BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20240310T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20241103T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20240323T160838Z UID:28A5CE24-C3F6-4065-9B47-48C23659A9F3 DTSTART;TZID=America/New_York:20240316T100000 DTEND;TZID=America/New_York:20240316T111000 DESCRIPTION:EPIC AI Failures\; Two AI Medical Case studies\, MYCIN and WATS ON\n\nAbstract: EPIC\, describing AI Failures are carefully worded and sel ected and meant to consider the level of failure when understanding MYCIN\ , a significant and historical rules-based LISP expert system. MYCIN began in 1974 with a team of Stanford MD's and PhDs led by Bruce G. Buchanan an d Edward H. Shortliffe\, spanning 10 years of MYCIN experiments and culmin ating with a publication of the classic MYCIN AI study\, "RULE-BASED EXPER T SYSTEMS: THE MYCIN EXPERIMENTS OF THE STANFORD HEURISTIC PROGRAMMING PRO JECT" by Buchanan and Shortliffe. For my Masters work in the mid80's\, I w as given the assignment to read (748 pages!)\, write an analysis of this w ork\, and to write in LISP a backward-chain inference engine. The book foc used on the need for MD's to rapidly identify both the specific bacteria i nfection agent and corresponding antibiotics.\n\nTwenty two years after MY CIN was released and no longer used by MD’s\, my sister\, father\, and m other were all victims of the lengthy time (~ 3 days) hospitals and labs r equired to incubate (in a petri dish) and identify both the infectious bac teria and the effective antibiotic. Three members of my family passed afte r 2 days and just before the answers came in from the lab. Hence my frustr ation. We are in the year 2024\, and the same test was applied in the 80's but the number of effective antibiotics is reduced! In some cases\, refer enced to the number zero. IBM's WATSON was introduced in 2011 as the AI qu estion-answering computer that beat Ken Jennings in "Jeopardy". IBM focuse d WATSON on answering significant medical problems and we will discuss why this system failed even after IBM spent over 60 million dollars and creat ed Medical partnerships. To end on a positive note\, we will mention embed ded ML and prove smart sensors have been measurably successful. You will f ind this well-referenced speech fascinating!\n\nBio: The speaker\, Joe Jes son\, co-founded & was CTO of a General Electric business\, Asset Intellig ence\, a GE business that designed\nand sold remote IoT sensors for the lo gistics and energy sectors. Machine learning and LPWAN sensor communicatio n became an\nintegral part of the remote monitoring and management of mobi le and remote assets. An ongoing research goal is to reduce the smart\nene rgy costs where 100% of the power is generated by ambient energy harvestin g. Joe is currently CEO of RF Sigint Group and has\nover 25+ years of engi neering and management experience with Motorola APD\, Oak Technology\, BP\ , and General Electric. Master's\ndegree from DePaul University & working on a Ph.D.defense. Contact: jejesson4@gmail.com\n\nNote: this is a TCF Eve nt - No need to register\, but you need to purchase a TCF all-day admissio n ticket at https://tcf-nj.org/\n\nRoom: ED204\, Bldg: Education Building \, The College of New Jersey\, Metzger Dr\, Ewing\, New Jersey\, United St ates\, 08618 LOCATION:Room: ED204\, Bldg: Education Building \, The College of New Jerse y\, Metzger Dr\, Ewing\, New Jersey\, United States\, 08618 ORGANIZER:jejesson4@gmail.com SEQUENCE:17 SUMMARY:EPIC AI Failures\; Two AI Medical Case studies\, MYCIN and WATSON URL;VALUE=URI:https://events.vtools.ieee.org/m/409971 X-ALT-DESC:Description: <br /><h3 class="ieee_primary_blue">EPIC AI Failure s\; Two AI Medical Case studies\, MYCIN and WATSON</h3>\n<p><strong>Abstra ct</strong>: EPIC\, describing AI Failures are carefully worded and select ed and meant to consider the level of failure when understanding MYCIN\, a significant and historical rules-based LISP expert system. MYCIN began in 1974 with a team of Stanford MD's and PhDs led by Bruce G. Buchanan and E dward H. Shortliffe\, spanning 10 years of MYCIN experiments and culminati ng with a publication of the classic MYCIN AI study\, "RULE-BASED EXPERT S YSTEMS: THE MYCIN EXPERIMENTS OF THE STANFORD HEURISTIC PROGRAMMING PROJEC T" by Buchanan and Shortliffe. For my Masters work in the mid80's\, I was given the assignment to read (748 pages!)\, write an analysis of this work \, and to write in LISP a backward-chain inference engine. The book focuse d on the need for MD's to rapidly identify both the specific bacteria infe ction agent and corresponding antibiotics.</p>\n<p>Twenty two years after MYCIN was released and no longer used by MD&rsquo\;s\, my sister\, father\ , and mother were all victims of the lengthy time (~ 3 days) hospitals and labs required to incubate (in a petri dish) and identify both the infecti ous bacteria and the effective antibiotic. Three members of my family pass ed after 2 days and just before the answers came in from the lab. Hence my frustration. We are in the year 2024\, and the same test was applied in t he 80's but the number of effective antibiotics is reduced! In some cases\ , referenced to the number zero. IBM's WATSON was introduced in 2011 as th e AI question-answering computer that beat Ken Jennings in "Jeopardy". IBM focused WATSON on answering significant medical problems and we will disc uss why this system failed even after IBM spent over 60 million dollars an d created Medical partnerships. To end on a positive note\, we will mentio n embedded ML and prove smart sensors have been measurably successful. You will find this well-referenced speech fascinating!</p>\n<p><strong>Bio: < /strong>The speaker\, Joe Jesson\, co-founded &amp\; was CTO of a General Electric business\, Asset Intelligence\, a GE business that designed<br>an d sold remote IoT sensors for the logistics and energy sectors. Machine le arning and LPWAN sensor communication became an<br>integral part of the re mote monitoring and management of mobile and remote assets. An ongoing res earch goal is to reduce the smart<br>energy costs where 100% of the power is generated by ambient energy harvesting. Joe is currently CEO of RF Sigi nt Group and has<br>over 25+ years of engineering and management experienc e with Motorola APD\, Oak Technology\, BP\, and General Electric. Master's <br>degree from DePaul University &amp\; working on a Ph.D.defense. Contac t: jejesson4@gmail.com</p>\n<p><strong>Note: this is a TCF Event - No need to register\, but you need to purchase a TCF all-day admission ticket at <a href="https://tcf-nj.org/">https://tcf-nj.org/</a></strong></p> END:VEVENT END:VCALENDAR