Paper #1 Peer Review

  • only put your number on your feedback sheet! These will be anonymous so there's less risk of embarassment/bias/hurt feelings
  • once you're done answering questions in the sheet, move on to filling out the rubric
    • circle which category applies
  • mark up the paper with a pen/pencil if you catch any errors, leave a note

CMSC 304

Social and Ethical Issues in Information Technology

Data, Information, Knowledge, Wisdom

Introduction

  • We are currently living in a “data revolution”

    • ​Some call it the Fourth Industrial Revolution

    • Before computers + internet, data collection was laborious, slow, and manual

  • In addition to the ability to collect, store, and transmit all this data, there's been a change in what we consider to be data

  • The question becomes how to manage and use all this data

    • What does it get us?

    • Are we really better off?

    • Where is it all headed?

What do you already know? 

On your sheet jot down some ideas:

  • What is "data"? 
  • What distinguishes data from information, if anything?
  • What kind of data have you worked with before, if any?

Some Additional Questions

  • As soon as we have enough data, do we have all the information?

  • How do we best manage all this data, information and knowledge?

  • What effect does so much information have on us and our world?

  • How can we best use data and information to make ethical decisions and contribute to social good?

Some Additional Questions

  • What effect does so much information have on us and our world?

    • ​"History repeats itself" - these questions are not necessarily new

Some Additional Questions

  • What effect does so much information have on us and our world?

    • ​"History repeats itself" - these questions are not necessarily new

    • There have been several "paradigm shifts     " in history that caused people to experience fear, excitement, trepidation, doomerism     , etc.​

      • The Printing Press

      • Writing

Doomers are people who are extremely pessimistic or fatalistic about global problems such as overpopulation, peak oil, climate change, ecological overshoot, pollution, nuclear weapons, and runaway artificial intelligence. The term, and its associated term doomerism, arose primarily on social media. Some doomers assert that there is a possibility these problems will bring about human extinction.

https://en.wikipedia.org/wiki/Doomer

Tech Paradigm Shift Examples

  • The Printing Press radically increased access to information

    • Invented in Germany in mid-15th century

    • Entire culture of the country was changed almost immediately

https://stock.adobe.com/search?k=antique+printing+press

  • Tons of backlash, complaints about “confusing and irritating multitude of books” and “so many books that we do not even have time to read the titles”

  • Concerns over whether this new tech would make people dumber

    • If access to info is so easy (e.g. just read a book), people won’t need to memorize or understand anything anymore!

Tech Paradigm Shift Examples

  • Writing in general radically increased our ability to store and manage information

    • Still, there was push back about that too

    • Socrates said it will “introduce forgetfulness into the soul of those who learn it: they will not practice using their memory because they will put their trust in writing, which is external and depends on signs that belong to others…the appearance of wisdom, not its reality”

    • "they will imagine that they have come to know much while for the most part they know nothing.”

    • While it’s hard to argue now that being able to read and write text is a problem, it did in fact change the way humans store and process information

      • Before, everything had to be memorized, including the entire history of their people, local ecological knowledge, trades, techniques

      • Called “oral tradition”

We continue to see this pattern of freakouts

"We know more than ever, and this makes us crazy."

https://www.pewresearch.org/2010/02/19/does-google-make-us-stupid/

Course Rhythm

  • There seems to be this theme with tech and fears about our collective intelligence, both as individuals and as a society
  • But we have plenty of data, information, and knowledge, so why are there so many fears about becoming stupid?
  • There must be another concept

How to get to the bottom of it?

There are two important discussion points about data, information, knowledge, and wisdom:

  1. People have limited capacity for absorbing, processing, and storing information

    • Some of that can be outsourced to technology

    • But the sheer volume of data forces us to be selective

    • We often retain what is easiest to assimilate (i.e. agrees with what we already know, instead of what best meets our needs)

  2. Data and information are not neutral

    • Even though it seems like numbers and facts should be objective

    • The ways that we collect, interpret, process, and apply data and information reflects our own values and society’s values

      • these values change over time

Data vs knowledge

Here is my insightful data that I collected:

Basil      7         S       Pear

Data vs knowledge

What a-priori knowledge is required to make sense of this data?

  • one example: the units of age are probably in "years"
    • Why can we make this assumption?
      • As humans capable of reasoning, we know (maybe) that a 7 month-old is probably too young to have fruit preferences
  • what are some other examples? take a few mins to jot some on your sheet

Recall our slide on: Why Ethics?

  • Ethics is the theory and practice of ways to make good choices and lead a good life

 

  • It involves both knowledge and skills (i.e. practice)

 

 

 

Markkula Center for Applied Ethics

Recall our slide on: Why Ethics?

  • Ethics is the theory and practice of ways to make good choices and lead a good life
    • How can we know what choices to make, how do we DECIDE? Data, information, knowledge and wisdom are all ingredients in ethical decision-making

      • You need to consider your options, rank them

      • You need to predict outcomes

      • You need to determine what’s at stake

      • You need life experience to learn the above

  • It involves both knowledge and skills (i.e. practice)
    • what is the difference between data, information, knowledge, and wisdom?
    • how can we obtain these skills using the above?

Markkula Center for Applied Ethics

Data, Information, Knowledge, Wisdom

"Choruses" by T. S. Eliot:

Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information?

https://en.wikipedia.org/wiki/DIKW_pyramid

  • You may see this model in information science  textbooks, called the DIKW Pyramid
  • Let's try to narrow down some definitions

Data, Information, Knowledge, Wisdom

https://en.wikipedia.org/wiki/DIKW_pyramid

  • It can help to really dig into the differences between data, information, and knowledge
    • Because our brains are so good at abstraction from context, we think we know what these words mean
  • The structure of this model implies a hierarchical relationship, that the lower parts are used to form the upper parts

Data, Information, Knowledge, Wisdom

https://en.wikipedia.org/wiki/DIKW_pyramid

  • The structure of this model implies a hierarchical relationship, that the lower parts are used to form the upper parts

Data is synthesized into information

Information synthesized into knowledge

Knowledge synthesized into wisdom

this is a good starting point

Data, Information, Knowledge, Wisdom

https://en.wikipedia.org/wiki/DIKW_pyramid

Data is synthesized into information

Information synthesized into knowledge

Knowledge synthesized into wisdom

Data

  • Typically we think of data as “raw” observations about the world, that we can collect and process into “information” or “knowledge”. It could include colors, heights, shoe size, GPA
  • But it implies something that has been collected (not just exists) and organized into some “set” often called a dataset.
    • If there’s a difference between “data” and “objects that simply exist” what might that difference be?

Data, Information, Knowledge, Wisdom

https://en.wikipedia.org/wiki/DIKW_pyramid

Data is synthesized into information

Information synthesized into knowledge

Knowledge synthesized into wisdom

Information

  • Information is data that has been processed to give it meaning, to serve as a descriptor of the world or some concept

Data, Information, Knowledge, Wisdom

https://en.wikipedia.org/wiki/DIKW_pyramid

Data is synthesized into information

Information synthesized into knowledge

Knowledge synthesized into wisdom

Knowledge

  • Knowledge comes from a synthesis of information, like a web of interconnected pieces of information

  • It’s said that knowledge transforms information into instructions

  • Whereas information deals with some detail of a system, knowledge helps understand the system as a whole

     

Data, Information, Knowledge, Wisdom

https://en.wikipedia.org/wiki/DIKW_pyramid

Data is synthesized into information

Information synthesized into knowledge

Knowledge synthesized into wisdom

Wisdom

  • Wisdom is related to effectiveness - the ability to judge which objectives are worth pursuing.

    • The others relate to efficiency - how well can you do it

  • Wisdom isn’t external, it becomes part of a persons character

    • Developed from experience, similar to virtue ethics

Data, Information, Knowledge, Wisdom

Data is synthesized into information

Information synthesized into knowledge

Knowledge synthesized into wisdom

  • HOWEVER, higher levels will also affect lower levels
    • Not everyone will discover the same set of instructions or knowledge from the same data
    • In practice, people’s existing knowledge and assumptions about how the world works determines what instructions they glean, how they absorb and process information

Knowledge requires a knower, and a knower is human, which means:

  • knowledge is not static
  • knowledge exists within the context of a society or community

Data, Information, Knowledge, Wisdom

Data is synthesized into information

Information synthesized into knowledge

Knowledge synthesized into wisdom

  • In addition, higher levels will effect lower levels
    • Not everyone will discover the same set of instructions or knowledge from the same data
    • In practice, people’s existing knowledge and assumptions about how the world works determines what instructions they glean, how they absorb and process information
  • New information is always slotted into current knowledge, your brain doesn’t erase every time
  • Knowledge exists before data and information-- our worldview shapes them

Data, Information, Knowledge, Wisdom

  • New information is always slotted into current knowledge, your brain doesn’t erase every time
  • Knowledge exists before data and information-- our worldview shapes them
  • a worldview = implicit assumptions, perspectives, or biases that shape how data is collected, interpreted, and presented
    • Just like an individual's worldview affects how they perceive and interpret the world
  • a dataset's worldview can include:
    • selecting which data to collect. This is guided by assumptions and priorities
    • deciding how to collect it. Surveys, instruments, sensor placement, cookies, etc
    • what NOT to collect. Populations of interest, generalizations, etc.

Example dataset worldviews: computer vision

Knowledge Cultures

  • Information is shaped by ability to make correct inferences about relationships between data observations
  • When we encounter new data or information, it changes our existing knowledge, and we must integrate and manage this old + new knowledge
    • Our existing knowledge acts as a filter or screen, which is the product of cultures of information
  • Knowledge cultures can be big or small
    • sports team fans, religious groups, others with same politics, each of your classes, geographic region, etc.
  • Some new information fits well within a knowledge culture's current knowledge, others not so much
    • The way we absorb and use knowledge can have profound impact on our judgement of “what should I do?”
    • Systems that collect, organize, and synthesize data or information also shape their users’ view of what is true, and what therefore can or should be done

Finally, wisdom

  • The ethical frameworks we've looked at emphasize wisdom in different ways:
    • In deontology: To be wise is to understand one’s obligations, duties, and responsibilities, and also to possess knowledge about how to apply them practically
    • In virtue ethics: Living well requires a balance of reasoning about how to interact in the world and knowledge about how to flourish, both individually and collectively
    • In utilitarianism: Wisdom requires a thorough and accurate understanding of how actions effect change in the world. The goal is to maximize happiness, and wisdom requires awareness of how to do this
  • Although we can write code to process data automatically, neither data nor information actually exist without human interference
    • Neither data nor information have universal defined the parameters by which they can be collected, known, and understood
    • ​When we present data, processing, or software as "value neutral," this can cause harm, as there is no absolute "neutral"

Course Rhythm

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  • Step between data and information is some processing, including “data cleaning”

Data Cleaning

https://www.kdnuggets.com/mastering-the-art-of-data-cleaning-in-python

Activity

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Key Takeaways

  • There's no such a thing as "raw data" or "objective data"
    • "Data need to be imagined as data to exist and function as such, and the imagination of data entails an interpretative base"
      • a person selects which data is relevant
      • a person cleans that data
      • a person has to give the data context and meaning
  • It's not possible to create systems that are completely independent of human thought processes
    • this makes sense, because what are we trying to do with AI in the first place? Replicate human capabilities!
  • Data not only produces knowledge, it is also the product of human knowledge

Course Rhythm

out of how many?

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https://marketoonist.com/

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Handling Missing Values

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https://medium.com/@nikhil_garg/a-compilation-of-comics-explaining-statistics-data-science-and-machine-learning-eeefbae91277

dikw

By Rebecca Williams

dikw

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