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AI LITERACY - Social and Economic Implications - AI is the new Wealth of Nations.

AI LITERACY The Social and Economic Implications

AI is generating the new “Wealth of Nations.”

We live in the AI boom time.

Once upon a time, reading, writing and “rhythmatic” were considered literacy. That is alpha-numeric literacy. Then entered computer literacy. For many reasons artificial intelligence (AI) literacy upends it all. Arrhythmatic and computers are no longer near enough. You see, the all-knowing AI autocorrect makes it hard for me to write with errors. Better yet, it keeps on running ahead of me, trying to outguess me, telling me what I really want to write.

What is artificial intelligence – AI literacy?

AI literacy is a set of competencies that enables individuals to critically evaluate AI technologies; to communicate and collaborate effectively with AI; and use AI as a tool online, at home, and in the workplace. It is needed because AI is increasingly integrated in user-interface technology. The general public understanding of these technologies is limited. AI education is seriously needed.

Education is a capital asset. AI literacy is a capital asset.

Read this last line above again. Let it sink in. I can’t emphasize it enough.

Teaching AI systems and their effects on people's lives raises students' knowledge, awareness, and skills. AI literacy can be achieved in a classroom and at home. Schools and teachers will be responsible for developing this kind of literacy in children where they learn the essential characteristics of AI systems and what real-world problems AI helps solving.

AI literacy is the ability to critically evaluate information in order to understand what a device is doing, what it can or cannot do, and how it typically works.

AI literacy helps people detect fake news, understand automated decision support systems, help them assess evidence based medical recommendations, facilitate their trust of automation in personal devices such as cars, personal phones and help develop fair and equitable human-robot interactions.

AI is an area of computer sciences that creates of intelligent computers that work and reacts like humans. In addition to trying to invent thinking machines, researchers are using AI tools (algorithms), to solve some of the world's most complicated problems. The term AI encompasses a variety of sub-disciplines including Machine Learning, Natural Language Processing, and Computer Vision and Hearing.


Almost every country is moving forward to develop national strategies for AI research & Development . A “Grand Challenge” has been set by the U.S. government for robust and understandable AI that would be able to explain its reasoning in language that a layperson could understand.

It is hard for anyone who is not an expert to judge whether a routine job or product feature has been made more convenient through the use of AI. But the low bar of awareness suggests that so far little has changed. People must master the elements of AI in order to harness its power towards making their lives better. For technologists and governments, this calls for a much wider and smarter public-communication and education campaigns.

AI literacy is now a critical life skill.

Today’s teenagers are tomorrow’s adults, and most of them will not be computer programmers. The demand is now growing for professionals who understand how AI technologies work, and can evaluate them critically.

The professionals who can communicate with AI agents and use them wisely, enjoy growing compensation and benefits.

Benefits of AI literacy for everyone are:

• It helps users make informed decisions about using AI products and services

• It fosters trust and transparency between users and AI systems

• It can promote ethical and responsible use of AI for social good

• It can inspire creativity and innovation with AI embedded in our daily tools.

AI Literacy and the Market Place

AI literacy is a critical life skill as are reading, writing and arithmetic.

Higher educational achievement is an important advantage leading towards higher monetary incomes. Lower levels of education are associated with unemployment rates and lower earnings.

The U.S. Bureau of Labor Statistics data shows that the more you learn, the more you earn. The median weekly earnings in 2017 for those with the highest levels of educational achievement—doctoral and professional degrees—were more than triple those with the lowest level, less than a high school diploma.

In Europe, according to Eurostat data, the average salary for those with a high level of education (at least one year of tertiary education) in the EU salaries were approximately 50% higher than those with a medium level of education (secondary/high-school), and 70% higher than those with only a low level of education (anything below secondary/high-school). The basic correlation was consistent across all EU member states.

A report from University of Michigan analyzed 4.3 million jobs in Michigan. In 2020 - 79% of jobs earning over $64,240 annually required a minimum four years B.A. degree. Lower educational achievement was associated with lower wages.

Deep Dive into the Meaning of Literacy

How is literacy defined?

Adult literacy in the U.S. includes "quantitative literacy" (numeracy) in its definition of literacy. Literacy is defined as "the ability to use printed and written information to function in society, to achieve one's goals, and to continue developing one's knowledge and potential".

But the “three Rs” are no longer sufficient literacy. Enters the AI Literacy.

We are now confronted with the Four Big Questions:

1. How to define the term “AI literacy”?

2. How do instructors help students and all other folks, develop AI literacy?

3. How to evaluate the trade workers and non-technology AI literacy skills?

4. What are the ethical concerns that lack of AI literacy creates?

As defined above AI Literacy is - the set of competencies that enables individuals to critically evaluate AI technologies; communicate and collaborate effectively with AI; and use AI as a tool everywhere its available – online - at home, and in the workplace.

Education researchers and authors propose that AI literacy includes three components: AI concepts for evaluation; using AI concepts for understanding the new real world; and problem solving.

This later definition is intangible, which tell us that AI literacy still hasn’t reached a final, agreed upon, clear definition.

Around 2019 the definition of AI was broadened to include ability to perform cognitive tasks particularly learning and problem-solving with the technological innovations such as machine learning and neural networks.

From these attempted definitions it is clear that AI Literacy is difficult to present in simple terms to folks with an average education record. Sadly so, people from the majority walks of life need continuing AI education.

Historically, since the 1970s, computer applications have gained popularity across industries. It was necessary for users to become competent in using computer systems related to their specific task or job.

The term “computer literacy” emerged to assess basic computer-related concepts and skills. The importance of computer literacy increased as more people depended on the use of computer technologies to develop new social and economic opportunities.

The use of AI is spreading across all industries (e.g., business, science, engineering, art & design and design, education), to enhance users’ experience and improve business efficiency. Applications of AI exist in most parts of our everyday life, e.g. smart home appliances, smart phones, car driving, Google, Siri. The majority of the public acknowledge the vague existence of AI services and devices, but seldom do they understand the concepts and the technology behind it, or aware of potential ethical issues related to AI.

AI literacy has emerged as a new skill set in response to this new era of intelligence, unlike classic literacy which include reading, writing and arithmetical skills.

Following the digital technology advancements, AI started to rise and imitate human like intelligence in machines - for computers to perceive learn, reason and respond.

The Big Ideas of AI

There are five “big ideas” of AI which provide a foundation for future progress on promoting AI literacy in education, and professional skills to meet the future job demands. The five big ideas of AI are:

1. Perception. Computers perceive the world using sensors. Computers are data gatherers through their sensors.

2. Representation and Reasoning. AI Agents maintain data representations of the world and use them after reorganization for reasoning (like Google maps, Uber).

3. Learning. Computers learn from data. Computers use a lot of data (as they are data gatherers). And they process the data for learning after reasoning.

4. Natural Interaction. Intelligent AI agent requires many kinds of knowledge to interact with humans in a trustworthy manner. Example: You can trust Google-translate to say the right words in a different language. (I do). For accurate facial recognition the algorithm is trusted to identify the correct unique person. (Not their identical twin).

5. Social Impact. AI impacts society in positive and negative ways.

Initiatives of AI Education - Topics

Examples of challenges, curriculum creation, and education under the wide label of AI literacy include, exploring and mapping relationship between facial features and personal data values. Applying AI concepts to brainstorm other objects, digital games, and airline pilots simulation flights for training, arts and crafts, such as Lego, music, and technical and architectural design. Designing and creating new antibiotics, reading clinical diagnostic human images, and interpreting ECG tracings to name a few common daily procedures.

Evaluate and create AI high-order thinking skills (e.g., evaluate, appraise, predict, design) with AI applications. Design and build experiences: technology exploration and creation activities that support AI students in making sense of the underlying AI concepts.

Social Ethics

On a different level, AI ethics and human-centered considerations, (e.g. fairness, accountability, transparency, ethics) emerged as critical issues. “AI for social good” measures an individual’s perception of the surrounding social environment the behavior, relative to subjective norms.

It requires including AI literacy training in routine educational levels to enhance professional skills.

More examples of issues to be resolved are defining AI literacy as the ability to understand the basic techniques and concepts behind AI in diverse products and services. Many people know that these AI-empowered services, but they are not familiar with the underlying concepts such as computational thinking concepts, or data structures behind the services.

Evaluate and create AI: AI augments human intelligence with digital automation and engaging learners of AI literacy in higher-order thinking activities.

Researchers engaged citizens in co-creating AI amenities in public spaces to broaden their public AI literacy and experiences. It was demonstrated that students with the ability to evaluate and create AI could infer from, connect, manipulate, and categorize AI concepts together in novel ways.

In Norway a policy document titled was adopted. It is titled: “AI for everyone: Elements of AI” and asserted that the government will make AI learning courses globally accessible in 2020. It aimed to provide AI literacy as education to all citizens about the elements of AI that have no prior knowledge.

China laid out a national AI plan, since 2017, that included introduction of AI as an academic discipline. A year later, the education ministry had a detailed five-year plan to develop 50 AI research centers, and train more than 500 teachers and 5,000 students every year.

The spreading democratization of AI technologies encourages students and adults to create intelligent agents and machine learning models without the need to program their machines. In this context, there is an opportunity for educators to ensure access to AI literacy and reinforce the AI concepts using present and future emerging tools. Educators and trainers design learning activities to foster students’ AI literacy without using a computer through engaging approaches such as case study, role-playing, storytelling and group discussions.

Group discussions on AI literacy, are an important component to promote participants awareness and intention to learn and possess basic knowledge about AI. Researchers assess the knowledge acquisition of K-12 and university students via group discussion and pre- and post-knowledge tests and students’ perceived abilities.

Self-reported questionnaires show results that assess students’ output by using outcome products such as computer programs, documentations and presentations of their experiments. Instructors can also collect qualitative data by taking pictures, field notes during teaching, and interviewing students to understand their motivations, expectations and lessons learned.

Ethical concerns surround AI literacy. As AI plays an important role in day-to-day decision making, misused or poorly designed AI may cause irreparable harm to humans in their society. AI-concerned scientists and engineers expound on the horrors that future AI technologies may wreak on humanity in years to come.

Academic studies do not always mention human-centered considerations or call attention to educate citizens to become socially responsible. It was found that students pay little attention to ethical concerns such as bias in AI, legal responsibility, and intellectual property.

Teachers and educators should not only focus on enhancing students’ AI skills and interests, but also help students to realize the societal impact and ethical concerns.

Broadening participation in AI culture for the wider population is necessary to ensure that the design and utilization of AI technologies are inclusive to address under-representation of minorities in AI learning opportunities.

There is already growing public demand that the foundation of future AI-based industries will be built on “principles of inclusivity, provide equitable access to AI, include consideration of multiple stakeholders and potential users, and minimize the potential for bias”.

Conceptualizing AI literacy with human-centered considerations is crucial to building a future inclusive society.

Since AI literacy is an emerging field there is a lack of professional magazine and other periodicals published in this field. Ongoing studies are needed to examine effective means to foster students’ AI literacy, its assessment criteria, parameters and ethical concerns.

This discussion about AI literacy is an incomplete answer to the four big questions that were presented earlier above.


AI is part of the Fourth Industrial Revolution

This part is a phase of industrial changes is the merging of technologies like artificial intelligence, gene editing, and advanced robotics that blur the lines between the physical, digital, and biological worlds.

Throughout this ongoing revolution fundamental shifts are taking place on how the global production and supply network operates using continuing automation of traditional manufacturing and industrial practices, using modern smart technologies, large-scale machine-to-machine communication, and the internet of things.


Say it loud, say it clear: Education is a capital asset.

Acquiring education is akin to building an endowment that keeps on disbursing dividends.

People who manifest the ability to manipulate symbols of any kind, be it written language, mathematical symbols, or computer program coding are able to realize higher income. That’s a fact.

Software engineers earn $90-100K per year depending on their experience. A language Python software developer commands as high as 125K annually. And a senior Python developer can expect up to $150-200K annually.

(AI software engineers use Python programing language to build smart algorithms to perform their magic.)

Folks who lack AI literacy and have no idea what visionary AI entrepreneurs create are up to abe frustrated by the idea that these open-minded prodigies end up with huge fortunes after creating AI controlled service companies like Amazon, Uber, Palantir or Airbnb. Example. To decipher polypeptides and re-right them, an AlphaFold algorithm platform was designed by Google. AlphaFold is the artificial intelligence (AI) program developed by Alphabets's/Google's DeepMind, which performs predictions of protein structure. The program is designed as a deep learning system.

Example. Pfizer and Moderna were able to manufacture an mRNA vaccine by using an AI algorithms that artificially mimicked, reconstructed, produced in vitro, and then in scale the peptide structure of the Covid notorious spike. Sure enough Google, Pfizer and their likes are multi-billion companies.

The high net-worth economic class of the 2010s is a result of proliferating AI literacy and democratization of AI powered services and manufacturing companies.


In the year 2020 an AI agency was made public. It was dubbed GPT-3. Then an intermittent 3.5 upgrade was released and now we are left to figure out how is GPT-4 is the new GPT glass ceiling breaker. It is. Well, I asked “chatGPT”: what is the difference between the last two renditions. The answer I got left me wondering: “GPT-4 is more reliable, creative, and able to handle much more nuanced instructions than GPT-3.5. It has a significantly better context size and window than its predecessor model. GPT-4 is more of a data-to-text model, and can do things the previous version never dreamed of.” Go figure.


Of Significance. Running large and complex AI algorithms requires large and powerful super-computing “machines”.

At the same time products of large technology corporations like the ones mentioned above contribute to their country’s GDP.

As a result There is a positive correlation between AI literacy and GDP.

Because, GDP is a marker of the wealth of a nation.

Only a miniscule group of people are able to comprehend the significance of what is happening behind the monitor screen and inside the CPU of the computer which actually operate under the direction of an algorithm that was written by a software application developer.

The social consequences - individuals who don’t know – don’t know what they don’t know. Hence, they act out socially and politically against the “billionaires and the millionaires”…

As a result we see the formation of political and socio-economic classes divisions due to a novel kind of literacy or absence of the newly emerging literacy.

Let it sink in.

Economic disparities have the potential to find their social expression in street demonstrations, political upheavals and class warfare.

For those reasons AI literacy of the public is important. It’s important for advancing productive outcomes. Yet AI is used for nefarious purposes in some countries for AI based facial recognition becoming an instrument to control and surveil restive populations.

For good or bad, AI literacy is a social and economic necessity.


People with AI literacy have intellectual advantages compared to people who are sadly AI illiterate, such as:

Personalization: AI-based solutions can adapt to students’ level of education, speed of learning, and current educational goals.

Tutoring: Many students require extra help outside the classroom. AI can provide personalized feedback and guidance.

Quick responses: AI can answer students’ questions faster and more accurately than human teachers.

Availability: AI can offer learning opportunities anytime and anywhere, regardless of geographical or time constraints.

Creativity: AI triggers and inspire new ways of thinking and creating and by generating music, art, or text.

Diversity: Expanding AI literacy to include people from more diverse backgrounds and walks of life will further expand the ability of the human workforce to imagine new ways to apply and benefit from AI technology.

Dude, where are you?


The temporary last word:

- I asked my AI agent to give me a haiku. Here is its response:

Aye, crocs in space,

Jaws open wide, stars in sight,

Pirates beware, yarrr!

1 comentário

23 de mar. de 2023

Summary: In his paper, Mandy Lender argues that AI literacy is the new wealth of nations. He defines AI literacy as the ability to understand, use, and critically evaluate AI technologies. He argues that AI literacy is essential for individuals, businesses, and governments to succeed in the 21st century. Lender cites a number of studies that have shown that AI literacy is correlated with economic prosperity. For example, a study by the World Economic Forum found that AI-literate workers earn 25% more than those who are not AI-literate. Another study by the McKinsey Global Institute found that AI could add $13 trillion to the global economy by 2030. Lender also argues that AI literacy is essential for individuals to protect themselves from the…

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