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ECE 5444 - Advanced Technological Singularity (3C)

Course Description

Investigation, conceptualization and analysis of Technological Singularity -- the potential impact of true artificial machine intelligence on engineering and society. Historical perspectives. Barriers to whole brain emulation and the engineering of superintelligence. The role of consciousness in achieving true machine intelligence. Potential scenarios if superintelligence would come into being. Pre: Graduate Standing

Why take this course?

This course is needed at Virginia Tech because many prominent figures believe that true Artificial Intelligence (AI) will arrive during the careers of our current class of engineering students, creating widespread disruption on society. And yet, while many of our students perform research in machine learning, few can articulate what true machine intelligence would look like, or mean for society, if it would emerge. Awareness of the potential implications of true machine intelligence, as well as identification of what true machine intelligence would look like, will be an enormous differentiator of our engineering students. The study of true machine intelligence is also an ideal focus for social and ethical awareness of the central role engineers play in the shaping of the future of, to include the potential survival of, humankind. This course fits with machine learning and computer systems areas, but is appropriate for all ECE graduate students. The quest for AI dates back to the days of Alan Turing, but true machine intelligence still remains a holy grail of computing. AI has become more identified with algorithmic solutions such as neural nets and machine learning, none of which come close to the essence of true machine intelligence. While AI has been seen as a purely algorithmic (software) solution, the concept of Technological Singularity (TS) also encompasses structure, self-replication and economic and societal impacts. TS has re-raised the questions of identification, limitations, challenges, impact and desirability of true machine intelligence.

Learning Objectives

  • 1. Place historical predictions of machine intelligence into perspective.
  • 2. Identify and quantify barriers to achieving whole brain emulation.
  • 3. Articulate goals and limitations in the engineering of true machine intelligence.
  • 4. Develop and critique potential societal impacts and desirability of superintelligence.
  • 5. Research and assess how the arrival of true artificial intelligence could impact to their own research/thesis domain.