CIT Summer Series - David A. Fisher - Why Software Fails and Why AI cannot Help
This is a weekly session of the CIT Summer Series, with David A Fisher presenting 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: 03 Aug 2023
- Time: 06:30 PM to 08:00 PM
- All times are (UTC-06:00) Central Time (US & Canada)
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Meeting ID: 876 4406 8603
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- Starts 12 June 2023 06:00 AM
- Ends 03 August 2023 04:00 PM
- All times are (UTC-06:00) Central Time (US & Canada)
- No Admission Charge
Speakers
David A Fisher
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.
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.].