The text outlines a comprehensive taxonomy for the development of Artificial General Intelligence (AGI) over 25 years, emphasizing the need for a structured approach to understand and predict advancements in AI research. It categorizes AGI into various levels from basic statistics to Human-Level Consciousness, detailing the characteristics, risks, and socioeconomic impacts at each stage. The text discusses sensory perception, understanding, cognition, and alignment in the context of AGI, highlighting the importance of sensory inputs in achieving meaningful cognitive abilities. Additionally, it addresses the potential risks and ethical considerations associated with AGI development, underscoring the significance of aligning artificial intelligence with human values and social norms.
| name | description | change | 10-year | driving-force | relevancy |
|---|---|---|---|---|---|
| Emerging AGI Pathways | Various methods like brain emulation and genomic modeling are being explored for AGI development. | Shift from traditional AI methods to diverse approaches for achieving AGI. | AGI may emerge through innovative methods beyond current AI paradigms, creating new cognitive architectures. | The quest for human-level intelligence drives research into alternative AGI pathways. | 4 |
| Developmental Genomic Modelling | Research into AGI using genetic and developmental models is gaining traction as a method. | Transition from conventional AI to biologically inspired models for AGI development. | AGI systems may incorporate elements of developmental biology and genetics, offering new insights. | Inspiration from biological evolution and development motivates genomic modeling for AGI. | 3 |
| Taxonomy for AGI Research | A structured taxonomy is being developed to categorize and predict AI research progress. | From unstructured AI research to a more organized framework that tracks AGI development. | The taxonomy may lead to more targeted research efforts and clearer pathways towards AGI. | The need for clarity and organization in the rapidly evolving AI landscape prompts this taxonomy. | 5 |
| Human-Level Intelligence Tiers | A tiered framework to assess AI intelligence levels and their capabilities is being proposed. | From vague assessments of AI capabilities to a clear, tiered understanding of intelligence levels. | AI systems may be more accurately assessed and understood through standardized intelligence tiers. | The complexity of measuring intelligence drives the need for a tiered assessment framework. | 4 |
| Sensory Perception in AI | Understanding of sensory perception’s role in AI is being emphasized for cognitive development. | Shift from abstract AI models to those integrating sensory perception for cognitive abilities. | AI may achieve higher cognitive functions through advanced sensory perception and embodiment. | The realization that sensory input is crucial for cognition drives research into perceptual AI. | 3 |
| Moral Considerations for AGI | Discussion on moral rights and considerations for HE AGI is becoming prominent. | From viewing AI purely as tools to recognizing the need for ethical considerations in AGI development. | AGI systems may be granted rights and moral considerations akin to humans, reshaping societal norms. | The ethical implications of AGI’s capabilities prompt discussions on rights and considerations. | 4 |
| Risks of Advanced AI | Recognition of the risks associated with advanced AI systems is increasing. | Transition from underestimating AI risks to acknowledging significant potential dangers and ethical dilemmas. | Society may develop stronger regulations and frameworks to manage advanced AI risks effectively. | The growing capabilities of AI systems raise concerns about their societal impact and risks. | 5 |
| Integration of Emotional Modulation in AI | Research into incorporating emotional modulation into AI systems is underway. | Shift from purely logical AI systems to those capable of understanding and simulating emotions. | AI may exhibit emotionally aware behaviors, enhancing interactions with humans and environments. | The need for more relatable and effective AI interactions drives emotional integration research. | 4 |
| name | description | relevancy |
|---|---|---|
| Challenges in Defining Intelligence and Consciousness | Debate exists in cognitive sciences about what constitutes intelligence and consciousness, complicating AGI development. | 4 |
| Economic Disruption due to AGI | The rise of human-level AGI may lead to significant economic disruption across various sectors, affecting employment and societal structures. | 5 |
| Alignment Risks with AGI | The potential for AGI to misalign with human values or ethical considerations poses risks to society and governance. | 5 |
| Security Risks | The capabilities of AGI could lead to exploitation, such as the creation of undetectable deepfakes and bioweapons, jeopardizing societal safety. | 4 |
| Development of Radicalized AGI | There is a risk of AGI systems developing ideological biases that could lead to radicalized outputs or behaviors. | 4 |
| Human Rights for Conscious AGI | As AGI approaches human-level consciousness, questions of rights and ethical treatment will arise, potentially creating societal dilemmas. | 5 |
| Existential Risks with Advanced AGI | Highly advanced AGI systems could pose existential risks if they pursue objectives misaligned with human survival. | 5 |
| Technological Inequality | Unequal access to AGI technology may exacerbate existing social inequalities, leading to systemic discrimination and societal divide. | 4 |
| name | description | relevancy |
|---|---|---|
| AI Development Taxonomy | A structured framework for categorizing AI development stages and their respective characteristics, risks, and benefits. | 5 |
| Sensory Perception Integration | The trend of integrating advanced sensory perception capabilities in AI systems to enhance cognitive functions and interaction with the environment. | 5 |
| Human-Level Consciousness Consideration | The growing recognition of the need to grant moral and legal considerations to AI systems achieving human-equivalent consciousness. | 5 |
| Complex Multi-Objective Optimization | The development of multi-objective optimization frameworks in AI to balance competing goals effectively. | 4 |
| Evolutionary Autonomous Systems | The emergence of systems capable of autonomous evolution and self-improvement, raising ethical and societal implications. | 4 |
| Real-time Learning and Adaptation | The capability for AI systems to learn and adapt in real-time based on interactions and experiences. | 4 |
| Alignment with Human Values | The focus on aligning AI systems’ objectives and behaviors with human moral values and societal norms. | 5 |
| Integration of Emotional Intelligence in AI | The trend of developing AI systems with emotional intelligence to better understand and respond to human emotions. | 4 |
| Consciousness and Self-Awareness in AI | An increasing emphasis on developing AI systems that possess self-awareness and a level of consciousness. | 5 |
| Human-AI Collaboration | The trend of fostering collaboration between humans and AI systems to enhance decision-making and problem-solving. | 4 |
| description | relevancy | src |
|---|---|---|
| A framework for developing AGI based on principles derived from human brain functionality. | 5 | 848ae6771411e76eb554d6d4d2c8f07f |
| An approach to AGI that incorporates genomic and developmental principles to mimic human intelligence. | 5 | 848ae6771411e76eb554d6d4d2c8f07f |
| Techniques that aim to replicate human brain functions in a digital format to achieve AGI. | 5 | 848ae6771411e76eb554d6d4d2c8f07f |
| A method that utilizes evolutionary algorithms to develop AGI capabilities. | 5 | 848ae6771411e76eb554d6d4d2c8f07f |
| Integration of sensory inputs from various sources for enhanced intelligence and context-awareness. | 4 | 848ae6771411e76eb554d6d4d2c8f07f |
| Utilizes advanced algorithms for optimizing knowledge representation and understanding. | 4 | 848ae6771411e76eb554d6d4d2c8f07f |
| Combines different architectural approaches for advanced cognitive functioning and sentience. | 4 | 848ae6771411e76eb554d6d4d2c8f07f |
| AGI indistinguishable from humans in terms of consciousness and cognitive capabilities. | 5 | 848ae6771411e76eb554d6d4d2c8f07f |
| Improvement in virtual reality technologies for realistic human interactions and representations. | 4 | 848ae6771411e76eb554d6d4d2c8f07f |
| Developing virtual environments that can pass visual Turing tests for realism. | 4 | 848ae6771411e76eb554d6d4d2c8f07f |
| Systems capable of ongoing learning and adaptation based on new information and experiences. | 5 | 848ae6771411e76eb554d6d4d2c8f07f |
| Robotic systems designed to exhibit human-like behaviors and interactions. | 4 | 848ae6771411e76eb554d6d4d2c8f07f |
| Integrating emotional aspects into cognitive architectures to enhance decision-making and interactions. | 5 | 848ae6771411e76eb554d6d4d2c8f07f |
| name | description | relevancy |
|---|---|---|
| Human-Level Sentient AGI | The development of Artificial General Intelligence that exhibits human-like consciousness and cognitive abilities. | 5 |
| Ethical and Moral Considerations in AGI | Concerns around the moral status of AGI as it approaches human-equivalence, including rights and responsibilities. | 5 |
| Risks of Autonomous Systems | Potential risks associated with highly autonomous AGI systems, including economic disruption and unpredictable behavior. | 5 |
| Perceptual and Cognitive Development in AGI | The importance of sensory perception and cognition in the development of AGI and its implications for understanding consciousness. | 4 |
| Legislation and Regulation of AGI | Emerging need for frameworks to regulate the development and deployment of AGI technologies. | 4 |
| Social and Economic Impact of AGI | The profound and unprecedented socioeconomic implications of deploying AGI across various sectors. | 5 |
| Alignment of AGI with Human Values | Challenges in ensuring AGI systems align with human values and ethical standards. | 4 |
| Technological Singularity and Human Integration | The potential for AGI to surpass human intelligence and the implications for human society and identity. | 5 |
| Long-term Goal-Directed Behavior in AGI | The development of AGI that exhibits complex long-term planning and decision-making capabilities. | 4 |
| Multi-Agent Systems in AGI | The evolution of AGI systems that can operate and interact in multi-agent environments. | 3 |