Re: AI for Understanding Human Goals

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
>>
>>
>>
>>