India ST Entrepreneurship Recommendations
Analysis and Recommendations on Scientific Entrepreneurship In India
Concept Paper for Ministry of S&D
Table of Contents
In June 2020, the United States President’s Council of Advisors on Science and Technology (PCAST), released an important report identifying sectors, technologies and strategies where they believe the United States should invest and build capacity to maintain global leadership. Nish Acharya, the CEO of Equal Innovation, previously advised PCAST in his role as Director of Innovation and Entrepreneurship in the Obama Administration. The Council consists of eminent scientists, corporate executives and thought-leaders appointed by the President to guide the decisions of the President’s Office of Science and Technology Policy (OSTP) and is generally not partisan in its work.
Equal Innovation believes that many of the recommendations made by PCAST for the United States apply to India as well. Emerging technologies, such as artificial intelligence, synthetic biology and quantum computing are already priorities for Indian researchers and India already has a robust startup ecosystem around these advanced technologies. While R&D and innovation ecosystems are further developed in the United States, Equal Innovation believes that several of the recommendations made by PCAST are relevant for India as well.
The multiple crises of 2020 – COVID-19, the resultant economic recession and global geopolitical challenges, highlight the importance of locally developed innovations and technologies. Research and development (R&D) underpin India’s security, health, economic strength, and innovation enterprise. But India needs new collaborative initiatives that leverage the nation’s substantial assets - multi-sector partnerships that bring together the best ideas and capabilities, bringing people to the table; and strategies for greatly accelerating progress and removing barriers to innovation. Moreover, India must leverage the full potential of its human resources by overcoming historical barriers that have limited inclusion of individuals in STEM. This can unleash new potential and create pathways to economic prosperity for all, while helping to meet critical workforce needs.
India must think about how it will provide technologies that are cutting edge starting today, to the majority of its population by 2030. It must nurture private investment in startup companies and innovation that will make new products and services relevant to the Indian context. These range from technologies supporting remote learning and enhanced capabilities in medicine and telemedicine, to the rapid production of medical counter.
The Government of India, in partnership with philanthropy and private capital, can advance S&T entrepreneurship in multiple ways. The first, is to increase its traditional support for scientific research through grant making to scientists in academia and industry. In addition, the Government can continue to build innovation ecosystems at Indian research universities, hospitals and accelerator programs.
To expedite investment and entrepreneurship in these areas of Industries of Tomorrow, India will have to create new vehicles to drive investment. It must establish hybrid sovereign wealth fund or venture capital fund models focused on technologies and areas that it deems of strategic value, and then connect those technologies to its long-range economic development plans. The overall returns of the fund—from public markets and the companies it has backed—will ensure its perpetual survival beyond initial government funding. An initial investment of $10 billion, backed by the government of India and Indian private investors, will be on par with similar efforts around the world. Under this model, India will have $3 billion annually to invest in the best technologies and startup companies in the world. India can identify products, services, and innovation for the long-term on the basis of global mega-trends and India’s own development priorities for large-scale job-creation, with the vital filters of environmental sustainability and potential infrastructure challenges. India will also have to think creatively about how to build new ecosystems that connect to American and global markets but can succeed under India’s infrastructure constraints. This will require the linking of multiple cutting-edge technologies to meet focused goals.
The continued development of the Indian workforce is another area where new programming will be required. While the Government has invested heavily in skilling, it needs to take full advantage of its administrative authorities to connect its emerging STEM-trained population with industry and academia in new and innovative ways, particularly to ensure the effective development of research-culture, and the transition and translation of early-stage research outcomes into applications at scale.
Maintaining India’s competitive position on the upcoming areas of Artificial Intelligence, QIS and Synthetic Biology is of critical importance to the future of the nation as it enters the era of 4th Industrial Revolution in Science and Technology. Though this era is marked by great challenge as other nations advance rapidly, it also is marked by great promise. Equal Innovation has analyzed the PCAST Report, “Recommendations for Strengthening American Leadership in Industries of the Future” for the Indian context. Our analysis and recommendations are explained in the following pages.
AI touches nearly every aspect of modern society, from our daily lives to business operations to how research is performed. Advancing rapidly as a technological force, AI is affecting all industries and economies. AI has the potential not only to transform S&T, speeding up the pace of scientific discovery and technical innovation, but also to improve essential activities, such as developing solutions to COVID-19. Globalized access to information and accelerated technology adoption are collapsing the timescale for innovation—AI in particular is advancing at a pace not seen in any technological field in the last century.
The advances in AI that are powering today’s rapid progress are originating around the globe, and India cannot risk falling behind. To keep up with the world, India will need to move swiftly to increase investment and restructure its R&D partnerships across industry, academia, and government, and with other nations. Aiming at goals such as “creating 10 new critical materials and molecules for 10 industry sectors in 10 years”i, as PCAST repo can be vital for driving innovation in AI and broadly advancing intrinsic capabilities in S&T. The Department Of Science & Industrial Research should create a Test and Evaluation (T&E) foundationii for AI that defines and implements standard evaluation methodologies and measures for AI systems and quantifies critical dimensions of performance for trustworthy AI including accuracy, fairness, robustness, traceability, and transparency.
Five of the top industry technology leaders (Amazon, Facebook, Google, IBM, and Microsoft) spent over $65 billion in R&D in 2018. A large and growing portion of this spending involves work in artificial intelligence. The Indian government should target its investments in a way to lay the foundation for future transformative discoveries in AI and incentivizing innovation in and investment by the private sector in India. Economies of scale can be achieved by sharing resources, materials, data, and infrastructure. More broadly, identifying and replacing duplication with synergistic, streamlined activities could enhance the combined capability and result in significant cost savings that could then be reinvested in the research enterprise.
New initiatives are needed to create trustworthy AI systems that advance AI capabilities and reduce the likelihood of adverse impacts. This input should be used to build trust and understanding of mutual contributions to assure a successful partnership model and record best practices in the existing successful agreements. To achieve this, central agencies, like DST, AICTE and UGC, should elevate the importance given to partnerships with industry to develop and deploy AI applications at scale, including applications such as intelligent citizen care and modernizing data and information technology. They should also bolster support for basic research on cross-cutting areas such as AI security and vulnerability; connectivity and communications; data curation and governance; privacy and ethics; and the implementation of associated best practices.
Fully seizing the opportunities presented by AI requires a robust collaboration among industry, academia, and government, facilitated by significant and sustained investments to address research and workforce development challenges.
The premiere technology-research centers, like IITs, ICMR, TIFR etc., should establish partnerships with industry to create a co-funded program that supports faculty and post-doctoral students working in AI to spend time in industry to better understand needs for AI technology and obtain continuous feedback for basic research. Universities should also create a framework and incentives (accelerator funds, seed grants, industry- supported sabbatical leave) to support basic, application-driven, and interdisciplinary AI research and ease the process for rotational assignments across industry and academia. It is important to create a virtuous cycle aimed at the innovation infrastructure itself that can continuously accelerate R&D in AI.
Keeping in mind that education is a subject in the Concurrent list, state governments should continue to balance AI R&D across near-term and long-term goals according to the directives laid by the Central investment in both fundamental research and translational efforts across academia, government, and industry. These could include companion “mission-driven” AI laboratories that expand on the by providing facilities that allow AI researchers from academia, industry, and DST powered research centers to access unique data, tools, and expertise. These centers would enable research on core and applied AI (e.g., AI for agriculture, AI for manufacturing)iii as well as on cross-cutting topics such as AI for social good, the future of work, and harnessing big data.
Recommendations to Increase AI Capability and Innovation:
Data is the fuel for AI, and in India, there is an urgent need for the vast and highly significant amounts of data currently being generated to be made AI-ready from the start, and to manage critical elements of successful collaborations, including common ontologies, data ownership, and access. To tackle this urgent need for building data management systems that support data governance, provenance, semantics, curation, and assessment of quality. In alignment with the PCAST Report of June’20, Equal Innovation also recommends that every ICMR Centre and DST Laboratory should appoint qualified data science officers to achieve this goal.
Increasing investment in STEM education will be more important and relevant than ever in the post-COVID-19 crisis world, given the growing requirements for data science, data management, curation and access, ML, and AI engineering. We also need to start engaging secondary schools and universities with a curriculum addressing emerging interdisciplinary AI areas, the societal applications and implications of AI, and highlight AI policy and ethical behaviors with regard to fairness, privacy, and data provenance. This would help train a highly skilled AI workforce at community colleges, and via certificate programs, online degrees, university programs, and workforce retraining programs. Participation of under-represented and under-served populations to expand the talent pool and create outreach, diversity, and inclusion programs for AI should also be on the radar.
India will also need to move quickly to address AI skills shortages in the workforce. While industry pledges to scale investments on training and education of the Indian workforce in AI, they should also launch education and certification programs in AI, programs for reskilling workers in AI, and sponsoring research fellowships and residency programs in AI. Promoting faculty entrepreneurship and split appointments between academia and faculty-driven start-ups is also of great significance. This can be done by facilitating a stronger alignment between faculty and industry by increasing faculty joint appointments with industry and industry appointments with universities, including industry engagement in curriculum development, teaching, and training. Employee contracts could be streamlined with non-compete requirements, and AI faculty workloads could be redefined, to enable faculty who are significantly engaged with industry.
Government should also support the Ministry of Human Resource Development (MHRD) to develop a new national program for building AI skills digitally for an AI-ready workforce that empowers and enables students and mid-career professionals to realize the opportunity AI represents through continuous and tailored online training and education.
Enhancing AI capabilities require establishing a joint AI Residential- fellowship program, AI Research Institutes in all 28 States and 8 Union-Territories, National AI Testbeds, partnerships for curating and sharing large datasets, and joint international programs for attracting and retaining the best global talentiv, and research and development (R&D) and training for trustworthy AI. This should be accomplished, in part, by expanding the programmatic funding of existing offices, directorates, and programs that support AI R&D at Department of Science & Technology, ICMR, IITs, and the UGC.
Furthermore, India should seek out, among its allies and like-minded partners, increased international collaborations with academic institutions and industry. This is critical for allowing the India to stay up front in the global AI race, particularly in working with other countries that are making significant investments and have strengths that complement Indian capabilities. For this, we could come up with a program that allows for the exchange of scientists across partner unions and nations to improve collaboration and information sharing in artificial intelligence.
There has been much talk about the 21st century being the biological century—and for good reason. The visions for the role of biology and life sciences are often prophetic, and these scenarios will unfold only over the long term. Countries like India, which possess the requisite talent and technical capabilities, can modernise the industrial landscape in the next 20 years by converting to cheaper, more environmentally sustainable processes that rely on locally sourced biological inputs. Many of those organisms are likely to possess genes and proteins that could be harnessed in next generation therapeutics or bio-based industrial processes.
In line with these developments is synthetic biology, which is the deployment of a set of technologies to transform the insights from basic research in life sciences to bio-based solutions that either enhance or replace existing industrial processes. Those enhancements or replacements can take the form of engineered enzymes or engineered organisms. It starts with a characterisation of naturally occurring microbial organisms as sources for molecular components that can be applied to industrial processes.
Given the pace at which technology is advancing, it is not impractical to imagine a world where 15% of chemical industry revenues will be generated from products made with engineered microbes, 30% of bench science will be transitioned to computational biology and 20% of inherited and metabolic diseases will be cured through gene therapy and stem cell therapy.
A few core technologies are transforming these breakthroughs into useful tools for companies, physicians, farmers, and others. The sooner India invests in these upcoming technologies, and builds the requisite professional talent pool—leveraging existing talent in the pharmaceutical and IT industries— the earlier it can begin to build the industrial ecosystems for these start-ups and technologies that will ultimately create large numbers of jobs and economic growth.
Given India’s biodiversity and the scale of its needs, the ability to harness these natural endowments becomes even more pressing. Indeed, India is considered to be one of the most bio-diverse countries in the world, with an immense number of plant, animal, and microbial species. Many of those organisms are likely to possess genes and proteins that could be harnessed in next generation therapeutics or bio-based industrial processes. India will also have to think creatively about how to build new ecosystems that connect to global markets but can succeed under India’s infrastructure constraints. This will require the linking of multiple cutting edge technologies to meet focused goals.
In order to create manufacturing jobs for India’s youth, Distributed Manufacturing (DM) model can be adopted. It links several cutting-edge technologies such as 3D printing, bioreactors, bio-based plastics, computer-aided design, data analysis, and small-scale logistics. Considering the fact that India’s manufacturing strategy cannot mimic that of the U.S. or China, most of the products are also likely to be in the form of high-value added engineering products made in small batches This is frequently referred to as “mass customisation” as opposed to the “mass production” of standard products during the last industrial revolution. We can, hence, make use of 3D printing which enables the highly distributed production of customised products with minimal capital expenditure.
As software was the key of India’s growth story in the 1990s, technologies like 3D printing will drive the global markets in 2020.The 3D printing facilities can use the bio-based plastics to create products that are then transported to central distribution centres for local or international customers. These facilities could be located in Tier II and Tier III Indian cities, creating a large number of high-paying manufacturing jobs as well as ancillary employment extending from the farm with the generation of waste carbon inputs, to the logistics and transport of those inputs for conversion to plastics, and the final delivery of the bio-based plastics back to the 3D printing centres.
These can then be linked to global markets through e-commerce, in ways similar to how small-scale Chinese manufacturers are linked to global customers by sites such as Alibaba. The string of these technologies can, ironically, enable the modern realisation of Gandhi’s vision of sustainable, local manufacturing that creates large-scale employment and generate incomes.
Quantum Information Science:
With India's active Internet user base predicted to hit 639 million by the end of 2020, development of quantum information science (QIS) is crucial. QIS includes the fields of quantum computing, quantum communications (and more generally quantum networking) and quantum sensing. Collectively, they represent the next frontier in the worlds of information processing and computation, secure communications, and novel navigation systems. Quantum computing user facilities will undoubtedly become equally essential for a broad range of research needs of the Indian R&D enterprise in this decade.
A quantum network would provide a test-bed for developing required components, such as qubit transducers and quantum repeaters, and a mechanism to explore quantum network protocols, cryptography. This work would exploit synergies between quantum computing and quantum communication. Linking these two fields early could enable researchers to demonstrate remote entanglement technologies and protocols for secure quantum sensing, communication networks, and secure quantum cloud computing.
Also, establishing national quantum computing user facilities to jump-start quantum algorithm and application development and quantum computer science, make available a critical scientific and computational resource to scientists at Indian research laboratories and Universities, and serve as a market-making catalyst to accelerate the growth of Indian industry producing quantum hardware and software.
Considering the all-encompassing nature of QIS applicability, there is a need of a National Quantum Act aimed at accelerating quantum R&D through increased spending, and a strengthening coordination of quantum R&D across the Central Government, and new QIS consortia around the country. There should be a clause ensuring education to a dedicated quantum workforce, create pre-competitive quantum research collaborations, establish quantum foundational discovery institutes, and to attract and retain the best global talent. Under the very Act, provisions for targeted investments should be made, ranging from open access to quantum technology systems and services to developing and sharing open source quantum software communities and open quantum curriculum, including quantum textbooks, YouTube channels, and lecture series.
Universities are uniquely positioned to lead new forms of partnership in QIS. Many of the intellectual drivers for QIS have come from academia, where exploration of the boundaries of conventional disciplines and expansion of intellectual frontiers are essential mandates. Thus, universities can act as the pivot point for partnerships supported by private foundations and industrial partners, in which academic researchers may work together in focused efforts targeting foundational and long-range research in QIS University researchers can collaborate creatively in partnerships with industry and government to accelerate the development of quantum information processing in all aspects. For instance, establishment of university-based institutes of quantum researchers funded by private foundations— facilitated or co-funded by NSF or other appropriate agencies—that collaborate with industrial partners. Such foundational discovery institutes would provide long-term funding for teams of faculty members to work together in focused efforts, targeting crucial issues relevant to quantum technologies: new materials, devices, algorithms, and applications.
We have to keep in mind that Indian universities as a whole do not have curricula in place to train the next generation of specialists in these fields. By leveraging public-private partnerships, institutions of higher education across the subcontinent can create novel curricula and training programs to spark undergraduates, graduate students, post-doctoral fellows, educators, and faculty interest and advance QIS education. And as the quantum generation, new modes of teaching are needed for a new science that is characterized by the unusually large extent of interdisciplinary work that characterizes QIS. Creation of a flexible curricula and industry-infused shared education modules will require new modalities for appointments and leaves-of-absence in all three sectors, to enable teaching or co- teaching across both traditional disciplinary boundaries and the conventional boundaries between academia, industry, and research centers.
High Processing Computing:
Quantum computers are still at the dawn of their innovation journey, the potential for accurate simulations of chemical reactions is real. Today’s supercomputers can simulate relatively simple molecules, but when researchers try to develop new complex compounds—whether for life-saving drugs or better batteries—classical computers cannot achieve the same accuracy and may not be able to carry out a simulation at all.
Continuous advances in HPC have helped accelerate discovery, for example by reducing vast libraries of potentially useful molecules to a much smaller set of probable leads for therapeutically active compounds. Ever-more powerful computational software is helping simulate molecular interactions for more targeted cancer immunotherapy, leading to better catalysts for creating high-performance plastics, and creating more durable electrolytes for high-energy-density batteries for electrical transport.
The discovery and design process of small molecules for drugs or industrial materials remains a lengthy and costly endeavor in both human expertise and computational power. Two additional computing approaches—quantum computing and AI—have the potential to reshape discovery by complementing the strength of classical HPC while addressing its shortcomings. As quantum computing addresses the accuracy limits of classical HPC simulations for solving chemistry problems, AI can play a crucial role in efficiently and constructively exploring the vast chemical search space—and already is making a mark on the process of discovery.
The Accelerated Discovery Workflow: Catalyzing Innovation
Following Accelerated Discovery Workflow (ADW)v leads to the convergence of HPC, AI, and quantum computing, which in turn, leads to the enhancement of the productivity of scientists and engineers involved in the process of discovery. The use of massive AI and HPC capabilities can help identify new targets by analyzing the large amounts of biological data being generated through new technologies.
The ADW of Deep Search (step A) leverages AI to derive information and data from the collective domain knowledge stored in documents such as scientific publications and lab reports. Intelligent Simulation (step B) augments the known with classical or quantum simulations optimized to yield maximum information gain. AI Generative Models (step C) trained on the aggregate data from steps A and B, identify new ideas and possibilities. Driven Experimentation (step D) AI accelerates experimentation by performing in-situ analysis during the experiments and using this analysis for real-time control of experimental parameters in labs.
Benefits from the convergence of HPC, AI, and quantum computing include metamorphic manufacturing; financial technology (FinTech), such as algorithmic trading; marketing by aggregating huge volumes of data to influence consumer decisions and spending precisely; meteorology through improved pattern recognition and processing speed for weather prediction; and logistics through optimization of workflows associated with transport management, fleet operations, traffic control and supply chain management.
Most computing in the future will be delivered via the cloud, and the massive investments in that space should be leveraged. A stronger emphasis should be on the importance of addressing software challenges, including complexity, correctness, trust, and sustainability. The usability and enablement of advanced computing for those without deep supercomputing skills should be equally prioritized. It is important to recognize that future computing initiatives should focus directly on scientific, economic, and societal impact, rather than on simply building systems with increased peak performance.
Institutes for the Industries of Tomorrow (IOTO):
The Institutes for the Industries of Tomorrow (IOTOs)vi present a new means of catalyzing world-shaping research; foster cross-agency and industry partnerships; maximize time for research by reducing unnecessary bureaucracy; facilitate a business-friendly IP framework that encourages investment; establish world-class multi-user facilities that likewise support the Workforce of the Future; strengthen the pipeline for the technical talent pool; and develop world-class personnel with access to stable funding streams—all of which lead to a positive and sustainable national economic impact. This convergence through multi-sector partnerships, partner-favorable IP policies, tax incentives to accelerate economic growth, the formation of a competitive ecosystem to increase the pool of talented researchers in IoTo, and close cooperation between basic and applied research endeavors to maximize intellectual interactions for a virtuous cycle of innovation.
The best way to move forward would be to set up an appropriate group of experts to define the most important materials to pursue for Indian success across a broad array of sectors (e.g., vaccine discovery, fertilizers in agriculture, and new lithium chemistry batteries for electric transportation). Define three categories: top-5 materials to discover in the next 5 years, top-10 in the next 10 years, and top-20 in the next 20 years. Establishing leadership involves strategically combining two or more of those areas on compelling problems of societal importance. Then the IoTo Institutes will expand upon a strong existing national foundation by implementing new models to accelerate the delivery of S&T advances and by introducing improvements to increase return on investment and drive commercialization of technology at scale.
Opportunity lies in applying several of the five IoTo areas in a cross disciplinary manner, in order to solve grand challenge imperatives of societal significance. Basic and applied research are both required to realize this vision, better integration of basic and applied initiatives will improve the transfer of fundamental discoveries to commercial markets Unnecessary and ineffective administrative burdens will be reduced or eliminated, addressing IP challenges and opening the door for exploration of new ideas, especially those having high intellectual risk but potentially enormous societal benefit. Tight coupling between fundamental and applied research will also enable rapid feedback and improve deployment.
The proposed IoTo Institutes leverage the same or similar mechanisms to enable favorable tax treatment in the form of capital gains tax deferrals and/or tax breaks, informed by lessons learned from prior Opportunity Zone investments. Equal Innovation believes that similar incentives, together with well-defined IP terms, could be exceptionally valuable in driving collaboration in the advancement of IoTo for the economic development of local communities and the Nation as a whole.
We envision the IoTo Institutes as a prominent venue for concentrating S&T talent and facilitating the cross-fertilization of ideas among leading researchers from all sectors. We also propose engaging a diverse set of early career researchers, selected through a highly competitive process, to collaborate with the luminaries of the IoTo Institutes. The economic resilience of STEM fields and their corresponding potential to impact economic recovery through innovation and commercialization are also acknowledged.
Along the lines of the PCAST recommendations, Equal Innovation’s first proposed institute would combine R&D in AI and biotechnology to enhance the Nation’s biosecurity, biosafety, and biosphere sustainability. The COVID-19 pandemic has revealed both daunting challenges and important opportunities within the field of biotechnology, particularly at the interface of biology, medicine, and advanced digital technologies. There is a clear need to sustain and expand the Nation’s biological and biomedical R&D to improve our ability to manage and treat infectious disease. It would work to expand analytical methods enabled by AI and ML to advance our understanding of the spread of disease and improve the efficacy of treatments and vaccines—and accelerate their discovery. More fundamentally, an improved understanding of transport phenomena for sub-atomic, atomic, and molecular moieties across the cell membrane and within cells will provide mechanistic foundations for biosecurity, advanced therapies, and food security for the country.
The second proposed Institute focuses on the R&D required to enhancing AI and ML tools and capabilities relevant to generative design in advanced manufacturing. Given the clear and far-reaching implications of AI and ML that continue to emerge in nearly all areas of S&T, another institute would ideally focus on R&D for leveraging the myriad data-intensive benefits of AI and ML within the particular context of advanced manufacturing and generative design, while also addressing a pressing need to expand Indian manufacturing capabilities in the context of advanced communication integration & infrastructure (5G and beyond). Similar institution finds mention in the PCAST report as well.
Intellectual Property and the IoTo Regime:
It is important to highlight the value of flexible IP terms in public-private partnerships for accelerating commercialization. Coming at an understanding about how IP will be governed is a key issue. This is critical in the context of the challenges India currently faces with intellectual property with multinationals—it can sidestep these by outlining IP ownership from the start, for the Indian market and outside of India. First, if industry participants cover all costs, then they should be able to dictate IP terms independent of the physical or digital capabilities used in the course of creating any given invention. On the other hand, if industry participants are only partially covering costs or using lab capabilities on an in-kind basis, then further negotiation on foreground IP ownership and potential royalty fees are anticipated. Easing of regulations to enable more flexibility in responding to the COVID-19 pandemic may foster accelerated innovation in some markets/applications related to managing and fighting the virus.
Workshops of the Future:
Equal Innovation also envisions Workshops of the Future (WotF)vii leveraging advanced physical and virtual assets for dramatically enhanced versatility and efficiency. IoTo Institutes will serve as a mechanism for conceiving, testing, and ultimately implementing these benefits. A key enabler for WotF is deployment of digital twins—digital replicas or simulations of all of the factory’s assets that allow companies to model, track, and understand their entire factory by mirroring operational performance computationally. Once mature, they enable manufacturing companies to transform operational decision-making and capabilities. Coupling digital twins with additive manufacturing could enable rapid improvements or adjustments to equipment, removing the need to identify a problem, place an order, and wait for parts.
Reliable digital twins, enabled by development and utilization of AI/ML far beyond today’s capabilities, would create new opportunities for improvements at scale. Once digital twin status is achieved, the global competitiveness of Indian manufacturing will be greatly enhanced by facilitating prediction of failure modes well in advance of their physical manifestation and to thereby enable realization of associated competitive improvements in WotF output. The digital twin concept can also be extended beyond the manufacturing plant to encompass entire supply chains: from the supply of raw materials and goods, to individual plants, to downstream distribution of finished goods. These logistics and supply chain relationships are incredibly complex; the combination of reliable digital twins with smart manufacturing (known as Industry 4.0), along with emerging AI/ML (and potentially quantum computing capabilities) could enable competitive benefits for Indian industry.
We must leverage the full potential of our human resources, which will require a commitment to ensuring inclusion of individuals who have been underserved and underrepresented in STEM—whether on the basis of race, ethnicity, gender, sexual orientation, disability, socioeconomic background, or geographic location. Broadening access to those who are in underrepresented and underserved communities—including those who have been displaced by pandemic-related economic disruption—can unleash new potential and create pathways to economic prosperity while helping to meet critical workforce needs in STEM.
Educational programs designed with industry-recognized, skills-based credentials would give students confidence their degrees are preparing them to succeed in the jobs of tomorrow. For individuals already in the workforce, certifications would provide guidance for reskilling, upskilling, and making informed career advancement decisions resulting in increased economic prosperity. Such credentialing programs could be informed by existing models such as certification for public accountants (CPAs), licensed nurse practitioners (LNPs), and paralegals (CPs).
In light of the need to adapt academic programs to the constraints posed by COVID-19, Equal Innovation recommends a concerted focus on training courses based upon both in-person and virtual learning for the near term. In addition, partnership-driven opportunities for experiential learning through research, internships, and apprenticeships will help build the necessary skills to meet the growing demands of the future STEM workforce at all education and training levels. These can also reinforce positive relationships between local public and land-grant universities, which drive regional innovation and economic development of the States. For employers, committing to create skills-based, standard job codes tied to industry certifications will clarify hiring requirements for firms seeking to fill positions and provide a clear understanding of what prospective employees are capable of doing.
It is essential that India build up its ability to strengthen, grow, and diversify its science, technology, engineering, and mathematics (STEM) workforce at all levels—from skilled technical workers to researchers with advanced degrees. DST should establish a grant program to create and pilot multi-sector, Workforce of the Future STEM Retraining Boards that connect individuals to new or existing opportunities for continuing education, training, certification, and reskilling in STEM fields.
Federal funds, matched by support from the private sector and universities, are needed to create industry-recognized curricula and work-based learning and training programs in QIS, AI, and advanced manufacturing. Structured as public-private partnerships, these efforts should yield universal skills-based licenses and certifications targeting IoTo.
This is the opportune time to establish a new variety of world-class, multi-sector R&D institute that catalyzes innovation at all stages of R&D—from discovery research to development deployment, and commercialization of new technologies. We also need to utilize innovative intellectual property terms that incentivize participation by industry, academia, and non-profits as a means for driving commercialization. These institutes would be located to maximize multi-sector collaboration and the ability to function as regional hubs for technological, economic, and skill development. The first would focus on the integration of AI and advanced manufacturing, while the second would combine AI and biotechnology to enhance biosecurity, biosafety, and biosphere sustainability.
Finally, these recommendations should be pursued in a manner that preserves momentum on programs with established value; the intention is not to reinvent the wheel, but rather to assure alignment of purpose and maximum impact in the interest of our nation. The pace of technology continues to accelerate, and therefore solutions are needed that can address near-term challenges while simultaneously laying the groundwork for the future.