Big Data: The Digital Revolution and its Impact on Society

Report by Michael McLoughlin and Oliver Röpke

1. Introduction

Big Data is a phrase we are all hearing more and more and one, which is increasingly having a major impact on our lives. The production of user-generated data was expected to grow by 2000% globally to 20201. There is no real clear and agreed definition of precisely what big data is although in many respects we know it when we see it. The varying definitions and descriptions of big data all have in common the fact that they refer to a large amount of data, much larger than what can be analysed on a single computer today, coming from different sources and in different, often unstructured, formats.

Some of the agreed descriptions can be summed up using the five V’s;2

1. Volume, referring to the scale of data; 2. Variety, since data is produced by different data sources in different formats; 3. Velocity, which is connected to the analysis of streaming data;4. Veracity, as data is uncertain and needs to be verified before or during use; 5. Value, which can be produced by analysing Big Data.

The amount of data being generated is growing exponentially and more and more of it has been generated in the most recent past. As consumers, we know of many of the sources as we both contribute to this data and consume it. The most common elements for citizens may be social networking sites, video streaming, banking, various online services and databases, medical records, and Government data, in fact the list is endless. While there are many forms of big data we may be somewhat aware of, there are also many we may not be and the future growth of the Internet of Things may further this trend.

The rapid spread of the internet and improvements in bandwidth and mobile technology are spurring on the growth and importance of Big Data. In assessing Big Data, we are confronted with many profound questions, which we need to grapple with globally. The questions surrounding Big Data and its impact will thus feature more and more in public debate, international relations, workplaces, trade and politics. We can see at a glance the immense benefits from Big Data; it brings about

1 Tucker (2013). Has Big Data made anonymity impossible? In: Big Data gets personal – MIT Technology Review

2 Based on an IBM synthesis and quoted in The ethics of Big Data: Balancing economic benefits and ethical questions of Big Data in the EU policy context (EESC)

EESC-2019-03036-00-00-TCD-TRA

tremendous efficiencies in the rapid and indeed instantaneous sharing of information. It can detect vital trends and ensure we can rapidly respond to emergencies, diseases or social phenomenon.

Similarly, there are many concerns about Big Data. It has been described as a hugely asymmetric occurrence as citizens, consumers and critically regulators do not possess sufficient knowledge to understand it and more importantly deal with it. Privacy and transparency are major concerns relating to the impact of Big Data today and in the future. The ability to reconcile these challenges is the core issue in assessing the social impact of Big Data.

2. The Potential of Big Data

There are a number of areas of great potential for society in the field of Big Data, which can be seen thematically. At the most basic level computational power provides for levels of aggregation never before experienced at similar speeds which are advancing all the time. Such data power also involves merging and overlaying different data sources once again previously not possible. These processes combined create huge value and indeed power which can be harnesses for business, public service and social good. As if often the case the potential and advantages can often depend on how one sees it or what angle one is coming from. One person’s advantage can be another person’s nightmare. However, it is still important to be clear on the many benefits of big data for society, which can be seen in just a brief selection of areas.

3. Health

Health and healthcare are possibly the most often mentioned benefits of big data. Much of the development of healthcare is dependent on research and development and harvesting patterns and results from human and other behaviour and reactions. Modelling the spread of disease or viruses and understanding how large numbers of people respond to differing treatments have always the core of understanding and responding to various conditions and developing medicines and health advice. Diet and nutrition is perhaps the biggest data set of all.

The products and processes in this field are truly widespread too. We can imagine the immense benefits to researchers from utilising new and large datasets. Wearable technology and phone based apps can monitor human activity around the clock and provide real time information. Other types of data such as transport information, immigration, social media, video streaming, CCTV and many more can tell us a lot about how we live and how we can make simple everyday health improvements.

At the more technical level, patient data can be shared and analysed much easier and quicker at the Meta level to examine the most serious conditions. Big Data increasingly allows clinicians work remotely and provide medical assistance to people in very remote areas. All of this is before we get in to the related fields of machine learning and robotics where many more medical applications are possible.

The Human Genome Project is perhaps the most celebrated application of Big Data in the field of health and life sciences. Indeed, creating and analysing large-scale data sets is not particularly new in human genetics research contexts, since a single human genome contains 2× 3.2 billion nucleotides worth of information. Genetics will continue to be produce some of the most significant health impacts for example in the fields of gene therapy and these may raise some of the most fundamental questions surrounding Big Data.

4. Planning and Transport

Big Data will assist all types of spatial planning. Instantaneous and real time data and tends from a variety of sources can provide planners with information to radically reshape traffic and transport plans. Housing need and behaviour can be mapped against human behaviour. Changing leisure and social behaviour can be tracked to enable various public and private services to respond appropriately.

Supply chain management and the field of logistics will also see major impact from the continuing acceleration of Big Data. Better matching of capacity, supply and multiple delivery will be observed. We are already aware of the development of ride sharing and further efficiencies can be imagined alongside an entire reimagination of the concepts of car ownership and car usage. The related concepts of autonomous vehicles, which will be major consumers and producers of big data will certainly revolutionise how we see and experience transport and may even change the very fabric of our cities and settlement pattern. Some have argued car ownership may almost disappear along with concepts such as “parking”.

5. Government, Economics and Policy Making

These areas are hugely dependent on data and statistics so any step change in its volume and utility will have a considerable impact. Many economic models rely on assumptions and surveys but real-time large data sets gathered from new sources and the Internet of Things will provide more real information that can be used in forecasting and responding to behavioural trends for economic regulation.

Greater efficiencies can be imagined by the improved and precise allocation of resources responding to real human behaviour. Commentators have even used online dating as an example of the power of the efficiency of Big Data to eliminate waste and duplication of effort! E-Government has been at the centre of new thinking on service delivery and removing geographical boundaries to service delivery and small countries like Estonia have been seen to lead the way. Thus Geography may fade considerably as a barrier in many fields.

6. Banking, Finance and Retail

There has already been a considerable shift in the working methods of finance and banking and they are two of the most globalised sectors in the world. However much more change can be expected. In essence, while the speed of transactions has advanced hugely the overlay of different data sets will provide even further rapid change. Real-time financial information is becoming the norm. Customer experience can be improved by the use of big data and there is significant change coming via new fintech actors who do not have the same issues and costs as traditional providers.

Crowd funding and a variety of other person-to-person finance solutions can also become realities. Similarly, customer segmentation can be significantly enhanced as can profiling of customer types and needs. Big Data technology can improve the predictive power of risk models, exponentially improve system response times and effectiveness, provide more extensive risk coverage, and generate significant cost savings by providing more automated processes, more precise predictive systems, and less risk of failure. Risk teams can gain more accurate risk intelligence from variety of sources in nearly real-time.

Retailing and marketing were arguably the first to engage in the Big Data revolution garnering more and more information about customers and their behaviours. Loyalty schemes, discounts and promotional work have all provided large data sets in these fields for a number of years. However again a further step up can be envisaged here particularly once again with the combining of different data sets and the move towards even more online retailing.

7. Education

As Big Data has revolutionised other sectors so it will be for education at all levels. Student behaviour, learning and evaluation can be compared easier and across much broader datasets even internationally. We have already seen the growth of MOOCs and education will become further globalised. Better analysis of student data should improve education standards and curricula. Improved learning environments can be fostered for examples with the use of augmented reality and real-time information in a variety of areas.

The delivery and evaluation of learning can also be enhanced with more variety in methods moving away form “chalk and talk” methods to a diversity of measurement for projects, continual assessment. Career guidance and more personalised social supports for students at all levels should benefit from greater levels of information and it's speedily availability.

8. The Risks of Big Data

The risks or potential drawbacks with big data have received a lot of coverage and have been the subject of much public debate. It is important to engage with these and understand their basis. There are several different thematic and overlapping concerns at play. Some may be due to the rapid change, which is evident with all new technology but others are very focused on the unique and distinct facets of Big Data itself.

Again, as mentioned previously, one person’s advantage or positive may be another person’s risk either due to differing interpretation or simply a disagreement about the balance of merits and demerits or indeed the need for a certain level of risk. Trust issues are also in evidence. Once more, it is helpful to try to disaggregate the risks seen in public debate to understand how to evaluate the social impact of Big Data, the most common are;

9. Privacy

From the literature on the subject, it is probably reasonable to conclude that privacy is one of the biggest risk in the development of Big Data. Again, understanding precisely what we mean by privacy can be a challenge. The idea can differ from culture to culture and even between different groups in society. Generally, we see privacy as major personal right, the right to have one’s own space that others cannot intrude. Many see it as the right to be separate when chosen, and to be apart from the society around us. Clearly, these notions resonate with the debate on Big Data. The EU derives many of these from human rights law and gives expression to them in the Treaties though the Charter on Fundamental Rights.

There is considerable regulation of data collection systems around the world but the notion of privacy is at their heart. Privacy relates to the concept of “personal data” which once more is central to data protection regimes for example the EU’s GDPR. Many proponents of Big Data will assert that the phenomenon rarely intrudes on personal data, as much of the data concerned is anonymous. However, this is a highly contested area. The aggregation of Big Data may involve anonymous information, but it is far from clear whether reidentification is possible at a later stage.

More importantly, the commonly held understanding of privacy may not be robust enough to cope with the advances of Big Data. New enormous data sets may tell us a lot more about people living in a particular region, about racial groups, about the search habits of certain groups or about some of their most “private” thoughts and desires. While the individual may not be completely identified the aggregation combining, blending and overlaying of their data may still have a huge impact on them in many ways in terms of access to services and how a group they may be a part of is treated, or how they are treated subsequently as an individual.

While privacy is personal, we lack any concept of group privacy, but Big Data will certainly further the need to think about such concepts. There can be an asymmetry between groups and Big Data players, which we should examine. Is this a feature of Big Data or a drawback? This is one of the issues that could be argued both ways, either as an improved way of doing business and targeting groups and regions or as an overstepping of the mark in terms of the rights of the groups and the concept of equal treatment. The answers we might give to these questions could of course vary from case to case. It is clear our societal, moral and legal systems may fall behind in dealing with the rapid changes brought about by Big Data in the field of privacy. However, there are privacy rules and data protection systems in place around the world and actions have and are been taken against some of the biggest companies in the field even at the time of writing.

10. Security

Loosely related to privacy but for many people a separate but major concern with Big Data is the security of their data. It is important to point out that generally these laws around the world exempt state security services and such operations. While the public and some commentators may conflate the two and although there can be linkage there are plenty of concerns about personal data for individuals and others even without examining state security.

Ten or fifteen years ago, we would have heard very little about the concept of a “data breach” but this is common today and raises major concerns for individuals, consumers, companies and public authorities. With the rise of Big Data and the value of large data sets, the notion of data falling in to the wrong hands is a critical issue. This may involve wrongdoing by means of hacking, criminal activity or leaking often targeted at financial institutions or sensitive personal data like medical or social security records.

Breaches may also be entirely innocent involving errors by employees or unsafe systems. However, the impact for individuals is the same and companies can be vulnerable both commercially and in terms of their reputation. While improved data protection regimes may eliminate some of the risks in this area it is also reasonable to assume that further growth in the centrality of Big Data will increase the incentives for criminal and nefarious activity, to get at large datasets and the hacking community is often extremely inventive. Similarly the number of inadvertent breaches will surely grow also.

11. Competition and Anti-trust

In some respects Big Tech. and Big Data go hand in hand fuelling concerns that dominance in the field of data leads to dominance in the field of business and the concentration of power in a small number of mega corporations that can resist regulation, eliminate competition, bring significant lobby power to bear and generally misuse a dominant position. Data has been compared to oil in the 1930s in terms of been a critical commodity for economic dominance. This also raises the prospect of competition and antitrust action similar to that seen in the oil industry in the U.S. in the past. Household names in the technology field are seen as the obvious culprits in this field and potential resistance is building to their role. However many industries of the future may exhibit the same tendencies if data itself is concentrated in too few hands.

Larger companies have been subject to action in recent times. Increasingly there is pressure to view big tech firms more like utilities than commercial companies. There is also a view that tech firms are not just conduits for content or products but providers of both product and the delivery method thus placing them at all points of transactions. This may be most obvious where online retailers move in to the high street. It will not be long before social media and other tech giants develop financial services tailored to peoples need based on their datasets.

These actions have been called “disruptors” exploiting the natural advantages of Big Data but others may feel such rapid change will have negative social impacts. We can also imagine much more of this activity with the related developments of the Internet of Things and Artificial Intelligence for example in the car industry.

12. Human Rights

Privacy is a qualified, fundamental human right in all of the major international and regional human rights instruments such as the United Nations Declaration of Human Rights (UDHR) 1948, and the International Covenant on Civil and Political Rights (ICCPR) 1966. Big Data may also contribute to the erosion of other basic human rights if not managed properly. We have seen how there can often be a basic asymmetry between Big Data and ordinary citizens. At its core, it may be that people simply cannot keep up with the pace of change wrought by Big Data. The stretching of the concept of privacy opens completely new areas of concern about judgements and decisions about groups and individuals who are part of such groups.

At the heart of this concern is the use and development of algorithms. Algorithms are essentially automated machine-based processes that make decisions based on observed and historical data-based patterns. Once more a familiar question arises here as to whether this is a natural progression with Big Data or something that goes to the heart of our human nature and needs regulating. Certainly, there are well-documented examples of algorithms making decisions based on racial profiling and assisting in critical decisions about insurance premiums and other matters all drawing on Big Data.

Even further along a similar spectrum there is now a debate about how people act and respond in a society where they know or suspect that Big Data is already gathering significant information on them. This is seen as a further blurring of the Public v Private space. It is even suggested that these concerns about Big Data may raise some of the most fundamental questions about human nature and “Who am I”. When combined with some of the advances in Artificial Intelligence and the science fiction predictions, which seem closer to many people we can see how Big Data certainly raises some profound questions for us all.

Again, many of the earlier stated advantages of Big Data and related advances are also seen as disadvantages. Artificial Intelligence certainly raises many concerns as we have seen. Machine learning is a related concept that now genuinely raises the question of where the machine starts and the person stops, this apparently is even playing itself out in the cockpits of our aircraft. In one of the most positive fields, that of genetics, people naturally have fears about the impact of playing with what can be seen as a natural order. In addition, the eradication or reduction of disease is not necessarily always seen as positive and may lead to fears of latter-day eugenics. Speculation about the possible eradication of Downes Syndrome has given rise to a most profound debate about disability and society.

13. Workplace Issues

Big Data naturally will affect the workplace in all sorts of ways. Applications of Big Data can increase productivity and make some tasks easier and faster to perform. Workers will have to adapt to these new realities and learn how to handle Big Data and Artificial Intelligence at their workplace and it is important to keep a human-centred approach over their introduction, design and use.

However, major concerns abound about the impact on employees of new systems of monitoring and productivity drives. These have already been aired, most notably in relation to some online retailers and their systems. Once more, there is a potential conflict between individual, community and

collective rights. Surveillance and other such systems will be enhanced by common access to Big Data. In 2017, the EESC already raised the question of who owns the data gathered of workers during work time, in an opinion on the protection of personal data.3 There are worries about the security of workers' data, and calls for better involvement of works councils in deciding what data is collected and how it is used and secured.4

There is also a concern about the nature of the gig economy where more jobs may be casualised by the use of just-in-time systems powered by Big Data. This changes the nature of work from traditional, secure contracts with an employer to false self-employment structures which put the full burden of insecurity, insurance and administration on the worker. Increasingly many of these are young and often from minority communities. There are concerns about the inability of these workers to organise and increasingly more people being falsely classified as self-employed. All these features can be further exacerbated by the greater use of Big Data.

14. Digital Divide

Despite enormous advances in internet access globally there remains a concern about a digital divide where the better off benefit most form access and particularly access to new and innovative developments such as 5G, streaming and premium services. Education is a major factor here and as has been seen throughout this report the concept of asymmetry is a recurring one so citizens need to be fully informed particularly about the data they provide. Lack of understanding of the critical concepts will further a digital divide and fuel a "Big Data divide".

Data literacy is another key concept that emerges here. The OECD has highlighted the important role that infomediaries (e.g. civil society, media and developers) play in the ongoing process of making sense of and creating value from “raw” data, as well as helping to steer the direction of how data is accountably collected, analysed and applied. Open data and its operation can contribute to transparency and to some degree narrow a digital and Big Data divide. Civil society can and has played a role in this field.

15. The Global Situation

15.1 Europe

The EU’s General Data Protection Regulation (GDPR) has marked a substantial step in balancing the advantages of Big Data and concerns about privacy. As earlier noted, the EU’s Charter of Fundamental Rights provides a strong basis for such action and EU is committed to ensuring freedom online. The advent of GDPR could lead to several papers and conferences in and of itself.

Article 5 of the Regulation distils the entire EU approach. That data must be;

processed lawfully, fairly and in a transparent manner collected for specified, explicit and legitimate purposes and not further processed in a

manner that is incompatible with those purposes adequate, relevant and limited to what is necessary in relation to the purposes for which

they are processed accurate and, where necessary, kept up to date; and subject to correction or deletion

3 EESC (2017). TEN/631-EESC-2017: Protection of personal data. https://www.eesc.europa.eu/en/our-work/opinions-information-reports/opinions/protection-personal-data

4 ETUI (2018). Artificial intelligence: a game changer for the world of work. https://www.etui.org/Publications2/Foresight-briefs/Artificial-intelligence-a-game-changer-for-the-world-of-work

kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the personal data are processed;

processed in a manner that ensures appropriate security of the personal data

While building on pre-existing legislation the regulation has meant considerable change for business and others inside and outside the EU as many of its provisions can apply to those outside the EU doing business inside and vice versa. In some respects, given the EU’s economic importance this sets up a global norm in the area. After much initial industry resistance many businesses now want to see a uniform approach to data protection globally and increasingly see the EU approach as offering a useful route, this is an important consideration in the U.S., which is considering federal laws in this area.

15.2 China

China's equivalent law is the Personal Information Security Specification, which came into effect on May 1st 2018. The Specification has a key implementing role in relation to China’s Cyber Security Law in respect of protecting personal information in China. The 2016 Cyber Security Law provides for how companies should approach security and privacy within the country. It includes strict controls around online activities and provisions around storing data locally, having joint venture partners, and in some cases registering network assets. It also has mandatory requirements around breach notification, appointing a head of cybersecurity, incident response plans, and more.

The Specification introduces a concept of “sensitive personal information”, distinguishing such information from other personal information. Sensitive personal information is any personal information, which, if lost or misused, may endanger personal security or property, cause damage to personal reputation, mental health and physical health, or lead to discriminatory treatment.

Under the Specification, sensitive personal information includes ID card numbers, biological identifying information, bank accounts, religious belief, sexual orientation (other typical sensitive personal information is listed in the appendix to the Specification). In addition, personal information relating to minors under 14 years old is generally deemed sensitive personal information.

The Specification sets out different rules regarding the collection and use of personal sensitive information. Many are similar to those in the EU regulation for example the “minimization principle” requires that the type of personal information to be collected should be directly related to carrying out a relevant business activity or service; and the frequency and amount of personal information should be limited to the minimum standard necessary for performing the business activity or service. The Specification confirms that the basic principle for legally collecting personal information consists of the following: (i) the collecting entity needs to explicitly notify relevant individuals of the rules regarding collecting personal information; and (ii) the collecting entity shall obtain consent from relevant individuals.

15.3 The United States

The origin of the many of the concepts involved in data protection come from the United States even if other jurisdictions have arguably gone further in their regulatory regimes. For many years, the U.S. issued Federal Information Processing Standards covering similar issues. The U.S. regulates data and privacy at the federal and state level, while the situation is currently changing there is no one single source of law and regulation. The right to privacy is widely recognised from the common law and other sources.

The U.S. thus has rather a patchwork system of law and regulation in this field. Added to this has been a strong constitutional protection for the concept of freedom of speech, which can militate

against privacy concerns and also a consistent policy to facilitate industry in regulating itself and providing a wide latitude in this field. Suffice it say this is now changing and increasingly the role of large tech firms is becoming a political issue where both their dominance and the issues of Big Data and privacy strongly feature.

In June 2018 the California Consumer Protection Act, or CCPA, became law and was the first-ever state data privacy law. It is due to take effect in 2020. In many respects, California was reacting to global and EU trends in introducing this law. However, it has now led to a flurry of activity by legislators, business and lobbying at the Federal Level where it seems a universal federal law will emerge. Perhaps of most note here is that tech firms generally support such a move mainly due to their desire to eradicate the patchwork of regulation in the U.S. and globally, in effect business is buying in to minimal privacy law, at least in principle.

There is also debate as to whether a Federal standard might be weaker than California’s. It is generally accepted that the CCPA does not go as far in the direction of protecting privacy as the EU’s GDPR. While it may be hard to predict the content, it now seems clear that the U.S. will have a Federal Data Protection law in the near future. Commentators believe that the lack of a fundamental rights approach and the centrality of the tech industry there will give rise to a different approach in the U.S. however.

15.4 Others

Japan and the EU in their recently agreed trade deal have provided for the mutual recognition of each other's data protection regimes. On September 7, 2018, Japan’s Personal Information Protection Commission (PPC) announced supplementary rules regarding how personal data transferred from the EU should be processed following the adequacy recognition. To all intents and purposes, the two systems are similar with regard to their core content. Such a development illustrates how privacy and its interaction with Big Data is beginning to feature in the world of international trade. However generally, the GDPR provides greater protection for data subjects and stricter regulations on the companies that process personal data than the Japanese APPI.

The Russian Federal Law on Personal Data (No. 152-FZ) establishes Russia’s privacy laws and requires data operators to take "all the necessary organizational and technical measures required for protecting personal data against unlawful or accidental access". Russia's Federal Service for Supervision of Communications, Information Technology and Mass Media is the government agency tasked with overseeing compliance

India does not yet have specific legislation on data protection or anything similar to GDPR. It has however amended its Information Technology Act (2000) to give a right to compensation for improper disclosure of personal information. The Government have issued Information Technology Rules in 2011, which were somewhat similar to GDPR type provisions, but there are no apparent examples of their usage.

A global picture is emerging of the regulation of Big Data for social benefit chiefly related to privacy. This is of course uneven and varied but GDPR has significantly developed the concepts and has influenced others to examine this field.

16. Conclusions

There is clearly a need to balance the huge advantages of Big Data for society with the well-identified risks. Increasingly this is a global task. There is a normative development of privacy regulation, which is emerging around the world, and this should be supported.

The Universal Declaration of Human Rights and the International Covenant on Civil and Political Rights provide international legal support and back-up to these efforts. Increasingly these issues will feature in other international agreements including trade agreements.

We need to continually reflect on who regulates and how. The law and practice on Big Data will continue to develop and civil society actors will play an increasing role in the closing the Asymmetry gap and the potential "Big Data Divide"

More work is needed on key concepts in privacy laws such as a definition of "processing purpose" and the forthcoming review of the GDPR may allow for this.

The concept of anonymous data, aggregation, niche data, disaggregation and re-identification are in need of constant invigilation and review.

Our concept of privacy needs to expand or our approach to aggregation needs tighter regulation to assure the public that Big Data will not erode long cherished personal rights and freedoms.

The Five Compensating Measures set out by the EESC in its 2017 Study "The ethics of Big Data: Balancing economic benefits and ethical questions of Big Data in the EU policy context" are helpful to dealing with many of these questions;

1 “EU privacy management platform” – EU wide voluntary web portal – control and ownership to individual – risk as to whether companies take part and reliability

2 “Ethical Data Management Protocol (ED-MaP)” – Certification System identifying virtuous companies – ISO Link – clear system with cert or logo – risk of low uptake

3 “Data Management Statement” – companies voluntarily produce the statement – transparency benefit – risk of limited impact

4 “European E-health Database” - European database which contains health related data of EU citizens – consent etc. and different access for different parties – advantages of control, awareness and trust – risk in security and potential breaches

5 “Digital Education on Big Data”

See https://www.eesc.europa.eu/sites/default/files/resources/docs/qe-04-17-306-en-n.pdf