Chapter 12: Digital Cognition and Agency

In **Chapter 12: Digital Cognition and Agency** Hinton explains the
origins of digital agents, beginning with information science. He focuses on
the definition of information and how information is different for humans and
digital systems. As digital agents become more present in the physical world, the translation of
information between humans and computers becomes an important science. The need
for good translation is delved into with a look at ontology in computers and
interface design.

## Shannon’s Logic

Hinton begins the chapter by covering the science of information, which existed long before computers. Claude
Shannon, known as the “Father of Information Theory”, was one of the biggest
influences on how information is used in today’s digital technology.

Shannon removed human meaning from
the language passed to machines to create more accurate transmissions. Hinton explains
that Shannon’s information starts “with definition and measurement” . Shannon redefined information as a structure to be
represented by Boolean logic in the form of 1's and 0's. In contrast, humans
work with information that originates from perception, not logic. Digital
technology adopts Shannon’s information definition and enforces a translation
barrier between digital and human information. Translating between that barrier
is a core part of the field of design.

## DigitalLearning and Agency

Computing used to be a human job,
but humans make errors and have limits on the amount of work they can take on. By
the mid-1900s a field emerged around creating computing machines. Hinton states
these computing machines were “made of logic itself” and came along thanks to
Shannon Claude, Alan Turing, and Norbert Wiener . For example, the Turing Machine used
Boolean logic to create rules that dictated its actions. Turing’s idea was that “anything that could be *represented* by
mathematical symbols and logic could be computed" . So if the world was
represented to the Turing Machine through logic, then the machine could compute
decisions without direct human commands. Turing's theory leads to digital agency. The digital system acts as an agent that is capable of functioning alone
and makes decisions based on the given rules.

Digital agency changed human
culture. The human world had to be represented by algorithms so that
computers to could make decisions autonomously. However, human and computer
cognition differ in how they use information. Humans perceive the
physical world and afterwards can develop a method to abstract it through
symbols or language. Computers can only work with information that has already been
abstracted.

Abstracting
information becomes more difficult the less logical it is. *Moravec’s Paradox*
is the increased difficulty that
appears when teaching a computer tasks from logical to cognitive*.* For
example, a computer can easily be taught to recognize the text “berry” because it is
already abstracted. But the recognition becomes harder to teach when it involves recognizing different pictures of a berry, a trivial task for a human
to learn.

Since a computer cannot find meaning in objects like a human can that information must be
purposefully given to it. An example of a digital agent that must be given meaning is Siri from iOS. Siri is a software that performs actions based on human voice
inquiries. At some point, abstracted information must be written to tell Siri
what humans want when they say things such as “Find me a restaurant nearby.”

## Everyday Digital Agents

Hinton compares digital and physical
information. Physical information is dominated by concrete laws. Digital
information lacks friction to slow it down. Even if left alone, digital information will continue to make decisions. The *Flash Crash* shows the negative
effects the lack of friction can have. In 2010, software trading at a faster rate than humanly possible caused
the stock market to drop 9% in minutes before rising back up in the next hour.

Another issue that arises with
digital agents is knowledge of cause. When an event occurs due to a computer
algorithm, humans are stuck guessing what the digital agent was trying to accomplish unless the agent was programmed to tell them. In 2012, anonymous trading software performed 4%
of trading activity in a week by making and canceling orders***.*** The reasons behind
the software's actions remain unknown.

On a more positive note, as software
evolves, people without programming knowledge are given their own ways
of creating digital agents. Hinton gives the example of an application called IFTTT(If This
Then That) which allows people to define a digital action that should occur in
response to a digital event, such as saving a shared photo. Hinton explains
that IFTTT turns human actions into “triggers" .
Many programs have defined responses to events, such that
an event triggers another event.  With
IFTTT, the humans can easily define their digital actions as the triggers.
Hinton states that digital agents will continue to evolve and automate actions. Ironically, digital agents will evolve to control the increasing complexity they can add to human life.

## Ontologies

Computers do not rely on human
information to function. Only when humans must receive or give information is
translation required. From human-computer translation stems the new definition of ontology.

In philosophy, ontology is used in *metaphysics*
to study “being” and its relationship with language. Hinton defines the
ontology in information science as “the way we teach digital machines how to
understand the inputs we expect them to process” . He means that humans must
provide definitions for computers to understand the information humans give computers. The contrast in human and computer information explained in section two through the berry example is why definitions are needed. For example, a computer does not understand what the word
“calendar” means to humans unless it has been defined.

Computers must also be made to translate their information in a format understandable to humans. The translation is necessary so that the two can interact. Hinton finally defines the ontology for user interface
design as “establishing understandable *semantic function* that solves for the contextual gap
between person and machine”.While similar to ontology in information science,
this definition focuses more on benefiting the user.An example of failed ontology is with
the definition of “friend” used in Google’s Buzz application in 2010. Buzz
automatically generated lists of “friends” for users based on their Gmail
activity. Ex-spouses, bosses, and more were added to the lists without user knowledge. The friend lists were also public
for all to see. The definition of friend for humans is complex. The definition changes for
everyone and can change for the same person depending on the situation. The
definition of friend given to Buzz was much too simple to account for people's varying definitions. Therefore
disaster followed.

## Analysis

Digital writing includes writing code or posting content on a digital platform. Hinton explains how the digital platform works by first explaining the shift to creating information based on logic. He shows how information science led to machines based on logic, or computers. Computing machines can only work with information presented in an abstract form and require a set of rules to dictate their actions. Code tells the computer the meaning behind given information. Code also tells the computer what to do with the information depending on the meaning. Digital agents are capable of making autonomous decisions only because of code.  Therefore, a person writing code must understand how computers interact with information.

Chapter 12 is about understanding
the need for information translation.
Efficiency in machines can be increased by translating human information
into a logical form.  Hinton states that computers “begin with
abstraction” . Hinton is talking about how computers accept information in
semantic form, such as text.  Humans accept information through perception rather than abstract symbols.  Only with good translation can humans and computers interact.  In the final section about ontologies, Hinton talks about the disaster of automatic friend lists by
Google’s Buzz. The translation failure with the word ‘friend’ proves how important it is for digital writers to properly define the human world for digital agents.  When Buzz had the information about who a person frequently emailed, it should have known that it was not enough to define friendship.

In his piece “Writing as a
Technology”, Bolter offers supporting definitions to Hinton's while analyzing digital
writing technology.  He defines computers as machines that process information and replace skill, yet cannot “function
as the writing space in the absence of human writers and readers" . Bolter's statement emphasizes
the need for translation.  Digital writing and reading will only
continue and it requires human computer interaction.  For that interaction to be fruitful, interface designs must perform proper
translation of information before humans and computers.  In other words, a proper ontology must be
used.

## References

1. ↑ Hinton, Andrew, and Peter Morville. Understanding Context: Environment, Language, and Information Architecture. Sebastopol: O'Reilly, 2014. Print. Page 201
2. ↑ 2.0 2.1 Hinton, Andrew, and Peter Morville. Understanding Context: Environment, Language, and Information Architecture. Sebastopol: O'Reilly, 2014. Print. Page 203
3. ↑ Hinton, Andrew, and Peter Morville. Understanding Context: Environment, Language, and Information Architecture. Sebastopol: O'Reilly, 2014. Print. Page 210
4. ↑ Hinton, Andrew, and Peter Morville. Understanding Context: Environment, Language, and Information Architecture. Sebastopol: O'Reilly, 2014. Print. Page 211
5. ↑ Hinton, Andrew, and Peter Morville. Understanding Context: Environment, Language, and Information Architecture. Sebastopol: O'Reilly, 2014. Print. Page 214
6. ↑ Hinton, Andrew, and Peter Morville. Understanding Context: Environment, Language, and Information Architecture. Sebastopol: O'Reilly, 2014. Print. Page 204
7. ↑ Bolter, Jay David. 2001. “2. Writing as Technology.” Writing
Space: Computers, HyperText, and the Remediation of Print. 15-17. Pdf.

http://williamwolff.org/wp-content/uploads/2008/01/bolter-writing-20011.pdf