The most fundamental progress that technology has made over the past few decades is a dramatic increase in computing power coupled with a reduction in the cost of storage. Such progress has enabled us to run algorithms and code over swathes of data and at a fraction of the cost, thus yielding what some may consider more insights. Consequently, we are able to find patterns in large amounts of data. This, by some limited definition, is construed as intelligence and has been demonstrated in specific classes of activities such as detecting diabetes from retinal scans, driving cars, playing games, etc. In these cases, software can emulate human behaviour and perhaps even exceed human capabilities. But the fact is that we have not yet invented any new magic wand to make software “think” on its own or have any sense of “consciousness”, in the way humans do.
The limitation is grounded in the fact that software still operates, for the most part, on the paradigm of Gigo (garbage in garbage out), meaning it mostly only does whatever we tell it to and is biased based on whatever data we train it with. Give it incorrect data and it will pick up incorrect patterns.
But the vision and aspiration of computer science has always been to build a machine that can “accurately” emulate human “intelligence”. However, we still have a long way to go before we can build a software system that is functionally capable the same way a human is. Software “intelligence”, though defined in academic circles, has been fairly misused (and misunderstood) in popular reporting, giving people the impression that software can do just about anything a human being can. This notion is fundamentally misguided. We are not there. Or at least not yet. The gap between software and the human mind is still massive.
These gaps help to deflate claims that artificial intelligence (AI) and automation are ready to take over people’s jobs, and about the potential for mass unemployment, particularly in the Indian IT industry. This industry employs a couple of million people, largely consisting of our middle class, and recently it has been called out by commentators as being under threat from automation.
But automating away this labour force is not an easy task. Computer scientist believe in the superiority of silicon (computers) over carbon (humans), the work and study over the past few years in this industry have given reasons to pause and consider the unique contributions and value that humans bring to the table in enabling businesses the world over. Automating these unique attributes requires emulating the same human value.
In the case of the IT industry, for example, professionals perform a range of activities, from understanding customers’ business requirements to writing code, maintaining software systems and processing transactions. Working in teams, they perform a variety of different actions touching several information systems, coordinate with each other, navigate uncertain or changing scenarios, report to their managers, take bottom- line responsibilities for their respective systems, are accountable and serve customers across the globe. All these activities engender a deep sense of trust and confidence among their customers the world over.
At an individual level, each has traits such as intuition, experience, common sense, and an ability to identify and fix the unusual. These are fundamental traits that all humans share, though, admittedly, some more than others. Even in the most seemingly “robotic” of tasks, each human has the potential and ability to apply these traits without necessarily being told to do so a priori, traits that are inherent to each one of us, and ultimately create trust and confidence in our colleagues. This trust and confidence are the fuel that all businesses run on. Therefore, it has always been about more than just following “simple” rules.
Hence, any attempt by “intelligent” software at automating all that work done by a single individual or an entire team of humans must involve recreating the same trust and confidence. This necessarily requires addressing the whole gamut of these activities that humans perform on a regular basis and with similar human traits, but in software. This is no longer about small piecemeal tasks that are easy to automate. It must involve emulating the same traits of common sense, intuition, teamwork, communication, and an ability to deal with the unexpected.
Therefore, the next stage of innovation in computer science will be not just to make software run faster but also about how to get software to emulate more human-like traits and ultimately become truly trustworthy (like humans).
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- In the Large States category (overall), Chhattisgarh ranks 1st, followed by Odisha and Telangana, whereas, towards the bottom are Maharashtra at 16th, Assam at 17th and Gujarat at 18th. Gujarat is one State that has seen startling performance ranking 5th in the PAI 2021 Index outperforming traditionally good performing States like Andhra Pradesh and Karnataka, but ranks last in terms of Delta
- In the Small States category (overall), Nagaland tops, followed by Mizoram and Tripura. Towards the tail end of the overall Delta ranking is Uttarakhand (9th), Arunachal Pradesh (10th) and Meghalaya (11th). Nagaland despite being a poor performer in the PAI 2021 Index has come out to be the top performer in Delta, similarly, Mizoram’s performance in Delta is also reflected in it’s ranking in the PAI 2021 Index
- In terms of Equity, in the Large States category, Chhattisgarh has the best Delta rate on Equity indicators, this is also reflected in the performance of Chhattisgarh in the Equity Pillar where it ranks 4th. Following Chhattisgarh is Odisha ranking 2nd in Delta-Equity ranking, but ranks 17th in the Equity Pillar of PAI 2021. Telangana ranks 3rd in Delta-Equity ranking even though it is not a top performer in this Pillar in the overall PAI 2021 Index. Jharkhand (16th), Uttar Pradesh (17th) and Assam (18th) rank at the bottom with Uttar Pradesh’s performance in line with the PAI 2021 Index
- Odisha and Nagaland have shown the best year-on-year improvement under 12 Key Development indicators.
- In the 60:40 division States, the top three performers are Kerala, Goa and Tamil Nadu and, the bottom three performers are Uttar Pradesh, Jharkhand and Bihar.
- In the 90:10 division States, the top three performers were Himachal Pradesh, Sikkim and Mizoram; and, the bottom three performers are Manipur, Assam and Meghalaya.
- Among the 60:40 division States, Orissa, Chhattisgarh and Madhya Pradesh are the top three performers and Tamil Nadu, Telangana and Delhi appear as the bottom three performers.
- Among the 90:10 division States, the top three performers are Manipur, Arunachal Pradesh and Nagaland; and, the bottom three performers are Jammu and Kashmir, Uttarakhand and Himachal Pradesh
- Among the 60:40 division States, Goa, West Bengal and Delhi appear as the top three performers and Andhra Pradesh, Telangana and Bihar appear as the bottom three performers.
- Among the 90:10 division States, Mizoram, Himachal Pradesh and Tripura were the top three performers and Jammu & Kashmir, Nagaland and Arunachal Pradesh were the bottom three performers
- West Bengal, Bihar and Tamil Nadu were the top three States amongst the 60:40 division States; while Haryana, Punjab and Rajasthan appeared as the bottom three performers
- In the case of 90:10 division States, Mizoram, Assam and Tripura were the top three performers and Nagaland, Jammu & Kashmir and Uttarakhand featured as the bottom three
- Among the 60:40 division States, the top three performers are Kerala, Andhra Pradesh and Orissa and the bottom three performers are Madhya Pradesh, Jharkhand and Goa
- In the 90:10 division States, the top three performers are Mizoram, Sikkim and Nagaland and the bottom three performers are Manipur and Assam
In a diverse country like India, where each State is socially, culturally, economically, and politically distinct, measuring Governance becomes increasingly tricky. The Public Affairs Index (PAI 2021) is a scientifically rigorous, data-based framework that measures the quality of governance at the Sub-national level and ranks the States and Union Territories (UTs) of India on a Composite Index (CI).
States are classified into two categories – Large and Small – using population as the criteria.
In PAI 2021, PAC defined three significant pillars that embody Governance – Growth, Equity, and Sustainability. Each of the three Pillars is circumscribed by five governance praxis Themes.
The themes include – Voice and Accountability, Government Effectiveness, Rule of Law, Regulatory Quality and Control of Corruption.
At the bottom of the pyramid, 43 component indicators are mapped to 14 Sustainable Development Goals (SDGs) that are relevant to the States and UTs.
This forms the foundation of the conceptual framework of PAI 2021. The choice of the 43 indicators that go into the calculation of the CI were dictated by the objective of uncovering the complexity and multidimensional character of development governance
The Equity Principle
The Equity Pillar of the PAI 2021 Index analyses the inclusiveness impact at the Sub-national level in the country; inclusiveness in terms of the welfare of a society that depends primarily on establishing that all people feel that they have a say in the governance and are not excluded from the mainstream policy framework.
This requires all individuals and communities, but particularly the most vulnerable, to have an opportunity to improve or maintain their wellbeing. This chapter of PAI 2021 reflects the performance of States and UTs during the pandemic and questions the governance infrastructure in the country, analysing the effectiveness of schemes and the general livelihood of the people in terms of Equity.
Growth and its Discontents
Growth in its multidimensional form encompasses the essence of access to and the availability and optimal utilisation of resources. By resources, PAI 2021 refer to human resources, infrastructure and the budgetary allocations. Capacity building of an economy cannot take place if all the key players of growth do not drive development. The multiplier effects of better health care, improved educational outcomes, increased capital accumulation and lower unemployment levels contribute magnificently in the growth and development of the States.
The Pursuit Of Sustainability
The Sustainability Pillar analyses the access to and usage of resources that has an impact on environment, economy and humankind. The Pillar subsumes two themes and uses seven indicators to measure the effectiveness of government efforts with regards to Sustainability.
The Curious Case Of The Delta
The Delta Analysis presents the results on the State performance on year-on-year improvement. The rankings are measured as the Delta value over the last five to 10 years of data available for 12 Key Development Indicators (KDI). In PAI 2021, 12 indicators across the three Pillars of Equity (five indicators), Growth (five indicators) and Sustainability (two indicators). These KDIs are the outcome indicators crucial to assess Human Development. The Performance in the Delta Analysis is then compared to the Overall PAI 2021 Index.
Key Findings:-
In the Scheme of Things
The Scheme Analysis adds an additional dimension to ranking of the States on their governance. It attempts to complement the Governance Model by trying to understand the developmental activities undertaken by State Governments in the form of schemes. It also tries to understand whether better performance of States in schemes reflect in better governance.
The Centrally Sponsored schemes that were analysed are National Health Mission (NHM), Umbrella Integrated Child Development Services scheme (ICDS), Mahatma Gandh National Rural Employment Guarantee Scheme (MGNREGS), Samagra Shiksha Abhiyan (SmSA) and MidDay Meal Scheme (MDMS).
National Health Mission (NHM)
INTEGRATED CHILD DEVELOPMENT SERVICES (ICDS)
MID- DAY MEAL SCHEME (MDMS)
SAMAGRA SHIKSHA ABHIYAN (SMSA)
MAHATMA GANDHI NATIONAL RURAL EMPLOYMENT GUARANTEE SCHEME (MGNREGS)