The Four Cs Of AI Literacy: Building The Workforce Of The Future AI & Surroundings

The AI market is projected to be 190 billion by 2025. AI applications, once the purview of only the most advanced technologists are now pervasive. The average human is likely to interact with at least one AI in their daily life, whether it is auto-correct on their phone, a movie or product recommendation, or, for some, a self-driving car or a digital assistant. While these are the AIs that the average person can see, the impact of the technology is possibly even greater in the AIs that they don’t see, that assist their doctors, their bank’s loan approvals, their city’s budget decisions, and more. The next generation, our children, are the first AI-Native Generation They have never known life without AI.

As AI permeates every industry, AI knowledge just in the hands of Data Scientists and technologists will not be sufficient. We are seeing the rise of a new type of literacy, AI Literacy, which will complement Digital Literacy in the workforce of the future. But what is AI Literacy and how can it be acquired? 

I consider AI Literacy to be the ability to understand and form opinions of the role of AI in our lives, industries, and communities. This includes understanding the basics of what an AI is, how it works, and what the strengths and limitations of the technologies are. Just as I do not need to be a computer programmer to appreciate the role of the internet in my life, understand my role in managing my online privacy, and how to leverage the internet for everything from restaurant reservations to job searches, AI Literacy does not require a Ph.D. in Computer Science. While some may require or desire a deeper learning of data science, algorithms, and programming, broad AI Literacy can be acquired through the following four Cs:

Concepts 

AIs operate via certain core concepts. For example, most AIs need to learn, and this learning occurs either by examining past data or trial and error experimentation and adaptation. For humans, understanding an AI’s need to learn can give them great insight into what the technology is capable of and what its limitations are. Similarly, as many AIs leverage data to learn, this concept helps humans appreciate the relationship between their personal information and the AIs that they interact with.

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Context

After core concepts, the next critical area to appreciate is context. The use of AI, its strengths and limitations, and its suitability can be extremely context-dependent. For example, if an AI is used to recommend a movie to me, the worst-case scenario is that I will end up watching a part of a movie I am not enjoying. While this can be concerning to the movie provider company if it happens too frequently – I may get irritated and stop using the service – that is the extent of the damage. On the other hand, a mistake made by an AI in a medical context can easily become life-threatening. An AI mistake in a financial context can damage both the user and the company via subsequent lawsuits. Accusations of AI bias can damage a company’s brand image. As with most technologies, the technical advances are ahead of the regulatory ones. Understanding these contexts can help industries implement best practices to protect themselves and their customers and drive the greatest return on investment while managing risk.

Capability

As AIs become more widespread, many humans will need to take some action regarding AI. The action itself can range widely. For example – a parent may need to guide their child on how to communicate with a digital assistant while preserving privacy. A doctor may need to understand what AI tools are available to assist them in their practice and how such tools work. An application programmer may need to learn how to build an AI and integrate it into their application. A lawmaker may need to review AIs that can be measured to drive effective regulatory approaches. Each of these requires not just understanding a core concept but also learning how to apply it in some context-specific way.

Creativity

Finally, while AIs are all around us, we are only at the beginning of applying AI technologies. New usages emerge daily, applying AI to everything from generating music to writing entire books. 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. 

Early Learnings

While AI Literacy is still a fairly new concept, it is already being applied worldwide with impressive results. AI learning programs for kids have proven that children, as young as 10 years old, can understand the core concepts and apply them in creative ways to solve problems in their communities. Companies are creating AI learning and upskilling initiatives  to broadly educate the workforce to fill the expanding skills gap. Non-profit organizations are organizing AI challenges to increase global awareness and encourage diverse participation and education. 

What the Future Holds

As our worldwide information economy expands, the role of data, and AI to generate insights from data, will continue to grow. Broad AI Literacy will enable countries, governments, industries, and private citizens to leverage AI technology safely and effectively. As more people become AI Literate, we can expect to see yet more usages and creative applications of this transformative technology.

social experiment by Livio Acerbo #greengroundit #thisisnotapost #thisisart