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Synthesizing Intelligence

Synthesizing Intelligence

We are constantly getting better at designing software tools to help us navigate an ever growing ocean of information and negotiate methods of applying it wisely. We ask our tools for advice and decide how to use the advice they offer. We use some of these new tools to aid in the design of better tools. Our tools offer better advice as they improve. We accept the advice with greater confidence as the quality level improves.

The combination of organically developed human intelligence with artificially developed digital advisors (verticallized AI) is creating a synthetic hybrid quasi-intelligence that can outperform either by themselves.

Meet Amy, Your Personal AI Assistant – [medium.com/backchannel]

The degree to which scheduling meetings totally sucks needs no introduction. Few parts of professional life are as clunky. For well over half a century artificial intelligence has been heralded as the panacea for our woes; after all, Isaac Asimov penned the 3 laws of robotics in 1942. With intelligent systems now being deployed to, among other things, count the number of cars on a bridge or write news articles, computers seem to have attained sufficient power and learning ability to finally force real change.

But asking a computer to maintain a complicated human interaction demands far more sophistication. Ten years ago as soon as you heard the automated voice of customer service you’d start howling “Operator!” Now those systems are almost — almost — bearable. On many company websites you can instant-message with a virtual agent about your issues. But if you get stuck, you can usually find a path back to a human. That path is important, because no AI can handle all the small quirks of human conversation and the nuanced needs of every customer. This is why many developers and upstarts zero in on a specific problem, or what Mortensen calls “verticalized AI.”

The Three Breakthroughs That Have Finally Unleashed AI on the World – [wired.com]

If AI can help humans become better chess players, it stands to reason that it can help us become better pilots, better doctors, better judges, better teachers. Most of the commercial work completed by AI will be done by special-purpose, narrowly focused software brains that can, for example, translate any language into any other language, but do little else. Drive a car, but not converse. Or recall every pixel of every video on YouTube but not anticipate your work routines. In the next 10 years, 99 percent of the artificial intelligence that you will interact with, directly or indirectly, will be nerdily autistic, supersmart specialists.

What we want instead of intelligence is artificial smartness. Unlike general intelligence, smartness is focused, measurable, specific. It also can think in ways completely different from human cognition.

Synthetic Intelligence (SI) – [conceptualizedintelligence.com]

As we develop intelligence, we learn to abstract basic patterns from the swirl of chaotic information around us. Then we learn to extrapolate expansions and trends based upon those basic abstractions and this allows us to begin to predict. By observing the success of our predictions, we can modify the process of abstraction and extrapolation to improve our predictions. Eventually, we attempt to replicate some pattern and apply it in a new environment. All of this accumulates knowledge.

Eventually, we get to a point where we have sufficient intelligence tools and accumulated knowledge to synthesize new abstract patterns that we have never observed but can postulate by need.

When our ability to synthesize reaches a point of creating a new standalone node of conscious intelligence, it should be called Synthetic Intelligence or SI.

Post Biological Intelligence
Through a Wormhole of Intelligence
After the Singularity
Artificial Ethics

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