By Ananthanarayanan Venkateswaran and Shaji Joseph
By 2030, it is predicted that AI could be contributing $15.7 trillion to the global economy as per PwC’s Global Artificial Intelligence Study. But what would be the consequence if this AI learning and implementation happens without a much needed and stronger focus on digital literacy and governance? Billions may be left behind!
For example, a 2023 UNESCO’s global education monitoring report discusses the impact of actual learning and technology with digital integration.
Today, it is imperative for us to question whether students globally have the digital literacy skills needed for AI-powered jobs? And what can be done to ensure that they are learning to not just be certification ready, but are actually employable with valuable skills.
Nations across the globe stand at the cusp of a technological revolution. Artificial Intelligence (AI) is not just about which country or organisation is ready. But the impact of AI is so huge that it is clearly poised to redefine socio-economic structures completely.
AI education and customised frameworks:
When we think of a framework that provides very strong and truly valuable insights into making AI education accessible, we need to ensure that it takes into account the nation’s core or specific requirements. In other words, the frameworks adopted should be something that can truly fit right into the system too for a smooth execution. For example, when it comes to India, Dr. C.K. Prahalad’s ‘Bottom of the Pyramid (BoP)’, would be something that can be customised for maximum impact. On similar lines, when it comes to the United States, Dr. Clayton Christensen’s ‘Disruptive Innovation’ theory would be particularly relevant. In terms of UAE, the country’s ‘UAE AI Strategy 2031’ serves as a guiding vision, when it comes to Singapore, the nation’s ‘Smart Nation’ vision stands out, as for Japan, the ‘Society 5.0’ vision offers a strong foundation and so on.
This is particularly crucial in ensuring digital inclusivity across different socioeconomic groups and at the same time to up-skill the workforce for the AI-driven future for the right reasons with the right vision.
AI and it’s challenges:
At the same time, there are several regulatory challenges in the social media space too which highlight the need for clear data ownership rights along with fair competition and of course, clearly defined ethical digital practices.
Surprisingly, when it comes to AI’s adoption in developing countries, it is not infrastructure or technological challenge that is the main hurdle. It is digital literacy. For example, infrastructure such as mobile networks, cloud computing etc are growing, becoming cheaper, better quality of services is available and all of this is happening at a blinding pace, but at the same time, there are many people in developing nationals who lack the skills to leverage AI-powered tools effectively.
Education here is clearly the key as far as developing countries go. Well designed, planned and executed educational training programs in addition to strong policy initiatives can be ways to ensure they truly stand out as crucial steps for broader AI adoption. At the same time, when it comes to developed countries, the things they need to pay more attention to while focusing on AI are regulatory frameworks, data privacy concerns, and ethical considerations.
One thing that needs to be common whether for developed countries or developing nations is that, there needs to be a clearly defined educational program that can help explain how important regulating exploitative data practices by dominant platforms are. At the same time, they need to make sure that the users are cautious while using the technologies and platforms. This will allow them to make informed choices, use it responsibly and be aware of their digital footprint.
Industry-academia collaboration and fair competition:
Educational institutions truly need to step away from focusing on, “only theory” and or “grades” alone. They need to ensure those up-skilling with their learning programs are able to bridge the talent gap through industry-academia collaboration. This is also crucial today for regulatory measures to curb monopolistic digital practices.
Another important aspect here is that, these AI solutions should be co-developed with local educational institutions. This will help in preventing the concentration of AI knowledge within a few institutions or organisations, in the same manner as digital governance should ensure market fairness.
Digital transformation and ethical data practices:
AI-driven digital transformation has tremendous impact, especially in sectors of agriculture, healthcare, and manufacturing. Here, being guided by ethical data usage is of utmost importance.
Globally, there are cases that have shown how exploitative data-sharing practices have damaged and breached the trust of end users. AI-driven solutions must ensure transparency. At the same time, it needs to also make sure that the users have complete control over their data.
For example, its a great idea to have AI-enabled tools, that empower and boost speech recognition in regional languages. They can go a long way in providing tremendous support for education in rural and urban areas. But their deployment must align with very clearly defined and strong data protection laws. This will help to prevent unauthorised data harvesting.
Language and accessibility: User-centric digital rights:
AI education must prioritise language inclusivity. AI learning platforms should integrate vernacular languages to ensure broad participation. A good start when it comes to excellent learning on similar lines are examples from the Aarogya Setu app in India, The Immuni tracing app in Italy, TraceTogether app from Singapore, the Alhosn app in UAE, the COCOA app from Japan, The EU Digital COVID Certificate etc are all wonderful examples of how different nationals focused on ways in which these technologies empowered users with transparency in data-sharing and management of the same.
Up-skill: Governance and education:
What we need is a system that will ensure up-skilling and education in AI as a unified vision for AI and digital governance.
With this, the concern about data regulation on social media platforms, digital governance challenges across sectors need to be addressed. This will not only make way for a secure and inclusive digital future but also create a framework that can be a global example.
Educational institutions are taking steps toward democratising AI education. In this process, the educators, stakeholders and decision makers need to make sure that its success is also intrinsically linked to the broader digital ecosystem. This includes educating the masses on digital hygiene, data privacy, digital literacy while ensuring the systems supports fair competition among various digital platforms.
During the decade, we have seen various cases across the globe to draw lessons from. Especially when it comes to data regulation. Many such cases have shown us ‘what not to do’ and ‘what needs to be done’ to ensure it doesn’t happen again. For this, educational institutions must build an AI education and governance framework that prioritises inclusivity, competition, and user rights while looking at the future across various socio-economic demographics too.
There is no doubt that there needs to be an urgent need of AI education, but this needs to happen in connect and sync with digital governance. The lessons from the past showcases the urgent and dire need for clearly defined AI frameworks that not only prioritise user empowerment, fair competition but also transparency while ensuring educating the masses.
Educational programs need to integrate best practices from data governance into AI education policies. These as discussed above need to be customised across different nations and industries too, so as to be able to set a global benchmark in digital inclusivity.
This will also ensure that while AI’s use is empowering towards safeguarding democracy and user rights, it also serves as an exemplary force and example for equitable progress. In simple terms, revisiting Dr. C.K. Prahalad’s teachings emphasising innovation at the BoP, we can learn that irrespective of the nation or educational institution, this requires rethinking assumptions in a manner that will allow us to embrace this mindset to reshape AI’s future responsibly. It will also make sure that the technological advancement remains inclusive and ethical thereby catering to developing and developed nations.
AI is not going to wait for anyone to catch up. We are at a stage today that we cannot afford to fail in the process of building an inclusive AI education system. One in which ethical governance is an integral part of. If not, we risk deepening global inequalities tomorrow and leaving behind a confused workforce.
(Venkateswaran is the founder and chief executive officer at Techdivine Creative Services and Shaji is a faculty of corporate governance at Symbiosis Centre for Information Technology.)
