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Ethics of Big Data: A Socio-Economic Perspective
Mohammed Abdullah Omar Nasseef Assistant Professor, Islamic Economics Institute, King Abdulaziz University, Jeddah, Saudi Arabia
ABSTRACT. With the development of information technology, artificial intelligence, and robots, capitalism has increasingly assumed a form of platform capitalism which is
‘reconceptualizing our economy’ to the extent that it is ‘forcing us to rethink economics’. Capitalism and various institutions controlled by this system have been the subject of criticism in the past and need was expressed to reform them. But today it has become most obvious that there is need for ‘replacing it with a more caring and provisioning sustainable system’. The steps taken by the 28 European Union countries regarding General Data Protection Regulation (GDPR) are commendable. It is recommended that Muslim countries should adopt similar regulations for the protection of the data of their citizens as it is in full conformity with the Qur’ānic teaching of privacy preservation.
KEYWORDS: Platform capitalism, Data ethics, Artificial intelligence, GDPR, Privacy protection.
JELCLASSIFICATION: A10, D00 KAUJIECLASSIFICATION: H33, G1
1. Introduction
The subject of platform capitalism, big data, and data ethics is one of the burning issues that has generally occupied the thoughts of our contemporary scholars.
Reardon (2020) in his lead discussion paper has tried to answer many questions that haunt minds facing the spread of this new form of capitalism. At the same time, he raised many issues to be answered by the new generation of economists. One can hardly disa- gree with him that platform capitalism is “reconcep- tualizing our economy” to the extent that it is “forc- ing us to rethink economics” (p. 60). Thinkers in the past have criticized capitalism and its various institu- tions and have expressed the need to reform them.
But today it has become most obvious that there is a need for “replacing it with a more caring and provi- sioning sustainable system” (p. 60). There is no doubt that “economics, if reconstituted and reconceptual- ized, can adequately help solve the problems of our generation” (p. 64). Reardon has unveiled an open secret that economics textbooks lack discussion on ethics and morals. I must appreciate his efforts. I would like to mainly address ethics of big data in this article.
2. Big Data: Reality and Tools
Eight years ago, big-data became a universal term used to describe all the data that is generated by peo- ple from their smart phones, web browsing history, social media, and purchasing behavior together with any other information that an organization can hold onto. These big data can be distinguished into two categories: structured such as databases and spread- sheets, and unstructured such as text, audio, video, images, etc. (Herweijer & Waughray, 2018, p. 5).
Additionally, there are trillions of sensors deployed in appliances, packages, autonomous vehicles, and elsewhere. These sensors’ job is to collect data. Thus, big data will get bigger and bigger. Moreover, tools that assess the processing of this big data to discover patterns, predict more efficiently by the day. They make more effective recommendations and other useful stuff for businesses. This will continue to grow for many reasons.
Firstly, the development of technologies such as cloud computing and graphics processing units have made it cheaper and faster to handle large volumes of data.
Secondly, social media platforms and continuous connectivity have, to a certain extent, changed how individuals interact. The spread of information and encouraged cultures of sharing knowledge has led to the emergence of a ‘collective intelligence’, including open source communities, that provide artificial intel- ligence (AI) tools and sharing applications.
Thirdly, researchers have made advances in sev- eral subdivisions of AI, particularly in ‘deep learn- ing’, which involves layers of neural networks that are inspired by the human brain’s approach to pro- cessing information (Herweijer & Waughray, 2018, p. 5).
In addition, many businesses have fueled the rise of AI because of competitive pressures. They have been using improved algorithms and open-source software to boost their competitive advantage. Thus, they can augment their returns through, for example, increasing personalization of consumer products or utilizing intelligent automation to increase their productivity (Herweijer & Waughray, 2018, p. 5).
In a 2017 PwC survey of global executives, 54%
reported making substantial investments in AI, while a lack of digital skills remains an important concern.
As organizations continue to invest in tools, people, and AI-enabled innovations, the realized values are expected to increase exponentially (Herweijer &
Waughray, 2018, p. 5). According to one research study, the annual revenue from AI-enabled systems will be growing from $1.4 billion in 2016 to $59.8 billion by 2025 (Tractica, 2017).
According to Steven Finlay, AI has become a game changer for all industries. AI could contribute up to $15.7 trillion to the global economy in 2030. Of this, $6.6 trillion is likely to come from increased productivity and $ 9.1 trillion is likely to come from consumption side effects (Rao & Verweij, 2017, p.
3). The expected economic impact due to AI could be due to productivity gains such as automating process- es including use of robots and autonomous vehicles.
Furthermore, businesses could automat their existing labor force with AI technology. Use of AI may also result in increased consumer demand due to the availability of personalized or higher quality AI de- veloped product and services (ACS, 2018, p. 21).
Nowadays, the financial services industry (FSI) is evolving rapidly and is profoundly affected by major trends such as the digital transformation, the expo- nential growth of data volume, and advances in AI (G.R.I.D. by Deloitte, 2017, p. 14). Numerous AI- based applications are already implemented, and new innovative solutions have the potential to change business activities from operations, risk, finance, to compliance. AI-based applications in the FSI encom- pass robot-advisors, pattern recognition, virtual agents, and intelligent automation.
These numerous applications of AI can be catego- rized into three broad types. AI is used for cognitive engagement, cognitive insights, or cognitive automa- tion. In cognitive engagement, cognitive agents use cognitive technology in order to interact with users in natural language, understand the meaning of the data they receive, and conduct actions on behalf of the users. Usually these kinds of applications are various types of chatbots. For cognitive insights, AI algo- rithms are used that perform data analysis and can provide cognitive insights out of huge amounts of data sets. Cognitive insights agents can help enter- prises with deep, actionable visibility into not only what has already happened, but what is happening now, and what is likely to happen next. Another ap- plication of AI is for cognitive automation which enables machines to replicate human actions and judgments with the help of robotics and cognitive technologies (G.R.I.D. by Deloitte, 2017, p. 15).
3. Big Data: Economical and Ethical Dimensions Two critical ethical and economical questions arise here, one related to the future of the workforce, and the second relevant to the work decision-making process. No doubt, the rapidly increasing use of new technologies has a substantial impact on the work- force. Thus, it is not surprising that so many large tech firms have achieved broad economic scale with- out many employees (West, 2015, p. 6). Derek Thompson’s following statement is a very clear proof of this phenomenon: “Google, is worth $370 billion but has only about 55,000 employees – less than a tenth the size of AT&T’s workforce in its heyday [in the 1960s]” (Thompson, 2015, para. 16).
Martin Ford issues an equally strong warning. In his book, The Lights in the Tunnel (2009), he argues that
as technology accelerates, machine automation may ultimately penetrate the economy to the ex- tent that wages no longer provide the bulk of con- sumers with adequate discretionary income and confidence in the future. If this issue is not ad- dressed, the result will be a downward economic spiral. (p. 237)
He also warns that
at some point in the future – it might be many years or decades from now – machines will be able to do the jobs of a large percentage of the
‘average’ people in our population, and these peo- ple will not [emphasis in original] be able to find new jobs. (p. 9)
Carl Frey and Michael Osborn (2017), of Oxford university, claim that technology will transform many sectors of life. They studied 702 occupational group- ings of the U.S. economy and found that 47% percent of U.S. workers have a high probability of seeing their jobs automated over the next 20 years (p. 268).
According to their estimations, jobs like telemarket- ers, title examiners, hand sewers, mathematical tech- nicians, insurance underwriters, watch repairers, car- go agents, tax preparers, photographic process workers, new accounts clerks, library technicians, and data-entry specialists have a 99 percent of having their jobs computerized (p. 278). At the other end of the spectrum, jobs like recreational therapists, me- chanic supervisors, emergency management direc- tors, mental health social workers, audiologists, oc- cupational therapists, health care social workers, oral surgeons, supervisors of fire fighters, and dieticians have less than a one percent chance of having their tasks computerized (p. 269). They base their analysis upon the improving levels of computerization, the wage levels, and the education required in different fields.
Unfortunately, the only objective in the corporate mind is to maximize profit. As for the interest and benefit of the people who are the subject of those decisions, that is not their primary concern.
On the other hand, the use of machine learning (ML) and predictive models (PM) raises some important ethical questions. This is especially true when such systems are used to create automated decision-making systems that decide how people will be treated without any human supervision in the decision-making process. Unfortunately, these days
such systems are being used more than ever and are becoming increasingly widespread across almost every aspect of western daily life, such as a bank manager deciding who to lend to or a doctor deciding who to treat. As we all know, AI machines use algo- rithms (a set of sequential rules to be followed in problem-solving) created by humans. Hence, if the creator has any inherent biases, or is judgmental in some way, those biases can be built into the machine and that will affect the ultimate decision of the concerned economic agent (Whitsett, n.d., para. 6).
Moreover, behind an automated decision-making system there are data that have been extracted from our personal information. Using these data to make predictions about people’s behavior, exploiting per- sonal information such as someone’s gender, age, religion, marital status, or race should not be accepta- ble. Similarly, they should not be allowed to be used when deciding how someone is dealt with, especially when it comes to dealing with decisions that have to do with people’s lives, or health, or deciding who to hire for a job or to fire on the basis of things like gen- der, or charging more for services based on, for ex- ample, their religion or income.
Modern laws tend to address those problems that have occurred in the past in similar cases and usually do not consider new situations. Thus, almost always a loophole exists that allows law manipulation by big companies. For example, in the U.S., when it comes to personal data and its use within automated deci- sion-making systems, it can be harvested and used to maximize organization’s goals, and the law stands unable to prevent such things.
However, countries within the European Union (EU) have adopted a different approach. Citizens have control over who can hold their data to be used for a given purpose. Therefore, US companies such as Google and Facebook struggle to find common ground in EU countries in terms of how personal data can be gathered and used. For the 28 countries that comprise the EU, which includes 4 of the world’s 10 biggest economies with a combined population of more than half a billion, clear regulation of personal data and how it can be used has been adopted for many years. The most significant data protection legislation ever enacted anywhere in the world came into force in all EU countries on the 25th of May, 2018 (Palmer, 2019). The General Data Protection
Regulation (GDPR) places great responsibilities on organizations over how they gather, manage, and process peoples’ personal information.
These regulations apply to all organizations oper- ating in the EU, even if their base of operations is elsewhere. Companies which fail to comply with the GDPR, are liable for fines of up to 4% of their global turnover for every breach of the regulation that oc- curs (GDPR Associates, n.d.). On the other hand, in the US there is no overarching legislation specifically around the gathering of personal data or how that data is used in automated decision-making processes.
4. Concluding Remarks
Islam considers the right to privacy as one of the fun- damental human rights. This is very well understood from the following verses of the Holy Qur’ān:
O you who believe! Shun much suspicion; for lo!
some suspicion is a crime. And spy not, neither backbite one another. Would one of you love to eat the flesh of his dead brother? You abhor that (so abhor the other)! And keep your duty (to Allah). Lo! Allah is Relenting, Merciful. (49:12) O you who believe! Enter not houses other than your own without first announcing your presence and invoking peace upon the folk thereof. That is better for you, that you may be heedful. (24:27) And if you find no-one therein, still enter not until permission has been given. And if it is said to you:
Go away, then go away, for it is purer for you.
Allah knows what you do. (24:28)
Islam advises that full precautions should be taken in visiting and meeting so that even an accidental bad scene is avoided. Allah says in the Holy Qur’ān:
And tell the believing women to lower their gaze and be modest, and to display of their adornment only that which is apparent, and to draw their veils over their bosoms, and not to reveal their adornment save to their own husbands or fathers or husbands’ fathers, or their sons or their husbands’ sons, or their brothers or their brothers’
sons or sisters’ sons, or their women, or their slaves, or male attendants who lack vigor, or children who know nothing of women's nakedness. And let them not stamp their feet so as to reveal what they hide of their adornment. And turn towards Allah together, O believers, in order that you may succeed. (24:31)
Not only outside, this training is given at home as well:
O you who believe! Let your slaves, and those of you who have not come to puberty, ask leave of you at three times (before they come into your presence): Before the prayer of dawn, and when you lay aside your raiment for the heat of noon, and after the prayer of night. Three times of privacy for you. It is no sin for them or for you at other times, when some of you go round attendant upon others (if they come into your presence without leave). Thus, Allah makes clear the revelations for you. Allah is Knower, Wise.
And when the children among you come to puberty then let them ask leave even as those before them used to ask it. Thus, Allah makes clear His revelations for you. Allah is Knower, Wise. (Qur’ān, 24:58-59)
Even in selecting the data one should be very careful.
Due to free entry, authenticity of information may not be guaranteed. In chapter 49 of the Holy Qur’ān, Almighty Allah says:
O you who believe! If an evil-liver brings you tidings, verify it, lest you smite some folk in igno- rance and afterward repent of what you did. (49:6) Hayat (2007) has rightly observed:
The human rights recognized in modern constitu- tions, charters and international treaties are em- bedded in the religion of Islam, and respect for life, privacy, freedom, equality, property and reli- gious belief is an essential feature of Islam. … If someone happens to come across private infor- mation, further disclosure of that information is not permitted. [Therefore,] managing the affairs of the private domain is the exclusive right of the in- dividual. (pp. 137-138)
No doubt the steps taken by the 28 European Union countries regarding the General Data Protection Reg- ulation (GDPR) are commendable. It is recommend- ed that Muslim countries should also adopt, if they do not already have, regulations similar to the GDPR for the protection of data of their citizens as it is in full conformity with the Qur’ānic teaching of privacy preservation.
References
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Sydney, Australia: Author. Retrieved from:
https://bit.ly/35c4Gby
Finlay, S. (2018). Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies (3rd ed.). London, UK:
Relativistic.
Ford, M. (2009). The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future. Lexington, USA: Acculant Publishing.
Frey, C.B., & Osborne, M.A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological forecasting and social change, 114, 254-280.
G.R.I.D. by Deloitte. (2017). AI and you: Perceptions of Artificial Intelligence from the EMEA financial services industry. Milan, Italy: Deloitte Consulting.
Retrieved from: https://bit.ly/39Apkps
GDPR Associates. (n.d.). GDPR Fines. Retrieved from:
https://bit.ly/2QCFjdV
Hayat, M.A. (2007). Privacy and Islam: From the Quran to data protection in Pakistan. Information &
Communications Technology Law, 6(2), 137-148.
Herweijer, C., & Waughray, D. (2018). Fourth Industrial Revolution for the Earth: Harnessing Artificial Intelligence for the Earth. A report of PricewaterhouseCoopers (PwC). Retrieved from:
https://pwc.to/2Qu5cMV
Palmer, D. (2019, May 17). What is GDPR? Everything you need to know about the new general data protection regulations. Retrieved from: https://zd.net/
36ep2SV
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https://pwc.to/2tgdM9U
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Islamic Economics, 33(1), 59-69.
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2u0DZtv
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Mohammed Abdullah Omar Nasseef is currently Vice Dean for Development at the Islamic Economics Institute (IEI), King Abdulaziz University, Saudi Arabia. He earned his PhD in sustaining TQM (Total Quality Management), and designing software that can help companies reach Excellence and maintain a competitive advantage, from Bradford University, UK in 2009. He completed his MSc in Project Management form Northumbria University and BSc in Public Administration from King Abdulaziz University, Saudi Arabia. He worked as a business coordinator at Health Outreach and Business Affairs in King Faisal Hospital, Saudi Arabia for three years. He is a certified Project Manager in Applied Project Management, a certified Black Belt in Six Sigma Quality, a certified Manager in Process Excellence, a member of the American Society for Quality (ASQ), and an Executive member at the Saudi Quality Council. He is also an Assessor for the Emirates Government Excellence Award – Sheikh Khalifa Government Excellence Program, Dubai, UEA, Assessor Training Workshop based on 2010 EFQM Model, Dubai, UAE and Certified Training Of Trainers (TOT), London Academy of Management Study, UK.
E-mail: [email protected]
يعامتجا روظنم :ةمخضلا تانايبلا تايقلاخأ -
يداصتقا
الله دبع دمحم رمع
فيصن
،دعاسم ذاتسأ يملاسلإا داصتقلاا دهعم
،ةدج ،زيزعلا دبع كللما ةعماج ةيدوعسلا ةيبرعلا ةكلملما
صلختسلما .
ايجولونكتل عراستلما روطتلا عم تعس ،يعانطصلاا ءاكذلاب ةصاخلا مولعلاو تامولعلما
يأ نم ةدرجلما ةيدالما ةدافتسلاا ضرغب تانايبلا عمج تاصنم معد ىلع ةيلامسأرلا ،ةيناسنإ تارابتعا
داصتقلاا ملع يف ريكفتلا ةداعإ وحن طغضلا كلذكو ىلع تاصنلما هذه ةرطيس للاخ نم هسفن
اهيلع رطيسم تاسسؤلما نم ديدعلاو ةيلامسأرلا نإ .داصتقلاا لصافم ىلع يلاتلابو نيلماعتلما تانايب يذ نم احاحلإ رثكأ ةجاح كانه ايلاحف ،يملاعلا داصتقلاا لصافم يف مكحتي "ماظن" لبق نم لبق
رلا ماظنلا لادبتساب ةبلاطلما و رييغتلا وحن رثكأ رخآ ماظنب يلاحلا يلامسأ
ةيباجيإ و امامتهاو ةمادتسا
.
إ ةوطخلا ن ةيباجيلإا
تمدقأ يتلا اهيلع
28 ماظن ليعفتب ةصاخلا ،يبورولأا داحتلاا لود نم ةلود
ةماعلا تانايبلا ةيامح
GDPR
دارفلأل تانايبلا لوادت عنمي يذلاو ،يبورولأا داحتلاا لخاد ةماعلا
تاكرشلا نيب ةيصخشلا ام وهو ،ىربكلا ةيلامسأرلا
ح ماظن ضرف يملاسلإا ملاعلا لود ىلع ىنمتن ةيام
ف عمتجلما دارفأ يمحي هباشم ي
اهتانايب ةيصوصخب بعلاتلا نمو تاكرشلا هذه .
دلا تاملكلا ةيامحل ةماعلا ةحئلالا ،يعانطصلاا ءاكذلا ،تانايبلا تايقلاخأ ،تاصنلما ةيلامسأر :ةلا
ةيصوصخلا ةيامح ،تانايبلا .
فينصت
:JEL A10, D00
فينصت
KAUJIE :
H33, G1
