The artificial intelligence (AI) market is projected to grow 309.6 billion by 2026 at a Compound Annual Growth Rate (CAGR) of 39.7 per cent during the forecast period, according to Markets and Markets. Factors such as the growth of data-based AI, advancement in deep learning, and the need to achieve robotic autonomy to stay competitive in a global market are expected to drive AI solutions and services adoption.
AI applications, once the domain of advanced technologists, have now become ubiquitous. It is likely that the average human interacts with AI at least once a day, whether it is auto-correct on their phone, a recommendation for a movie or product, or, for some, a self-driving car or a digital assistant. Even though these AI-powered regular programmes or devices are seen by the average person, there is probably a larger impact on the average person by AI they do not even see, such as those that assist their doctors and their banks for loan approvals.
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Since AI has permeated every industry, AI knowledge in the hands of data scientists and technologists is not sufficient. In the future workforce, AI literacy will complement digital literacy. What is AI literacy, and how can it be acquired?
Achieving AI literacy means understanding and forming opinions about AI’s role in our lives, industries, and communities. Knowing what AI is, how it works, and what strengths and limitations are. It doesn’t matter if you’re not a computer programmer to appreciate the role of the internet in your life, even though you use AI in your everyday life by managing your online privacy to book a table in the restaurant or do a job search. Some may desire a deeper understanding of data science, algorithms, or programming, but broad AI literacy can be acquired through the following four Cs:
AI is based on certain core concepts. AI, for example, must learn, and they learn by examining past data or by trial-and-error experimentation and adaptation. The ability for humans to understand how an AI learns can help them determine what the technology can do and what its limitations are. Similarly, since many AI-powered techniques use data to learn, this concept allows humans to appreciate the relationship between their personal information and the AI they interact with.
Context is another essential factor to be considered. Using AI, its limitations, strengths, and suitability can vary greatly depending on a wide range of factors. For example, if an AI recommends a movie to someone, the scenario can be that the user might end up watching a movie they are not even interested in. But if it happens too frequently, the user might stop using the service, which is all the damage it will do. Alternatively, a mistake made by an AI in a medical context can be life-threatening. Through subsequent lawsuits, an AI error in an economic context can damage the user and the company. AI bias accusations can damage a company’s brand image. In most technologies, the technical advances take precedence over the regulatory ones. Industry leaders can use these contexts to implement best practices to protect themselves and their customers and drive the greatest return on investment (ROI) while managing risk.
People will need to take action regarding AI as it becomes more prevalent. The action itself can vary widely. For example, parents may need to teach their children how to respect their privacy when communicating with a digital assistant. Doctors may need to understand what AI tools are available to assist them in their practice and how such tools work. It may be necessary for an application programmer to learn how to build an AI and integrate it into their application. To drive effective regulation, a legislator might examine AI that can be measured. Understanding a core concept is not enough; one must also learn to apply it in a specific context.
AI is applied to everything from music to writing books, with new applications being created daily. By being more inclusive of people with diverse backgrounds and life experiences, a broader range of perspectives will be represented in the human workforce, allowing them to imagine new applications and benefits of AI.
Although AI literacy is still a relatively new concept, it has already impacted the world. Companies are creating AI learning and upskilling initiatives to broaden the education of their workforce to close the growing skills gap. Various non-profit organisations are organising AI challenges to increase global awareness and provide diverse participation and education opportunities.
In a world that is becoming information-centric, the use of data and AI to interpret data will become increasingly important. To leverage AI technology safely and effectively, countries, governments, industries, and private citizens need a broad understanding of AI. AI will be used in more creative ways, and more applications as people become more proficient in it.