception system which leads to detection of emotion in any articulation

scholarly journals Data Mining, Machine Learning, Deep Learning, Chemometrics. Definitions, common points and Trends (Spoiler Alert: VALIDATE your models!)

2021 ◽  
Vol 8 (32) ◽  
pp. 22-38
Author(s):  
José Manuel Amigo
Keyword(s):  
Analytical Chemistry ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Mining ◽  
Deep Learning ◽  
Daily Life ◽  
Big Data Analysis ◽  
Mining Machine ◽  
Learning Data ◽  
Made In

Concepts like Machine Learning, Data Mining or Artificial Intelligence have become part of our daily life. This is mostly due to the incredible advances made in computation (hardware and software), the increasing capabilities of generating and storing all types of data and, especially, the benefits (societal and economical) that generate the analysis of such data. Simultaneously, Chemometrics has played an important role since the late 1970s, analyzing data within natural science (and especially in Analytical Chemistry). Even with the strong parallelisms between all of the abovementioned terms and being popular with most of us, it is still difficult to clearly define or differentiate the meaning of Machine Learning, Data Mining, Artificial Intelligence, Deep Learning and Chemometrics. This manuscript brings some light to the definitions of Machine Learning, Data Mining, Artificial Intelligence and Big Data Analysis, defines their application ranges and seeks an application space within the field of analytical chemistry (a.k.a. Chemometrics). The manuscript is full of personal, sometimes probably subjective, opinions and statements. Therefore, all opinions here are open for constructive discussion with the only purpose of Learning (like the Machines do nowadays).

The Analysis of Smart Car Guided by Electromagnetism

2013 ◽  
Vol 380-384 ◽  
pp. 508-511
Author(s):  
Wen Zhuo Li
Keyword(s):  
Artificial Intelligence ◽  
Electromagnetic Field ◽  
Daily Life ◽  
Power Source ◽  
Control Methods ◽  
Artificial Intelligence Techniques ◽  
The Road ◽  
Electromagnetic Sensor ◽  
Smart Cars ◽  
And Control

Nowadays, since there are many artificial intelligence techniques introduced into our daily life, which brings us much convenience, its a real hope that our transportation can be improved by artificial intelligence. In this article, a smart car with the detecting and following ability is introduced. The whole system is composed of the road track signal device; the electromagnetic sensor; the power source manage device; the engine drive device and the parking position detecting device. By using the PID, Bang-Bang and fuzz control methods, the smart car can collect the signal automatically and control the car moving effectively. When there are specially designed roads with electromagnetic field, our smart cars can automatically drive themselves.

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