Why everyone should be data literate | Jordan Morrow | TEDxBoise
Summary
TLDRThe speaker emphasizes the importance of data literacy in the digital age, equating it to the Fourth Industrial Revolution. Data literacy is defined as the ability to read, work with, analyze, and argue with data, skills essential for informed decision-making. The talk encourages curiosity and creativity to enhance data understanding, advocating that everyone, not just data scientists, should develop these skills to navigate the information-rich world effectively.
Takeaways
- 📺 Data literacy is crucial in our digital world where there's instant access to information, and it helps us discern and make informed decisions.
- 🌐 The era we live in is termed the Fourth Industrial Revolution, characterized by a digital world and the ubiquity of technology in everyday life.
- 🧊 Data is often referred to as the new oil, signifying its value, but it needs to be processed and understood to be truly valuable.
- 🔍 Data literacy is not about becoming a data scientist; it's about being comfortable with data to succeed in the digital age.
- 📚 The four key skills of data literacy are the ability to read, work with, analyze, and argue with data.
- 🛒 The script uses the example of buying a refrigerator to illustrate how these data literacy skills can be applied in practical, everyday scenarios.
- 🔖 Reading data involves comprehending the information provided, which is essential for making smart decisions.
- 🔄 Working with data means being comfortable with information and being able to discern hoaxes or misinformation.
- 🔍 Analyzing data goes beyond observation to gain insights and understand the 'why' behind the information.
- 🗣️ Arguing with data involves questioning the information presented and being able to support one's position with facts and data.
- 🤔 The speaker emphasizes the importance of curiosity and creativity in developing data literacy, suggesting that these traits can enhance our ability to understand and utilize data effectively.
Q & A
What is the main topic discussed in the script?
-The main topic discussed in the script is data literacy and its importance in the era of the Fourth Industrial Revolution.
Why is data literacy considered a crucial skill in today's digital world?
-Data literacy is considered crucial because it empowers individuals to understand, analyze, and make informed decisions based on the vast amount of data and information available.
What does the author compare data to and why?
-The author compares data to oil, highlighting that like oil, data is a valuable asset that needs to be refined and processed by people to extract its value.
What are the four skills that define data literacy according to the script?
-The four skills that define data literacy are the ability to read data, work with data, analyze data, and argue with data.
How does the script illustrate the concept of reading data?
-The script illustrates reading data by using the example of comparing refrigerators in a store and comprehending the information provided to make an informed purchase.
What does 'working with data' mean in the context of data literacy?
-In the context of data literacy, 'working with data' means being comfortable with information when it is presented and being able to discern the truth from misinformation, such as identifying hoaxes.
Can you explain the concept of analyzing data as discussed in the script?
-Analyzing data involves going beyond mere observation to gain insights and understanding the 'why' behind the data. It includes asking questions and being comfortable with challenging the information presented.
What is the significance of 'arguing with data' and how is it different from arguing with a salesperson?
-Arguing with data means interrogating the information presented, asking questions, and backing up one's position with facts and data. It is different from arguing with a salesperson as it is about critically evaluating the data rather than engaging in a personal dispute.
What are 'The Two Cs of Data Literacy' mentioned in the script and why are they important?
-The Two Cs of Data Literacy are Curiosity and Creativity. They are important because curiosity drives the questioning of data, leading to deeper understanding, while creativity allows for the application of human insight in conjunction with data and AI.
How can one start improving their data literacy skills according to the script?
-One can start improving their data literacy skills by becoming curious and asking questions about everything, and by using creativity to find insights and understanding in data.
What is the final advice given by the speaker regarding data literacy and success in the digital world?
-The final advice given by the speaker is to become data literate as it is a foolproof way of succeeding in the future and in the digital world.
Outlines
📚 The Importance of Data Literacy in the Digital Age
The speaker introduces the concept of data literacy as a crucial skill in the Fourth Industrial Revolution, an era characterized by digital connectivity. They emphasize the ubiquity of digital devices, like smartphones, and the resulting explosion of data. The speaker discusses the value of data, comparing it to oil, and the need for people to refine it to extract its true value. Data literacy is defined as the ability to read, work with, analyze, and argue with data, which is essential for making informed decisions in today's world.
🛒 Mastering Data Literacy: Skills for Smart Decisions
This paragraph delves into the four key skills of data literacy using the metaphor of purchasing a refrigerator. The first skill is the ability to read data, which involves comprehending the information provided. The second is working with data, which means being comfortable with information as it's presented. The third skill is analyzing data, which is about understanding the 'why' behind the data to gain insights. The final skill is arguing with data, which involves interrogating the information and using it to support a position. The speaker suggests that these skills are not just for personal use but are applicable across various sectors, including business and public service.
🔍 The Two Cs of Data Literacy: Curiosity and Creativity
In the final paragraph, the speaker presents 'The Two Cs of Data Literacy': Curiosity and Creativity. Curiosity is encouraged as a means to question everything and stay engaged with the information and data we encounter. Creativity is highlighted as a way to leverage the human mind in conjunction with technology and artificial intelligence. The speaker argues that by combining these elements, we can unlock the power of data and information to improve society, business, and personal lives. The speaker concludes by emphasizing the importance of becoming data literate for success in the digital world.
Mindmap
Keywords
💡Data Literacy
💡Fourth Industrial Revolution
💡Smart Devices
💡Information Overload
💡Data
💡Data Science
💡Reading Data
💡Analyzing Data
💡Arguing with Data
💡Curiosity
💡Creativity
Highlights
The importance of questioning the accuracy of data and information in today's digital world.
The prevalence of skepticism towards media and the need to discern real from fake news.
The analogy of the Momo Challenge to illustrate the impact of viral hoaxes and the necessity to verify stories.
The concept of data literacy as a crucial skill for making informed decisions in the digital age.
The definition of the Fourth Industrial Revolution and its implications for our digital lives.
Examples of technology integration in everyday appliances, like smart refrigerators and dishwashers.
The comparison of data to oil, emphasizing its value and the need for refinement to extract insights.
The definition of data literacy as the ability to read, work with, analyze, and argue with data.
The distinction between data literacy and data science, and the accessibility of data literacy to everyone.
The four characteristics of data literacy: reading, working with, analyzing, and arguing with data.
The historical context of the ability to read as a powerful skill, now applied to reading data.
The example of buying a refrigerator to illustrate the practical application of data literacy skills.
The process of analyzing data to move from observation to insight, using the refrigerator example.
The importance of questioning and interrogating data presented to us, as part of data literacy.
The concept of arguing with data to interrogate information and support positions with facts.
The 'Two Cs of Data Literacy': Curiosity and Creativity, as the starting points for developing data literacy.
The role of human creativity in combining with data and AI for a comprehensive understanding of information.
The call to action for individuals to become data literate for personal, societal, and business improvement.
The conclusion that data literacy is key to success in the Fourth Industrial Revolution and the digital world.
Transcripts
Translator: L. Lam Reviewer: Lisa Rodriguez
How many of us
have ever been watching the news,
and a story comes on, and we get captivated by it,
and then we start asking questions such as,
"Is this data and information correct?"
Or how many of us
have ever been in a check-out stand, looking at the newspapers and magazines -
and for those that don't know what a newspaper is,
it's printed word, not on social media -
but how many times have we been in that check-out stand
and said, "Nah, that can't be real?"
Or third, turning to social media,
how many of us have ever been on social media
and we see these viral stories that go around
that make us think or worry, kind of like the Momo Challenge,
and then we find out that it's a hoax?
The world we live in today
is producing so much instant access to information.
How do we decipher through it all?
And not only decipher through it all:
how do we take it to make a smart, informed decision?
Now what if I told you
that there is legitimately a skill in the world
that everyone can learn -
and not just learn, but get good at -
that will empower us to understand data and information better
and then to make a data-informed decision?
Sound too good to be true?
I promise it's not.
It is real, and it is accessible to everybody.
And this skill is data literacy.
Now before I jump in to exactly what data literacy is,
I want to set this foundation for us more
so we understand the era and the world that we live in
with technology and information.
Now the time period in which we live
has been called the Fourth Industrial Revolution.
Now what in the world does that actually mean?
It means a digital world,
and I think all of us can agree that we live in a very digital world.
In fact, it is very hard-pressed
to find people who don't have a computer in their pocket now, in a smartphone.
To help paint this picture even better,
I'm going to go through a few examples with you
just to show you how connected we are
and how much information is being produced.
The first example:
Did you know that nowadays
you need a refrigerator that has a touchscreen on it?
(Laughter)
And not just has a touchscreen,
but it can play a YouTube video for you, it can tell you the weather.
These things exist, did you know that you need it?
Now, in full disclosure, guess who has one of those?
(Laughter)
Second: Did you know that you need a dishwasher
that connects to your Internet?
Because I can't think of anything
I have ever wanted more when I'm at a movie theater
than to know when my dish-washing cycle is complete.
(Laughter)
Did you know you need that?
Third: Did you know
that it is becoming way too difficult
to turn a knob to turn your shower on?
(Laughter)
That now you can download an app
that can turn the water on and - by golly -
set it to the exact temperature that you want?
Not only that,
but you can have a touchscreen in your shower,
and that mixture of electricity and water -
(Laughter)
Did you know you need that?
The reality is, everything is being connected.
And not just connected: guess what that produces for us?
Data and information.
Now data has been called the new oil,
but I think we need to take a step back from that statement
to understand it better.
Data is this valuable asset,
but just like oil,
it has to go through people and refinement to get value.
This is data literacy.
Now by definition,
data literacy is the ability to read,
work with, analyze, and argue with data -
four skills that reside across a spectrum.
Notice what I did not say:
data literacy is not data science.
Not everyone in this world needs to be data scientist,
but everyone needs to be comfortable with data
to be able to succeed in the Fourth Industrial Revolution.
So let's dive through these four skills
to help us understand them better.
And to do that, we are going to imagine
that we all are buying a refrigerator.
Now the principles I'm about to teach and talk through
apply not only in a personal life;
they apply in the public sector,
they apply in business, and they apply in society.
The first characteristic is the ability to read data.
Now imagine that we are going to a store,
and we are looking at all these refrigerators,
and we have no clue which one is going to fit our world the best.
So the first step is
we are going to read the information and data that is provided to us,
and if you were to Google the word "to read":
it means to look at something and comprehend it.
So when we walk into the store and there are 30 refrigerators all over,
hopefully some without a touchscreen,
we can read the information that is given to us,
and comprehend it to make a smarter decision.
Reading data is one of the most powerful things
that can free up our minds in the Fourth Industrial Revolution.
If you think back hundreds of years,
did you know it could be a criminal act
to be able to read?
In no way am I saying it will be a criminal act to be able to read data,
but just like it did hundreds of years ago with all of this information around us,
the ability to read it and comprehend it is a key skill.
So back to our refrigerators.
We move along
and we get to the second characteristic of data literacy.
This is the ability to work with data.
Now one might ask themselves,
"Does this mean I have to get good at computer science and statistics
to work with data?"
The answer is no.
It means being comfortable with information
when it is presented to you.
If we think of those viral stories
that go around and they make us uncomfortable,
we become relieved when we find out it's a hoax.
Working and reading with data allows us
to determine it's a hoax before we have to find out.
So when we're buying these refrigerators
and each refrigerator has an information sheet,
we're comfortable taking that and consuming it,
to move along to the third characteristic of the data literacy definition,
and that means to analyze data.
Now what analyzing data does is it gets to the "why?" behind it.
I often say we want to move beyond an observation and get to the insight.
In reality, when a story is going around on social media,
most of the time,
we are making an observation of the information presented to us.
In the case of a refrigerator,
we walk into a store, see 30 refrigerators
and maybe five of them catch our attention:
we made an observation.
We then need to analyze the information about those five refrigerators
so that we can take it in
and find the insight that will lead to a smarter decision.
Analyzing also means being comfortable asking questions.
That's not something that happens too often
with social media in our day and age.
We should be questioning everything.
The fourth piece of the pie
is arguing with data.
Now, a little side note,
I am not encouraging you to go argue with the salesperson
as you try and pick your refrigerator.
Arguing with data means two things.
One: interrogate the information as it is presented to you.
Ask a lot of questions of the salesperson,
interrogate what they're giving you.
The second side of arguing with data and information
is this ability to put a position forward and back it up with information.
So put yourself in my shoes.
Let's say, my wife and I are remodeling and picking out this fridge.
We agree on absolutely everything.
No.
(Laughter)
We each have our position,
and then we argue it and back it up with facts and data
to arrive at the best refrigerator for us.
Four characteristics:
reading, working with, analyzing, and arguing with data
empower us as individuals to make sense of all the information that is out there
and then to make decisions with it.
Now I am asked very often,
"How do I start? What do I do?"
"Do I need to back to school and get good at statistics?"
"Do I need to learn how to code?"
Now I understand greatly, not everyone is as big a nerd as myself.
Not everyone wants to read a statistics textbook -
I promise you I do.
So what do you do to start?
I've coined a phrase that I use called "The Two Cs of Data Literacy."
The first C is I want you to become Curious.
I have five children.
Guess how many questions they ask me on a daily basis?
(Laughter)
And here's the kicker: I never ever want my kids to stop.
I watch their brains working through information and data in front of them,
to come to answers that I could only dream of making myself.
Because for some reason,
when we become adults, our curiosity disappears.
Become curious and ask questions of everything.
That is the start to powerful data literacy.
The second C of data literacy
is Creativity.
There is a lot of hype and a lot of discussion in the world
on what is AI, artificial intelligence, computers, machines
going to do to the future.
We're already in the Fourth Industrial Revolution.
We are already living in a digital world,
and I'm here to tell you the most powerful computer that is out there is in here;
it's in our minds.
The human element should never be stripped away from data.
It is a combination of those machines of data and artificial intelligence
combined with the human element.
And remember: those four characteristics are on a spectrum of skills.
But the second C of Creativity allows us to open up our human mind
to something that might seem boring or mundane,
but data and information have power.
Now overall, this world that we're living in truly can be improved
in society, in business, and in our own personal lives,
as we improve ourselves in reading,
working with, analyzing, and arguing with data.
If you want to have a foolproof way of succeeding in the future
and in this digital world
become data literate.
Thank you.
(Applause)
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