University Course Planner The University of Adelaide Australia

PHIL 7005 - Machine Learning and Artificial Intelligence

Career: Postgraduate Coursework
Units: 3
Term: Trimester 3
Campus: North Terrace
Contact: Up to 3 hours per week
Restriction: This course is available to students enrolled in any relevant Postgraduate Masters degree, subject to approval by the relevant Department.
Available for Study Abroad and Exchange: No
Available for Non-Award Study: No
Incompatible: PHIL 7005OL
Assessment: Online assignments 50%, Essay/Assignments 50%
Syllabus:

Spectacular advances in Artificial Intelligence (AI) are the result of applying techniques of Deep Learning in Artificial Neural Networks (DLANNs) to a host of problems (face and speech recognition, data collection and customization, translation, navigation, conversation, industrial production, child and aged care) intractable to previous generations of computational systems. So much so that some have predicted the replacement of human by superior artificial intelligence in many domains with catastrophic results. Other argue that interface with DLANNs is already changing the nature of human cognition by enabling the harvesting and deployment of massive amounts of data by algorithms whose operations are opaque to everyday understanding. Deep Learning systems raise a series of related questions about the nature of intelligence and reasoning, bounded rationality, learning, ethical reasoning, emotion, human sociality and, ultimately, cognition itself. This course looks at those issues in depth. It is suitable for computer scientists interested in contextualizing their work in a wider theoretical and practical framework and others interested acquiring a deeper understanding of Machine Learning. No knowledge of coding or relevant mathematics is assumed. Topics covered may include the nature of representation in Deep Learning networks (compositional and hierarchical) and differences between DLANNs and other forms of computation; ethical decision making by humans and DLANNs; empathy and emotion in human/AI interactions; the nature of reinforcement learning; Bayesian reasoning; the role of emotion in deliberation; how contextual information is represented in human and artificial systems; Noam Chomsky versus Deep Learning. Chomsky, a founder of the “cognitive revolution” remains a sceptic arguing that DLANNS represent a quantitative ( exponentially more and faster) not a qualitative improvement in cognition. Students from any background should come away with a deeper understanding not only of DLANNs but of the nature of thought itself.

Course Fees

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Student Status

Domestic
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What type of place are you studying in

Commonwealth supported
Full fee paying

Study Level

Undergraduate
Postgraduate Coursework
Non Award

Program of Study

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Only some Postgraduate Coursework programs are available as Commonwealth Supported. Please check your program for specific fee information

Units
EFTSL
Amount
3
0.125
          
  


Course Outline

A Course Outline which includes Learning Outcomes, Learning Resources, Learning & Teaching for this course may be accessed here


Critical Dates

Term Last Day to Add Online Census Date Last Day to WNF Last Day to WF
Trimester 3 Mon 19/09/2022 Wed 21/09/2022 Fri 28/10/2022 Wed 23/11/2022


Class Details

Enrolment Class: Seminar
Class Nbr Section Size Available Dates Days Time Location
36413 SE01 60 44 5 Sep - 21 Nov Monday 3pm - 5pm Ingkarni Wardli, 232, Teaching Room