Human-Like Machine Intelligence

2021 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Leading Edge ◽  
Machine Intelligence ◽  
Funding Agency ◽  
Human Society ◽  
Third Wave ◽  
Learning Approaches ◽  
Human Beings ◽  
The Third ◽  
Algorithmic Approaches

In recent years there has been increasing excitement concerning the potential of Artificial Intelligence to transform human society. This book addresses the leading edge of research in this area. The research described aims to address present incompatibilities of Human and Machine reasoning and learning approaches. According to the influential US funding agency DARPA (originator of the Internet and Self-Driving Cars) this new area represents the Third Wave of Artificial Intelligence (3AI, 2020s–2030s), and is being actively investigated in the US, Europe and China. The EPSRC’s UK network on Human-Like Computing (HLC) was one of the first internationally to initiate and support research specifically in this area. Starting activities in 2018, the network represents around sixty leading UK groups Artificial Intelligence and Cognitive Scientists involved in the development of the inter-disciplinary area of HLC. The research of network groups aims to address key unsolved problems at the interface between Psychology and Computer Science. The chapters of this book have been authored by a mixture of these UK and other international specialists based on recent workshops and discussions at the Machine Intelligence 20 and 21 workshops (2016,2019) and the Third Wave Artificial Intelligence workshop (2019). Some of the key questions addressed by the Human-Like Computing programme include how AI systems might 1) explain their decisions effectively, 2) interact with human beings in natural language, 3) learn from small numbers of examples and 4) learn with minimal supervision. Solving such fundamental problems involves new foundational research in both the Psychology of perception and interaction as well as the development of novel algorithmic approaches in Artificial Intelligence.

Artificial intelligence, explanations, trust, responsibility, and justice

2019 ◽  
Author(s):  
Ronald M. Baecker
Keyword(s):  
Artificial Intelligence ◽  
Sigmund Freud ◽  
Machine Intelligence ◽  
Training Data ◽  
Human Beings ◽  
News Stories ◽  
The Neural Networks ◽  
Successful Approach ◽  
Smart Cars ◽  
Year 2000

There have been several challenges to our view of our position and purpose as human beings. The scientist Charles Darwin’s research demonstrated evolutionary links between man and other animals. Psychoanalysis founder Sigmund Freud illuminated the power of the subconscious. Recent advances in artificial intelligence (AI) have challenged our identity as the species with the greatest ability to think. Whether machines can now ‘think’ is no longer interesting. What is important is to critically consider the degree to which they are called upon to make decisions and act in significant and often life-critical situations. We have already discussed the increasing roles of AI in intelligent tutoring, medicine, news stories and fake news, autonomous weapons, smart cars, and automation. Chapter 11 focuses on other ways in which our lives are changing because of advances in AI, and the accompanying opportunities and risks. AI has seen a paradigm shift since the year 2000. Prior to this, the focus was on knowledge representation and the modelling of human expertise in particular domains, in order to develop expert systems that could solve problems and carry out rudimentary tasks. Now, the focus is on the neural networks capable of machine learning (ML). The most successful approach is deep learning, whereby complex hierarchical assemblies of processing elements ‘learn’ using millions of samples of training data. They can then often make correct decisions in new situations. We shall also present a radical, and for most of us a scary, concept of AI with no limits—the technological singularity or superintelligence. Even though superintelligence is for now sciencefiction, humanity is asking if there is any limit to machine intelligence. We shall therefore discuss the social and ethical consequences of widespread use of ML algorithms. It is helpful in this analysis to better understand what intelligence is, so we present two insightful formulations of the concept developed by renowned psychologists.

scholarly journals A Survey on Artificial Intelligence Overview

2020 ◽  
Author(s):  
Aggarwal AJuhi ◽  
Shailesh Kumar
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Expert System ◽  
Pattern Matching ◽  
Machine Intelligence ◽  
Human Beings ◽  
Matching Method ◽  
System P ◽  
Wide Range ◽  
Computational Relationship

Artificial Intelligence (AI) is the branch of computer science concerned with the study and creation of computer of computer system are more intelligence than human. Artificial Intelligence programmed by the human beings. We can increase the AI’s capabilities by the supervised and unsupervised teaching. Artificial Intelligence works with pattern matching method which attempts to describe objects, events or process in terms of their qualitative features, logical and computational relationship. AI can also be used to make predications in future. Artificial Intelligence helps people to make their tasks easily and efficiently. Intelligence is the way of thinking and acting upon the environment, this might depend upon the the programming. There is huge difference on the Natural Intelligence (NI), Machine Intelligence (MI) and Artificial Intelligence. There is wide range of application for that ranges from computer vision to expert system.

scholarly journals Deep Learning does not Replace Bayesian Modeling : Comparing research use via citation counting

2021 ◽  
Author(s):  
Breck Baldwin
Keyword(s):  
Artificial Intelligence ◽  
Popular Culture ◽  
Deep Learning ◽  
Computer Science ◽  
Bayesian Modeling ◽  
Citation Count ◽  
Funding Agency ◽  
Research Use ◽  
Learning Approaches ◽  
The Impact

One could be excused for assuming that deep learning had or will soon usurp all credible work in reasoning, artificial intelligence and statistics, but like most ‘meme’ class broad generalizations the concept does not hold up to scrutiny. Memes don’t generally matter since the experts will always know better but in the case of Bayesian software like Stan and PyMC3 even its developers and advocates bemoan the apparent dominance of deep learning as manifested in popular culture, breathtaking performance and most problematically from funding agency peer review that impacts our ability to further advance the field. The facts however do not support the assumed dominance of deep learning in science upon closer examination. This letter simply makes the argument by the crudest of possible metrics, citation count, that once Computer Science is subtracted, Bayesian software accounts for nearly a third of research citations. Stan and PyMC3 dominate some fields, PyTorch, Keras and TensorFlow dominate others with lots of variation in between. Bayesian and deep learning approaches are related but very different technologies in goals, implementation and applicability with little actual overlap so this is not a surprise. While deep learning is backed by industry behemoths (Google, Facebook) the Bayesian efforts are not and it would behoove funders to recognize the impact of Bayesian software given its centrality to science.

scholarly journals The Impact of Intelligent Society on Human Essence and the New Evolution of Humans

Proceedings ◽  
2020 ◽  
Vol 47 (1) ◽  
pp. 44
Author(s):  
Kun Wu ◽  
Kaiyan Da
Keyword(s):  
Karl Marx ◽  
Biological Evolution ◽  
Machine Intelligence ◽  
Human Society ◽  
Human Beings ◽  
Human Essence ◽  
Comprehensive Development ◽  
Life Itself ◽  
Traditional Sense ◽  
The Impact

When we enter intelligent society, we need to rethink about the topic of human essence. As we know, human beings have no absolute, fixed essence. The essence of human beings is the combination of an innate substrate and acquired creation. As the degree of machine intelligence in the development of human society continues to increase, human beings are constantly changing and creating their own essence, and they are also constantly liberated from the bondage of a certain single old essence, creating and enriching the richer and more diverse aspects of its essence. The transformation of labor from its alienation to its return is also a transformation of labor from the centralized form to the non-centralized form of human essence according to Karl Marx. The new fusion of artificial intelligence and bioengineering will lead to a new track of evolution that “reshapes and regenerates” life itself. This new evolutionary path will fuse the two-track evolution, biological evolution and cultural evolution, which have been relatively isolated in the traditional sense. If human beings are able to work hard together to design and implement a new social system that adapts to the future intelligent development, then the comprehensive development of intelligence that human beings bring about would be not a disaster, but a bright future.

scholarly journals Comparative analysis of HAR datasets using classification algorithms

2021 ◽  
pp. 43-43
Author(s):  
Suvra Nayak ◽  
Chhabi Panigrahi ◽  
Bibudhendu Pati ◽  
Sarmistha Nanda ◽  
Meng-Yen Hsieh
Keyword(s):  
Comparative Analysis ◽  
Assisted Living ◽  
Absolute Error ◽  
Vital Role ◽  
Living Condition ◽  
Classification Algorithms ◽  
Kappa Statistics ◽  
Human Society ◽  
Learning Approaches ◽  
Human Beings

In the current research and development era, Human Activity Recognition (HAR) plays a vital role in analyzing the movements and activities of a human being. The main objective of HAR is to infer the current behaviour by extracting previous information. Now-a-days, the continuous improvement of living condition of human beings changes human society dramatically. To detect the activities of human beings, various devices, such as smartphones and smart watches, use different types of sensors, such as multi modal sensors, non-video based and video-based sensors, and so on. Among the entire machine learning approaches, tasks in different applications adopt extensively classification techniques, in terms of smart homes by active and assisted living, healthcare, security and surveillance, making decisions, tele-immersion, forecasting weather, official tasks, and prediction of risk analysis in society. In this paper, we perform three classification algorithms, Sequential Minimal Optimization (SMO), Random Forest (RF), and Simple Logistic (SL) with the two HAR datasets, UCI HAR and WISDM, downloaded from the UCI repository. The experiment described in this paper uses the WEKA tool to evaluate performance with the matrices, Kappa statistics, relative absolute error, mean absolute error, ROC Area, and PRC Area by 10-fold cross validation technique. We also provide a comparative analysis of the classification algorithms with the two determined datasets by calculating the accuracy with precision, recall, and F-measure metrics. In the experimental results, all the three algorithms with the UCI HAR datasets achieve nearly the same accuracy of 98%.The RF algorithm with the WISDM dataset has the accuracy of 90.69%,better than the others.

scholarly journals Human health care against COVID-19 via environmental management

2022 ◽  
Author(s):  
Biswaranjan Paital
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Medical Care ◽  
Human Life ◽  
Particulate Matters ◽  
Third Wave ◽  
Human Beings ◽  
Angiotensin Converting Enzyme 2 ◽  
The Third ◽  
Antibiotic Drugs ◽  
Preventive Methods

Although vaccines are successfully developed against Severe Acute Respiratory Syndrome Coronavirus-19 (COVID-19), and many anticancer, anti-malarial, antibiotic drugs have been repurposed against the disease, it has been just impossible to save valuable human lives in specific conditions. Therefore, medical care has been developed against COVID-19 but not fully able to save human life from the disease. As a result, the third wave is noticed in many countries. Preventive methods such as social distancing, wearing masks, and hand salinization have been accepted as the main strategies to break the chain of the disease. Due to the reduction in pollution under less or no industrial and vehicular operations, water and air ecosystems have been restored in an unseen manner. Especially, NO<sub>2</sub>, SO<sub>2</sub> and particulate matters etc. modulated higher expression of angiotensin-converting enzyme 2, the receptor of Severe Acute Respiratory Syndrome Coronavirus -2 in humans have also been emphatically documented. Therefore, along with medical care, environmental protection (especially to regulate NO<sub>2</sub> emissions) along with practicing COVID-19 guidelines is to be maintained fully to combat COVID-19 the disease. Human beings must use this knowledge and experience as a spotlight to save nature in current and future times.

Mind and Machine

Mind Shift ◽  
2021 ◽  
pp. 396-410
Author(s):  
John Parrington
Keyword(s):  
Artificial Intelligence ◽  
Human Brain ◽  
Genomic Analysis ◽  
Human Mind ◽  
Machine Intelligence ◽  
Human Consciousness ◽  
Human Beings ◽  
New Techniques ◽  
The World ◽  
Future Technologies

This chapter explores how future technologies might impact on human consciousness. It begins by discussing how new techniques are continuing to add to the understanding of the human mind. There are many exciting technologies available now to the neuroscientist, such as genomic analysis, optogenetics, gene editing, and brain organoids. To what extent could such technologies be used to investigate the model of human consciousness outlined in this book? The chapter then considers whether artificial intelligence might come to rival that of human beings, and possible interfaces between human and machine intelligence. Our growing ability to develop functioning robots raises the question of whether an artificial human brain might be used to control such a robot, creating in effect a cyborg. However, the creation of such an entity could make a big difference in terms of an artificial brain’s sense of identity in the world, as well as its rights.

scholarly journals Between Life and Non-Life: Sachiko Kodama’s Black and Bridget Riley’s Pink

2019 ◽  
pp. 109
Author(s):  
Yukiko Kato
Keyword(s):  
Artificial Intelligence ◽  
Media Studies ◽  
Visual Arts ◽  
Cutting Edge ◽  
Consumer Society ◽  
Human Society ◽  
Contemporary Society ◽  
Human Beings ◽  
Contemporary World

The contemporary world is so technological that humans are located on the verge of life and non-life. Computers, cyborgs, artificial intelligence, and androids permeate human society, and people are even fascinated by such menaces of the non-life. This paper clarifies why contemporary society loves the idea of the rise of artificial beings by analyzing the use of artificial colors – black and pink – by the cutting-edge female artists Sachiko Kodama and Bridget Riley.Media artist Kodama uses black liquid while the abstract artist Riley uses pink pigments as key materials. According to Asao Komachiya, black is the color of the blind; it appears on the verge of being and non-being. Meanwhile, Barbara Nemitz identifies pink as an artificial color that does not exist in the spectrum of sunlight. Both colors are highly evaluated in technological and consumer society and widely used on many goods. Kodama’s and Riley’s high reputation signifies that contemporary society likes the precarious artificial beings between life and non-life. Moreover, their original and unique works have realized the field of liberty as their extensive use of artificial colors black and pink indicates ultra-human.Kodama’s and Riley’s gender is also key. As Dora Haraway suggests in “Cyborg Manifesto” (1991), contemporary women, historically dealt with as peripheral existences, survive as ultra-human beings rather than the ancient goddesses. By considering significant female artists such as Kodama and Riley, we can understand not only the contemporary aesthetics of visual arts, but also the concurrent yearning of contemporary society for liberty, ultra-humanity, and non-life. Article received: April 17, 2019; Article accepted: June 23, 2019; Published online: September 15, 2019: Review articleHow to cite this article: Kato, Yukiko. "Between Life and Non-Life: Sachiko Kodama’s Black and Bridget Riley’s Pink." AM Journal of Art and Media Studies 19 (2019): 109-115. doi: 10.25038/am.v0i19.311

scholarly journals The Impact of Intelligent Society on Human Essence and the New Evolution of Humans

Proceedings ◽  
2020 ◽  
Vol 47 (1) ◽  
pp. 44
Author(s):  
Kun Wu ◽  
Kaiyan Da
Keyword(s):  
Karl Marx ◽  
Biological Evolution ◽  
Machine Intelligence ◽  
Human Society ◽  
Human Beings ◽  
Human Essence ◽  
Comprehensive Development ◽  
Life Itself ◽  
Traditional Sense ◽  
The Impact

When we enter intelligent society, we need to rethink about the topic of human essence. As we know, human beings have no absolute, fixed essence. The essence of human beings is the combination of an innate substrate and acquired creation. As the degree of machine intelligence in the development of human society continues to increase, human beings are constantly changing and creating their own essence, and they are also constantly liberated from the bondage of a certain single old essence, creating and enriching the richer and more diverse aspects of its essence. The transformation of labor from its alienation to its return is also a transformation of labor from the centralized form to the non-centralized form of human essence according to Karl Marx. The new fusion of artificial intelligence and bioengineering will lead to a new track of evolution that “reshapes and regenerates” life itself. This new evolutionary path will fuse the two-track evolution, biological evolution and cultural evolution, which have been relatively isolated in the traditional sense. If human beings are able to work hard together to design and implement a new social system that adapts to the future intelligent development, then the comprehensive development of intelligence that human beings bring about would be not a disaster, but a bright future.

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