The Failure of Search: Let Many Flowers Bloom and… Die Alone and Sad
November 1, 2022
I read “Taxonomy is Hard.” No argument from me. Yesterday (October 31, 2022) I spoke with a long time colleague and friend. Our conversations usually include some discussion about the loss of the expertise embodied in the early commercial database firms. The old frameworks, work processes, and shared beliefs among the top 15 or 20 for fee online database companies seem to have scattered and recycled in a quantum crazy digital world. We did not mention Google once, but we could have. My colleague and I agreed on several points:
- Those who want to make digital information must have an informing editorial policy; that is, what’s the content space, what’s included, what’s excluded, and what problem does the commercial database solve
- Finding information today is more difficult than it has been our two professional lives. We don’t know if the data are current and accurate (online corrections when publications issue fixes), fit within the editorial policy if there is one or the lack of policy shaped by the invisible hand of politics, advertising, and indifference to intellectual nuances. In some services, “old” data are disappeared presumably due to the cost of maintaining, updating if that is actually done, and working out how to make in depth queries work within available time and budget constraints
- The steady erosion of precision and recall as reliable yardsticks for determining what a search system can find within a specific body of content
- Professional indexing and content curation is being compressed or ignored by many firms. The process is expensive, time consuming, and intellectually difficult.
The cited article reflects some of these issues. However, the mirror is shaped by the systems and methods in use today. The approaches pivot on metadata (index terms) and tagging (more indexing). The approach is understandable. The shift to technology which slash the needed for subject matter experts, manual methods, meetings about specific terms or categories, and the other impedimenta are the new normal.
A couple of observations:
- The problems of social media boil down to editorial policies. Without these guard rails and the specialists needed to maintain them, finding specific items of information on widely used platforms like Facebook, TikTok, or Twitter, among others is difficult
- The challenges of processing video are enormous. The obvious fix is to gate the volume and implement specific editorial guidelines before content is made available to a user. Skipping this basic work task leads to the craziness evident in many services today
- Indexing can be supplemented by smart software. However, that smart software can drift off course, so specialists have to intervene and recalibrate the system.
- Semantic, statistical, or behavior centric methods for identifying and suggesting possible relevant content require the same expert centric approach. There is no free lunch is automated indexing, even for narrow vocabulary technical fields like nuclear physics or engineered materials. What smart software knows how to deal with new breakthroughs in physics which emerge from the study of inter cell behavior among proteins in the human brain?
Net net: Is it time to re-evaluate some discarded systems and methods? Is it time to accept the fact that technology cannot solve in isolation certain problems? Is it time to recognize that close enough for horseshoes and good enough are not appropriate when it comes to knowledge centric activities? Search engines die when the information garden cannot support the buds and shoots of finding useful information the user seeks.
Stephen E Arnold, November 1, 2022
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