Towards Artificial Common Sense

 The key part of AI we don't know h0w to do yet. Good overview of current state and directions.   What most all of us consider the important starting point for useful intelligence.  It is often also has the ability to explain why and how it came to a conclusion.

Seeking Artificial Common Sense   By Don Monroe  in CACM

Communications of the ACM, November 2020, Vol. 63 No. 11, Pages 14-16 10.1145/3422588

Although artificial intelligence (AI) has made great strides in recent years, it still struggles to provide useful guidance about unstructured events in the physical or social world. In short, computer programs lack common sense.

"Think of it as the tens of millions of rules of thumb about how the world works that are almost never explicitly communicated," said Doug Lenat of Cycorp, in Austin, TX. Beyond these implicit rules, though, commonsense systems need to make proper deductions from them and from other, explicit statements, he said. "If you are unable to do logical reasoning, then you don't have common sense."

This combination is still largely unrealized; in spite of impressive recent successes of machine learning in extracting patterns from massive data sets of speech and images, they often fail in ways that reveal their shallow "understanding." Nonetheless, many researchers suspect hybrid systems that combine statistical techniques with more formal methods could approach common sense.

Importantly, such systems could also genuinely describe how they came to a conclusion, creating true "explainable AI" (see "AI, Explain Yourself," Communications 61, 11, Nov. 2018).   ... " 

New Tries at Common Sense Reasoning

We saw it at the very beginning, common sense reasoning is the key part of creating the most useful and powerful kinds of AI. There have been many attempts to do this, we tested a number, but they did not past our tests.  The excerpt from a non technical article from Wired below describes the challenge.  Looking forward to see more.

Watson's Creator Wants to Teach AI a New Trick: Common Sense
David Ferrucci built a computer that mastered Jeopardy. Since then, he's been attacking a more challenging task.   .... '

Ferrucci and his company, Elemental Cognition,    hope to fix a huge blind spot in modern AI by teaching  machines to acquire and apply everyday knowledge that lets humans communicate, reason, and navigate our surroundings. We use common sense reasoning so often, and so easily, that we barely notice it.

Ernest Davis, a professor at NYU who has been studying the problem for decades, says common sense is essential for advancing everything from language understanding to robotics. It is “central to most of what we want to do with AI,” he says.  .... "

Also see Elemental's blog.

Machine Common Sense

Been a challenge for along time. At DARPA and elsewhere.   One of our first challenges during the first AI revolution.     Putting humans in the loop is the easiest current solution, assuming you can leverage the common sense they have.     We engaged briefly with CYC on this, they were working with the US government then, busily encoding all human common sense, where is that now?

DARPA Embraces ‘Common Sense’ Approach to AI  By George Leopold in Datanami

The Pentagon’s top research agency is focusing its considerable AI efforts on the interim stage of machine intelligence between “narrow” and “general” AI.

The Defense Advanced Research Projects Agency (DARPA), which announced a multi-year $2 billion “AI Next” “campaign last month, is tightening its focus on teaching machine “common sense” reasoning. That capability remains beyond the reach of current AI constructs, and the research agency said it hopes to launch a “third wave” of AI technology that is adaptable while shedding light on the mystery of how machines learn.

Common sense reasoning is defined as “the basic ability to perceive, understand, and judge things that are shared by nearly all people and can be reasonably expected of nearly all people without need for debate.”

AI experts note the gap between AI inference and the ability to design systems that can draw directly on the rules of inference to achieve common sense reasoning. “Articulating and encoding this obscure-but-pervasive capability is no easy feat,” DARPA program managers note.

The lack of machine common sense is also seen as among the biggest barriers to advancing beyond narrow to general AI applications. The DARPA effort, dubbed “Machine Common Sense,” seeks to move beyond current frameworks that the agency considers “brittle” and lacking in semantic understanding. .... "

Reasoning with Common Sense

Can we teach machines common sense?  Which points back to our own look at the work Doug Lenat was doing with the Cyc Project. We wanted to create a means by which an agent could understand the basic terminology and goals of an organization like a company, and reason about it with the right language and direction.  That did not happen,  but the goal is still there.   And Cycorp has been active for 34 years, and produced a stable software release just three months ago.  We talked to them back then, but it didn't meet our needs. And every time we make some progress, like our broad use of assistants, now in many homes, we see the need again.

See the Cyc Wikipedia Article.  and

The Limits of Explainability
Academics, economists, and AI researchers often undervalue the role of intuition in science. Here's why they're wrong.
by Joi Ito in Wired ....

Paul Allen Wants to Teach Machines Common Sense 
By Cade Metz in the NYT. .... "

Toward a Layer of Common Sense

Admittedly dated, but been reexamining the 'common sense' ontology Cyc again recently, this article reexamines the premise and progress. Circa 2005. I recall thinking that we might be able to build our own ontologies on top of this one. Give them a layer of badly needed common sense.   Has anyone done that for enterprise applications?  Pointers to experience?

Finally Leveraging 30 Years of Knowledge in AI?

In the Enterprise we talked to Cyc for potential application in the enterprise, but at the time there were no clear applications.   Cyc is an attempt to record and make useful common knowledge that can be part of AI. Ultimately fundamental to create generally useful virtual assistants.

In Technology Review:
Doug Lenat’s creation is Cyc, a knowledge base of semantic information designed to give computers some understanding of how things work in the real world.

Cyc has been given many thousands of facts, including lots of information that you wouldn’t find in an encyclopedia because it seems self-evident. It knows, for example, that that Sir Isaac Newton is a famous historical figure who is no longer alive. But more important, Cyc also understands that if you let go of an apple it will fall to the ground; that an apple is not bigger than a person; and that a person cannot throw an apple into space.

And now, after years of work, Lenat’s system is being commercialized by a company called Lucid. .... 
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