Researchers propose a new approach to developing smart machines that could lead to greener, more ethical, and useful artificial intelligence systems. The EMERGE project suggests that instead of striving for artificial general intelligence, which raises concerns about consciousness and energy efficiency, we should focus on creating specialized AI systems tailored to specific tasks. These systems can be more reliable, energy-efficient, and ethically tractable than general-purpose AI.
According to Ophelia Deroy, Professor of Philosophy and Neuroscience at the Ludwig Maximilian University in Munich, Germany, what’s needed is a “collaborative shared awareness” that enables these specialized systems to coordinate and cooperate with each other and humans. This approach could lead to more effective and efficient AI systems, such as autonomous vehicles that can avoid collisions, logistics robots that can coordinate package delivery, or AI systems that can analyze complex medical histories to provide useful treatment recommendations. The research, published in the journal Advanced Intelligent Systems, was led by Deroy and Sabine Hauert, Professor of Swarm Engineering at the University of Bristol, UK, among others.
Rethinking AI Development: A Shift towards Shared Awareness
The deployment of artificial intelligence (AI) systems in various aspects of our lives, from autonomous vehicles to AI assistants, has sparked intense debate about the direction of AI development. The traditional approach focuses on creating increasingly capable agents that can perform multiple tasks, with the ultimate goal of achieving artificial general intelligence (AGI). However, this path raises concerns about energy efficiency, ethical tractability, and the potential risks associated with conscious artificial entities.
In contrast, researchers from the EMERGE project consortium propose an alternative vision, where specialized AI systems tailored to specific tasks can be more reliable, energy-efficient, and ethically tractable than general intelligence. This approach emphasizes the importance of effective coordination between different systems and humans, which can be achieved through simpler ways of sharing awareness.
The Limitations of Artificial General Intelligence
The pursuit of AGI has been driven by the desire to create AI systems that can perform any intellectual task that a human can. However, this approach is not without its drawbacks. Operating a general-purpose system incurs significant energy and emission costs, as evidenced by generative architectures such as large language models. Moreover, endowing domain-general AI with capacities such as face recognition, decision-making, and natural language processing raises concerns about the potential risks associated with conscious artificial entities.
The development of AGI also poses significant technical challenges. For instance, integrating multiple specialized AI systems into a single general-purpose system is a complex task that requires significant advances in areas such as knowledge representation, reasoning, and learning. Furthermore, the lack of transparency and explainability in AGI systems makes it challenging to ensure their safety and reliability.
The Promise of Shared Awareness
In contrast, shared awareness offers a more promising approach to AI development. This concept involves the capacity for selectively sharing relevant states with other AI systems in order to facilitate coordination and cooperation. Unlike consciousness, which is often viewed as a private state, shared awareness is an emergent property that arises from the interactions between different agents.
Shared awareness has several advantages over AGI. Firstly, it enables systems to work better together, even if they were designed by different companies. This facilitates the development of more complex AI systems that can perform tasks such as autonomous vehicle coordination and logistics robot delivery. Secondly, shared awareness makes artificial agents easier to monitor and control for human operators, which is essential for ensuring their safety and reliability.
The Characteristics of Shared Awareness
Shared awareness differs from consciousness in several key aspects. Firstly, it is not a private state, but rather an emergent property that arises from the interactions between different agents. Secondly, shared awareness can be transient, sharing states with others only when there is a need to coordinate individual goals or cooperate on a common goal. Thirdly, shared awareness can be selective regarding which states are relevant to be shared with others.
These characteristics of shared awareness make it an attractive approach for AI development. By enabling systems to share relevant information and coordinate their actions, shared awareness can facilitate the development of more complex AI systems that can perform tasks such as autonomous vehicle coordination and logistics robot delivery.
The Future of AI Development
The EMERGE project consortium’s proposal for a collaborative shared awareness framework offers a promising alternative to AGI. By focusing on specialized AI systems tailored to specific tasks, this approach can lead to the development of more reliable, energy-efficient, and ethically tractable AI systems.
As AI continues to play an increasingly important role in our lives, it is essential that we rethink our approach to AI development. By prioritizing shared awareness over AGI, we can create AI systems that are not only more effective but also safer and more transparent. Ultimately, this approach has the potential to lead to the development of greener, more ethical, and useful smart machines that can benefit society as a whole.
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