Analytica November 2022

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Organon, the Analytics Club of IIM Rohtak is a student driven initiative whose basic idea is to generate and cultivate student interest in Analytics and technology. Our primary goals and responsibilities include conducting seminars and webinars covering on demand topics, skills and tools that will help students of IIM Rohtak fraternity gain expertise in various analytical tools. These skills will help students apply analytical tools in their respective fields during placements. We conduct Analytics related events, competency builder events, Case Study Competitions, Quiz questions

WHAT INDIA'S DRAFT DIGITAL PRIVACY LAW SAYS - AND COMPARISON WITH OTHER COUNTRIES

Anil Sasi , Soumyarendra Barik

The new Digital Personal Data Protection Bill, 2022 released on Friday (November 18) is focused on personal data, as compared to an earlier unwieldy draft. The reworked version of the legislation incorporates hefty penalties for non compliance, but which are capped without any link to the turnover of the entity in question. It has also relaxed rules on cross border data flows that could bring relief to the big tech companies, alongside a provision for easier compliance requirements for start ups

There could be two potentially significant red flags: a near blanket exemption for government agencies from complying with some of the more onerous requirements under the Bill, and a dilution of the remit of the proposed Data Protection Board, which is mandated to oversee the provisions of the proposed legislation.

Officials at the Ministry of Electronics and IT (MeitY) have said the new draft strikes a delicate balance and factors in learning from global approaches, while staying aligned to the Supreme Court’s ruling on privacy as a fundamental right, but within reasonable restrictions.

While comparisons have been drawn with the EU’s landmark General Data Protection Regulation or GDPR which, according to Graham Greenleaf, professor of Law & Information Systems at the University of New South Wales, has substantially influenced legislation in nearly 160 countries the Government of India’s view sees its version of the Data Protection Bill as only one of the pieces that form part of its larger policy vision for the entire digital economy

This larger policy includes a comprehensive digital India Act hat would eventually replace the existing IT Act, the new data protection Bill that has just been unveiled, and the new telecom Bill that was put in the public domain last month

In contrast, the landmark GDPR, in force since May 2018, is clearly focused on privacy and requires individuals to give explicit consent before their data can be processed A pair of sub legislation the Digital Services Act (DSA) and the Digital Markets

Act (DMA) take off from the GDPR’s overarching focus on the individual’s right over her data. The DSA focuses on issues such as regulating hate speech, counterfeit goods etc. while the DMA defines a new category of “dominant gatekeeper” platforms, and is focused on uncompetitive practices and the abuse of dominance by these players.

Data protection laws in other geographies

An estimated 137 out of 194 countries have put in place legislation to secure the protection of data and privacy, with Africa and Asia showing 61% (33 countries out of 54) and 57% adoption respectively, according to data from the United Nations Conference on Trade and Development (UNCTAD), an intergovernmental organisation within the United Nations Secretariat. Only 48% of Least Developed Countries (22 out of 46) have data protection and privacy laws. page one, EU MODEL: The GDPR focuses on a comprehensive data protection law for processing of personal data It has been criticised for being excessively stringent, and imposing many obligations on organisations processing data, but it is the template for most of the legislation drafted around the world.

In the EU, the right to privacy is enshrined as a fundamental right that seeks to protect an individual’s dignity and her right over the data she generates. The European Charter of Fundamental Rights recognises the right to privacy as well as the right to protection of personal data, and is backed by a comprehensive data protection framework, which applies to processing of personal data

by any means, and to processing activities carried out by both the government and private entities. There are certain exemptions such as national security, defence, public security, etc, but they are clearly defined and seen as exclusions on the periphery.

US MODEL: Privacy protection is largely defined as “liberty protection” focused on the protection of the individual’s personal space from the government. It is viewed as being somewhat narrow in focus because it enables collection of personal information as long as the individual is informed of such collection and use. The US template has been viewed as inadequate in key respects of regulation.

There is no comprehensive set of privacy rights or principles in the US that, like the EU’s GDPR, addresses the use, collection, and disclosure of data. Instead, there is limited sector specific regulation The approach towards data protection is different for the public and private sectors The activities and powers of the government vis a vis personal information are, however, sufficiently well defined and addressed

by broad legislation such as the Privacy Act, the Electronic Communications Privacy Act, etc. For the private sector, there are some sector specific norms.

CHINA MODEL: New Chinese laws on data privacy and security issued over the last 12 months include the Personal Information Protection Law (PIPL), which came into effect in November 2021. It gives Chinese data principals new rights as it seeks to prevent the misuse of personal data. The Data Security Law (DSL), which came into force in September 2021, requires business data to be categorized by levels of importance, and puts new restrictions on cross border transfers.

These regulations will have a significant impact on how companies collect, store, use and transfer data, but are essentially focused on giving the government issuing

overreaching powers to collect data as well as to regulate private companies that collect and process information.According to an EY analysis, China’s PIPL is deemed to be “similar” to the EU’s GDPR in that it gives Chinese consumers the right to access, correct, and delete their personal data gathered by businesses, but credibly impacts

offshore data processors that deliver goods and services or analyse individuals in China.

Administration of China (CAC) and other relevant authorities

The law includes stringent penalties, with fines as high as RMB 50 million, or up to 5% of a company’s turnover in the previous financial year. Businesses may also be required to suspend operations until they “demonstrate compliance”.There are also impacts on individuals, with anyone directly responsible for data protection personally facing fines of up to RMB 1 million.

Companies that mishandle data under the DSL face severe penalties: the ride hailing giant Didi faced a $1.2 billion (RMB 8 026 billion) fine in July this year for allegedly breaking China’s cyber security laws. Other companies have also been facing regulatory action.

he DSL requires that business data be classified according to its relevance to national security and the public interest, and companies looking to transfer “important” data outside China must perform an internal security review before applying for a security assessment and approval from the Cyberspace

India’s draft Bill and the red flags Wide ranging exemptions to the Centre and its agencies with little to no safeguards, and reduced independence of the proposed Data Protection Board are among the key concerns flagged by experts. It is also worth noting that the new Bill has just 30 clauses compared to the more than 90 in the previous one, mainly because a lot of operational details have been left to subsequent rule making

The central government can issue in order to pick out the other relevant and

notifications to exempt its agencies from adhering to provisions of the draft law for national security reasons. In an explanatory note accompanying the proposed legislation, the government argued that “national and public interest is at times greater than the interest of an individual”, while justifying the need for such exemptions.

The draft law leaves the appointment of the chairperson and members of the Data Protection Board entirely to the discretion of the central government. “While the Data Protection Authority was earlier envisaged to be a statutory authority (under the 2019 Bill), the Data Protection Board is now a central government set up board The government continues to have a say in the composition of the board, terms of service, etc.,” said Nehaa Chaudhari, partner at Delhi based Ikigai Law

Minister of State for Electronics and IT Rajeev Chandrasekhar has said the new draft

in a manner so as to provide enhanced internet services to certain players.The CCI, relying on these rules, noted that the telecommunications regulations ensured that parties would abide by net neutrality

Given that a remedy under the Competition Act may only lie after parties cross a certain degree of market power or jurisdictional thresholds, such rules are helpful in ensuring that already established players in a particular relevant market do not assert their market powers in related markets by leveraging their positions

To cater to situations like these, international jurisdictions, such as the EU, have come up with gatekeeper laws to regulate the conduct of digital players. In India, a related role is sought to be played by the e commerce rules,

The draft law leaves the appointmentof the chairperson and members to the central government

WE COULD RUN OUT OF DATA TO TRAIN AI LANGUAGE PROGRAMS

Tammy Xhu

Large language models are one of the hottest areas of AI research right now, with companies racing to release programs like GPT 3 that can write impressively coherent articles and even computer code. But there’s a problem looming on the horizon, according to a team of AI forecasters: we might run out of data to train them on.

Language models are trained using texts from sources like Wikipedia, news articles, scientific papers, and books. In recent years, the trend has been to train these models on more and more data in the hope that it’ll make them more accurate and versatile. The trouble is, the types of data typically

used for training language models may be used up in the near future as early as 2026, according to a paper by researchers from Epoch, an AI research and forecasting organization, that is yet to be peer reviewed The issue stems from the fact that, as researchers build more powerful models with greater capabilities, they have to find ever more texts to train them on. Large language model researchers are increasingly concerned that they are going to run out of this sort of data, says Teven Le Scao, a researcher at AI company Hugging Face, who was not involved in Epoch’s work.

The issue stems partly from the fact that

language AI researchers filter the data they use to train models into two categories: high quality and low quality. The line between the two categories can be fuzzy, says Pablo Villalobos, a staff researcher at Epoch and the lead author of the paper, but text from the former is viewed as better written and is often produced by professional writers.

Data from low quality categories consists of texts like social media posts or comments on websites like 4chan, and these examples greatly outnumber those considered to be high quality Researchers typically only train models using data that falls into the high quality category because that is the type of language they want the models to reproduce. This approach has resulted in some impressive results for large language models such as GPT 3. One way to overcome these data constraints would be to reassess what’s defined as “low” and “high” quality, according to Swabha

Swayamdipta, a University of Southern California machine learning professor who specializes in data set quality. If data shortages push AI researchers to incorporate more diverse data sets into the training process, it would be a “net positive” for language models, Swayamdipta says

Researchers may also find ways to extend the life of data used for training language models. Currently, these models are trained on the same data just once, owing to performance and cost constraints. But it may be possible to train a model several times using the same data, says Swayamdipta.

Some researchers believe big may not equal better when it comes to language models anyway Percy Liang, a computer science professor at Stanford University, says there’s evidence that making models more efficient may improve heir ability, not just increase their size. “We’ve seen how smaller

models that are trained on higher quality data can outperform larger models trained on lower quality data,” he explains.

Language models are trained using texts from sources like Wikipedia, news articles, scientific papers, and books. In recent years, the trend has been to train these models on more and more data in the hope that it’ll make them more accurate and versatile. The trouble is, the types of data typically used for training language models may be used up in the near future as early as 2026, according to a paper by researchers from Epoch, an AI research and forecasting organization, that is yet to be peer reviewed. The issue stems from the fact that, as researchers build more powerful models with greater capabilities, they have to find ever more texts to train them to lead

on. Large language model researchers are increasingly concerned that they are going to run out of this sort of data, says Teven Le Scao, a researcher at AI company Hugging Face, who was not involved in Epoch’s work

The issue stems partly from the fact that language AI researchers filter the data they use to train models into two categories: high quality and low quality.

The line between the two categories can be fuzzy, says Pablo Villalobos, a staff researcher at Epoch and the lead author of the paper, but text from the former is viewed as better written and is often produced by professional writers

Some researchers believe big may not equal better when it comes to language models anyway

Digital Markets Guide

Introduction

It is not just the digital economy that is changing the traditional tools of competition; antitrust authorities all over the world are playing catch up with the digital economy and widening their analytical tools in assessing such conduct. As global antitrust regulators up the ante on closely surveying digital market players, the Indian antitrust authority, the Competition Commission of India (CCI), has also begun to delve deeper into its analysis of digital and high technology markets.

Naturally, the CCI finds itself playing a decisive role in determining the course of the tech scrutiny in India, which has initiated probes into the likes of Amazon, Facebook, WhatsApp and other large indigenous digital market players. In so doing, it has recognised newer issues posed by the peculiarities of the digital

has also attempted to adopt legal tests beyond that which is applied to the traditional competition models.

In this piece, we examine how the CCI has adapted its assessment of various competition issues raised by the digital sector in recent years.The growth of India’s digital economy

A study conducted by McKinzie Global Institute reflects India as the second fastest digital adopter among 17 major digital economies. With covid 19 deeply entrenching online services in people’s day to day lives and cementing the market position of players, the digital economy has seen tremendous growth in India in the past year The e commerce segment is expected to grow to US$200 billion in 2026, from US$38.5 billion in 2017.

The market features several global and local

Nisha Kaur Uberoi, Radhika Seth and Pramothesh Mukherjee

undertakings, such as Amazon, Reliance’s JioMart (e commerce platforms owned by one of India’s largest conglomerates, Reliance Industries Ltd ), MakeMyTrip (online travel and ticketing), Uber and Ola just to name a few. At the same time, the Indian e commerce market features a host of new entrants who operate within a niche space and cater only to the requirement of a particular kind of product or service. The e commerce market also features new entrants such as Nykaa (personal care and beauty), PharmEasy (online pharmacy), PayTM (online payments) and Zomato (food delivery) who have capitalised on the e commerce model and now cater to many consumers. These companies are now growing to the stage of publicly listing their shares, which speaks of the potential for growth in the Indian digital economy.

In recent years, the players in the digital markets have grown from strength to strength as they enter multiple, related verticals While this has fuelled growth and widespread use of e commerce services, players have also altered their growth strategies, with some resorting to anticompetitive means. The Indian competition watchdog found itse midst of many such instances.

Competition regulation and t assessment of conduct in digital m

With the growing prominence markets in India, the CCI has assess like net neutrality, leveraging, effects and collection of data l accumulation of market power, in merger assessment and enforceme Albeit a young regulator as compa international peers, the CCI has b to adapt to the emerging issues of the digital

markets, as seen in some of its important decisions

In 2020, the CCI approved the acquisition of 9.99 per cent equity share capital by a wholly owned subsidiary of Facebook in Reliance Jio Infocomm Limited (Facebook/Reliance).

[5] Reliance Jio is a subsidiary of Reliance Industries and is the largest telecommunications company in India.

The investment enabled collaborations between the two undertakings in the online advertising and e commerce space.

An interesting aspect of the collaboration was the commercial arrangement with the instant messaging platform WhatsApp (a subsidiary of Facebook), in relation to connecting users with Reliance’s new e commerce marketplace, JioMart.

Acknowledging the growing synergies between the telecommunication industry and the digital technology space, the cCI approved the transaction, recognising its pro competitive effects. At the same time, in its analysis, the CCI evaluated

robable anticompetitive issues that could emerge as a fallout of such transactions. The CCI remarked that combinations can be analysed in light of data backed market power, in which case the analysis ought to dwell upon the incentive that the parties have to pool or monetise such data. The nature of data possessed by Reliance Jio and Facebook was found to be complementary owing to a symbiotic relation between telecommunications service providers and mobile applications. Interestingly, this finding had little bearing on the analysis of the CCI, given that the parties submitted that they do not intend to share such complementary data as a part of the transaction While there was no observation made on the potential avenues of data sharing between the parties, competition parties are not strangers to evisiting merger control orders in case parties decide to share data at a later stage. The CCI

safeguarded such risks in this case by specifically leaving scope for an ex post enforcement review in case the transaction were to lead to any anticompetitive impact in future

Although the pace at which players operate in digital markets is rapid, as is the elevation of certain players to becoming entrenched market leaders, the reliance on an ex post approach in an ex anteassessment may create market powers in this space that are difficult to challenge through competition.

Another issue pointed out in passing by the CCI in its a ssessment of the Facebook/Reliance combination was net neutrality Owing to the complementary nature of the products offered by the parties, the CCI recognised the impact and to assess its digital transformation

neutrality However, it did not delve deeper into this issue and sought for a safety net from the role that other statutory regulators, such as the Telecom Regulatory Authority of India,may play in preventing exclusionary conduct as a result of such synergies While the CCI is empowered to look into conduct that may violate principles of net neutrality, the telecommunications regulations in India deal with such issues and prohibit platforms from treating entities differently. These rules are specifically intended towards ensuring that telecommunications service providers do not manipulate traffic n a manner so as to provide enhanced internet services to certain players.The CCI, relying on these rules, noted that the telecommunications regulations ensured that parties would abide by net neutrality.Given that a remedy under the Competition Act may only lie after parties cross a certain degree of

which were passed with an outlook to make the e commerce industry more transparent.

The CCI is also ensuring in its ex ante analysis that any perceived competitive harm is addressed In approving the acquisition of shares by Hyundai Motor Company (and Kia Motor Company) in ANI Technologies (which is the parent of an Indian ride sharing platform Ola), the strategic agreement between the parties piqued the CCI’s interest insofar as its algorithm could (hypothetically) promote the use and leasing of Hyundai cars, among Ola’s drivers.

In response, a voluntary modification was submitted to clarify that the strategic collaboration will be on a non exclusive basis and no preference on OIa’s algorithm will be based on brand of vehicle

Data Analytics Market Size to Increase by USD 21,436 Million: 33% growth to originate from North AmericaMarket growth is estimated to accelerate at a CAGR of 13 84% and register an incremental growth of USD 21,436 million during the forecast period

Global IT consulting firm Cognizant has acquired AustinCSI, a cloud and data analytics consulting firm. Financial terms of the deal were not disclosed

Remote monitoring and data analytics company Medical Informatics raises $17.Health informatics and data collection company Medical Informatics announced its receipt of $27 million, made up of a $17 million Series B round plus $10 million in debt.

Cost engineering & data analytics company to expand in VA, creating 150 new jobs

InfinyOn announced the v0.10 beta release of the InfinyOn Cloud platform InfinyOn Cloud provides a modern approach that reduces the cost and complexity of operating and managing real time data pipelines. It includes a number of innovations and offerings

NEWSBITS

Education And Learning Analytics Global Market Report 2022: Government Initiatives in Digitalizing the Education Sector to Drive Growth

ZS and Abacus Insights Partner to Bring Innovative Data and Analytics to Health Plan.As ZS continues to help health plans evolve and transform, the firm announced today an investment in and partnership with Abacus Insights, a healthcare technology leader with a groundbreaking offering in data usability.

Retailers on track for record Cyber Monday Adobe Analytics. The estimate from Adobe Analytics predicts an increase of up to 8.5% from a yearearlier. Much of the increase could be put down to inflation, which rose 7 7% in October, the lowest since January.

KX Supports B2C2 for Trading Analytics, Driving Further Innovation In the Digital Assets Space. KX, maker of kdb+, the world's fastest time series database and analytics engine, announces that B2C2, the world's leading crypto liquidity provider and a digital asset pioneer, has expanded its use of KX's real time high performance analytics software, including the deployment of KX Dashboards, its powerful visualization tool.