Centre for Internet and Society

Project on Gender, Health Communications and Online Activism with City University

ambika — 2019-12-02T09:38:21Z

CIS is a partner on the project 'Gender, Health Communications and Online Activism in the Digital Age'. The project is lead by Dr. Carolina Matos, Senior Lecturer in Sociology and Media in the Department of Sociology at City University.

It is funded by the Global Challenges Research Fund. Ambika Tandon, Policy Officer at CIS, conducted fieldwork for the project in May and June 2019 as a research assistant.

The goal of the project is to advance research on how new communication technologies (ICTs) can be used to create awareness of gender equality and sexual and reproductive rights. It aims to assess how the use of technologies, by women's groups and feminist NGOs can empower women in developing countries to advance citizen and human rights with the intent to influence policy at the global and local level. More information on the preliminary findings of the project can be found in the downloadable presentation."

You may find Dr. Carolina Matos's presentation here.

For more details visit https://cis-india.org/internet-governance/blog/project-on-gender-health-communications-and-online-activism-with-city-university

Concept Note and Agenda for Stakeholder Consultation

ambika — 2020-04-07T13:10:01Z

Digital Assets for Women’s Economic Empowerment (WEE): Addressing Barriers and Enhancing Opportunities for Women in the Informal Economy and Agriculture Day & Date: Friday, 6 December 2019 Timing: 9:30 am to 4:30 pm Venue: Conference Hall, The Claridges Hotel,12 Dr APJ Abdul Kalam Road, New Delhi

For more details visit https://cis-india.org/raw/concept-note-and-agenda-for-stakeholder-consultation

AI in the Future of Work

ambika — 2021-12-07T01:51:42Z

Artificial Intelligence and allied technologies form part of what is being called the fourth Industrial Revolution.

Some analysts project the loss of jobs as AI replaces humans, especially in job roles that consist of repetitive tasks that are easier to automate. Another prediction is that AI, as preceding technologies, will enhance and complement human capability, rather than replacing it at large scales. AI at the workplace includes a wide range of technologies, from machine-to-machine interactions on the factory floor, to automated decision-making systems.

Studying the Platform Economy

The platform economy, in particular, is dependent on AI in the design of aggregator platforms that form a two-way market between customers and workers. Platforms deploy AI at a number of different stages, from recruitment to assignment of tasks to workers. AI systems often reflect existing social biases, as they are built using biased datasets, and by non-diverse teams that are not attuned to such biases. This has been the case in the platform economy as well, where biased systems impact the ability of marginalised workers to access opportunities. To take an example, Amazon’s algorithm to filter workers’ resumes was biased against women because it was trained on 10 years of hiring data, and ended up reflecting the underrepresentation of women in the tech industry. That is not to say that algorithms introduce biases where they didn’t exist earlier, but that they take existing biases and hard code them into systems in a systematic and predictable manner.

Biases are made even more explicit in marketplace platforms, that allow employers to review workers’ profiles and skills for a fee. In a study of platforms offering home-based services in India, we found that marketplace platforms offer filtering mechanisms which allow employers to filter workers by demographic characteristics such as gender, age, religion, and in one case, caste (the research publication is forthcoming). The design of the platform itself, in this case, encourages and enables discrimination of workers. One of the leading platforms in India had ‘Hindu maid’ and ‘Hindu cook’ as its top search term, reflecting the ways in which employers from the dominant religion are encouraged to discriminate against workers from minority religions in the Indian platform economy.

Another source of bias in the platform economy are rating and pricing systems, which can reduce the quality and quantum of work offered to marginalised workers. Rating systems exist across platform types - those that offer on-demand or location-based work, microwork platforms, and marketplace platforms. They allow customers and employers to rate workers on a scale, and are most often one-way feedback systems to review a worker’s performance (as our forthcoming research discusses, we found very few examples of feedback loops that also allow workers to rate employers). Rating systems have been found to be a source of anxiety for workers, as they can be rated poorly for unfair reasons, including their demographic characteristics. Most platforms penalise workers for poor ratings, and may even stop them from accessing any tasks at all if their ratings fall below a certain threshold. Without adequate grievance redressal mechanisms that allow workers to contest poor ratings, rating systems are prone to reflect customer biases while appearing neutral. It is difficult to assess the level of such bias without companies releasing data comparing ratings of workers by their demographic characteristics, but it has been argued that there is ample evidence to believe that demographic characteristics will inevitably impact workers ratings due to widespread biases.

Searching for a Solution

It is clear that platform companies need to be pushed into solving for biases and making their systems more fair and non-discriminatory. Some companies, such as Amazon in the example above, have responded by suspending algorithms that are proven to be biased. However, this is a temporary fix, as companies rarely seek to drop such projects indefinitely. In the platform economy, where algorithms are central to the business model of companies, complete suspension is near impossible. Amazon also tried another quick fix - it altered the algorithm to respond neutrally to terms such as ‘woman’. This is a process known as debiasing the model, through which any biased connections (such as between the word ‘woman’ and downgrading) being made by the algorithm are explicitly removed. Another solution is diversifying or debiasing datasets. In this example, the algorithm could be fed a larger sample of resumes and decision-making logics from industries that have a higher representation of women.

Another set of solutions could be drawn from anti-discrimination law, which prohibit discrimination at the workplace. In India, anti-discrimination laws protect against wage inequality, as well as discrimination at the stage of recruitment for protected groups such as transgender persons. While it can be argued that biased rating systems lead to wage inequality, there are several barriers to applying anti-discrimination law for workers in the platform economy. One, most jurisdictions, including India, protect only employees from discrimination, not self-employed contractors. Another challenge is the lack of data to prove that rating or recruitment algorithms are discriminatory, without which legal recourse is impossible. Rosenblat et al. (2016) discuss these challenges in the context of the US, suggesting solutions such as addressing employment misclassification or modifying pleading requirements to bring platform workers under the protection of the law.

Feminist principles point to structural shifts that are required to ensure robust protections for workers. Analysing algorithmic systems from a feminist lens indicates several points in the design at which interventions must be focused to ensure impact. The teams designing algorithms need to be made more diverse, along with integrating an explicit focus on assessing the impact of systems at the stage of design. Companies need to be more transparent with their data, and encourage independent audits of their systems. Corporate and government actors must be held to account to fix broken AI systems.

Ambika Tandon is a Senior Researcher at the Centre for Internet & Society (CIS) in India, where she studies the intersections of gender and technology. She focuses on women’s work in the digital economy, and the impact of emerging technologies on social inequality. She is also interested in developing feminist methods for technology research. Ambika tweets at @AmbikaTandon.

The blog was originally published in the Organization for Ethical Source

For more details visit https://cis-india.org/raw/oes-ambika-tandon-ai-in-the-future-of-work

Locating Migrants in India’s Gig Economy

ambika — 2022-01-04T15:01:02Z

For more details visit https://cis-india.org/raw/locating-migrants-in-india-gig-economy.pdf

Future of Work: Report of the ‘Workshop on the IT/IT-eS Sector and the Future of Work in India’

ambika — 2020-03-05T19:03:07Z

This report provides an overview of the proceedings and outcomes of the Workshop on the IT/IT-eS Sector and the Future of Work in India (hereinafter referred to as the “Workshop”), organised at Omidyar Networks’ office in Bangalore, on June 29, 2018.

This report was authored by Torsha Sarkar, Ambika Tandon and Aayush Rath. It was edited by Elonnai Hickok. Akash Sriram, Divya Kushwaha and Torsha Sarkar provided transcription and research assistance. A PDF of the report can be accessed here.

Introduction

The Workshop was attended by a diverse group of stakeholders which included industry representatives, academicians and researchers, and civil society. The discussions went over various components of the transition in the sector to Industry 4.0, including the impact of Industry 4.0-related technological innovations on work broadly in India, and specifically in the IT/IT-eS sector (hereinafter referred to as the “Sector”). The discussion focused on the reciprocal impact on socio-political dimensions, the structure of employment, and forms of work within workspaces.

The Workshop was divided into three sessions. The first session was themed around the adoption and impact of Industry 4.0 technologies vis-a-vis the organisation of work. Within this the key questions were: the nature of the technologies being adopted, the causes that are driving the uptake of these technologies, and the ‘tasks’ constituting jobs in the Sector.

The second session focussed on the role of skilling and re-skilling measures as mitigators to projected displacement of jobs. The issues dealt with included shifts in company, educational, and social competency profiles as a result of Industry 4.0, transformations in the predominant pedagogy of education, vocational, and skill development programmes in India, and their success in creating employable workers and filling skill gaps in the industry.

The third session looked at social welfare considerations and public policy interventions that may be necessitated in the wake of potential technological unemployment owing to Industry 4.0. The session was designed with a specific focus on the axes of gender and class, addressing questions of precarity, wages, and job security in the future of work for marginalized groups in the workforce.

Preliminary Comments

The Workshop opened with a brief introduction on the research the Centre for Internet and Society (CIS) is undertaking on the Future of Work (hereinafter referred to as “FoW”) vis-a-vis Industry 4.0. The conception of Industry 4.0 that CIS is looking at is the technical integration of cyber-physical systems in production and logistics on one hand, and the use of internet of things (IoT) and the connection between everyday objects and services in the industrial processes on the other. The scope of the project, including the impact of automation on the organisation of employment and shifts in the nature and forms of work, including through the gig economy, and microwork, was detailed. The historical lens taken by the project, and the specific focus on questions of inequality across gender, class, language, and skill were highlighted.

It was pointed out that CIS’ research, in this regard, comes from the necessity of localising and re-examining the global narratives around Industry 4.0. While new technologies will be developed and implemented globally, the impact of these technologies in the Indian context would be mediated through local, political and socio-economic structures. For instance, the Third Industrial Revolution, largely associated with the massification of computing, telecommunications and electronics, is still unfolding in India, while attempts are already being made to adapt to Industry 4.0. These issues provided a starting point to the discussion on the impact of Industry 4.0 in India.

Qualifying Technological Change

Contexualising the narrative with historical perspectives

The panel for the first session commenced with a discussion around a historical perspective on job loss being brought about due to mechanisation. The distinction between Industry 3.0 and 4.0, it was suggested, was largely arbitrary, inasmuch as technological innovation has been a continuous process and has been impacting lives and the way work is perceived. It was argued that the only factor differentiating Industry 4.0 from previous industrial revolutions is ‘intelligent’ technology that is automating routine cognitive tasks. The computer, programmatic logic control (PLC) and data (called the ‘new oil’) were also a part of Industry 3.0, but intelligent technologies are able to provide greater analytical power under Industry 4.0.

The discussion also went over the distinction between the terms ‘job’, ‘task’ and ‘work’. It was argued that the term ‘job’ might be treated as a subset of the term ‘work’, with the latter moving beyond livelihood to encompass questions of dignity and a sense of fulfilment in the worker. With relation to this distinction, it was mentioned that the jobs at the risk of automation would be those that fulfill only the basic level in Maslow’s hierarchy - implying largely routine manual tasks. Additionally, it was explained that although these jobs will continue to use labour through Industry 4.0, it is only the nature of technological enablement that would change to automate more dangerous and hazardous tasks.

Technology as a long-term enabler of job creation

It was argued that technology has historically been associated with job creation. Historical instances cited included that of popular anxiety due to anticipated job loss through the uptake of the spinning machine and the steam engine, whereas the actual reduction in the cost of production led to greater job creation, increased mobility and improved quality of life in the long-term. Such instances were used to further argue that technology has historically not resulted in long-term job reductions.

The platform economy was posited as a model for creating jobs, through the efficient matching of supply and demand through digital platforms. It was indicated that rural to urban migration is aided by such platforms, as labourers voluntarily enrol in skilling initiatives given the certainty of employment through platformization. It was further argued that historically, Indian workers have been educated rather than skilled, and that platformization and automation, coupled with the elasticity of human needs, will provide greater incentives for technically skilled workers by creating desirable jobs.

Factors leading to differential adoption of automation

In relation to the adoption of the technologies Industry 4.0, it was argued that the mere existence of a technology does not necessitate its scalablity at an industrial level. Scalability would be possible only when the cost of labour is high relative to the costs entailed in technological adoption. This was supported by data from a McKinsey Report^{^[1]} which indicated that countries like the US and Germany would be impacted in the short term by automation, because their cost of labour is higher. Conversely, since the cost of labour in India is relatively cheap, the reality of technological displacement is still far away and the impact would not be immediate.

Similarly, a distinction was also made to account for the differential impact of automation in various sectors. For instance, it was indicated that since the IT/IT-eS sector in India is based on exporting services and outsourcing of businesses. Accordingly, if Germany automates its automobile industry, that would impact India less than if it automates the IT/IT-eS sector, as the latter is more reliant on exporting its services to developed economies. The IT/IT-eS sector was further broken down into sub-sectors with the intention of highlighting the differential impact of automation and FoW in each of these sub-sectors. It was agreed that the BPO sub-sector would be more adversely impacted than core IT services, given its constitution of routine nature of tasks at a higher risk of automation.

Disaggregating India’s Skilling Approach

The discussion around skilling measures was contextualised in the Indian context by alluding to data collected from the National Sample Survey Organisation (NSSO) surveys. The data revealed that around 36% of India’s total population is under the age of seventeen and approximately 13% are between 18 - 24. Additional statistics suggested that only around a quarter of the workforce aged 18-24 years had achieved secondary and higher secondary education and close to 13% of the workforce was illiterate. While these numbers included both male and female workers, it was pointed out that it was an incomplete dataset as it excluded transgender workers. It was suggested it should be this segment of the Indian demographic that is targeted for significant skilling pushes, which could be catalysed through specific vocational training centres. It was also suggested that there was a need for to restructure the role of the National Skill Development Corporation (NSDC) in the Indian skilling framework.

A comprehensive picture was painted by conceptualising the skilling framework in India as 5 distinct pillars. This conceptualisation was used to debunk the narrative around NSDC being the sole entity pushing for skill development in the country. The NSDC’s function in the skilling framework was posited as providing funding to skilling initiatives with programmes lasting for a period of 3 months. These 3- month programmes were critiqued for being insufficient for effective training, especially given the low skill levels of workers going into the programmes. The NSDC’s placement rate of 12% as per their own records was used to support this argument. Further suggestions on making the NSDC more effective were made in a later discussion^{^[2]}.

Related to this, the second pillar of vocational skilling was said to be the Industrial Training Institute (ITI). The third pillar was said to be the school system which was critiqued for does not offering vocational education at secondary and senior secondary levels. The fourth pillar comprised of the 16 ministries which governed the labour laws in India - none of whose courses were National Skills Qualifications Framework (NSQF) compliant.

The fifth pillar was construed as the industry itself and the enterprise-based training it conducted. However, it was stated that India’s share of registered companies who did enterprise-based training was dismal. In 2009, the share of enterprise-based training was 16% which rose in 2014 to 36%. Further, most of these 36% were registered large firms as opposed to small and medium sized enterprises. Unregistered companies, it was suggested, were simply doing informal apprenticeships.

Joint public and private skilling initiatives

In addition to government sponsored skilling initiatives, attention was directed to skill development partnerships that took the shape of public-private initiatives. As an example, it was said that that a big player in the ride-hailing economy had worked with NSDC and other skilling entities to ensure that soft skills were being imparted to their driver partners before they were on-boarded onto the platform.

It was also brought forth that innovative forms of skilling and training were gaining traction in the education sector as well in the private sector. This was instantiated through instances of uptake of platforms which apply artificial intelligence, and within that machine learning based techniques, to generate and disseminate easier- to- consume video-based learning.

Driving Job Growth: Solving for Structural Eccentricities of the Indian Labour Market

Catalysing manufacturing-led job growth

The discussion began by discussing specific dynamics of the Indian labour markets in the context of the Indian economy. It was pointed out the productivity level of the services sector is not as high as the productivity level of manufacturing, which is problematic for job creation in a developing economy such as India witnessing capital-intensive growth in the manufacturing sector. The underlying argument was that the jobs of the future in the Indian context will have to be created in the manufacturing sector.

Several macroeconomic policy interventions were suggested to reverse the trend of capital-intensive growth in order to make manufacturing the frontier for enhanced job creation. The need for a trade policy in consonance with the industrial policy was stated as imperative. This was substantiated by highlighting the lack of an inverted duty structure governing the automobile sector that has led India to be amongst the biggest manufacturers of automobiles. The inverted duty structure entails finished products having a lower import tariff and a lower customs duty when compared to import of raw materials or intermediates. However, it was highlighted that a dissonant industrial policy failed to acknowledge that at least 50% of india’s manufacturing comes from Micro, Small & Medium Enterprises (MSMEs) and provided no assistance to MSMEs in obtaining credit, market access or technology upgradation. On the other hand, it was asserted that large corporates get 77% of the total bank credit.

Another challenge that was highlighted was with the Government of India’s severely underfunded manufacturing cluster development programs under the aegis of the Ministry of Textiles and the Ministry of MSMEs. For sectors that contribute majorly towards India’s manufacturing output, it was asserted that these programmes were astonishingly bereft of any governing policy and suffer from several foundational issues. Moreover, it was observed that these clusters are located around the country in Tier 2, 3 and 4 cities where the quality of infrastructure is largely lacking. The Atal Mission for Rejuvenation and Urban Transformation (AMRUT) program devised for the development of these cities is also myopic as the the target cities are not the ones where these manufacturing clusters are located. The rationale behind such an approach was that building infrastructure at geographical sites of job creation would lead to an increase in productivity which would in turn attract greater investment. This would have to necessarily be accompanied by hastening the setting up of industrial corridors - the lackadaisical approach to which was stated as a key component of India being outpaced by other developing economies in the South East Asian region.

An additional policy intervention that was suggested was from the lens of setting up of skilling centres by NSDC in proximity to these manufacturing clusters where the job creation is being evidenced as opposed to larger metropolitan cities.

Carving out space for a vocational training paradigm

It was asserted that the focus of skilling needs to be on the manufacturing rather than services sector, given the centrality of manufacturing to a developing economy undergoing an atypical structural transformation^{^[3]} - as outlined above. Further compounding the problem of jobless growth, it was stated that 50% of the manufacturing workforce have 8 or less years of education and only 5% of the workforce including those that have technical education are vocationally trained, according to the NSS, 62nd Round on Employment and Unemployment.

A gulf in primary and secondary education vis-a-vis vocational training was pointed as one of the most predominant causes behind the much touted ‘skills gap’ that the Indian workforce is said to be battling with. Using data to further cull out the argument, it was said that in 2007, the net enrollment in India for primary education had already reached 97% and that between 2010 - 2015, the secondary education enrollment rate went from 58% to 85%.^{^[4]} It was hypothesised that the latter may have risen to 90% levels since. Furthermore, the higher education enrollment rate also commensurately went up from 11% in 2006 to 26-27% in 2017.^{^[5]} It was argued that this is impossible to achieve without gender parity in higher education. This gender parity in education was contrasted with the systematic decline in the women’s labour force participation that India has been witnessing in the last 30 years.

Consequently, the ‘massification’ of higher education in India over the past 10 years was critiqued as ineffectual in comparison to the Chinese model, as the latter focused on engaging students in vocational training, which the Indian education system had failed to do. The role of the gig economy in creating job opportunities despite this gap between educational and vocational training was regarded as important, especially given the lack of growth in the traditional job markets.

Accounting for the Margins

With relation to the profiles of workers within sectors, it was indicated that factors such as gender, class, skill, income, and race must be accounted for to determine the ‘winners’ and ‘losers’ of automation. Several points were discussed with relation to this disaggregation.

Technology as an equaliser? Gender and skill-biased technological change

First, the idea of technology and development as objective and neutral forces was questioned, with the assertion that human decision-makers, who more often than not tend to be male, allow inherent biases to creep into outputs, processes, and objectives of automation. Data from the Belong Survey in IT services^{^[6]} indicated that the proportion of women in core engineering was 26% of the workforce, while that in software testing was 33%. Coupled with the knowledge that automation and technology would automate software testing first, it was argued that jobs held by female workers were positioned at a higher immediate risk of automation than male workers.

The ‘Leaky Pipe Problem’ in STEM industries i.e. the observation that female workers tend to be concentrated in entry level jobs, while senior management is largely male dominated was also brought to the fore. This was used to bolster the argument that female workers in the Sector will lose out in the shorter term, when automation adversely impacts the lower level jobs.

A survey conducted by Aspiring Minds^{^[7]} which tracked the employability of the engineering graduates was utilised to further flesh out skill biased technological change. As per the survey, 40% of the graduating students are employable in the BPO sector, while only 3% of the students are employable in the sector for software production. With the BPO sector likelier to be impacted more adversely than core IT services, it was emphasised that policy considerations should be very specific in their ambit.

Social security and the platform economy

The discussion around the platform economy commenced with a focus on how it had created economic opportunities in the formal sector by matching demand and supply on one hand, and by reducing inefficiency in the system through technology on the other. It was pointed out that these newer forms of work were creating millions of entrepreneurship opportunities that did not exist previously. These opportunities, it was suggested, were in themselves flexible and contributing the greater push towards enhancing the numbers of those that come within the ambit of India’s formal economy.

This discussion was countered by suggesting that the shift of the workforce from the informal sector to the formal sector, which companies in the gig economy claimed they contributed to, have instead restricted the kind of lives gig workers have been living historically. As an instance, it was pointed out that a farmer who had been working with a completely different set of skills was now being asked to shift to a new set of skills which would be suited for a very specific role and not transposable across occupations. In other words, it would not be meaningful skilling. It was also pointed out that what distinguishes formal work from informal is whether the worker has social security net or not - mere access to banking services or filing of tax returns was not sufficient for characterising a workforce as being formal in nature.

Relatedly, the possibility of social security was discussed for the unorganised sector and microworkers. One of the possibilities discussed was to ensure state subsidised maternity, disability, and death security, and pensions for workers below the poverty line. The fiscal brunt borne by the government for such a scheme was anticipated to not be above 0.4% of the GDP. It was suggested that this would move forward the conversation on minimum wage and fair work, which would be of great importance in broader conversations around working conditions in the platform economy.

The interplay of gender and platformisation

It was highlighted that trends in automation are going to change the occupational structure in the digital economy - the effect of which will especially be felt in cognitive routine jobs given their increased propensity to platformisation. A World Economic Forum report^{^[8]} was cited which indicated the disproportional risk of unemployment faced by women given their concentration in cognitive routine jobs was also brought up.

The discussion logically undertook a deeper look at the platformisation of work with a specific focus on freelance microwork and its impact on the female labour force and culled out certain positive mandates arising from such newer forms of work. It was suggested that industries are more likely to employ female workers in microwork due to lower rates of attrition, and flexible labour. It was reiterated that freelancing in India extends beyond data entry and other routine jobs, to include complex work - thereby also catering to skilled workers desirous of flexibility. Platforms designing systems to meet the demand for flexible work were also discussed, such as platforms geared towards female workers undertaking reskilling measures and counselling for females returning from maternity leave or sabbaticals. Additionally, the difficulty of defining freelancing under existing frameworks of employment, compounded by the lack of legal structures for such work, was outlined.

Systemic challenges within the Indian labour law framework

Static design of legal processes

Labour law was, naturally, acknowledged as a key determinant in the conversation around both the uptake and impact of automative technologies encapsulated within Industry 4.0.

The archaic nature of India’s labour law framework was highlighted as a major impediment to ensuring both worker rights as well as the ease of conducting commerce. It was pointed out that organised labour continues to be under the ambit of the Industrial Disputes Act, which was made effective in 1947, has undergone minimal amendments since. This was critiqued on the basis that the framework for the law is embedded in its historical context, and while the industrial landscape in the country has transformed drastically since the implementation of the Industrial Disputes Act, the legal framework has not evolved. Similarly, the Karnataka Shops and Establishments Act, 1961 which regulates the Sector today was enacted much before the Sector even opened up in India in the 1990s.

Additionally, it was pointed out that the consolidation of the fragmented extant framework of labour laws in India was being consolidated into 4 labour codes without any wholesale modernisation push reforming the laws being consolidated. Consequently, it was argued that the government has to drive changes through policies alone as the legal framework remains static. Barriers to implementation of adequate policies were also discussed, such as the political impact of labour policies, lack of state initiative to deal with the impact of the future of work, apart from the historic inability of the law to keep up with the state of labour and economy.

Labour law arbitrage

One of the reasons behind the increasing contractualizing of labour in India was attributed to over-regulation. There was consensus that the labour law regime was not conducive to industry in India leading to greater opportunistic behaviours from industry participants. It was acknowledged that the political clout that a lot of contractors (of labourers) enjoy along with providing primary employers greater flexibility to hire and fire employees at will has led to a widespread utilisation of contract labour entities.

It was further stated that industry behaviour has adopted several other tools of arbitrage to not consider labour law as a key impediment in the ease of scaling business. Empirical evidence of labour law arbitrage was cited to drive home the point - according to national surveys, 80-85% of enterprises employ less than 99 workers as the law mandates stricter compliance requirements for enterprises employing 100 or more workers^{^[9]}. This was acknowledged a serious hurdle to scaling businesses.

Problems behind other apparently well-intentioned legislation from a public policy lens having counterproductive consequences was also highlighted. In the space of labour laws, the example of the recently enacted Maternity Benefit (Amendment) Act, 2017 was cited. By enhancing maternity benefits, without accounting for other provisioning such as a paternity benefit inclusion, it was anticipated that companies may entirely shy away from hiring women.

Policy Paralysis

The discussion progressed towards a high-level discussion around the efficacy of law vis-a-vis state policy as a means to create a system of checks and balances in the context of Industry 4.0. It was highlighted that law, by design, would be outpaced by technological change. The common law system of law operating in India is premised on a time-tested emphasis on post-facto regulation. In other words, it is reactionary. While policy making in India suffers from a similar plague of playing catch-up, it is in large part due to a bureaucratic structure premised on generalism - a pressing need for domain expertise in policy making was emphasised upon. Having said that, it was stated that it is the institutional design of policy making institutions that needs rectification. What was acknowledged was the success, albeit scant, that individual states have had in policy making catering to specific yet diverse domains. A greater push towards clear and progressive evidence-based policy pushes was stressed upon with the anticipation that it would lead to self-regulation by the industry itself - be it in terms of the future of employment or of the economic direction that the industry will embark on.

Concluding Remarks

The discussions during the course of the Workshop situated the discourse around Industry 4.0 within the contours of the Indian labour realities and the IT sector within that.

As a useful starting point, various broader perspectives around the impact of technological change on the quantum of jobs were brought forth. While the industry perspective was that of technology as an enabler of job creation in the long-run, it was sufficiently tempered by concerns around those impacted adversely in the short to medium-term time frames. These concerns coalesced towards understanding the potential impact of Industry 4.0 on the nature of work, as well as mitigation tools to ease the impact of technological disruption on labour.

Important facets of technological adoption within the Sector were highlighted, such as potential for scalability as well as the distinct eccentricities of the various sub-sectors the IT sector subsumed. The differential impact within the various sub-sectors was pegged to the differential composition of automatable tasks (routine, rule-based) within each sub-sector. However, questions regarding the exact contours of task composition were left unanswered signalling a potential area for further research. On the other hand, the primary challenge to technological adoption faced from the labour-supply side was skilling, or the lack thereof. This was contextualised in the larger scheme of structural issues plaguing the skilling machinery operating in the country, which lead to inadequate dispensation of technical and vocational education and training (TVET). In terms of additional structural issues that would potentially have an impact on how Industry 4.0 plays out in the Indian context, attention was directed towards overdue reform of the labour law framework which has already struggled with incorporating newer forms of working engagements such as platform and gig work, that are being evidenced as a part of Industry 4.0.

An underlying theme that found mention across sessions was the need to devote attention to prevent further marginalisation as a consequence of technological disruption of the already marginalised. Evidence from government datasets as well as from literature around concepts such as skill biased technological change, the leaky pipe problem, and the U-shaped curve of female labour force participation were cited to explicate these issues. The merits of different policy measures to address these concerns, such as social security, living wages, and maternity benefits were also discussed.

While the Workshop touched upon several facets of the discourse around Industry 4.0 in the Sector, it also sprung up areas that require further inquiry. Questions around where in the value chain use-cases for Industry 4.0 technologies were emerging needed a more comprehensive understanding. Moreover, the impact of Sector Skill Councils (SSCs), a central aspect of the skilling ecosystem in India, wasn’t touched upon. An additional path of inquiry that emerged pertained to evolving constructive reforms to legal and economic policy frameworks as top-down interventions within the Sector that could be anticipated to play a significant role in the uptake and impact of Industry 4.0 technologies.

^{^[1]} McKinsey Global Institute, A future that works: Automation, employment, and productivity, https://www.mckinsey.com/~/media/mckinsey/featured%20insights/Digital%20Disruption/Harnessing%20automation%20for%20a%20future%20that%20works/MGI-A-future-that-works-Executive-summary.ashx, (accessed 10 August 2018).

^{^[2]} See discussion under ‘Catalysing manufacturing-led job growth‘.

^{^[3]} R. Verma, Structural Transformation and Jobless Growth in the Indian Economy, The Oxford Handbook of the Indian Economy, 2012.

^{^[4]} S. Mehrotra, ‘The Indian Labour Market: A Fallacy, Two Looming Crises and a Tragedy’, CSE Working Paper, April 2018.

^{^[5]} ibid.

^{^[6]} Mohita Nagpal, ‘Women in tech: There are 3 times more male engineers to females’, belong.co, http://blog.belong.co/gender-diversity-indian-tech-companies, (accessed 10 August 2018).

^{^[7]} Aspiring Minds, National Programming Skills Report - Engineers 2017, https://www.aspiringminds.com/sites/default/files/National%20Programming%20Skills%20Report%20-%20Engineers%202017%20-%20Report%20Brief.pdf, (accessed 11 August 2018).

^{^[8]} World Economic Forum, The Future of Jobs Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution: Global Challenge Insight Report, January 2016.

^{^[9]} Ministry of Statistics and Programme Implementation, All India Report of Sixth Economic Census, Government of India, 2014.

For more details visit https://cis-india.org/internet-governance/blog/future-of-work-report-of-the-workshop-on-the-it-it-es-sector-and-the-future-of-work-in-india

Concept Note - Digital Citizen Summit

ambika — 2018-11-07T02:50:22Z

For more details visit https://cis-india.org/internet-governance/files/concept-note-digital-citizen-summit

DCS 2018 Agenda

ambika — 2018-11-07T02:51:36Z

For more details visit https://cis-india.org/internet-governance/files/dcs-2018-agenda

Feminist Information Infrastructure Workshop with Blank Noise and Sangama

ambika — 2018-08-13T15:21:59Z

Akriti Bopanna, Swaraj Paul Barooah and Ambika Tandon as part of the project on Feminist Information Infrastructure, conducted a full-day workshop with Sangama and Blank Noise on August 8, 2018 at CIS, Bangalore.

The workshop focused around fleshing out the research projects that interns at Blank Noise and Sangama will be undertaking, and going over ethical guidelines for feminist research for interviews.

There will be three projects across the two organizations, looking at

The identification process and challenges therein for the trans community,
The impact of mobile phone usage on sex work, and
Impact of social media on the lives of sexual minorities (specifically gay men), focusing on pleasure, social interaction, safety, and peerveillance.

For more details visit https://cis-india.org/internet-governance/news/feminist-information-infrastructure-workshop-with-blank-noise-and-sangama

Feminist Methodology in Technology Research: A Literature Review

ambika — 2018-12-25T15:18:21Z

This literature review has been authored by Ambika Tandon, with contributions from Mukta Joshi. Research assistance was provided by Kumarjeet Ray and Navya Sharma. The publication has been designed by Saumyaa Naidu.

Abstract

Feminist research methodology is a vast body of knowledge, spanning across multiple disciplines including sociology, media studies, and critical legal studies. This literature review aims to understand key aspects of feminist methodology across these disciplines, with a particular focus on research on technology and its interaction with society. Stemming from the argument that the ontological notion of objectivity effaces power relations in the process of knowledge production, feminist research is critical of the subjects, producers, and nature of knowledge. Section I of the literature review explores this argument along with a range of theoretical concepts, such as standpoint theory and historical materialism, as well as principles of feminist research derived from these, such as intersectionality and reflexivity.

Given its critique of the "god's eye view" (Madhok and Evans, 2014) of objectivist research, feminist scholars have largely developed qualitative methods that are more conducive to acknowledgement of power hierarchies. Additionally, some scholars have recognised the political value in quantification of inequalities such as the wage gap, and have developed intersectional quantitative methods that aim at narrowing down measurable inequalities. Both sets of methods are explored in Section II of the literature review, interspersed with examples from research focused on technology.

Introduction

According to authoritative accounts on the subject, while research focused on gender or women predates its arrival, the field of ‘feminist methodology’ explores questions of epistemology and ontology of research and knowledge. Initiated in scholarship arising out of the second wave of North American feminism, it theoretically anchors itself in the post-modernist and post-structuralist traditions. It additionally critiques positivism for being a project furthering patriarchal oppression. North American feminist scholars critique traditional methods within the social sciences from an epistemological perspective, for producing acontextual and ahistorical knowledge, replicating the tendency of positivist science to enumerate and measure subjective social phenomena. This, according to them, leads to the invisiblising of the web of power relations within which the ‘known’ and ‘knower’ in knowledge production are placed. This is then used to devise methods and underlying principles and ethics for conducting more egalitarian research, aimed at achieving goals of social justice.

The second wave feminist movement was itself critiqued by Black and other feminists from the global South for being exclusionary of non-white and heterosexual identities. Given its origins in the global North, scholars from the South have interrogated the meaning of feminism and feminist research in their context. Some African scholars even detail difficulty in disclosing a project as feminist publicly due to popular resistance to the term feminism, which stems from it being rejected by certain social groups as an alien social movement that’s antithetical to their “African cultural values." Their own critique of “White feminism” comes from its essentialization of womanhood and the resultant negation of the (neo)colonial and racialised histories of African women. This has led scholars from the global South to critically interrogate feminism and feminist methods. They acknowledge the multiplicity of feminisms, and initiate creative inquiries into different forms of feminist methodology. Feminist researchers that work in contexts of political violence, instability, repression, scarcity of resources, poor infrastructure, and/or lack of social security, have pointed out that traditional research methods assume conditions that are largely absent in their realities, leading them to experiment with feminist research.

Feminist research across these variety of contexts raises ontological and epistemological concerns about traditional research methods and underlying assumptions about what can be known, who can know, and the nature of knowledge itself. It argues that knowledge production has historically led to the creation of epistemic hierarchies, wherein certain actors are designated as ‘knowers’ and others as the ‘known’. Such hierarchies wreak epistemic violence upon marginalised subjects by denying them the agency to produce knowledge, and delegitimize forms of knowledge that aren’t normative. Acknowledging the role of power in knowledge production has the radical implication that the subjectivities of the researchers and the researched inherently find their way into research and more broadly, knowledge production. This challenges the objectivity and “god’s eye view” of traditional humanistic knowledge and its processes of production. Feminist research eschews scientifically orthodox notions of how “valid knowledge will look”, and creates novel resources for understanding epistemic marginalization of various kinds. It then provides a myriad of tools to disrupt structural hierarchies through and within knowledge production and dissemination.

Feminist research, given its evolution from living movements and theoretical debates, remains a contested domain. It has reformulated a range of qualitative and quantitative research methods, and also surfaced its own, such as experimental and action-based. What these have in common are theoretical dispositions to identify, critique, and ultimately dismantle power relations within and through research projects. It is thus “critical, political, and praxis oriented. Several disciplines with the social sciences, such as feminist technology studies, cyberfeminism, and cultural anthropology, have built feminist approaches to the study of technology and technologically mediated social relations. However, this continues to remain a minor strand of research on technology.

This literature review aims to address that gap through scoping of such methods and their application in technological research. Feminist methodology provides a critical lens that allows us to explore questions and areas in technology-based research that are inaccessible by traditional methods. This paper draws on examples from technology-focused research, covering key interdisciplinary feminist methods across fields such as gender studies, sociology, development, and ICT for development. In doing so, it actively constructs a history of feminist methodology through authoritative sources of knowledge.

Read the full paper here

For more details visit https://cis-india.org/internet-governance/blog/ambika-tandon-december-23-2018-feminist-methodology-in-technology-research

Feminist Methodology in Technology Research

ambika — 2018-12-25T15:17:02Z

For more details visit https://cis-india.org/internet-governance/feminist-methodoloty-in-technology-research.pdf

Big Data and Reproductive Health in India: A Case Study of the Mother and Child Tracking System

ambika — 2019-12-06T04:57:55Z

In this case study undertaken as part of the Big Data for Development (BD4D) network, Ambika Tandon evaluates the Mother and Child Tracking System (MCTS) as data-driven initiative in reproductive health at the national level in India. The study also assesses the potential of MCTS to contribute towards the big data landscape on reproductive health in the country, as the Indian state’s imagination of health informatics moves towards big data.

Case study: Download (PDF)

Introduction

The reproductive health information ecosystem in India comprises of a range of different databases across state and national levels. These collect data through a combination of manual and digital tools. Two national-level databases have been launched by the Ministry of Health and Family Welfare - the Health Management Information System (HMIS) in 2008, and the MCTS in 2009. 4 The MCTS focuses on collecting data on maternal and child health. It was instituted due to reported gaps in the HMIS, which records monthly data across health programmes including reproductive health. There are several other state-level initiatives on reproductive health data that have either been subsumed into, or run in parallel with, the MCTS.

With this case study, we aim to evaluate the MCTS as data-driven initiative in reproductive health at the national level. It will also assess its potential to contribute towards the big data landscape on reproductive health in the country, as the Indian state’s imagination of health informatics moves towards big data. The methodology for the case study involved a desk-based review of existing literature on the use of health information systems globally, as well as analysis of government reports, journal articles, media coverage, policy documents, and other material on the MCTS.

The first section of this report details the theoretical framing of the case study, drawing on the feminist critique of reproductive data systems. The second section maps the current landscape of reproductive health data produced by the state in India, with a focus on data flows, and barriers to data collection and analysis at the local and national level. The case of abortion data is used to further the argument of flawed data collection systems at the national level. Section three briefly discusses the state’s imagination of reproductive health policy and the role of data systems through a discussion on the National Health Policy, 2017 and the National Health Stack, 2018. Finally, we make some policy recommendations and identify directions for future research, taking into account the ongoing shift towards big data globally to democratise reproductive healthcare.

For more details visit https://cis-india.org/raw/big-data-reproductive-health-india-mcts

The Mother and Child Tracking System - understanding data trail in the Indian healthcare systems

ambika — 2019-12-30T17:18:05Z

This article was first published by Privacy International, on October 17, 2019

Case study of MCTS: Read

On October 17th 2019, the UN Special Rapporteur (UNSR) on Extreme Poverty and Human Rights, Philip Alston, released his thematic report on digital technology, social protection and human rights. Understanding the impact of technology on the provision of social protection – and, by extent, its impact on people in vulnerable situations – has been part of the work the Centre for Internet and Society (CIS) and Privacy International (PI) have been doing.

Earlier this year, PI responded to the UNSR's consultation on this topic. We highlighted what we perceived as some of the most pressing issues we had observed around the world when it comes to the use of technology for the delivery of social protection and its impact on the right to privacy and dignity of benefit claimants.

Among them, automation and the increasing reliance on AI is a topic of particular concern - countries including Australia, India, the UK and the US have already started to adopt these technologies in digital welfare programmes. This adoption raises significant concerns about a quickly approaching future, in which computers decide whether or not we get access to the services that allow us to survive. There's an even more pressing problem. More than a few stories have emerged revealing the extent of the bias in many AI systems, biases that create serious issues for people in vulnerable situations, who are already exposed to discrimination, and made worse by increasing reliance on automation.

Beyond the issue of AI, we think it is important to look at welfare and automation with a wider lens. In order for an AI to function it needs to be trained on a dataset, so that it can understand what it is looking for. That requires the collection large quantities of data. That data would then be used to train and AI to recognise what fraudulent use of public benefits would look like. That means we need to think about every data point being collected as one that, in the long run, will likely be used for automation purposes.

These systems incentivise the mass collection of people's data, across a huge range of government services, from welfare to health - where women and gender-diverse people are uniquely impacted. CIS have been looking specifically at reproductive health programmes in India, work which offers a unique insight into the ways in which mass data collection in systems like these can enable abuse.

Reproductive health programmes in India have been digitising extensive data about pregnant women for over a decade, as part of multiple health information systems. These can be seen as precursors to current conceptions of big data systems within health informatics. India’s health programme instituted such an information system in 2009, the Mother and Child Tracking System (MCTS), which is aimed at collecting data on maternal and child health. The Centre for Internet and Society, India, undertook a case study of the MCTS as an example of public data-driven initiatives in reproductive health. The case study was supported by the Big Data for Development network supported by the International Development Research Centre, Canada. The objective of the case study was to focus on the data flows and architecture of the system, and identify areas of concern as newer systems of health informatics are introduced on top of existing ones. The case study is also relevant from the perspective of Sustainable Development Goals, which aim to rectify the tendency of global development initiatives to ignore national HIS and create purpose-specific monitoring systems.

After being launched in 2011, 120 million (12 crore) pregnant women and 111 million (11 crore) children have been registered on the MCTS as of 2018. The central database collects data on each visit of the woman from conception to 42 days postpartum, including details of direct benefit transfer of maternity benefit schemes. While data-driven monitoring is a critical exercise to improve health care provision, publicly available documents on the MCTS reflect the complete absence of robust data protection measures. The risk associated with data leaks are amplified due to the stigma associated with abortion, especially for unmarried women or survivors of rape.

The historical landscape of reproductive healthcare provision and family planning in India has been dominated by a target-based approach. Geared at population control, this approach sought to maximise family planning targets without protecting decisional autonomy and bodily privacy for women. At the policy level, this approach was shifted in favour of a rights-based approach to family planning in 1994. However, targets continue to be set for women’s sterilisation on the ground. Surveillance practices in reproductive healthcare are then used to monitor under-performing regions and meet sterilisation targets for women, this continues to be the primary mode of contraception offered by public family planning initiatives.

More recently, this database - among others collecting data about reproductive health - is adding biometric information through linkage with the Aadhaar infrastructure. This data adds to the sensitive information being collected and stored without adhering to any publicly available data protection practices. Biometric linkage is aimed to fulfill multiple functions - primarily authentication of welfare beneficiaries of the national maternal benefits scheme. Making Aadhaar details mandatory could directly contribute to the denial of service to legitimate patients and beneficiaries - as has already been seen in some cases.

The added layer of biometric surveillance also has the potential to enable other forms of abuse of privacy for pregnant women. In 2016, the union minister for Women and Child Development under the previous government suggested the use of strict biometric-based monitoring to discourage gender-biased sex selection. Activists critiqued the policy for its paternalistic approach to reduce the rampant practice of gender-biased sex selection, rather than addressing the root causes of gender inequality in the country.

There is an urgent need to rethink the objectives and practices of data collection in public reproductive health provision in India. Rather than continued focus on meeting high-level targets, monitoring systems should enable local usage and protect the decisional autonomy of patients. In addition, the data protection legislation in India - expected to be tabled in the next session in parliament - should place free and informed consent, and informational privacy at the centre of data-driven practices in reproductive health provision.

This is why the systematic mass collection of data in health services is all the more worrying. When the collection of our data becomes a condition for accessing health services, it is not only a threat to our right to health that should not be conditional on data sharing but also it raises questions as to how this data will be used in the age of automation.

This is why understanding what data is collected and how it is collected in the context of health and social protection programmes is so important.

For more details visit https://cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare

Studying Platform Work in Mumbai and New Delhi

ambika — 2022-05-05T16:32:58Z

For more details visit https://cis-india.org/raw/studying-platform-work-in-mumbai-new-delhi.pdf

Designing Urban Nervous Systems

ambika — 2018-04-20T05:28:32Z

Dr. Anupam Saraph will be holding a talk on 'Designing urban nervous systems' at the CIS on Tuesday, March 27, 2018 at 3:30 p.m. The talk will revolve around looking at cities as living organisms, with nervous systems at the center of their being.

Dr. Anupam Saraph

Dr. Saraph is a future designer and an expert on complex systems. He holds a PhD in designing sustainable systems from the faculty of Mathematics and Natural Sciences of the Rijksuniversiteit Groningen, the Netherlands. He has worked on building digital governance solutions and sustainable and resilient organizations with government and civil society organizations.

For more details visit https://cis-india.org/raw/designing-urban-nervous-system