- From: David Booth <david@dbooth.org>
- Date: Sat, 6 Jul 2024 20:31:47 -0400
- To: public-aikr@w3.org
On 7/5/24 03:17, Dave Raggett wrote: > Just to note that machine readable formats now includes natural > language, images, video and sound. AI is good at handling imperfect > knowledge, I don't disagree with AI's ability to handle imperfect knowledge, but I do wish to quibble about the term "machine processable". I have been using terms like "machine readable" or "machine processable" for decades as a way to distinguish between formats that are readily amenable to precise, deterministic interpretation versus formats that can only be interpreted heuristically and not necessarily correctly. This is a key difference, for example, between a data formats like RDF and natural English. I have found this distinction useful, because The former requires a relatively tiny amount of processing power; the latter requires enormous amounts to reach high accuracy of interpretation, and even at its best you can never be sure that the machine guessed it right. Applying the term "machine processable" to natural language muddies the water, making it more difficult to identify and discuss this important qualitative difference. Thanks, David Booth e.g. imprecise and context sensitive information. However, > most knowledge is imperfect. In everyday life, argumentation is > commonplace with logic relegated to areas where formal models are a good > enough approximation, and moreover can provide valuable precision. > > The carbon footprint for AI is clearly a problem, and may limit how much > it is applied. As neuromorphic technologies improve, the energy demands > will dwindle, but this may take many years to come to fruition. I wonder > if techniques to derive symbolic knowledge from LLMs can provide a > shorter term solution, provided we use approaches that target imperfect > knowledge, such as the Plausible Knowledge Notation(PKN), where the > energy demands should be much better than for LLMs themselves. > >> On 4 Jul 2024, at 18:14, Owen Ambur <owen.ambur@verizon.net> wrote: >> >> Theoretically, yes, Paola, not only could more mature query services >> enable more precise discovery of machine-readable information but also >> more effective analysis and usage of it. >> >> Practically speaking, however, the incumbent search engines are not >> doing that and the AI/ML services are focusing (and spending >> unfathomable amounts of money and energy) on making sense of less >> mature, unstructured information. I view it as a case of artificial >> ignorance >> <https://www.linkedin.com/pulse/artificial-ignorance-owen-ambur/>. >> >> Your message prompted me to engage Claude.ai along this train of >> thought, to which it concluded: >> >> This situation raises important questions about the >> discoverability of structured data formats like XML on the web. It >> might indicate a need for better practices or standards in how >> such data is made available and indexed by search engines. >> >> >> Amen! Indeed, ChatGPT concludes >> <https://chatgpt.com/share/214b956a-c402-42ee-8843-708d3501997e>: >> >> By leveraging ... XML structures, search engines can more >> effectively crawl, index, and present web content, ultimately >> improving search relevance and user experience. >> >> >> With respect to strategic plans and performance reports, as well as >> website about us statements, I'm working toward that end at >> https://search.aboutthem.info/ <https://search.aboutthem.info/> >> >> Note also that U.S. federal agencies have been directed, by law >> <https://www.linkedin.com/pulse/open-gov-data-act-machine-readable-records-owen-ambur/>, to create and manage their records in machine-readable format. So the degree to which they begin doing so will be a key indicator of their accountability and trustworthiness. Moreover, since publishing information in open, standard, machine-readable format is a generic best practice, the same is true of agencies at all levels of government, worldwide. >> >> So this is much bigger than just a techie issue. It is key to the >> effectiveness and accountability of governments -- including allies >> and partners -- in the entire "free world". >> >> Incidentally, during less contentious times, China was among the five >> nations that initially agreed to work on the StratML standard in 2013 >> <https://stratml.us/history.htm#2013>. >> >> See also these StratML use cases: >> >> Goal 14: Partnerships & Multi-Organization Groups >> <https://stratml.us/carmel/iso/UC4SwStyle.xml#_0fc1e310-08a5-11e6-b06f-a2fa45c7ae33> ~ Use the Relationship elements to cross-reference common and complementary objectives in the plans of each member of a partnership, consortium, or other informal group. >> >> Goal 26: Conflict Resolution Services >> <https://stratml.us/carmel/iso/UC4SwStyle.xml#_203da842-d612-11e6-bf2d-1dd10ebcdb3b> ~ Document the personal values as well as the longer-term goals and near-term objectives of individuals and organizations in conflict. >> Goal 27: E-Diplomacy & International Development >> <https://stratml.us/carmel/iso/UC4SwStyle.xml#_de8587c0-46e2-11e7-9757-2508ff1fc704> ~ Publish plans in StratML format to support establishment of innovative tools for diplomacy and international development. >> >> >> As the sponsor of the XML and XSD standards, it would be nice to think >> the W3C might be up for the challenge of more enlightened leadership >> in their application and usage. If not, I trust that entrepreneurs >> will eventually capitalize on that opportunity and creatively destroy >> the incumbent powers-that-be. >> >> In the meantime, an unbelievable amount of money and energy is being >> wasted on outmoded practices, which of course serves the interests of >> those profiting from such inefficiencies. >> >> Owen Ambur >> https://www.linkedin.com/in/owenambur/ >> <https://www.linkedin.com/in/owenambur/> >> >> >> On Thursday, July 4, 2024 at 02:49:19 AM EDT, Paola Di Maio >> <paoladimaio10@gmail.com> wrote: >> >> >> Congrats Owen >> for publishing something on the web that machine can find and use >> Is it because machine simply looks for the machine readable info? >> >> On Thu, Jul 4, 2024 at 2:12 AM Owen Ambur <owen.ambur@verizon.net >> <mailto:owen.ambur@verizon.net>> wrote: >> >> When first I asked, ChatGPT disclaimed having any developers much >> less a plan. However, upon prompting, it disclosed the plan >> outlined in StratML format at https://stratml.us/docs/CGPT.xml >> <https://stratml.us/docs/CGPT.xml> >> >> Likewise, Claude.ai was a bit skittish about divulging its >> objectives but also disgorged some upon prompting, at >> https://stratml.us/docs/CLD.xml <https://stratml.us/docs/CLD.xml> >> >> From my perspective, a good explanation would report in open, >> standard, machine-readable format reliable metrics by which human >> beings can readily comprehend how well the avowed objectives are >> being served. >> >> I'll look forward to learning what other alternative there might be. >> >> Owen Ambur >> https://www.linkedin.com/in/owenambur/ >> <https://www.linkedin.com/in/owenambur/> >> >> >> On Tuesday, June 11, 2024 at 05:24:00 AM EDT, Dave Raggett >> <dsr@w3.org <mailto:dsr@w3.org>> wrote: >> >> >> First my thanks to Paola for this CG. I’m hoping we can attract >> more people with direct experience. Getting the CG noticed more >> widely is quite a challenge! Any suggestions? >> >> >>> It has been proposed that without knowledge representation. there >>> cannot be AI explainability >> >> That sounds somewhat circular as it presumes a shared >> understanding of what “AI explainability” is. Humans can explain >> themselves in ways that are satisfactory to other humans. We’re >> now seeing a similar effort to enable LLMs to explain themselves, >> despite having inscrutable internal representations as is also >> true for the human brain. >> >> I would therefore suggest that for explainability, knowledge >> representation is more about the models used in the explanations >> rather than in the internals of an AI system. Given that, we can >> discuss what kinds of explanations are effective to a given >> audience, and what concepts are needed for this. >> >> Explanations further relate to how to making an effective argument >> that convinces people to change their minds. This also relates to >> the history of work on rhetoric, as well as to advertising and >> marketing! >> >> Best regards, >> >> Dave Raggett <dsr@w3.org <mailto:dsr@w3.org>> >> >> >> > > Dave Raggett <dsr@w3.org> > > >
Received on Sunday, 7 July 2024 00:31:55 UTC