Artificial Consciousness Research Articles

GODS OF TRANSHUMANISM

Purpose of the article is to identify the religious factor in the teaching of transhumanism, to determine its role in the ideology of this flow of thought and to identify the possible limits of technology interference in human nature. Theoretical basis. The methodological basis of the article is the idea of transhumanism. Originality. In the foreseeable future, robots will be able to pass the Turing test, become "electronic personalities" and gain political rights, although the question of the possibility of machine consciousness and self-awareness remains open. In the face of robots, people create their assistants, evolutionary competition with which they will almost certainly lose with the initial data. For successful competition with robots, people will have to change, ceasing to be people in the classical sense. Changing the nature of man will require the emergence of a new – posthuman – anthropology. Conclusions. Against the background of scientific discoveries, technical breakthroughs and everyday improvements of the last decades, an anthropological revolution has taken shape, which made it possible to set the task of creating inhumanly intelligent creatures, as well as changing human nature, up to discussing options for artificial immortality. The history of man ends and the history of the posthuman begins. We can no longer turn off this path, however, in our power to preserve our human qualities in the posthuman future. The theme of the soul again reminded of itself, but from a different perspective – as the theme of consciousness and self-awareness. It became again relevant in connection with the development of computer and cloud technologies, artificial intelligence technologies, etc. If a machine ever becomes a "man", then can a man become a "machine"? However, even if such a hypothetical probability would turn into reality, we cannot talk about any form of individual immortality or about the continuation of existence in a different physical form. A digital copy of the soul will still remain a copy, and I see no fundamental possibility of isolating a substrate-independent mind from the human body. Immortality itself is necessary not so much for stopping someone’s fears or encouraging someone’s hopes, but for the final solution of a religious issue. However, the gods hold the keys to heaven hard and are unlikely to admit our modified descendants there.

On the problem of creating robotic systems with artificial consciousness and acting personality

On the problem of creating robotic systems with artificial consciousness and acting personality

The spatially conscious machine learning model

AbstractSuccessfully predicting gentrification could have many social and commercial applications; however, real estate sales are difficult to predict because they belong to a chaotic system comprised of intrinsic and extrinsic characteristics, perceived value, and market speculation. Using New York City real estate as our subject, we combine modern techniques of data science and machine learning with traditional spatial analysis to create robust real estate prediction models for both classification and regression tasks. We compare several cutting edge machine learning algorithms across spatial, semispatial, and nonspatial feature engineering techniques, and we empirically show that spatially conscious machine learning models outperform nonspatial models when married with advanced prediction techniques such as Random Forests, generalized linear models, gradient boosting machines, and artificial neural networks.

Theoretical Framework of Artificial Consciousness

Abstract Human consciousness is our most perplexing quality, still, an adequate description of it’s workings have not yet appeared. One of the most promising ways to solve this issue is to model consciousness with artificial intelligence (AI). This paper makes an attempt to do that on a theoretical level with the methods of philosophy. First I will review the relevant papers concerning human consciousness. Then considering the state of the art of AI, I will arrive at a model of artificial consciousness.

Information Flow Theory (IFT): A General Theory of Biologic and Artificial Consciousness

Strategies exploring the top-down mechanisms of conscious thought within the human brain have been unable to produce a generalized explanatory theory that scales through evolution and can be applied to non-human systems. Information Flow Theory (IFT) provides a novel framework for understanding both the development and nature of consciousness in any system capable of processing information. In prioritizing the direction of information flow over information computation, IFT explains how basic evolutionary processes produce the perception of consciousness and offers multiple experimental avenues to confirm its validity. The neural correlates of the information circuits predicted by IFT exist in humans and are theoretically identifiable in non-human biologic nervous systems. Perhaps most importantly, IFT disentangles artificial intelligence from artificial consciousness and predicts a specific architecture which may be used to create consciousness within neural networks.

Indicators and Criteria of Consciousness in Animals and Intelligent Machines: An Inside-Out Approach.

In today’s society, it becomes increasingly important to assess which non-human and non-verbal beings possess consciousness. This review article aims to delineate criteria for consciousness especially in animals, while also taking into account intelligent artifacts. First, we circumscribe what we mean with “consciousness” and describe key features of subjective experience: qualitative richness, situatedness, intentionality and interpretation, integration and the combination of dynamic and stabilizing properties. We argue that consciousness has a biological function, which is to present the subject with a multimodal, situational survey of the surrounding world and body, subserving complex decision-making and goal-directed behavior. This survey reflects the brain’s capacity for internal modeling of external events underlying changes in sensory state. Next, we follow an inside-out approach: how can the features of conscious experience, correlating to mechanisms inside the brain, be logically coupled to externally observable (“outside”) properties? Instead of proposing criteria that would each define a “hard” threshold for consciousness, we outline six indicators: (i) goal-directed behavior and model-based learning; (ii) anatomic and physiological substrates for generating integrative multimodal representations; (iii) psychometrics and meta-cognition; (iv) episodic memory; (v) susceptibility to illusions and multistable perception; and (vi) specific visuospatial behaviors. Rather than emphasizing a particular indicator as being decisive, we propose that the consistency amongst these indicators can serve to assess consciousness in particular species. The integration of scores on the various indicators yields an overall, graded criterion for consciousness, somewhat comparable to the Glasgow Coma Scale for unresponsive patients. When considering theoretically derived measures of consciousness, it is argued that their validity should not be assessed on the basis of a single quantifiable measure, but requires cross-examination across multiple pieces of evidence, including the indicators proposed here. Current intelligent machines, including deep learning neural networks (DLNNs) and agile robots, are not indicated to be conscious yet. Instead of assessing machine consciousness by a brief Turing-type of test, evidence for it may gradually accumulate when we study machines ethologically and across time, considering multiple behaviors that require flexibility, improvisation, spontaneous problem-solving and the situational conspectus typically associated with conscious experience.

Discovering Humanoid Robot Consciousness Within Caring Science

Why would humanoid caring robots (HCRs) need consciousness? Because HCRs need to be gentle like human beings. In addition, HCRs need to be trusted by their patients, and have a shared understanding of patients' life experiences, their illnesses, and their treatments. HCRs need to express “competency as caring” to naturally convey their nursing as healing to patients and their families. HCRs should also have self-consciousness and express their emotions without needing inducement by persons' behaviors. Artificial “brains” and artificial consciousness are therefore necessary for HCRs. The purpose of this article was to explore humanoid consciousness and the possibilities of a technologically enhanced future with HCRs as participants in the care of human persons.

On the Ethics of Algorithmic Intelligence

On the Ethics of Algorithmic Intelligence Roberto Simanowski (bio) Translated by Michel Brodmer and Jefferson Chase "perhaps the new intelligence will worship its creators, perhaps it will keep us as pets, or perhaps it will erase us. We simply don't know. What is certain is that if my arguments are correct we will lose control over evolution" (Gumbrecht 2018, 227). Those are the words of 21-yearold Sam Ginn, a student of computer science and comparative literature at Stanford University, who has set himself the task of inventing an artificial consciousness that understands its own existence in the world. His rather pessimistic assertion about what might result if he succeeds is contained in Weltgeist im Silicon Valley, a book by Hans Ulrich Gumbrecht, a professor of comparative literature at Stanford. The Weltgeist, or world-spirit, that Georg Wilhelm Friedrich Hegel saw embodied in 1806 by Napoleon riding through the university town of Jena, after defeating German troops, lives on 200 years later in California. The geopolitical transition from Central Europe to the American West Coast is simultaneously a change from the political to the scientific. The future no longer rests with politics or even the philosophy of Plato's Republic. It rests with science, as in Francis Bacon's Nova Atlantis, or more precisely, with computer science. We no longer have people like Napoleon revolutionizing their times with military campaigns or a Code civil. Instead it's people like Sundar Pichai and Mark Zuckerberg who, every day, with every new piece of data, increasingly determine the future we're rushing toward. Politicians are completely satisfied with this transition of power. If in times of post-political consensus all that matters is the administration of the established order, what they expect from progress [End Page 423] is above all more effective forms of such administration. It is thus hardly surprising that those in power embrace the digital revolution, or at least refrain from expressing any doubts or passing any laws when business demands that everything be bet "on a single card, the digital one"—as the president of Bitkom, Germany's Association for IT, Telecommunications, and New Media, said in the summer of 2017. The business-friendly Free Democratic Party (FDP) even campaigned in the 2017 German election with the slogan "Digital first, doubts second" (Digital first, Bedenken second). This sort of optimism vis-à-vis the future has complete faith in science. As Theresa May told the World Economic Forum in Davos in 2018: "Imagine a world in which self-driving cars radically reduce the number of deaths on our roads. Imagine a world where remote monitoring and inspection of critical infrastructure make dangerous jobs safer. Imagine a world where we can predict and prevent the spread of diseases around the globe" (May 2018). True believers justify their confidence with numbers. May said: "We have seen a new AI start-up created in the UK every week for the last three years. And we are investing in the skills these start-ups need, spending £45 million to support additional PhDs in AI and related disciplines." This is completely in keeping with the myopia of the post-political dogma that the future will be determined not by societal discussions but by quantifiable investments and innovations. But to what extent does the future truly reside in the hands of the science and start-ups May praises so fulsomely? Do scientists and entrepreneurs consciously decide, after possibly discussing the consequences, which inventions they will produce and support? Do they have the power to tell society how scientific achievements like splitting the atom or decoding DNA will be used? Do they abide by social imperatives not to engage in research whose consequences cannot be anticipated or controlled? Or would they seek out a society with other moral standards and legal regulations—perhaps on an artificial extraterritorial island financed by venture capitalist Peter Thiel's Seasteading Institute? And what should we think of the fact that in the case of artificial intelligence, the threat of unforeseen consequences [End Page 424] is no longer restricted to irresponsible usage of the invention, but includes the prospect that the invention might keep its inventors as pets instead of...

Nonconscious Cognitive Suffering: Considering Suffering Risks of Embodied Artificial Intelligence

Strong arguments have been formulated that the computational limits of disembodied artificial intelligence (AI) will, sooner or later, be a problem that needs to be addressed. Similarly, convincing cases for how embodied forms of AI can exceed these limits makes for worthwhile research avenues. This paper discusses how embodied cognition brings with it other forms of information integration and decision-making consequences that typically involve discussions of machine cognition and similarly, machine consciousness. N. Katherine Hayles’s novel conception of nonconscious cognition in her analysis of the human cognition-consciousness connection is discussed in relation to how nonconscious cognition can be envisioned and exacerbated in embodied AI. Similarly, this paper offers a way of understanding the concept of suffering in a way that is different than the conventional sense of attributing it to either a purely physical state or a conscious state, instead of grounding at least a type of suffering in this form of cognition.

An Integration of Deep Learning and Neuroscience for Machine Consciousness

Conscious processing is a useful aspect of brain function that can be used as a model to design artificial-intelligence devices. There are still certain computational features that our conscious brains possess, and which machines currently fail to perform those. This paper discusses the necessary elements needed to make the device conscious and suggests if those implemented, the resulting machine would likely to be considered conscious. Consciousness mainly presented as a computational tool that evolved to connect the modular organization of the brain. Specialized modules of the brain process information unconsciously and what we subjectively experience as consciousness is the global availability of data, which is made possible by a nonmodular global workspace. During conscious perception, the global neuronal work space at parieto-frontal part of the brain selectively amplifies relevant pieces of information. Supported by large neurons with long axons, which makes the long-distance connectivity possible, the selected portions of information stabilized and transmitted to all other brain modules. The brain areas that have structuring ability seem to match to a specific computational problem. The global workspace maintains this information in an active state for as long as it is needed. In this paper, a broad range of theories and specific problems have been discussed, which need to be solved to make the machine conscious. Later particular implications of these hypotheses for research approach in neuroscience and machine learning are debated.

THE EMERGENCE OF ARTIFICIAL CONSCIOUSNESS AND ITS IMPORTANCE TO REACH THE TECHNOLOGICAL SINGULARITY

The men admired a way to swim the fish, but today they sail faster than anyone. They'd like flying like the birds, but have been a lot higher. They searched for wisdom, now they have all the knowledge accumulated in the story available in a few clicks. Human evolution is about to meet its peak through the Technological Singularity, which can be understood as the future milestone reached at the moment that a computer program can think like a human, yet with quick access to all information already registered by society. It will not be like a man, but more intelligent than all mankind in history. So we have a big question: will this new entity has consciousness? Through a study of the levels of intelligent agents autonomy and in a timeless dialogue with Alan Turing, René Descartes, Ludwic Wittgenstein, John Searle and Vernor Vinge, we show the possibility of an artificial consciousness and thatthe quest for intentionality, promoted by sophisticated algorithms of learning and machine discovery, is the key to reach of Technological Singularity.

Consciousness: The Point of View of Process Philosophy and Genetic Structuralism

First a sketch of the current state of the debate of the phenomenon of consciousness is provided; based on it David Chalmer’s distinction between the weak and the hard problem of consciousness will be introduced. It will be indicated that Whitehead’s process philosophy is able to offer a promising basis for solving the hard problem by showing how the concept of consciousness is anchored in his metaphysical theory. In the remaining parts of the paper the so-called weak problem of consciousness will be addressed in more detail by comparing Whitehead’s speculative account with Piaget’s empirical research results concerning the phenomenon of consciousness. By showing that Whitehead’s and Piaget’s positions on consciousness overlap widely a kind of indirect empirical support of Whitehead’s philosophical position will be achieved. At those points where the two positions deviate – that is in only two points – there are indications that Whitehead holds the more plausible position. So this investigation confirms William Seager’s suggestion that more attention should be drawn to Whitehead’s process philosophy when trying to solve the hard, as well as the weak problem of consciousness. In order to substantiate this claim two topics are discussed from the point of view of Whitehead’s position of consciousness: (a) learning and consciousness and (b) artificial consciousness.

Modeling Working Memory to Identify Computational Correlates of Consciousness

Abstract Recent advances in philosophical thinking about consciousness, such as cognitive phenomenology and mereological analysis, provide a framework that facilitates using computational models to explore issues surrounding the nature of consciousness. Here we suggest that, in particular, studying the computational mechanisms of working memory and its cognitive control is highly likely to identify computational correlates of consciousness and thereby lead to a deeper understanding of the nature of consciousness. We describe our recent computational models of human working memory and propose that three computational correlates of consciousness follow from the results of this work: itinerant attractor sequences, top-down gating, and very fast weight changes. Our current investigation is focused on evaluating whether these three correlates are sufficient to create more complex working memory models that encompass compositionality and basic causal inference. We conclude that computational models of working memory are likely to be a fruitful approach to advancing our understanding of consciousness in general and in determining the long-term potential for development of an artificial consciousness specifically.

Rape Culture Reborn: A Posthuman Perspective on Rape in Westworld

The main objective of the essay is to present the problem of granting the status of a person who enjoys all human rights to artificial intelligence if it manages to develop artificial consciousness at the level allowing it for reflecting upon itself and recognizing the fact that it is an entity which has its own subjectivity and the right not to be exploited. Assuming the perspective of critical posthumanism, which here draws on research conducted by Stefan Sorgner, Francesca Ferrando, and Neil Badmington, the Author tries to give a concise presentation of the issue, which may still be perceived as part of speculative discourse stimulated by science-fiction, but which – as the Author proves – seems to be gradually becoming part of our everyday world that humanity will have to deal with on both ideological and legislative ground.

Screen Circuits: Fear and Paranoia in the Sprawl (circa 1995)

The 1990s was a strange time to be alive: a saxophone playing U.S. president waltzed into a Cold War vacuum left behind by the crumbling of the Soviet Eastern Bloc, while Gulf War 1.0 was the first mediated war, yet one lacking any meaningful optics - Baudrillard's so-called weak event. Meanwhile, technology, culture and information was rapidly beginning to coalesce in unexpected ways. The 1990s was more of a feeling than a knowing, there was certainly change afoot and the clock was ticking on a century of acceleration and shrinking horizons. Zygmunt Bauman (Liquid Modernity, 2000) and Paul Virilio (Open Sky, 1997) capture this time from the perspective of the machine's lens and big data's gathering torrents. We were only just beginning to stockpile our algorithmic future. There is of course a strong human element to all of this as well, as domesticity was about to be transformed in ways not seen since the automation of white goods in the 1950s. Installing a telephone line in a new rental was a priority as this was not just a communication device but a gateway to a new digital epoch (chat rooms, conspiracy theories, gaming mods and a seemingly limitless archive of music). Australians, who would become the new suitors of the boom in computer peripherals and digital gadgetry, turned the latent ability to send short text messages from their mobile phones into a new form of digital dialectics. Meanwhile, the cinema was signalling a grave warning of what all of this might mean if we could indeed become virtual, if the machine was in fact alive and information networks consciousness itself. From James Bond confronting a Rupert Murdock/Conrad Black-type media demigod in Tomorrow Never Dies (1997), to the digital psychedelics of the millennial rush in Strange Days (1995) to Henry Rollins raging against reality in the William Gibson penned Johnny Mnemonic (1995). These mid-nineties films tapped a rich vein of paranoia around the new vanguard of networked information and computer-generated image making while also expressing - in often garish terms - a deep anxiety about a not-to-distant future crackling into view beyond the millennial divide.

Can Computers Become Conscious and Overcome Humans?

The idea of machines overcoming humans can be intrinsically related to conscious machines. Surpassing humans would mean replicating, reaching and exceeding key distinctive properties of human beings, for example, high-level cognition associated with conscious perception. However, can computers be compared with humans? Can computers become conscious? Can computers outstrip human capabilities? These are paradoxical and controversial questions, particularly because there are many hidden assumptions and misconceptions about the understanding of the brain. In this sense, it is necessary to first explore these assumptions and then suggest how the specific information processing of brains would be replicated by machines. Therefore, this article will discuss a subset of human capabilities and the connection with conscious behavior, secondly, a prototype theory of consciousness will be explored and machines will be classified according to this framework. Finally, this analysis will show the paradoxical conclusion that trying to achieve conscious machines to beat humans implies that computers will never completely exceed human capabilities, or if the computer were to do it, the machine should not be considered a computer anymore.

Can artificially intelligent agents really be conscious?

Mind and intelligence are closely related with the consciousness. Indeed, artificial intelligence (AI) is the most promising avenue towards artificial consciousness (AC). However, in literature, consciousness has been considered as the least amenable to being understood or replicated by AI. Further, computational theories of mind (CTMs) render the mind as a computational system and it is treated as a substantial hypothesis within the purview of AI. However, the consciousness, which is a phenomenon of mind, is partially tackled by this theory and it seems that the CTM is not corroborated considerably in this pursuit. Many valuable contributions have been incorporated by the researchers working strenuously in this domain. However, there is still scarcity of globally accepted computational models of consciousness that can be used to design conscious intelligent machines. The contributions of the researchers entail consciousness as a vague, incomplete and human-centred entity. In this paper, attempt has been made to analyse different theoretical and intricate issues pertaining to mind, intelligence and AC. Moreover, this paper discusses different computational models of the consciousness and critically analyses the possibility of generating the machine consciousness as well as identifying the characteristics of conscious machine. Further, different inquisitive questions, e.g., “Is it possible to devise, project and build a conscious machine?”, “Will artificially conscious machines be able to surpass the functioning of artificially intelligent machines?” and “Does consciousness reflect a peculiar way of information processing?” are analysed.

Good Old-Fashioned Artificial Consciousness and the Intermediate Level Fallacy.

Recently, there has been considerable interest and effort to the possibility to design and implement conscious robots, i.e., the chance that robots may have subjective experiences. Typical approaches as the global workspace, information integration, enaction, cognitive mechanisms, embodiment, i.e., the Good Old-Fashioned Artificial Consciousness, henceforth, GOFAC, share the same conceptual framework. In this paper, we discuss GOFAC's basic tenets and their implication for AI and Robotics. In particular, we point out the intermediate level fallacy as the central issue affecting GOFAC. Finally, we outline a possible alternative conceptual framework toward robot consciousness.

The Active Inference Approach to Ecological Perception: General Information Dynamics for Natural and Artificial Embodied Cognition

The emerging neurocomputational vision of humans as embodied, ecologically embedded, social agents—who shape and are shaped by their environment—offers a golden opportunity to revisit and revise ideas about the physical and information-theoretic underpinnings of life, mind, and consciousness itself. In particular, the active inference framework (AIF) makes it possible to bridge connections from computational neuroscience and robotics/AI to ecological psychology and phenomenology, revealing common underpinnings and overcoming key limitations. AIF opposes the mechanistic to the reductive, while staying fully grounded in a naturalistic and information-theoretic foundation, using the principle of free energy minimization. The latter provides a theoretical basis for a unified treatment of particles, organisms, and interactive machines, spanning from the inorganic to organic, non-life to life, and natural to artificial agents. We provide a brief introduction to AIF, then explore its implications for evolutionary theory, ecological psychology, embodied phenomenology, and robotics/AI research. We conclude the paper by considering implications for machine consciousness.

Is Anyone Home? A Way to Find Out If AI Has Become Self-Aware.

Recent articles by Schneider and Turner (Turner and Schneider, 2017; Schneider and Turner, 2017) outline an artificial consciousness test (ACT); a new, purely behavioural process to probe subjective experience (“phenomenal consciousness”: tickles, pains, visual experiences, and so on) in machines; work that has already resulted in a provisional patent application from Princeton University (Turner and Schneider, in press). In light of the author’s generic skepticism of “consciousness qua computation” (Bishop, 2002, 2009) and Tononi and Koch’s “Integrated Information Theory”-driven skepticism regarding the possibility of consciousness arising in any classical digital computer (due to low φmax) (Tononi and Koch, 2015), consideration is given to the claimed sufficiency of ACT to determine the phenomenal status of a computational artificial intelligence (AI) system.