- From: Paola Di Maio <paoladimaio10@gmail.com>
- Date: Tue, 26 Jan 2021 14:29:04 +0800
- To: Chris Fox <chris@chriscfox.com>
- Cc: Owen Ambur <Owen.Ambur@verizon.net>, W3C AIKR CG <public-aikr@w3.org>
- Message-ID: <CAMXe=SrJhxiFr2R0Ts45iCB0ScF-p+tcV4aXJ_CAFiQ+qh5yeQ@mail.gmail.com>
i think you are right Chris how silly of me- what about: using the algo to infer the goal from any non xml doc, then convert to stratml would that be useful? maybe thats what I was thinking pdm On Tue, Jan 26, 2021 at 2:23 PM Chris Fox <chris@chriscfox.com> wrote: > It wouldn't be much of an algorithm if it couldn't infer goals from plans > in which they are clearly demarcated in XML? > > I think what you'd really want to do is run the algorithm against anything > that *wasn't* StratML and see if it could produce StratML. > > On Tue, 26 Jan 2021 at 02:46, Paola Di Maio <paoladimaio10@gmail.com> > wrote: > >> Maybe Chris can run the algo on a stratml set >> >> On Tue, Jan 26, 2021 at 10:12 AM Owen Ambur <Owen.Ambur@verizon.net> >> wrote: >> >>> Yes, Paola, it would be great to see what AI/ML algorithms might be able >>> to do with the existing StratML collection, which now comprises >5K files >>> ... but even more so if and hopefully when public agencies start publishing >>> their *performance reports* in open, standard, machine-readable >>> format... as U.S. federal agencies are ostensibly required by law to do. >>> >>> I'm always on the lookout for partners who might be willing and able to >>> begin to demonstrate such capabilities. >>> >>> While the initial benefit of enabling taxpayers to see what they are >>> getting for their money will be great, imagine how AI agents can help >>> agencies learn from failure and thus improve their performance over time. >>> >>> It is painful to watch agency leaders continue failing to capitalize on >>> that potential. >>> >>> Indeed, recent direction from the Trump administration's OMB director >>> on the way out the door >>> <https://www.linkedin.com/feed/update/urn:li:ugcPost:6701562085794492416?commentUrn=urn%3Ali%3Acomment%3A%28ugcPost%3A6701562085794492416%2C6757844681394032640%29> >>> goes so far as to imply that agency leaders have no accountability for most >>> of the objectives with which they are entrusted, as if those objectives are >>> merely jokes being played on taxpayers. Unfortunately, all that seems to >>> matter is what suits The Politics Industry. The question is how long >>> voters and taxpayers will put up with such behavior. Hopefully, not >>> indefinitely. >>> >>> Owen >>> >>> On 1/25/2021 7:19 PM, Paola Di Maio wrote: >>> >>> Thank you Owen >>> wouldn't it be great to try the algorithm on some stratml resources >>> >>> >>> On Tue, Jan 26, 2021 at 12:04 AM Owen Ambur <Owen.Ambur@verizon.net> >>> wrote: >>> >>>> "In the quest to capture ... social intelligence in machines, >>>> researchers from MIT’s Computer Science and Artificial Intelligence >>>> Laboratory (CSAIL) and the Department of Brain and Cognitive Sciences >>>> created an algorithm capable of inferring goals and plans, even when >>>> those plans might fail." >>>> >>>> "... ability to account for mistakes could be crucial for building >>>> machines that robustly infer and act in our interests ... Otherwise, AI >>>> systems might wrongly infer that, since we failed to achieve our >>>> higher-order goals, those goals weren’t desired after all. We’ve seen >>>> what happens when algorithms feed on our reflexive and unplanned usage >>>> of social media, leading us down paths of dependency and polarization. >>>> Ideally, the algorithms of the future will recognize our mistakes, bad >>>> habits, and irrationalities and help us avoid, rather than reinforce, >>>> them." >>>> >>>> >>>> https://scitechdaily.com/new-mit-social-intelligence-algorithm-helps-build-machines-that-better-understand-human-goals/ >>>> >>>> Wouldn't it be nice if AI-assisted business networking services helped >>>> us avoid polarization and needless dependencies on The Politics >>>> Industry >>>> as we strive to achieve public objectives documented in an open, >>>> standard, machine-readable format? >>>> >>>> >>>> https://www.linkedin.com/pulse/politics-industry-v-we-people-magic-formula-owen-ambur/ >>>> >>>> Owen >>>> >>>> >>>> >>>> > > -- > Chris Fox > Chris C Fox Consulting Limited > chris@chriscfox.com > +44 77 860 21712 > <http://www.chriscfox.com> > <https://calendar.x.ai/chriscfox/freeconsult> > <https://www.linkedin.com/in/chriscfox/> > <https://twitter.com/chriscfox> > <https://www.facebook.com/StrategicCoffee> > Have you tried https://www.StratNavApp.com <https://www.stratnavapp.com/>, > the online collaborative tool for strategy development and execution? > > Chris C Fox Consulting Limited is registered in England and Wales as a > Private Limited Company: Company Number 6939359. Registered Office: Unit 4 > Vista Place, Coy Pond Business Park, Ingworth Road, Poole BH12 1JY >
Received on Tuesday, 26 January 2021 06:29:55 UTC