The Ancient Imagination Behind China’s AI Ambition

Essay by Jennifer Bourne: “Artificial intelligence is a modern technology, but in both the West and the East the aspiration for inventing autonomous tools and robots that can think for themselves can be traced back to ancient times. Adrienne Mayor, a historian of science at Stanford, has noted that in ancient Greece, there were myths about tools that helped men become godlike, such as the legendary inventor Daedalus who fabricated wings for himself and his son to escape from prison. 

Similar myths and stories are to be found in China too, where aspirations for advanced robots also appeared thousands of years ago. In a tale that appears in the Taoist text “Liezi,” which is attributed to the 5th-century BCE philosopher Lie Yukou, a technician named Yan Shi made a humanlike robot that could dance and sing and even dared to flirt with the king’s concubines. The king, angry and fearful, ordered the robot to be dismantled. 

In the Three Kingdoms era (220-280), a politician named Zhuge Liang invented a “fully automated” wheelbarrow (the translation from the Chinese is roughly “wooden ox”) that could reportedly carry over 200 pounds of food supplies and walk 20 miles a day without needing any fuel or manpower. Later, Zhang Zhuo, a scholar who died around 730, wrote a story about a robot that was obedient, polite and could pour wine for guests at parties. In the same collection of stories, Zhang also mentioned a robot monk who wandered around town, asking for alms and bowing to those who gave him something. And in “Extensive Records of the Taiping Era,” published in 978, a technician called Ma Daifeng is said to have invented a robot maid who did household chores for her master.

Imaginative narratives of intelligent robots or autonomous tools can be found throughout agriculture-dominated ancient China, where wealth flowed from a higher capacity for labor. So, stories reflect ancient people’s desire to get more artificial hands on deck, and to free themselves from intensive farm work….(More)”.

Selecting the Most Effective Nudge: Evidence from a Large-Scale Experiment on Immunization

NBER Paper by Abhijit Banerjee et al: “We evaluate a large-scale set of interventions to increase demand for immunization in Haryana, India. The policies under consideration include the two most frequently discussed tools—reminders and incentives—as well as an intervention inspired by the networks literature. We cross-randomize whether (a) individuals receive SMS reminders about upcoming vaccination drives; (b) individuals receive incentives for vaccinating their children; (c) influential individuals (information hubs, trusted individuals, or both) are asked to act as “ambassadors” receiving regular reminders to spread the word about immunization in their community. By taking into account different versions (or “dosages”) of each intervention, we obtain 75 unique policy combinations.

We develop a new statistical technique—a smart pooling and pruning procedure—for finding a best policy from a large set, which also determines which policies are effective and the effect of the best policy. We proceed in two steps. First, we use a LASSO technique to collapse the data: we pool dosages of the same treatment if the data cannot reject that they had the same impact, and prune policies deemed ineffective. Second, using the remaining (pooled) policies, we estimate the effect of the best policy, accounting for the winner’s curse. The key outcomes are (i) the number of measles immunizations and (ii) the number of immunizations per dollar spent. The policy that has the largest impact (information hubs, SMS reminders, incentives that increase with each immunization) increases the number of immunizations by 44 % relative to the status quo. The most cost-effective policy (information hubs, SMS reminders, no incentives) increases the number of immunizations per dollar by 9.1%….(More)”.

Platform Workers, Data Dominion and Challenges to Work-life Quality

Paper by Mabel Choo and Mark Findlay: “Originally this short reflection was intended to explore the relationship between the under-regulated labour environment of gig workers and their appreciation of work-life quality. It was never intended as a comprehensive governance critique of what is variously known as independent, franchised, or autonomous service delivery transactions facilitated through platform providers. Rather it was to represent a suggestive snapshot of how workers in these contested employment contexts viewed the relevance of regulation (or its absence) and the impact that new forms of regulation might offer for work-life quality.

By exploring secondary source commentary on worker experiences and attitudes it became clear that profound information deficits regarding how their personal data was being marketed meant that expecting any detailed appreciation of regulatory need and potentials was unrealistic from such a disempowered workforce. In addition, the more apparent was the practice of the platforms re-using and marketising this data without the knowledge or informed consent of the data subjects (service providers and customers) the more necessary it seemed to factor in this commercialisation when regulatory possibilities are to be considered.

The platform providers have sheltered their clandestine use of worker data (whether it be from pervasive surveillance or transaction histories) behind dubious discourse about disruptive economies, non-employment responsibilities, and the distinction between business and private data. In what follows we endeavor to challenge these disempowering interpretations and assertions, while arguing the case that at the very least data subjects need to know what platforms do with the data they produce and have some say in its re-use. In proposing these basic pre-conditions for labour transactions, we hope that work-life experience can be enhanced. Many of the identified needs for regulation and suggestions as to the form it should take are at this point declaratory in the paper, and as such require more empirical modelling to evaluate their potential influences in bettering work-life quality….(More)”

The lapses in India’s Covid-19 data are a result of decades of callousness towards statistics

Prathamesh Mulye at Quartz: “India is paying a huge price for decades of callous attitude towards data and statistics. For several weeks now, experts have been calling out the Indian government and state heads for suppressing Covid-19 infection and death figures. None of the political leaders have addressed these concerns even as official data reflects a small fraction of what’s playing out at hospitals and cremation grounds.

A major reason why administrations are getting away without an answer is that data lapses are nothing new to India.

Successive regimes in the country have tinkered and twisted figures as per their convenience without much consequences. For years, the country has been criticised for insufficient and poor quality data relating to a range of topics, including GDP, farmer suicide, and even unemployment…

Before the pandemic started, the most prominent data controversy in India was around the GDP numbers, which the Modi government continuously changed and chopped to cover up the slowdown in economic growth. In 2019, the Modi government also chose not to publish an unemployment data report that showed that joblessness in the country was at a nine-year high in 2017-18. And last year, in the middle of the pandemic, the government said it had no data on the number of frontline workers who had lost their lives to Covid-19 or a list of police personnel fatalities due to the disease.

Experts say that India’s statistical machinery has been deliberately weakened over the past few years to protect various governments’ false claims and image.

“The weakened statistical machinery manifests itself in different ways such as delays and questions about data quality. Also, when the results of a survey don’t suit the government in power, it tries to suppress data. This happened, for instance, with nutrition data in previous governments too,” said Reetika Khera, associate professor at the Indian Institute of Technology (IIT), Delhi.

“Think of the economy as a patient: data captures its pulse rate. If you don’t listen to the pulse, you won’t be able to diagnose correctly, let alone cure it,” she added….(More)”

Resetting Data Governance: Authorized Public Purpose Access and Society Criteria for Implementation of APPA Principles

Paper by the WEF Japan: “In January 2020, our first publication presented Authorized Public Purpose Access (APPA), a new data governance model that aims to strike a balance between individual rights and the interests of data holders and the public interest. It is proposed that the use of personal data for public-health purposes, including fighting pandemics, be subject to appropriate and balanced governance mechanisms such as those set out the APPA approach. The same approach could be extended to the use of data for non-medical public-interest purposes, such as achieving the United Nations Sustainable Development Goals (SDGs). This publication proposes a systematic approach to implementing APPA and to pursuing public-interest goals through data use. The approach values practicality, broad social agreement on appropriate goals and methods, and the valid interests of all stakeholders….(More)”.

Governance Innovation ver.2: A Guide to Designing and Implementing Agile Governance

Draft report by the Ministry of Economy, Trade and Industry (METI): “Japan has been aiming at the realization of “Society 5.0,” a policy for building a human-centric society which realizes both economic development and solutions to social challenges by taking advantage of a system in which cyberspaces, including AI, IoT and big data, and physical spaces are integrated in a sophisticated manner (CPSs: cyber-physical systems). In advancing social implementation of innovative technologies toward the realization of the Society 5.0, it is considered necessary to fundamentally reform governance models in view of changes in social structures which new technologies may bring about.

Triggered by this problem awareness, at the G20 Ministerial Meeting on Trade and Digital Economy, which Japan hosted in June 2019, the ministers declared in the ministerial statement the need for “governance innovation” tailored to social changes which will be brought about by digital technologies and social implementation thereof.

In light of this, METI inaugurated its Study Group on a New Governance Model in Society 5.0 (hereinafter referred to as the “study group”) and in July 2020, the study group published a report titled “GOVERNANCE INNOVATION: Redesigning Law and Architecture for Society 5.0” (hereinafter referred to as the “first report”). The first report explains ideal approaches to cross-sectoral governance by multi-stakeholders, including goal-based regulations, importance for businesses to fulfill their accountability, and enforcement of laws with an emphasis on incentives.

Against this backdrop, the study group, while taking into consideration the outcomes of the first report, presented approaches to “agile governance” as an underlying idea of the governance shown in the Society 5.0 policy, and then prepared the draft report titled “Governance Innovation ver.2: A Guide to Designing and Implementing Agile Governance” as a compilation presenting a variety of ideal approaches to governance mechanisms based on agile governance, including corporate governance, regulations, infrastructures, markets and social norms.

In response, METI opened a call for public comments on this draft report in order to receive opinions from a variety of people. As the subjects shown in the draft report are common challenges seen across the world and many parts of the subjects require international cooperation, METI wishes to receive wide-ranging, frank opinions not only from people in Japan but also from those in overseas countries….(More)”.

Measuring Commuting and Economic Activity Inside Cities with Cell Phone Records

Paper by Gabriel Kreindler and Yuhei Miyauchi: “We show how to use commuting flows to infer the spatial distribution of income within a city. A simple workplace choice model predicts a gravity equation for commuting flows whose destination fixed effects correspond to wages. We implement this method with cell phone transaction data from Dhaka and Colombo. Model-predicted income predicts separate income data, at the workplace and residential level, and by skill group. Unlike machine learning approaches, our method does not require training data, yet achieves comparable predictive power. We show that hartals (transportation strikes) in Dhaka reduce commuting more for high model-predicted wage and high-skill commuters….(More)”.

As Jakarta floods again, humanitarian chatbots on social media support community-led disaster response

Blog by Petabencana: “On February 20th, #banjir and #JakartaBanjir were the highest trending topics on Twitter Indonesia, as the capital city was inundated for the third major time this year, following particularly heavy rainfall from Friday night (19/2/2021) to Saturday morning (20/02/2021). As Jakarta residents turned to social media to share updates about the flood, they were greeted by “Disaster Bot” – a novel AI-assisted chatbot that monitors social media for posts about disasters and automatically invites users to submit more detailed disaster reports. These crowd-sourced reports are used to map disasters in real-time, on a free and open source website,

As flooding blocked major thoroughfares and toll roads, disrupted commuter lines, and cut off electricity to over 60,000 homes, residents continued to share updates about the flood situation in order to stay alert and make timely decisions about safety and response. Hundreds of residents submitted flood reports to, alerting each other about water levels, broken infrastructures and road accessibility. The Jakarta Emergency Management Agency also updated the map with official information about flood affected  areas, and monitored the map to respond to resident needs. experienced a 2000% in activity in under 12 hours as residents actively checked the map to understand the flooding situation, avoid flooded areas, and make decisions about safety and response. 

Residents share updates about flood-affected road access through the open source information sharing platform, Thousands of residents used the map to navigate safely as heavy rainfall inundated the city for the third major time this year.

As flooding incidents continue to occur with increasing intensity across the country, community-led information sharing is once again proving its significance in supporting response and planning at multiple scales. …(More)”.

Collective bargaining on digital platforms and data stewardship

Paper by Astha Kapoor: “… there is a need to think of exploitation on platforms not only through the lens of labour rights but also that of data rights. In the current context, it is impossible to imagine well-being without more agency on the way data are collected, stored and used. It is imperative to envision structures through which worker communities and representatives can be more involved in determining their own data lives on platforms. There is a need to organize and mobilize workers on data rights.

One of the ways in which this can be done is through a mechanism of community data stewards who represent the needs and interests of workers to their platforms, thus negotiating and navigating the data-based decisions. This paper examines the need for data rights as a critical requirement for worker well-being in the platform economy and the ways in which it can be actualized. It argues, given that workers on platforms produce data through collective labour on and off the platform, that worker data are a community resource and should be governed by representatives of workers who can negotiate with platforms on the use of that data for workers and for the public interest. The paper analyses the opportunity for a community data steward mechanism that represents workers’ interests and intermediates on data issues, such as transparency and accountability, with offline support systems. And is also a voice to online action to address some of the injustices of the data economy. Thus, a data steward is a tool through which workers better control their data—consent, privacy and rights—better and organize online. Essentially, it is a way forward for workers to mobilize collective bargaining on data rights.

The paper covers the impact of the COVID-19 pandemic on workers’ rights and well-being. It explores the idea of community data rights on the platform economy and why collective bargaining on data is imperative for any kind of meaningful negotiation with technology companies. The role of a community data steward in reclaiming workers’ power in the platform economy is explained, concluding with policy recommendations for a community data steward structure in the Indian context….(More)”.

Monitoring the R-Citizen in the Time of Coronavirus

Paper by John Flood and Monique Lewis: “The COVID pandemic has overwhelmed many countries in their attempts at tracking and tracing people infected with the disease. Our paper examines how tracking and tracing is done looking at manual and technological means. It raises the issues around efficiency and privacy, etc. The paper investigates more closely the approaches taken by two countries, namely Taiwan and the UK. It shows how tracking and tracing can be handled sensitively and openly compared to the bungled attempts of the UK that have led to the greatest number of dead in Europe. The key messages are that all communications around tracking and tracing need to open, clear, without confusion and delivered by those closest to the communities receiving the messages.This occurred in Taiwan but in the UK the central government chose to close out local government and other local resources. The highly centralised dirigiste approach of the government alienated much of the population who came to distrust government. As local government was later brought into the COVID fold the messaging improved. Taiwan always remained open in its communications, even allowing citizens to participate in improving the technology around COVID. Taiwan learnt from its earlier experiences with SARS, whereas the UK ignored its pandemic planning exercises from earlier years and even experimented with crude ideas of herd immunity by letting the disease rip through the population–an idea soon abandoned.

We also derive a new type of citizen from the pandemic, namely the R citizen. This unfortunate archetype is both a blessing and a curse. If the citizen scores over 1 the disease accelerates and the R citizen is chastised, whereas if the citizen declines to zero it disappears but receives no plaudits for their behaviour. The R citizen can neither exist or die, rather like Schrödinger’s cat. R citizens are of course datafied individuals who are assemblages of data and are treated as distinct from humans. We argue they cannot be so distinguished without rendering them inhuman. This is as much a moral category as it is a scientific one….(More)”.