The path to more general artificial intelligence

Goertzel, Ted G.

doi:10.1080/0952813x.2014.895106

Cited by 28 publications

(12 citation statements)

References 23 publications

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“…It is clear that agent-based systems can be useful for modelling some behaviours, but care is needed when stepping beyond the real limitations that they possess. To validate an ABM against real human behaviour is still out of reach, and most likely will remain so until we develop an advanced AI that possesses both narrow and general intelligence (Goertzel, 2014). It is essential that any ABM that purports to replicate human behaviour should discuss human cognition to some level.…”

Section: Discussionmentioning

confidence: 99%

Organisational plasticity: can we really model human–agent behaviours?

Richards

2020

EBHRM

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PurposeThe ability for an organisation to adapt and respond to external pressures is a beneficial activity towards optimising efficiency and increasing the likelihood of achieving set goals. It can also be suggested that this very ability to adapt to one's surroundings is one of the key factors of resilience. The nature of dynamically responding to sudden change and then to return to a state that is efficient may be termed as possessing the characteristic of plasticity. Uses of agent-based systems in assisting in organisational processes may have a hand in facilitating an organisations' plasticity, and computational modelling has often been used to try and predict both agent and human behaviour. Such models also promise the ability to examine the dynamics of organisational plasticity through the direct manipulation of key factors. This paper discusses the use of such models in application to organisational plasticity and in particular the relevance to human behaviour and perception of agent-based modelling. The uses of analogies for explaining organisational plasticity is also discussed, with particular discussion around the use of modelling. When the authors consider the means by which the authors can adopt theories to explain this type of behaviour, models tend to focus on aspects of predictability. This in turn loses a degree of realism when we consider the complex nature of human behaviour, and more so that of human–agent behaviour.Design/methodology/approachThe methodology and approach used for this paper is reflected in the review of the literature and research.FindingsThe use of human–agent behaviour models in organisational plasticity is discussed in this paper.Originality/valueThe originality of this paper is based on the importance of considering the human–agent-based models. When compared to agent-based model approaches, analogy is used as a narrative in this paper.

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Section: Discussionmentioning

confidence: 99%

Organisational plasticity: can we really model human–agent behaviours?

Richards

2020

EBHRM

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“…In contrast, NAI is typically referred to as a machine that can make autonomous decisions within certain conditions and limits (Goertzel, 2015). In the case of NAI, if conditions and circumstance change, additional human intervention is often required to keep the system functioning correctly, unlike AGI, which can learn and apply existing information as autonomously as humans do (Goertzel, 2014).…”

Section: Artificial Intelligence and Robotsmentioning

confidence: 99%

Service Robots Usage in Marketing Hospitality in China

Ersoy

Cui²

2021

JBAR

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Since the coronavirus disease 2019(COVID-19) has had brought severe impact on all aspects of the world. A series of interpersonal distancing methods such as ensuring effective and safe social distancing among people, wearing masks, and traffic lockdown measures are also continuing to take effect to curb the continuing outbreak of the COVID-19 (“Advice for the public on COVID-19”, 2020). In response to the globally spread of COVID-19, many advanced technologies in the field of Artificial Intelligence (AI) were applied rapidly and played an essential role in the operation for several months. There are many different leading technology categories in the field of artificial intelligence and many different sub-categories within each main technology categories. Moreover, since the AGI technology does not yet reach the basic human intelligence level, this study will focus on the impact of service robots, which are already widely used in the NAI application category, on hospitality marketing in the current situation in China. In this paper the aim is to assess the effectiveness of use of service robots in Marketing Hospitality Industry during the pandemic through a quantitative study.

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“…AGI has been called "humanity's last invention" because of its potential to evolve itself as well as to potentially create other new technology faster than human beings might be able to [15]. The potential economic and other impacts of this capability have been suggested to be immense [5] - [10]. However, this potential impact is also a great risk [11].…”

Section: Introductionmentioning

confidence: 99%

“…As a competitive advantage for it's owner, AGI has the potential to be a massive generator of inequality, accumulating wealth from any markets in which transactions can be triggered through electronic communication [5] - [10]. And through doing so for the owner of the most powerful AGI potentially at a pace orders of magnitude greater than for others [16] - [18].…”

Section: Introductionmentioning

confidence: 99%

The Case for General Collective Intelligence Rather than Artificial General Intelligence being the Most Important Human Innovation in the History and Future of Mankind

Williams¹

2020

Preprint

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Artificial General Intelligence, that is an Artificial Intelligence with the ability to redesign itself and other technology on its own, has been called “mankind’s last invention”, since it may not only remove the necessity of any human invention afterwards, but also might design solutions far too complex for human beings to have the ability to contribute to in any case. Because of this, if and when AGI is ever invented, it has been argued by many that it will be the most important innovation in the history of the mankind up to that point. Just as nature’s invention of human intelligence might have transformed the entire planet and generated a greater economic impact than any other innovation in the history of the planet, AGI has been suggested to have the potential for an economic impact larger than that resulting from any other innovation in the history of mankind. This paper explores the case for General Collective Intelligence being a far more important innovation than AGI. General Collective Intelligence has been defined as a solution with the capacity to organize groups of human or artificial intelligences into a single collective intelligence with vastly greater general problem solving ability. A recently proposed model of GCI not only outlines a model for cognition that might also enable AGI, but also identifies hidden patterns in collective outcomes for groups that might make GCI necessary in order to reliably achieve the benefits of AGI while reliably avoiding the potentially catastrophic costs of AGI.

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The path to more general artificial intelligence

Cited by 28 publications

References 23 publications

Organisational plasticity: can we really model human–agent behaviours?

Organisational plasticity: can we really model human–agent behaviours?

Service Robots Usage in Marketing Hospitality in China

The Case for General Collective Intelligence Rather than Artificial General Intelligence being the Most Important Human Innovation in the History and Future of Mankind

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