posted by user: crealectics || 2516 views || tracked by 10 users: [display]

CREA 2019 : Anticipation and Anticipatory Systems: Humans Meet Artificial Intelligence

FacebookTwitterLinkedInGoogle

Link: https://www.oru.se/english/schools/humanities-education-and-social-sciences/conferences/anticipation2019/
 
When Jun 10, 2019 - Jun 10, 2019
Where Sweden
Submission Deadline Feb 28, 2019
Categories    anticipation   artificial intelligence   philosophy
 

Call For Papers

Science fiction writer Isaac Asimov imagined a science of prediction called “psychohistory” which enabled the future to be induced via statistical inference from big data. But is prediction and anticipation only about data? How should anticipation and anticipatory systems be conceived in order for human decisions to be respectful of pluralism in ecosystems and noosystems? Is there a common anticipatory feature in biological structures, cultural structures, and technological ones? How does anticipation influence movements, choices, emotions and representations? Is there a difference between prediction and anticipation in the context of technosocial systems?
Ancient divinatory practices have been replaced by AI-enhanced predictive planning and anthrobotic decision-making. Inferential prediction might prove effective for some technological systems, but in open ecosystems and complex noosystems, we could benefit from a general anticipatory paradigm that would integrate a form of care about the future — forms of life, forms of desire, and forms of hope.
The concept of anticipation emerged in part from theoretical research led by biologist and mathematician Robert Rosen, who developed a way of describing how complex biological systems differ from simple machine-like systems. A mechanistic approach can in the long term reduce the creativity of life if applied to complex systems (Rosen 1987). Rosen’s view was that biological and social organisms are complex systems that create predictive internal models of themselves and their environments and modify their behaviour in response to this future-oriented form of ideation. Relational biology has reintroduced the Aristotelian final cause, making teleology theoretically acceptable. From the perspective of anticipatory practice, this means that teleology – purpose, intentions, values and goals – could be added to the predictive toolkit. Recent research in neuroscience and philosophy of mind regards perception and action as arising from the brain’s essential activity as a hypothesis-making system that continually tries to minimise errors in its predictions about sensory input — perception relies on anticipatory processes (Hohwy 2013). Andy Clark speaks of “embodied prediction” (2015).
Human agency in particular includes an ability to shape desired outcomes. Organizations and human societies continually assess their environment and engage in deliberate anticipatory action to ensure future viability. With the emergence of big data and AI-driven systems of decision, it is important to ask how much of our freedom to co-create the future is affected, preserved or enhanced (in applied science, in management, in politics, etc.). A classic computational approach might turn out to produce a future that is impoverished by design.
We see anticipation as a promising paradigm in order to foster cross-disciplinarity and a cross-fertilization of ideas among researchers. Anticipation Studies is a growing field of research still in need of unification; it could shed a new light in current debates about the ethics and sustainability of Intelligent Systems.
Anticipation is a rich concept pointing to a cluster of cognitive/emotional/cultural phenomena, in a wide range of contexts and situations. As a keyword, anticipation plays a role in computer science, literature, psychology, the neurosciences, biology, etc., in disparate contexts that have not yet been bridged: can we envision a core aspect of anticipation beyond the diversity of anticipatory practices?
The relationship between the anticipatory paradigm and artificial intelligence in particular has been up to now understudied, especially from a techno-social perspective. We will bring together ten international world-leading specialist in the field of AI and/or anticipation studies. We wish to study and connect the various aspects of anticipation while deepening our knowledge about the relationship between ecosystems, noosystems and technosystems.
While the importance of studying anticipation is progressively recognized, as exemplified by the creation of the Unesco Chair in Anticipatory Studies, it is still unclear if there are radically different forms of anticipation (in biological systems, in cultural systems, in artificial systems) — anticipation would then function as a kind of metaphor —, or if there is a universal core in all anticipatory systems. This conference is a step towards the bridging of the various aspects of anticipation and the exploration of the missing link that might connect disparate anticipatory behavior. Can there be a holistic science of anticipation? Can anticipation be the paradigm that will reinvent cybernetics from a more holistic perspective? We want to consider and understand anticipation at the core of living beings, individual or collective.

Related Resources

EI-JCRAI 2020   2020 International Joint Conference on Robotics and Artificial Intelligence (JCRAI 2020)
ICDMML 2020   【EI SCOPUS】2020 International Conference on Data Mining and Machine Learning
CFMAI 2020   2020 2nd International Conference on Frontiers of Mathematics and Artificial Intelligence (CFMAI 2020)
ISBDAI 2020   【Ei Compendex Scopus】2020 International Symposium on Big Data and Artificial Intelligence
AICA 2020   O'Reilly AI Conference San Jose
EMNLP 2020   Conference on Empirical Methods in Natural Language Processing
AIKE 2020   IEEE Artificial Intelligence & Knowledge Engineering 2020
IEEE-CVIV 2020   2020 2nd International Conference on Advances in Computer Vision, Image and Virtualization (CVIV 2020)
Scopus-BDAI 2020   2020 International Conference on Industrial Applications of Big Data and Artificial Intelligence (BDAI 2020)
WI 2020   Web Intelligence