Planning and understanding: A computational approach to human reasoning

Russell, Daniel M.

doi:10.1016/0004-3702(84)90011-0

Cited by 95 publications

(149 citation statements)

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“…Erobots are “agents” in the sense that they are functional technological systems, like computer programs. Since it is beyond the scope of this paper to statute on the nature of agency , we here employ the broadest definition recognized and commonly used in the fields of AI, machine learning (ML), and robotics [ 221 , 257 , 258 , 284 ]. That is, the agency of machines refers to their capability to act intelligently in and on the world to achieve objectives on their own [ 221 ].…”

Section: Towards Eroboticsmentioning

confidence: 99%

“…That is, the agency of machines refers to their capability to act intelligently in and on the world to achieve objectives on their own [ 221 ]. Intelligence here simply refers to the capability to achieve goals [ 257 , 284 ]. Like their biological counterparts, artificially intelligent agents have the potential to communicate, adapt, behave, and/or interact with other agents using more or less complex learning algorithms.…”

Section: Towards Eroboticsmentioning

confidence: 99%

“…While these attempts modify “agents architecturally” and depict their internal states in a form interpretable for humans, others “[…] seek to build intermediating systems which learn to reduce dimensionality of the space of behaviour and represent it in more digestible forms ” [ 242 , p. 2]. Inverse Reinforcement Learning, for one, teaches algorithms to adapt behaviour to circumstances and learn from human–machine continued interaction [ 257 ]. Successful “consequence engines” in bots are also already capable of internally modeling their environment and other entities in order to avoid collisions, coordinate without communication, and reach their goals [ 30 ].…”

Section: Towards Eroboticsmentioning

confidence: 99%

“…With these objectives in mind, the following sections highlight how human-erobot interaction and co-evolution may increase the likelihood of erobot-related risks if this process limits the diversity of erobotic traits available, and/or if the current approach to AI design is not changed—otherwise known as the Standard Model of AI design (i.e., optimizing specific pre-set goals; [ 257 ]). As we have shown in the previous sections, erobots bring new agential and cognitive capabilities that may allow them to derive goals from their (erotic) interaction and co-evolution with humans.…”

Section: Beneficial Erotic Machinesmentioning

confidence: 99%

“…Finally, we underline how human-erobot interaction and co-evolution can be detrimental to human well-being—particularly if they hinder the diversity of erotic traits, and if we do not change our current approach to technological design [ 34 , 257 ]. As an alternative, we recommend implementing Stuart Russell’s [ 257 ] principles for beneficial machines to guide the development of beneficial erobots (Sect. 4 ).…”

Section: Introductionmentioning

confidence: 99%

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Foundations of Erobotics

Dubé

Anctil

2020

Int J of Soc Robotics

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Technology is giving rise to artificial erotic agents, which we call erobots ( erôs + bot). Erobots, such as virtual or augmented partners, erotic chatbots, and sex robots, increasingly expose humans to the possibility of intimacy and sexuality with artificial agents. Their advent has sparked academic and public debates: some denounce their risks (e.g., promotion of harmful sociosexual norms), while others defend their potential benefits (e.g., health, education, and research applications). Yet, the scientific study of human–machine erotic interaction is limited; no comprehensive theoretical models have been proposed and the empirical literature remains scarce. The current research programs investigating erotic technologies tend to focus on the risks and benefits of erobots, rather than providing solutions to resolve the former and enhance the latter. Moreover, we feel that these programs underestimate how humans and machines unpredictably interact and co-evolve, as well as the influence of sociocultural processes on technological development and meaning attribution. To comprehensively explore human–machine erotic interaction and co-evolution, we argue that we need a new unified transdisciplinary field of research—grounded in sexuality and technology positive frameworks—focusing on human-erobot interaction and co-evolution as well as guiding the development of beneficial erotic machines. We call this field Erobotics . As a first contribution to this new discipline, this article defines Erobotics and its related concepts; proposes a model of human-erobot interaction and co-evolution; and suggests a path to design beneficial erotic machines that could mitigate risks and enhance human well-being.

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Section: Towards Eroboticsmentioning

confidence: 99%

Section: Towards Eroboticsmentioning

confidence: 99%

Section: Towards Eroboticsmentioning

confidence: 99%

Section: Beneficial Erotic Machinesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Foundations of Erobotics

Dubé

Anctil

2020

Int J of Soc Robotics

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Artificial Intelligence and Health

2024

AI, Healthcare and Law

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Health is one of the areas where a significant contribution of artificial intelligence (AI) is expected, with implications for the cost, quality and efficiency of medical attention, including preparation and response capacities for health emergencies. Nevertheless, there are major challenges related to security, privacy and access to data, and the generation of inequalities. Legislation, regulation, evaluation and human supervision are key elements to facilitate its implementation in professional practice.Report C: Artificial intelligence and health: potential and challenges Date publication 14/11/2022 Production methodReports C are brief documents on subjects chosen by the Bureau of the Congress of Deputies that contextualise and summarise the available scientific evidence on the analysed subject. They also inform about areas of agreement, disagreement, unknowns, and ongoing discussions. The reports are drafted based on an in-depth review of the literature, supplemented by interviews with experts on the subject and a two-round review process.To produce this report, Oficina C referenced 270 documents and consulted 30 experts in the subject. Of this multidisciplinary group, 50% belong to the field of life sciences (medicine, bioinformatics, biomedical engineering, health regulation and evaluation, and ecology), 26% come from physics and engineering sciences (informatics engineering, natural language processing, electronic engineering and robotics engineering) and 19% from social sciences and humanities (behavioural sciences, ethics, philosophy and law); 87% work in Spanish institutions or centres, whereas 13 % have affiliations abroad.

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Artificial Intelligence: From Buzzword to Useful Tool in Clinical Pharmacology

Shahin,

Barth,

Podichetty

et al. 2023

Clin Pharma and Therapeutics

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The advent of artificial intelligence (AI) in clinical pharmacology and drug development is akin to the dawning of a new era. Previously dismissed as merely technological hype, these approaches have emerged as promising tools in different domains, including healthcare, demonstrating their potential to empower clinical pharmacology decision‐making, revolutionize the drug development landscape, and advance patient care. While challenges remain, the remarkable progress already made signals that the leap from hype to reality is well underway, and AI promises to offer clinical pharmacology new tools and possibilities for optimizing patient care is gradually coming to fruition. This review dives into the burgeoning world of AI and machine learning (ML), showcasing different applications of AI in clinical pharmacology and the impact of successful AI/ML implementation on drug development and/or regulatory decisions. This review also highlights recommendations for areas of opportunity in clinical pharmacology, including data analysis (e.g., handling large datasets, screening to identify important covariates, optimizing patient population) and efficiencies (e.g., automation, translation, literature curation, training). Realizing the benefits of AI in drug development and understanding its value will lead to the successful integration of AI tools in our clinical pharmacology and pharmacometrics armamentarium.

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Planning and understanding: A computational approach to human reasoning

Cited by 95 publications

References 1 publication

Foundations of Erobotics

Foundations of Erobotics

Artificial Intelligence and Health

Artificial Intelligence: From Buzzword to Useful Tool in Clinical Pharmacology

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