Cognitive computing systems aim to mimic human cognition through statistical and machine learning techniques. However, true understanding requires grounding symbols in real-world semantics that systems currently lack. While cognitive computing has advanced capabilities like IBM Watson, its abilities are not analogous to human cognition and it does not genuinely understand language. The document argues cognitive systems would benefit from greater collaboration with fields like linguistics and psychology that have knowledge of semantics and symbol grounding cognitive computers still need.

1. How to Talk to a Cognitive
Computer
I don’t know.
What’s a cognitive computer?
Csaba Veres
University of Bergen

2. ● What sort of a thing is Cognitive
Computing?
● Why should we care?
● A new proposal based on a (really good)
old one.
Overview

3. Origins of Cognitive Computing
Deep Blue
1997
Rumelhart & McClelland
PDP Volumes, 1986
October 1981
Fifth Generation Computer

4. Strong claims
“Typically, AI splits into two forms: Weak and
strong. Strong AI, exemplified by IBM Watson
…”
Alison Diana, Enterprise Tech

5. More strong clams
John Kelly, director of IBM Research

6. Reasonable claims
"the goal isn't to replicate human brains, though. This isn't about replacing human thinking with machine
thinking…. "
John Kelly, Smart Machines IBM's Watson and the Era of
Cognitive Computing
“Did we sit down when we built Watson and try to model human cognition?” Dave Ferrucci, who led the Watson
team at IBM, pauses for emphasis. “Absolutely not. We just tried to create a machine that could win at
Jeopardy.”
“I’m fascinated by how the human mind works, it would be fantastic to understand cognition, I love to
read books on it, I love to get a grip on it … but where am I going to go with it? Really what I want to do
is build computer systems that do something. And I don’t think the short path to that is theories of
cognition.”
Peter Norvig, one of Google’s directors of research, echoes Ferrucci almost exactly. “I thought he was tackling a
really hard problem,” he told me about Hofstadter’s work. “And I guess I wanted to do an easier problem.”
(http://www.theatlantic.com/magazine/archive/2013/11/the-man-who-would-teach-machines-to-think/309529/)

7. A Sensible Position
IEEE Technical Activity for Cognitive Computing
“an interdisciplinary research and application field” ... which
... “uses methods from psychology, biology, signal
processing, physics, information theory, mathematics, and
statistics” ... in an attempt to construct ... “machines that will
have reasoning abilities analogous to a human brain”.

8. But then, the truth comes out ...
Chomsky and Norvig, MIT symposium Minds, Brains and
Machines
"Chomsky ... must declare the actual facts of language use
out of bounds and declare that true linguistics only exists in
the mathematical realm ….. this may be very interesting from
a mathematical point of view, but it misses the point about
what language is, and how it works."
Linguistic competence is really a statistical model.

9. Statistical language?
“The dog killed the man.” Who died?
“It is such a nice sunny day, I would love to
have my lunch by the river. But I have to do
some chores. I wonder if that river bank is still
there? It used to be right by the water by the
jetty.”

10. Semantics
● “Bank” is not just a four character string which
happens to co-occur with other strings
● “Understanding” is not a statistical function
that maps strings to vector space
● Semantics is about something in the world,
which we happen to have a name for ...
o … and know something about
o Symbol grounding

11. Semantics
Searle:
“Watson did not understand the questions, nor its
answers, nor that some of its answers were right
and some wrong, nor that it was playing a game, nor
that it won—because it doesn't understand
anything.”
What’s a machine to do? Should it pull the plug?

12. Semantic Symbiotics
● Licklider
o Man-computer Symbiosis, 1960
o Two different organisms
● Are you doing science or engineering?
● Cognitive Computers should acknowledge their limitations and
let the psychologists back in
● My contribution: the “right” level of symbiosis is semantics /
symbol grounding
● Psychologists / Linguists know a lot about this, even if not
everything

13. Lexitags
● Back in the day of
social bookmarking,
tagging was a big deal.
● But tagging had its
problems (no
semantics)
o Clustering, etc.