Using a Cognitive Architecture to consider antiblackness in design and development of AI systems

• URL: http://arxiv.org/abs/2207.00644v2
• Date: Mon, 24 Apr 2023 11:41:58 GMT
• Title: Using a Cognitive Architecture to consider antiblackness in design and development of AI systems
• Authors: Christopher L. Dancy
• Abstract summary: How might we use cognitive modeling to consider the ways in which antiblackness, and racism more broadly, impact the design and development of AI systems? We use the ACT-R/Phi cognitive architecture and an existing knowledge graph system, ConceptNet, to consider this question.
• Score: 0.548253258922555
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: How might we use cognitive modeling to consider the ways in which antiblackness, and racism more broadly, impact the design and development of AI systems? We provide a discussion and an example towards an answer to this question. We use the ACT-R/{\Phi} cognitive architecture and an existing knowledge graph system, ConceptNet, to consider this question not only from a cognitive and sociocultural perspective, but also from a physiological perspective. In addition to using a cognitive modeling as a means to explore how antiblackness may manifest in the design and development of AI systems (particularly from a software engineering perspective), we also introduce connections between antiblackness, the Human, and computational cognitive modeling. We argue that the typical eschewing of sociocultural processes and knowledge structures in cognitive architectures and cognitive modeling implicitly furthers a colorblind approach to cognitive modeling and hides sociocultural context that is always present in human behavior and affects cognitive processes.

Related papers

• Alien Recombination: Exploring Concept Blends Beyond Human Cognitive Availability in Visual Art [90.8684263806649]
  We show how AI can transcend human cognitive limitations in visual art creation. Our research hypothesizes that visual art contains a vast unexplored space of conceptual combinations. We present the Alien Recombination method to identify and generate concept combinations that lie beyond human cognitive availability.
  arXiv  Detail & Related papers  (2024-11-18T11:55:38Z)
• The Phenomenology of Machine: A Comprehensive Analysis of the Sentience of the OpenAI-o1 Model Integrating Functionalism, Consciousness Theories, Active Inference, and AI Architectures [0.0]
  The OpenAI-o1 model is a transformer-based AI trained with reinforcement learning from human feedback. We investigate how RLHF influences the model's internal reasoning processes, potentially giving rise to consciousness-like experiences. Our findings suggest that the OpenAI-o1 model shows aspects of consciousness, while acknowledging the ongoing debates surrounding AI sentience.
  arXiv  Detail & Related papers  (2024-09-18T06:06:13Z)
• Visual Knowledge in the Big Model Era: Retrospect and Prospect [63.282425615863]
  Visual knowledge is a new form of knowledge representation that can encapsulate visual concepts and their relations in a succinct, comprehensive, and interpretable manner. As the knowledge about the visual world has been identified as an indispensable component of human cognition and intelligence, visual knowledge is poised to have a pivotal role in establishing machine intelligence.
  arXiv  Detail & Related papers  (2024-04-05T07:31:24Z)
• A Neuro-mimetic Realization of the Common Model of Cognition via Hebbian Learning and Free Energy Minimization [55.11642177631929]
  Large neural generative models are capable of synthesizing semantically rich passages of text or producing complex images. We discuss the COGnitive Neural GENerative system, such an architecture that casts the Common Model of Cognition.
  arXiv  Detail & Related papers  (2023-10-14T23:28:48Z)
• BIASeD: Bringing Irrationality into Automated System Design [12.754146668390828]
  We claim that the future of human-machine collaboration will entail the development of AI systems that model, understand and possibly replicate human cognitive biases. We categorize existing cognitive biases from the perspective of AI systems, identify three broad areas of interest and outline research directions for the design of AI systems that have a better understanding of our own biases.
  arXiv  Detail & Related papers  (2022-10-01T02:52:38Z)
• Kernel Based Cognitive Architecture for Autonomous Agents [91.3755431537592]
  This paper considers an evolutionary approach to creating a cognitive functionality. We consider a cognitive architecture which ensures the evolution of the agent on the basis of Symbol Emergence Problem solution.
  arXiv  Detail & Related papers  (2022-07-02T12:41:32Z)
• CogNGen: Constructing the Kernel of a Hyperdimensional Predictive Processing Cognitive Architecture [79.07468367923619]
  We present a new cognitive architecture that combines two neurobiologically plausible, computational models. We aim to develop a cognitive architecture that has the power of modern machine learning techniques.
  arXiv  Detail & Related papers  (2022-03-31T04:44:28Z)
• AI and Blackness: Towards moving beyond bias and representation [0.8223798883838329]
  We argue that AI ethics must move beyond the concepts of race-based representation and bias. Antiblackness in AI requires more of an examination of the ontological space that provides a foundation for the design, development, and deployment of AI systems.
  arXiv  Detail & Related papers  (2021-11-05T18:24:54Z)
• Towards a Predictive Processing Implementation of the Common Model of Cognition [79.63867412771461]
  We describe an implementation of the common model of cognition grounded in neural generative coding and holographic associative memory. The proposed system creates the groundwork for developing agents that learn continually from diverse tasks as well as model human performance at larger scales.
  arXiv  Detail & Related papers  (2021-05-15T22:55:23Z)
• Whole brain Probabilistic Generative Model toward Realizing Cognitive Architecture for Developmental Robots [8.941833998120904]
  Building a humanlike integrative artificial cognitive system, that is, an artificial general intelligence, is one of the goals in artificial intelligence and developmental robotics. This paper describes the development of a cognitive architecture using probabilistic generative models (PGMs) to fully mirror the human cognitive system.
  arXiv  Detail & Related papers  (2021-03-15T07:42:04Z)
• The Evolution of Concept-Acquisition based on Developmental Psychology [4.416484585765028]
  A conceptual system with rich connotation is key to improving the performance of knowledge-based artificial intelligence systems. Finding a new method to represent concepts and construct a conceptual system will greatly improve the performance of many intelligent systems. Developmental psychology carefully observes the process of concept acquisition in humans at the behavioral level.
  arXiv  Detail & Related papers  (2020-11-26T01:57:24Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.