Building AI Literacy as the Foundation for Digital Transformation

By Professor Sarah Jones, Pro Vice-Chancellor Education, Southampton Solent University

When we think about Artificial Intelligence, images of robots taking over the world come to the mind of many. There is a worry that the world presented in science fiction has become a reality. What is really going on is that we have a tool, AI, that we can work collaboratively with to generate different ideas, new thinking and efficiencies.

AI has been around for decades, but it was through the launch of ChatGPT that we have seen it transform industries and reshape the way we live and work. The prototype generative Artificial Intelligent tool grew to more than 100 million users in three months making it one of the most quickly adopted tools. Its influence across all sectors was evident, education being just one of them.

 Implications of this and of course, the usual scaremongering, have been well documented, but the question most in my mind is :

“instead of banishing the technology, how can we harness the full potential of AI, safely, effectively and in new ways to complement our work?”

 This boils down to literacy. I developed a framework to help us understand the core literacies essential to understand AI, built on the critical work of media and digital literacies.

This framework is built upon Privacy, Verification, Bias, Ownership and Transparency. By understanding these, we can seize the potential of AI and work with it collaboratively for great outcomes.

Privacy: Safeguarding Personal Information

We need to use AI technologies responsibly and ethically and for this we need knowledge of privacy. AI systems increasingly handle sensitive personal data, and data privacy laws set standards for protection and privacy. Understanding the principles of data anonymization and encryption can help safeguard personal information from unauthorized access and breaches.

Verification: Ensuring Accuracy and Reliability

There are lots of deep fakes out there from the Pope in Balenciaga or Donald Trump in a police attack in New York. Social media is awash with AI-generated content, so it is essential to verify the accuracy and reliability of information. There is a need to question and fact check to discern credible sources from misinformation. This includes understanding how AI algorithms work and the potential for errors or biases in AI-generated outputs.

Bias: Recognizing and Mitigating Prejudices

One of the biggest concerns with AI systems is that it is only as good as the data fed into it, or the algorithms themselves. Research on bias within AI systems already have found facial recognition systems less accurate in identifying people of colour, or language translations systems associating with certain genders or stereotypes. A Stanford University study found that written work by non-native English speakers was more likely to be flagged as AI-generated, which could lead to more accusations of academic misconduct. Recognizing and mitigating bias is a key aspect of AI literacy. By understanding these biases, we can all work towards developing fairer and more inclusive AI systems, including advocating for diverse and representative data sets.

Ownership: Understanding Data and Intellectual Property Rights

This follows seamlessly from bias, as who does own the data used to train AI models? There is a need to understand the rights of individuals whose data is being used and the responsibilities of organizations that collect and process this data. With AI software being used to generate images, we need to understand who owns the IP and the rights to what is being generated.  

Transparency: Promoting Openness and Accountability

As we move into a new era with integrations of AI working across the sector, transparency is essential for building trust in AI systems. Part of this comes from clear documentation on how AI models are trained, tested, and validated. AI technologies are accountable and their impacts are clearly communicated to stakeholders. We need to know when we maybe communicating with AI, or when we are supported by it.

Embracing Digital Ambition: Collaborating with AI

Through this framework of literacies, we can begin to be critical and skilled users of the technology, but I’m leaving out the most crucial skill for successful digital transformation: ambition.

 We must be ambitious when it comes to technology, or we fall into a mentality that “robots are taking over” or “technology is being done to us”. Digital ambition embraces and collaborates with AI rather than working against it. AI has the potential to augment human capabilities, enhance productivity, and drive innovation. AI needs a seat at the table to be a partner in our exploration of ideas. This involves staying curious, continuously learning about AI advancements, and exploring ways to integrate AI into our work. By fostering a collaborative mindset, AI can be used to solve complex problems and create new opportunities.

Digital Transformation

It seems we are all somewhere on the road to Digital Transformation but we are still early in understanding the full capabilities of where it can lead us. If we are to get to a place where we realise its full potential, we need ambition and awareness. Through the AI literacy framework, we can become engaged, critical users of the technology, fostering a mindset that values ethical considerations and social responsibility.

 This knowledge will help drive our ambition.

 This ambition fuels transformation.

 Here is where we get to work collaboratively with technology, ensuring that AI can be used for the benefit of all.