Why Software Fails and Why AI cannot Help
It was once widely believed that computers would enhance the speed, reliability, and applicability of human deductive reasoning in the physical and social sciences, much as motorized vehicles (e.g., cars, trains, airplanes) have enhanced the speed, reliability, and applicability of human manual abilities in transportation. Yet, 60 years later, computers can be used confidently only for paperwork tasks, analysis of regularly structured data, and simple process control applications. Complex software rarely satisfies user needs, is untrustworthy and difficult to maintain, and largely opaque to its users. Artificial intelligence (AI) methods including heuristics, machine learning, and statistical methods are in opposition to sound deductive reasoning. This presentation explains certain practical and logical impediments to computer enhancement of human deductive reasoning, the deductive limitations of modern programming languages, the role of AI, and provides some promising alternatives.
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- Date: 20 Oct 2022
- Time: 06:00 PM to 08:00 PM
- All times are (UTC-04:00) Eastern Time (US & Canada)
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- Starts 06 September 2022 09:00 AM
- Ends 19 October 2022 12:00 AM
- All times are (UTC-04:00) Eastern Time (US & Canada)
- No Admission Charge
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Why Software Fails and Why AI cannot Help
Biography:
David A Fisher is the founder and chief technologist at Reasoning Technology LLC and emeritus professor at Carnegie Mellon University (CMU). He has a Ph.D. in computer science from CMU, M.S.E from Moore School of Electrical Engineering at Univ. of Pennsylvania, and B.S. in mathematics from CMU. He was chief engineer for the CREATE high performance computing program within the Office of the Secretary of Defense, president of Incremental Systems Corporation, vice president for advanced development at Western Digital Corp (WDC), a program manager at National Institute of Standards and Technology (NIST), and a researcher at the Software Engineering Institute (SEI) . He has over 200 publications in programming language design, compiler construction, infrastructure protection and network security, bounded workspace and near linear time algorithms, embedded systems, theory of emergence, instruction set architectures, and high-performance computing. [ He lectures in the U.S., Canada, and Europe.].