Doc’s — Where Search Ends and Knowledge Begins!

In the past, street maps on paper were often unwieldy, origami-like traveling companions. While these maps had all the streets and roads named, they had very little else — no information on how to find commonly sought destinations or the best routes to travel to destination, for example.

Digital map services solved this problem by simply overlaying location map-pins to identify and highlight common destinations and entities — landmarks, restaurants, hospitals, schools, and so on — and route and destination information. The added-value and utility provided by map-pin overlays made navigating to unfamiliar destinations faster, easier, and less risky for everyone.

Today’s search engine results are limited as knowledge companions

Today’s search engines are like paper street maps. While they provide information for things we are already familiar with or trivial content, they are of very little help in discovering unfamiliar but important informational content we might really need.

A mix of experience, caution and laziness exacerbates this content discovery problem. That is, beyond the first or second page of search results provided, few of us ever look at anything more. In other words, we have conditioned ourselves to assume search results beyond those two pages are both far less relevant, likely to be riskier and thus a waste of time. But we really have no idea what is there.

These content discovery problems become really acute when searching for something we need to know — health, children, school, work, money, legal issues, business, and so on. When it is important to find reliable — credible, accurate and up to date — information that is totally unfamiliar, search engine results can be a pain.

At this point, instead of being the ultimate library of knowledge, using the Internet can become tedious “work.” And, while this work is similar to traditional library research, the fact is, it is far riskier in numerous ways (e.g., malware, viruses, scams, click-bait, porn).

In the end, search engines do nothing to indicate what is reliable or has quality content. In other words, there is no equivalent of “map-pins” overlaid onto search results.

Why don’t search engines have the equivalent of map-pins?

That is, search-pins.

The simple reason for these discovery problems is that search engines are mathematical algorithms. They are great at “counting” the number of links going to and from content providers to create a score for what is most “popular.” So the content with the highest score — the most popular — is what appears at the top of search results lists and arbitrarily described as the most “relevant.”

This raises the obvious question: How does link popularity and relevance relate to content reliability? Short answer — it doesn’t.

Fact: no algorithm can read, understand and qualitatively evaluate the substance of written and or spoken content on the Internet the way people understand and evaluate content reliability and quality.

Exacerbating these discovery problems is advertising and search engine optimization (SEO) techniques. The sole purpose of SEO is to game and manipulate search algorithms. The intent is to secure a top placement on the first or second page of search result regardless of the merits of the content.

Help from traditional companions — family and friends — is a mixed bag

So, when seeking to find need to know content, the default approach for most of us tends to be family and friends. However, unless they have strong first-hand knowledge of the topic or substantive direct experience, their opinions and antidotal suggestions are rarely better than today’s search engines.

Help from hitch-hikers — crowdsourcing and experts — is also a mixed bag

Crowdsourcing can be useful if there are sufficient quality control mechanisms on the content recommended. Unfortunately, this is rarely the case. Often the active participants in these services represent extreme points of view, or worse, game the results to advance special interest agendas.

Expert services can be worthwhile but the cost of generating reliable content in-house severely limits the scope of topics that can be covered adequately. More problematic is that experts can have biases, conflicts of interest, or be too conservative in recognizing or accepting superior content that is new, unfamiliar or approaches a subject differently.

Finally, even when certain crowdsourcing or expert services do provide reliable content, the discovery problem with search engines remains the same. That is, independently, each of us must

  • Find these resources within the global Internet phonebook
  • Judge the qualitative, substantive merits of all content found
  • Finally, even for those with good research skills and patience, this exercise can be extremely time-consuming and fraught with risks

In theory, machine learning (all the rage today) will eventually deliver qualitatively better search results. However, short of a truly artificial general intelligence (AGI) breakthrough (consensually, at least a decade or two away) today’s search engines are all there is.

Search-pins must become our new knowledge companions

Search-pins are an easy, straightforward way to eliminate the problem of discovering reliable content.

Curated database

The key is to first develop a curated database of superior content providers in topics people will need-to-know in the course of daily life but tend to ignore until the need arises.

In creating this database, it is critical to understand there is no one single content provider capable of adequately covering all dimensions of any given topic. In other words, there is no such thing as a “one size fits all” answer for any search query. Rather, as in any other real life situation, invariably there is a cluster of multiple resources from different sources, each with a slightly different approach to a given topic that could best fit the specific need.

In this respect, what is important is that the criteria used in evaluating content start by defining what constitutes an “ideal, superior” content resource within the specific topic. For example, criteria defining excellence in a medical topic will be completely different from the criteria used to define an ideal resource in a legal topic.

Interface and search-pins

Once the database is established and a search is made, the list of search results can automatically be compared with the database in real-time and search-pins indicating reliability scores overlaid onto the results list. (Full disclosure, this is what my company provides.)

Where Search Ends and Knowledge Begins!

Search-pins are a needed short-cut to discovering reliable content and knowledge on the Internet and filtering out the rest. It is simply the next, natural — less risky and time saving — evolutionary step in search engines.

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