Google and The Red Queen – An Essay By Extropia DaSilva


But what about search software? As something like Google gets better at recognising patterns in text, audio and video, and as their ability to extract high-level knowledge from low-level information becomes ever more effective, what different form might they evolve into? This is what Peter Norvig, Director of Research at Google, thinks:

“Instead of typing a few words into a search engine, people will discuss their needs with a digital intermediary, which will offer suggestions and refinements. The result will not be a list of links, but an annotated report (or a simple conversation) that synthesizes the important points”.

To me, that sounds less like a tool that you use, and more like a digital person that collaborates with you on whatever project. If you think about it, it is obvious that Google will evolve in this direction. For one thing, search engines attempt to do what human brains evolved to excell at, which is finding meaningful patterns within cultural information in all its guises.

Secondly, humans evolved to learn from other humans. It is the method of knowledge acqusition that they are most comfortable with. It stands to reason then, that the more effectively computers, AI and robots can work in familiar ways within their social networks (preferably not being annoying like the notorious ‘Clippy’) the more comfortable they will become in their presence.

Researchers at Stanford University have shown that in-car assistance systems encourage us to drive more carefully if the voice matches our mood, and researchers at the University of Southern California found that a robotic therapist had more influence if its personality matched that of its human patient.

“Emotion is one of the crucial factors influencing the success or failure of communication between humans”, said Shuji Hashimoto of Washeda University, Tokyo. “Robots are going to need similar emotional capabilities if they are to work smoothly and effectively in our residential environments”.

As with the emergence of the Digital Gaia’s all-pervasive surveillance system, this transformation from mere tool to collaborating partner will result from many thousands of tiny steps. As companies like Google get better at finding high-level knowledge, the search engines will become more effective at determining a person’s location, their current mood, what prior knowledge they have and their individual learning style.

Such things will be increasingly incorporated into a search engine’s database, enabling it to become better and better at finding exactly what you need, tailor-made to suit your personal ability. We may even speculate that future search engines will form theories of mind that enable them to anticipate when we are about to get stuck, and deliver timely advice that helps us find an effective solution.  Somewhere along this evolutionary route, the transformation from mere tool to collaborating digital person will occur. Just possibly, the change will be so subtle that we hardly notice it until we look back in retrospect to Google as it was in 2008.

By now, you have probably guessed what this has to do with avatars.

The Metaverse Roadmap’s vision for ‘avatar-mediated communication’ sounds rather like Peter Norvig’s digital intermediaries: “Given trends in automated knowledge discovery, knowledge management, and natural language processing, within ten years a caller should be able to have a primitive yet useful natural conversation with an avatar. This will include information about the user’s background, interests… answer FAQs and perform other simple transactions”.

It seems to me that it will be avatars that will trace the ultimate endpoint for search software evolution, which goes beyond any mere personal assistant bot.

As we move into an era of lifelogging, digital memories, and the automatic capturing of ‘memes’ and ‘bemes’ (the former being transmissible elements of culture relevant to a society as a whole, and the latter being highly individual elements of personality, mannerisms, recollections, stuff like that) we should expect a positive-feedback loop. The better the digital intermediary gets at finding meaningful patterns in data, the more it knows about you. And the more it knows about you, the better it gets at finding meaningful patterns in data.

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