By Dr Harini Santhanam, Associate Professor and HOD, Department of Public Policy, MAHE Bengaluru
Taming technology for realising societal outcomes such as education is a herculean task. In the contemporary educational landscape, if there was one field in education which experts, even until a few years ago, deemed collinear to the study of technology, it might be ‘Public Policy’. These subjects of study seemingly stretched towards the opposite boundaries of the educational spaces. Also, they did not coincide or converge on aspects of usage and useability of technology spaces that policies – both public and private – can create for their workforce and/or the societies. However, in today’s world of ‘Quantum supremacy’ among nations the stage is set to review how the traditional approach to public policy education is being transformed by emerging technologies due to two reasons:
- The evolving need to catch up with the delivery of the subjects on multiple platforms
- The increasing need to investigate the policy aspects of technology usage
It is interesting to observe how in her 2015 paper in Nature, aptly titled “The Quantum Gold Rush”, the author, Elizabeth Gibney had highlighted the burgeoning interest of many private investors and venture capitalists (VCs) of the then-Silicon Valley in a rush to found the next biggest quantum conglomerate that might control the entire decision-making space of human beings. Gibney’s spotlighted the increasing link of societal decision-making with the use of AI-based tools with strong examples from the IT space being created by the likes of Google and Microsoft. The work also stressed how quantum computing within the world of IT and AI, had the capability to offer precision computing, enforce unhackable encryption, produce supersensitive detection devices and use new forms of imaging. While these may have been considered buzzwords from the recent past, they indicate some key drivers behind the integration of emerging technologies with public policy education in the present times as a whole including the need for innovative solutions, data-driven decision-making, and interdisciplinary approaches.
Policy education is largely the crystallisation product of interactions between society, its laws and the administration. Learning from lived experiences becomes critical and core to the delivery of useful academic and research programmes in the domain. At a foundation level, the sheer amount of data available to teachers and researchers in Public policy is in reality, intimidating! Public policy education is hence, the superset of courses teaching practically everything mankind has lived through and/or experimented with. Thus, the challenge of delivering academics is new and needs to be met in new ways.
Technology, thus becomes an artificially intelligent, trusted knowledge partner for teaching public policy courses. They extend the capabilities of the teachers who deliver either full-time, part-time or executive courses in Public Policy to bring strong trans-disciplinarily, interconnectedness, domain depth and flavour to the exercise. In the case of researchers, AI-based inferential tools already have made a lot of difference in organising the literature reviews as well as the primary and secondary datasets. Access to the global library repositories and digital archives may not have been possible without the use of data mining techniques in existence.
However, while concurrent applications of AI generally begin to be viewed as beneficial, through the passage of time, it is deemed to illustrate gaps in its implementation and function. This observation by most industry experts underscores the need to apply evidence-based approaches to design appropriate AI policies for futuristic solutions. Take for example the use of block-chains in online payments. This is an illustrative example of a case of disappointment with technology, which is perceived as “fail-safe” among a majority of stakeholders, who have directly or indirectly invested in them. That is because of the huge expectations of societies on such revolutionary IT solutions, creating the demand that these methods work reliably during each and every time of access. Thus, the question here then of public services delivery is how “ready” AI-based technology can is for deployment in a public sector service field, or how reliant can Public Administration come to be on AI-based services for managing target audiences?
We are perpetually in search of such strong policies that can test the vagaries of time – envision for example, an odd YouTube sensation – a parrot impersonating a human voice, which is capable of repeatedly ordering a packet of sunflower seeds and strawberries for herself through an AI-based digital marketspace, without the supervision of a human caretaker/”owner”. This brings our attention to the integration of ethics with the use of AI-based technologies – how far can law and technology hold hands to produce positive social outcomes for public service delivery? Thus, the question now comes about how to optimise technology and legal readiness levels to achieve significant progress, while subscribing to the law of the land and strong implementation of the policies. I always stress in my own class of technologists-in-the-making how learning “technology and public policy” would bestow them with the vision of matching their core competencies with societal and organisational readiness levels as well.
Be it in the task of developing or delivering a course, or delivery of public services, technology would no doubt provide interesting insights when the four readiness factors are well defined and operate in harmony – the technological, social, legal and organisational readiness levels. A case in point is the move towards policies fostering integrated readiness in the European Union, which was presented at a recent conference by Bruno et al. The study aptly highlighted the need to develop a policy base that considers socio-technical assessments as complete in both contextual and inferential implementation modes, based on the aforementioned readiness levels.
Such assessments are key to determining the best-use scenarios of simulation tools, virtual reality, online collaboration platforms, and data visualization techniques to provide hands-on learning opportunities and simulate real-world policy scenarios. Public policy education aligning with the technology readiness to deliver the same would be beneficial to bridge the gap between Academia and Industry in three important ways:
- To highlight the importance of collaboration between academia and industry in keeping public policy education relevant to the rapidly changing technological landscape.
- To discuss partnerships, internships, and research collaborations that provide students with practical experiences and exposure to real-world policy challenges in emerging technology domains.
- To explore the learning outcomes and skills developed through these courses, such as critical thinking, data analysis, ethical considerations, and policy implementation.
This would mean successful leveraging of technology for Enhanced Learning, successfully addressing the challenges and considerations associated with integrating emerging technologies into public policy education and discussing potential ethical concerns, biases in algorithmic decision-making, privacy considerations, and the need for inclusive and equitable policy solutions in a classroom environment. The innovations arising from such integrated education will be helpful to judge the overall efficiencies of the policies to deliver public services successfully. The main challenge in achieving the desired readiness to adopt AI into Public policy education is to create assessments of competency frameworks to achieve the same among educators. At its best, technology can provide insights into the future implications of emerging technologies on public policy education. It can offer recommendations for policymakers, educators, and institutions on how to adapt and stay ahead of the curve in preparing students for the future of policy work.
