Artificial Intelligence (AI) & VisiRule

Different Types of AI

Narrow vs General AI

The White House "Preparing for the Future of AI" report stated:

"Remarkable progress has been made on what is known as Narrow AI, which addresses specific application areas such as playing strategic games, language translation, self-driving vehicles, and image recognition. Narrow AI underpins many commercial services such as trip planning, shopper recommendation systems, and ad targeting, and is finding important applications in medical diagnosis, education, and scientific research. These have all had significant societal benefits and have contributed to the economic vitality of the Nation."

"General AI (sometimes called Artificial General Intelligence, or AGI) refers to a notional future AI system that exhibits apparently intelligent behaviour at least as advanced as a person across the full range of cognitive tasks. A broad chasm seems to separate today’s Narrow AI from the much more difficult challenge of General AI. Attempts to reach General AI by expanding Narrow AI solutions have made little headway over many decades of research. The current consensus of the private-sector expert community, with which the NSTC Committee on Technology concurs, is that "General AI will not be achieved for at least decades."

You can read about this in VentureBeats "What is Artificial narrow AI (ANI)?".

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Academic AI vs Pragmatic AI

Historically, there has been a disconnect between the theoretically inclined academic community and the more pragmatic industrial researchers looking at AI. The academics have been almost trying to solve the complete challenge of understanding, modelling and replicating human conscious thought processes, whereas the pragmatists have just tried to use AI techniques to solve specific challenges. A good example is Watson by IBM, a computer program which was designed solely to beat the world's leading players in Jeopardy and succeeded. Whilst Watson was never intended to do any deep semantic analysis or attempt to derive the meaning behind questions, it was subsequently heralded as the 'answer' to many questions in law, healthcare and others.

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LPA are pragmatists. VisiRule strives to provide a transparent solution for delivering intelligent applications using both existing data and the knowledge of human experts, be they legal, medical, electrical or whatever.

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Hard AI vs Soft AI

The ABA states in 'How artificial intelligence is transforming the legal profession': "There are two types of artificial intelligence—hard and soft. Hard AI is focused on having machines think like humans, while soft AI is focused on machines being able to do work that traditionally could only be completed by humans. The main difference is that soft AI doesn’t necessarily involve machines thinking like humans."

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“Our perspective on artificial intelligence has changed significantly over the past several decades” says Jack Conrad, lead research scientist in corporate R&D at Thomson Reuters and president of the IAAIL. “AI failed to live up to the early expectations that focused largely on hard AI capabilities, such as the ability to perform human-like reasoning. When those lofty goals were not attained, researchers came to understand how difficult such achievements really were. After all, trying to teach computers to perform cognitive activities was an extremely challenging task. Over time, as expectations were lowered and research efforts became more narrowly directed, a shift towards ‘soft’ AI applications took place, focusing on providing intelligent tools and problem-solving resources to humans.”

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Knowledge Acquisition

A principal goal of VisiRule is to make it simple and easy-to-use, so that business users who understand their line of business can use it directly. Afterall, they hold the knowledge, and it is they that need help in extracting that precious knowledge and organizing it in a coherent and manageable way. VisiRule helps address this 'knowledge elicitation' problem, which historically has been the bottleneck in developing intelligent applications, by combining a visual model with rapid rule generation, instant compilation and immediate testing.

The key challenge is that of extracting and exposing knowledge which is buried within human brains, manuals, technical papers and transforming it into actionable rules to create automated systems. Experts do not know what they know, they often can not even explain how or why they came to a conclusion in a given situation. Concepts such as 'intuition' and 'instinct' are very, very hard to quantify and capture. VisiRule helps experts explore their own knowledge by providing a very soft and flexible framework.

Graphical Knowledge

VisiRule is a graphical tool which also plays the role of a rule generator. Rather than require the author define the rules using some rule language, the author simply draws a connected diagram which the VisiRule compiler translates into executable rules. The drawing task is helped by VisiRule knowing, to some extent, what the intended meaning and context is of each box as it is being drawn and/or linked. As the generated rule-base is executed, and questions presented, VisiRule can present a graphical view of the original chart and the active session.