The document discusses the concept of neural networks and machine learning as extensions of the mind in artificial intelligence, presenting ideas from the philosophy of mind. It explores how machines learn from sensory data and environmental cues, comparing this to biological cognition and the implications for hard AI. The author argues that neural networks exemplify the extended mind by processing external information and shaping cognitive responses.

1. Machine Learning and Neural Networks as Extended Mind Sarah Stewart – Philosophy of Mind March 2011

2. Outline Caution: “Work in Progress” Objective: Neural Networks and Machine Learning as examples of Extended Mind in AI What are neural networks? How do machines “learn”? How do Neural Networks exemplify Extended Mind? Implications for Hard AI Argument… Questions and Discussion…

3. Biological “Mind” Instinctive responses to environmental cues +/- reaction to external stimulii Cognition related to environmental stimulii

4. Machine Mind Relies on pattern recognition and organisation of information ( cf . Haugeland, 1997) Symbolic systems “ Hard AI” – Computer can reproduce the functions of the mind

5. Machine Learning Trained on datasets to incorporate models of real world Often requires a large diversity of datasets for real world operation (particularly in robotics) Machine “learns” from its experiences and from sensory data gleaned from the external environment.

6. Artificial Neural Networks Algorithmic model based on synapses in the brain. Usually involves a sensory layer (input) and output layer. Input from sensory systems or external databases.

7. Uses of Neural Networks Function Approximation (time series prediction) Classification (data mining, decision-making, pattern and sequence recognition Data processing (filtering, clustering, blind signal recognition) “ Fuzzy” conditions – multivariate, non-linear systems ideal! NASA’s AEMC ANN for Plant Growth Monitoring (http://aemc.jpl.nasa.gov/activities/bio_regen.cfm)

8. Extended Mind ( cf . Clark and Chalmers, 1998) Integration/coupling of mind-body and external environment External environment becomes part of cognitive mind, integrated with the self – Active Externalism Criteria: external objects function with same purpose as internal thoughts

9. Neural Nets as Extended Mind? Recognition of patterns of sensory input from external sources (databases, sensor input) Complex statistical processors to formulate output (decisions, classifications, responses) Must decide from a great diversity and variety of responses – cognitive objects in external environment

10. Extended Mind in AI Machine learns and experiences its external environment through neural networks Uses environment to shape mind – coupling of mind and environment Supports Hard AI argument for consciousness?