Re-Imagining Algorithmic Fairness in India and Beyond
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Pro-Poor Policies and Improvements in Maternal Health Outcomes in India M
Bhatia et al. BMC Pregnancy and Childbirth (2021) 21:389 https://doi.org/10.1186/s12884-021-03839-w RESEARCH ARTICLE Open Access Pro-poor policies and improvements in maternal health outcomes in India M. Bhatia1* , L. K. Dwivedi2, K. Banerjee2, A. Bansal2, M. Ranjan3 and P. Dixit4 Abstract Background: Since 2005, India has experienced an impressive 77% reduction in maternal mortality compared to the global average of 43%. What explains this impressive performance in terms of reduction in maternal mortality and improvement in maternal health outcomes? This paper evaluates the effect of household wealth status on maternal mortality in India, and also separates out the performance of the Empowered Action Group (EAG) states and the Southern states of India. The results are discussed in the light of various pro-poor programmes and policies designed to reduce maternal mortality and the existing supply side gaps in the healthcare system of India. Using multiple sources of data, this study aims to understand the trends in maternal mortality (1997–2017) between EAG and non EAG states in India and explore various household, economic and policy factors that may explain reduction in maternal mortality and improvement in maternal health outcomes in India. Methods: This study triangulates data from different rounds of Sample Registration Systems to assess the trend in maternal mortality in India. It further analysed the National Family Health Surveys (NFHS). NFHS-4, 2015–16 has gathered information on maternal mortality and pregnancy-related deaths from 601,509 households. Using logistic regression, we estimate the association of various socio-economic variables on maternal deaths in the various states of India. -
Space-Time Variability of Ambient PM2.5 Diurnal Pattern Over India
https://doi.org/10.5194/acp-2019-731 Preprint. Discussion started: 26 November 2019 c Author(s) 2019. CC BY 4.0 License. Manuscript for Atmos. Chem. Phys. 1 2 3 4 5 6 7 8 9 10 Space-time variability of ambient PM2.5 diurnal pattern over India 11 from 18-years (2000-2017) of MERRA-2 reanalysis data 12 13 14 15 16 1Kunal Bali*, 1,2Sagnik Dey, 1Dilip Ganguly and 3, 4Kirk R. Smith 17 1Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, 18 New Delhi, India 19 20 2Centre of Excellence for Research on Clean Air, Indian Institute of Technology 21 Delhi, Hauz Khas, New Delhi, India 22 23 3School of Public Health, University of California, Berkeley, USA 24 25 4Collaborative Clean Air Policy Center, New Delhi, India 26 27 28 29 *Corresponding author: [email protected] 30 31 32 33 34 35 36 37 38 1 https://doi.org/10.5194/acp-2019-731 Preprint. Discussion started: 26 November 2019 c Author(s) 2019. CC BY 4.0 License. Manuscript for Atmos. Chem. Phys. 39 Abstract 40 Estimating ambient PM2.5 (fine particulate matter) concentrations in India over many 41 years is challenging because spatial coverage of ground-based monitoring, while 42 better recently, is still inadequate and satellite-based assessment lacks temporal 43 continuity. Here we analyze MERRA-2 reanalysis aerosol products to estimate PM2.5 44 at hourly scale to fill the space-time sampling gap. MERRA-2 PM2.5 are calibrated 45 and validated (r = 0.94, slope of the regression = 0.99) against coincident in-situ 46 measurements. -
AI Principles 2020 Progress Update
AI Principles 2020 Progress update AI Principles 2020 Progress update Table of contents Overview ........................................................................................................................................... 2 Culture, education, and participation ....................................................................4 Technical progress ................................................................................................................... 5 Internal processes ..................................................................................................................... 8 Community outreach and exchange .....................................................................12 Conclusion .....................................................................................................................................17 Appendix: Research publications and tools ....................................................18 Endnotes .........................................................................................................................................20 1 AI Principles 2020 Progress update Overview Google’s AI Principles were published in June 2018 as a charter to guide how we develop AI responsibly and the types of applications we will pursue. This report highlights recent progress in AI Principles implementation across Google, including technical tools, educational programs and governance processes. Of particular note in 2020, the AI Principles have supported our ongoing work to address -
A Feminist Critique of Algorithmic Fairness
Redistribution and Rekognition: A Feminist Critique of Algorithmic Fairness Sarah Myers West AI Now Institute at New York University [email protected] Abstract Computer scientists, and artificial intelligence researchers in particular, have a predisposition for adopting precise, fixed definitions to serve as classifiers (Agre, 1997; Broussard, 2018). But classification is an enactment of power; it orders human interaction in ways that produce advantage and suffering (Bowker & Star, 1999). In so doing, it attempts to create order out of the messiness of human life, masking the work of the people involved in training machine learning systems, and hiding the uneven distribution of its impacts on communities (A. Taylor, 2018; Gray, 2019; Roberts, 2019). Feminist scholars, and particularly feminist scholars of color, have made powerful critiques of the ways in which artificial intelligence systems formalize, classify, and amplify historical forms of discrimination and act to reify and amplify existing forms of social inequality (Eubanks, 2017; Benjamin, 2019; Noble, 2018). In response, the machine learning community has begun to address claims of algorithmic bias under the rubric of fairness, accountability, and transparency. But it has dealt with these claims largely using computational approaches that obscure difference. Inequality is reflected and amplified in algorithmic systems in ways that exceed the capacity of statistical methods alone. This article examines how patterns of exclusion and erasure in algorithmic systems recapitulate and magnify a history of discrimination and erasure in the field of artificial intelligence, and in society more broadly. Shifting from individualized notions of fairness to more situated modeling of algorithmic remediation might create spaces of possibility for new forms of solidarity and West, Sarah Myers (2020). -
Artificial Intelligence and Healthcare in India
CSD Working Paper Series: Towards a New Indian Model of Information and Communications Technology-Led Growth and Development Artificial Intelligence and Healthcare in India ICT India Working Paper #43 Nirupam Bajpai and Manisha Wadhwa January 2020 CSD Working Paper Series – Artificial Intelligence and Healthcare in India Abstract Artificial Intelligence (AI), also referred to as the new electricity, is the emerging focus area in India. AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making. Most of the AI systems rely on historical large datasets for predicting future trends and outcomes at a pace which humans would not be able to match. The development of AI in India is in the initial stages and there is no regulatory body focused solely on AI. However, recently, Government of India has taken various initiatives related to AI such as establishment of Artificial Intelligence Task Force, formulation of NITI Aayog's National Strategy for Artificial Intelligence #AIFORALL, setting up of four Committees for AI under Ministry of Electronics and Information technology etc. Some of India’s state governments have also taken few initiatives, such as establishment of Centre of Excellence for Data Science and Artificial Intelligence (CoE-DS&AI) by Karnataka, Safe and Ethical Artificial Intelligence Policy 2020 and Face Recognition Attendance System by Tamil Nadu, AI-Powered System for monitoring driving behaviour by West Bengal, AI System to fight agricultural risks by Maharashtra etc. As with any other technology, AI brings with it a span of opportunities and challenges. In healthcare, AI could be beneficial in mining medical records; designing treatment plans; forecasting health events; assisting repetitive jobs; doing online consultations; assisting in clinical decision making; medication management; drug creation; making healthier choices and decisions; and solving public health problems etc. -
India: Internal Flows and the Challenges in Indian Subcontinent
India: Internal Flows and the Challenges in Indian Subcontinent Xavier Jeyaraj, S. J. Internal migration from one state to another within the Indian subconti- nent, similar to that of migrants from one country to another in any part of the world, cause great challenge due to cultural, linguistic, ethnic differ- ences. Some examples are: • More than 300 people across six districts of Gujarat [Western India] have been arrested for inciting violence against the state’s migrant population, following the rape of a 14-month-old in Himmatnagar district. Fearing a further backlash, migrants are making a bolt for their home states of Uttar Pradesh, Bihar and Madhya Pradesh [Central and North India] (Doval, 2018). • Assam [North East] migrant worker killed in Kerala [South]: ‘More than 50 men watched… nobody bothered to help’ (Kashyap & Philip, 2016). • On 19 October 2008, Maharashtra [Western India] Navanirman Sena (a regional political party) activists beat up north Indian candidates who were appearing for the all-India Railway Recruit- ment Board entrance exam for the Western region in Mumbai (Gaikwad, 2008). • On 24 November 2007, Assam tribals [originally from Central India], who were demanding the tribal status in Assam were at- tacked brutally, and around 20 tribals were killed, though the gov- ernment claims that only two were killed. A tribal girl was stripped naked, molested and chased naked on the street (Talukdar, 2007). • On 4 December 2009, migrant workers, predominantly from Uttar Pradesh and Bihar [Central North], have been brutally at- tacked in the industrial town of Ludhiana in Punjab [North West India] (Fazal, 2016). -
World Bank Document
Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized In the Dark SOUTH ASIA DEVELOPMENT FORUM In the Dark How Much Do Power Sector Distortions Cost South Asia? FAN ZHANG © 2019 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington, DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved 1 2 3 4 21 20 19 18 This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved. Rights and Permissions This work is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) http:// creativecommons.org/licenses/by/3.0/igo. Under the Creative Commons Attribution license, you are free to copy, distribute, transmit, and adapt this work, including for commercial purposes, under the following conditions: Attribution—Please cite the work as follows: Zhang, Fan. -
State-Level Trends of Malnutrition Burden and Its Indicators 1990-2017
State-Level Trends of Malnutrition Burden and its Indicators 1990-2017 India State-Level Disease Burden Initiative Malnutrition Collaborators 18 September 2019 India State-Level Disease Burden Initiative ▪ Launched in October 2015 as a joint effort of the ICMR, PHFI and IHME, in collaboration with the Ministry of Health and Family Welfare ▪ Disease burden and risk factors estimation for all states of India as part of the Global Burden of Disease Study (GBD) ▪ Extensive exercise to engage relevant domain experts, policy makers and other stakeholders across India: 300 collaborators from over 100 institutions across India ▪ Clear guidelines for collaborators, including primary ownership of India-specific research outputs with domain experts ▪ Clearly defined roles for ICMR, PHFI and IHME ▪ Identify major data gaps and contribute to building long-term data systems ▪ Advisory Board comprising of senior level policy makers and stakeholders NNM 2022 and WHO/UNICEF 2030 Targets for Malnutrition Indicators Indicator National Nutrition Mission 2022 targets WHO/UNICEF 2030 targets Low birthweight 2% points prevalence annually: 2017-2022 30% prevalence: 2012-2030 Child stunting Prevalence of 25% by 2022 50% number of children under-5 who are stunted: 2012-2030 Child underweight 2% points prevalence annually: 2017-2022 Child wasting Prevalence of less than 3% by 2030 Anaemia 3% points prevalence annually in children 50% prevalence in reproductive age under-5 and reproductive age women: women from 2012 to 2030 2017-2022 Exclusive Prevalence of exclusive -
India-Switzerland Relations Political Relations India and Switzerland
India-Switzerland Relations Political Relations India and Switzerland have had cordial and friendly relations since India’s Independence, based on shared values of democracy and the rule of law. India’s policy of non-alignment and Switzerland’s traditional policy of neutrality led to a close understanding between the two countries. Switzerland established diplomatic relations with India soon after Independence. A Treaty of Friendship between India and Switzerland was signed at New Delhi on August 14, 1948, one of the first such treaties to be signed by independent India and an important milestone in Indo-Swiss relations. The Treaty provided for the establishment of diplomatic missions between the two countries and missions were opened in Berne and Delhi soon after. Switzerland established its Consulates General in Mumbai and Bangalore. India has a Consulate General in Geneva. In 2008 India and Switzerland celebrated the 60th anniversary of the signing of the Friendship Treaty. In recognition of the growth of multi- faceted bilateral relations over six decades and to outline areas of mutual interest and cooperation, India and Switzerland decided to establish a Privileged Partnership. From 1971 to 1976, during and after Bangladesh’s struggle for Independence, Switzerland represented India’s interests in Pakistan and vice versa. Switzerland celebrated the centenary of setting up the Mumbai Swiss Consulate on 17 July, 2015, which had been opened to help Swiss cotton traders and protect business interests. The celebrations also coincided with 75 years of the Swiss Business Hub in Mumbai. Till last year the Swiss Consulate in Mumbai issued the maximum number of visas by any Swiss Consulate before it was transferred to the Swiss Embassy in Delhi. -
Children and Adolescents in Urban India: an Empirical Analysis’ Has Been Undertaken
CChildrenhildren aandnd AAdolescentsdolescents iinn UUrbanrban IIndiandia SScalecale aandnd NNatureature ooff DDeprivationeprivation AAnn EEmpiricalmpirical AAnalysisnalysis April 2020 Supported by: National Institute of Urban Affairs CChildrenhildren aandnd AAdolescentsdolescents iinn UUrbanrban IIndiandia SScalecale aandnd NNatureature ooff DDeprivationeprivation AAnn EEmpiricalmpirical AAnalysisnalysis April 2020 Supported by: Prepared by: National Institute of Urban Affairs Foreword Urban India is home to the largest number of children and adolescents in the world. They have a significant contribution in determining the developmental trajectory of urban India. The Sustainable Development Goals (SDGs) of the United Nations recognise early childhood and adolescence as a significant phase of development throughout the lifespan of an individual, which forms the basis of later life outcomes. In fact, SDGs on poverty (goal 1), zero hunger (goal 2), good health and well-being (goal 3), quality education (goal 4), gender equality (goal 5), clean water and sanitation (goal 6), reduced inequality (goal 10), sustainable cities and communities (goal 11) are directly linked to the overall development of children and adolescents. Achievement of these goals would be a positive move towards the implementation of the ‘New Urban Agenda’ (Habitat III, 2016), leaving no one behind in the process of development. The principle is that cities need to invest in their clusters of human capital. At this juncture, it is important to understand the scale and nature of deprivation among children and adolescents in India. The United Nations Children’s Fund (Delhi office) has entered into a research collaboration with National Institute of Urban Affairs (NIUA). Under this collaboration, this research study titled ‘Scale and Nature of Deprivation among Children and Adolescents in Urban India: An Empirical Analysis’ has been undertaken. -
Wanda Muñoz Autonomous Weapons
Autonomous weapons systems: an analysis from human rights, humanitarian and ethical artificial intelligence perspectives This paper is based on Wanda Muñoz’ intervention at the briefing for diplomats on “The Normative and Operational Framework on Autonomous Weapon Systems” held on 28/05/2021. Today I will share with you two angles of analysis on the issue of autonomous weapons. Firstly, I will share some perspectives of human rights activists and humanitarian workers. Secondly, I will talk about how the discussion on autonomous weapons could be informed by international discussions on ethical approaches to artificial intelligence (AI). A/ Humanitarian and Human Rights Concerns The topic of autonomous weapons should not be seen only as a military and diplomatic issue, because it is much more than that; it is also a social and humanitarian issue. Unfortunately, what we see in the world today is that thousands of civilians have to deal with the consequences of violence and weapons daily, and that humanitarian organizations are at the forefront of the response. From this perspective, I would like to highlight four key reasons why autonomous weapon should be banned. 1. Human dignity. We believe that no one ever should face any risk of harm or death by autonomous weapons, because this would go against human dignity. This has already been said but we will keep insisting on it until autonomous weapons that target humans are banned. What message do you think we would send to those populations where autonomous weapons would be deployed? In my view, we would be telling them: “To us, your value as a human being is so little, that we don’t care about the risks, and even a machine can do the job of killing you”. -
Mx. Joy Buolamwini, Founder, Algorithmic Justice League
United States House Committee on Science, Space and Technology June 26, 2019 Hearing on Artificial Intelligence: Societal and Ethical Implications Written Testimony of Joy Buolamwini Founder, Algorithmic Justice League Masters in Media Arts and Sciences, 2017, Massachusetts Institute of Technology MSc Education (Learning & Technology), 2014, Distinction, University of Oxford BS Computer Science, 2012, Highest Honors, Georgia Institute of Technology PhD Pending, MIT Media Lab Made Possible By Critical Input from Dr. Sasha Costanza-Chock Injoluwa Deborah Raji For additional information, please contact Joy Buolamwini at [email protected] Dear Chairwoman Johnson, Ranking Member Lucas, and Members of the Committee, Thank you for the opportunity to testify on the societal and ethical implications of artificial intelligence (AI). My name is Joy Buolamwini, and I am the founder of the Algorithmic Justice League (AJL), based in Cambridge, Massachusetts. I established AJL to create a world with more ethical and inclusive technology after experiencing facial analysis software failing to detect my dark-skinned face until I put on a white mask. I’ve shared this experience of algorithmic bias in op-eds for Time Magazine and the New York Times as well as a TED featured talk with over 1 million views.1 My MIT thesis and subsequent research studies uncovered substantial skin type and gender bias in AI services from companies like Microsoft, IBM, and Amazon.2 This research has been covered in over 40 countries and has been featured in the mainstream media including FOX News, MSNBC, CNN, PBS, Bloomberg, Fortune, BBC, and even the Daily Show with Trevor Noah.3 Figure 1.